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1 ADOLESCENT RISK TAKING, DOPAMINE SIGNALING, AND COCAINE SELF ADMINISTRATION: A VICIOUS CYCLE By MARCI RAE MITCHELL A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2012
2 2012 Marci Rae Mitchell
3 T o my family my parents, my siblings, and my husband as they inspire me, support me, and encourage me each and every day
4 ACKNOWLEDGMENTS I would like to thank Barry Setlow and Jennifer Bizon for being two of the most fantastic mentors anyone could have. You both have been there for me and believed in me even when I did not believe in myself, both inside and outside of the la b. You have been my lab parents I strive for your approval and that has been more rewarding than papers or grants. I would like to thank my committee members Drake Morgan has been there to help me troubleshoot through self administration procedures and his journal club has taught me how to analyze papers from a new perspective. Sara Jo Nixon has continuously challenged me to push myself further and to fully embrace what I once thought was beyond my capabilities. Jesse Dallery has not only supported me i n my academic pursuit, but has also been an advisor for my career and life in general. Each one has played a very important role in creating the researcher I am today and I am incredibly thankful to have had the opportunity to have them in my life I would like to thank my lab mates as we have been here together on early mornings, late nights, and a cross country move. Nick and Ian have since moved on from the Bizon/Setlow labs, but they will forever hold very large spaces within the labs as they have been critical in building the foundation. Cristina Ba uelos will forever be one of the best storytellers and full of wisdom. Colin Vokes helped me pilot this project and jump start my dissertation work. Ginny Weiss helped me to conduct my studies, even on weeke nds, and I could not have asked for a better undergraduate to mentor. I wish her the best of luck at the University of Kentucky as she pursues her doctorate. I could not have completed my in situ hybridization data without Sofia Beas and thank her greatly for taking the time out of her schedule to help me, even at 5am. Dominique Ouimet has become my partner in crime in the animal lab since her hire and with her
5 ex it corresponding with my own, will be bittersweet I would also like to thank Karienn Montgomer y and Kristy Shimp as we will always be part of the same science family and I will miss you both. I would like to thank my family, in particular my husband Brandon as he has endured failed experiments alongside me, put up with my ever changing lab schedule and proofread papers to help me obtain my degree without asking anything in return. I would not have been able to complete my degree without his constant support even when I was not in the best moods. I would also like to thank the National In stitute of Heath and the National Institute on Drug Abuse for their support through the Ruth L. Kirschstein National Research Service Award ( NRSA ) (F31DA033074 )
6 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 10 ABSTRACT ................................ ................................ ................................ ................... 11 CHAPTER 1 BACKGROUND ................................ ................................ ................................ .......... 13 Measuring Behavioral Disinhibition ................................ ................................ ......... 14 Measures of Impulsivity in Humans ................................ ................................ .. 14 Measures of Risk Taking in Humans ................................ ................................ 15 Animal Measures of Impulsivity ................................ ................................ ........ 18 Animal Measures of Risk Taking ................................ ................................ ...... 19 Chronic Cocaine Use & Behavioral Disinhibition ................................ .................... 20 Cocaine Use is Associated with Behavioral Disinhibition in Humans ............... 21 Cocaine Us e Can Cause Increases in Behavioral Disinhibition ........................ 22 Behavioral Disinhibition Can Predict Vulnerability to Cocaine Use ................... 24 Adolescence & Behavioral Disinhibition ................................ ................................ .. 26 Dopamine ................................ ................................ ................................ ............... 29 Dopaminergic Regulation of Behavioral Disinhibition ................................ ....... 31 Dopamine & Relationships between Behavioral Disinhibition and Cocaine Use ................................ ................................ ................................ ................ 35 Dopamine & Adolescent Development ................................ ............................. 36 2 PURPOSE ................................ ................................ ................................ .................. 40 3 EXPERIMENT 1: TO TES T THE HYPOTHESIS THA T ADOLESCENT RISK TAKING IS PREDICTIVE OF AND ALTERED BY CO CAINE SELF ADMINISTRATION. ................................ ................................ ................................ 42 Introduction ................................ ................................ ................................ ............. 42 Methods ................................ ................................ ................................ .................. 43 Subjects ................................ ................................ ................................ ............ 43 Apparatus ................................ ................................ ................................ ......... 43 Behavioral Procedures ................................ ................................ ..................... 44 Shaping ................................ ................................ ................................ ...... 44 Risky Decision Making Task ................................ ................................ ...... 45 Implantation of Intravenous Jugular Catheters ................................ ................. 46
7 Cocaine Self Administration Group ................................ ................................ .. 47 Sucrose Self Administration Group (Control) ................................ ................... 48 Reassessment of Risky Decision making ................................ ......................... 48 Data Analysis ................................ ................................ ................................ ... 48 Results ................................ ................................ ................................ .................... 49 Adolescent Risk Taking as a Predictor of Future Cocaine Self Administration ................................ ................................ ............................... 49 Long term Alterations in Risky Decision making as a Result of Cocaine Self Administration ................................ ................................ ........................ 50 Activity Measures ................................ ................................ ............................. 51 Other Variables ................................ ................................ ................................ 52 Discussion ................................ ................................ ................................ .............. 52 4 EXPERIMENT 2: TO CHA RACTERIZE THE HYPOTH ESIZED RELATIONSHIP BETWEEN D1 AND D2 RE CEPTOR M RNA EXPESSION AND RI SKY DECISION MAKIN G ................................ ................................ .............................. 64 Introduction ................................ ................................ ................................ ............. 64 Methods ................................ ................................ ................................ .................. 64 Subjects ................................ ................................ ................................ ............ 64 Tissue Preparation ................................ ................................ ........................... 65 Probe preparation ................................ ................................ ............................. 65 I n Situ Hybridization ................................ ................................ ......................... 66 Data Analysis ................................ ................................ ................................ ... 67 Results ................................ ................................ ................................ .................... 68 Discussion ................................ ................................ ................................ .............. 69 5 EXPERIMENT 3: TO FUN CTIONALLY TEST HYPOT HESIZED CAUSAL RELATIONSHIP BETWEEN DOPAMINE SIGNALING I N SPECIFIC BRAIN REGIONS AND RISKY DE CISION MAKING ................................ ........................ 80 Introduction ................................ ................................ ................................ ............. 80 Methods ................................ ................................ ................................ .................. 81 Subjects ................................ ................................ ................................ ............ 81 Experimental Design ................................ ................................ ........................ 81 Implantation of Bilateral Cranial Cannulae ................................ ....................... 82 Microinfusion Procedure ................................ ................................ ................... 82 Data Analysis ................................ ................................ ................................ ... 83 Assessment of Cannula Placement ................................ ................................ .. 83 Results ................................ ................................ ................................ .................... 84 Discussion ................................ ................................ ................................ .............. 85 6 SUMMARY AND CONCLUSIONS ................................ ................................ ............. 93 LIST OF REFERENCES ................................ ................................ ............................. 104 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 125
8 LIST OF TABLES Table page 3 1 Locomotion Values for Adolescent RDT Performance. ................................ ...... 63 3 2 Locomotion Values for Adult Post SA RDT Performance. ................................ .. 63 3 3 Correlations Summary Table for Cocaine Intake ................................ ................ 63 3 4 Correlations Summary Table for Adolescent RDT Performance ........................ 63 5 1 Omissions, Locomotion, and Shock Reactivity during Quinpirole Microinjections ................................ ................................ ................................ .... 92
9 LIST OF FIGURES Figure page 1 1 Delay Discounting Curvet. ................................ ................................ .................. 37 1 2 Risky Decision making Task ................................ ................................ .............. 38 1 3 Risky D ecision making Task Performance ................................ ........................ 38 1 4 Individual Variability in Risky Decision making Task Performance. .................... 39 3 1 Individual Variability in RDT Performance During Adolescence (Pre SA). ......... 59 3 2 Adolescent Risk Taking P redicts Cocaine Sself Administration in Adulthood .... 60 3 3 Cocaine Self Administration Causes Long Las ting Elevations in Risky Choice ................................ ................................ ................................ ............... 61 3 4 Cocaine Self Administration Causes Long Lasting Elevations in Risky Choice. ................................ ................................ ................................ ............... 62 4 1 RDT Performance of Adolescent Rats Used for In Situ Hybridization Analyses. ................................ ................................ ................................ ............ 76 4 2 Hybridization of Radiolabeled Dopamine mRNA in Prefrontal Cortex and Striatum. ................................ ................................ ................................ ............. 77 4 3 D1 mRNA Expression is Relate d to Adolescent RDT Performance .................. 78 4 4 D2 mRNA Expression is Relate d to Adolescent RDT Performance ................... 79 5 1 RDT Performance After Dorsal Striatal Microinjections of Quinpirole. ............... 90 5 2 RDT Performance After Ventral Striata l Microinjections of Quinpirole ................ 91 6 1 Dopaminergic Modulation of the Direct and Indirect Pathways. ....................... 103
10 LIST OF ABBREVIATION S 5CSRTT 5 Choice Serial Reaction Time Task ACSF Artificial Cerebral Spinal Fluid CGT Cambridge Gambling Task DL S Dorso lateral Striatum DM S Dorso medial Striatum IGT Iowa Gambling Task ITI Intertrial Interval IV Intravenous M PFC Medial Prefrontal Cortex NACc Nucleus Accumbens Core NAC SH Nucleus Accumbens Shell OFC Orbitofrontal Cortex PB Phosphate Buffer PD PET Positron Emission Topography RDT Risky Decision making Task SA Self Administration
11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy ADOLESCENT RISK TAKING, DOPAMINE SIGNALING, AND COCAINE SELF ADMINISTRATION: A VICIOUS CYCLE By Marci Rae Mitchell December 2012 Chair: Barry Setlow Major: Medical Sciences Neuroscience In adolescence, p oor decision making risk taking, a nd drug use have been strongly linked; however t he causal relationships among these factors are poorly understood. As causality is dif ficult to disentangle in humans, an animal model of risk taking was used to investigate causal relationships between adolescent risk taking and cocaine self administration in rats. Specifically, a Risky Decision making Task (RDT) that was developed in our la boratory was used to i nvestigate whether risky decision making is a pre exist ing condition which may predict the propensity for drug use and/ or if elevated risk taking is a result of drug use itself. In addition, the RDT was used to determine if the relationships be tween risky decision making are mod ulated by dopaminergic signaling in the prefrontal cortex and striatum as these brain regions have been heavily implicated in mediating both risky decision making and drug use. Findings from the experiments indicated that individual variability in RDT per formance during adolescence significantly predicted cocaine intake (i.e ., greater risk taking was associated with greater cocaine intake) and that cocaine self administration rats exhibited greater risk taking compared to controls even after 6 weeks of abs tinence. Moreover, lower striatal D1 and D2 re ceptor expression was associated with greater
12 adolescent risk taking and activation of D2 receptors in the ventral, but not dorsal, striatum biased choice behavior toward a more risk averse pattern. These data indicate that adolescent risk taking predicts acquisition of cocaine self administration, and that coca ine self administration can cause long lasting elevations in risk taking. The findings that lower dopamine receptor expressi on in striatum was associate d with elevated risk taking and that activation of dopamine (especially D2 ) receptors in the ventral striatum biased choice behavior in the RDT toward greater risk aversion strongly suggest that D2 receptors play a causal role in both risk taking behavior and cocaine use. between risk taking and cocaine use which may be regulated by D2 receptors and might contribute to addictive processes.
13 CHAPTER 1 BACKGROUND Adolescence is a period of substantial maturation, both physically and ment ally. This period is often marked by p oo r decisi on making, including elevated risk taking, and the onset of drug use (for review see (Spear, 2000) ) By age 18 nearly 48% of 71% have sampled alcohol ( NIDA, 2010 ) ; however, it remains unclear whether adolescent elevations in risk taking and the initiation of d rug use are related. In addition c hronic drug users also have poor decision making capabilities, includin g elevated risk taking (for review see (Lucantonio et al., 2012) ) a l though it is unclear whether such elevated risk taking is a cause or consequence of drug use A better un derstand ing of the mechanism s that underlie the relationship s between risk taking and drug use (such as dopamine signaling which has been implicated in both decision making and drug use) may open new doors for behavioral or pharmacological intervention f or the attenuation of such behaviors. There is a large literature in humans regarding both maladaptive decision making and drug use and it will be necessary to understand these h uman conditions in order to appropriately model such behavior in animals. Moreover, animal models are critical to understanding the mechanisms which may underlie relationships between risk taking and drug use as such relationships are often difficult to di sentangle in humans. In order to begin to unravel such relationships, we will first review literature on 1.) measures of impulsivity and risk taking in both humans and rodents 2.) the relationships between chronic drug (particularly cocaine) use and behav ioral disinhibition and evidence for behavioral disinhibition being either predictive or a result of drug use, 3.) adolescence and how adolescent behavioral disinhibition
14 may increase propensity for future drug use and 4) dopamine and its influence on beh avioral disinhibition, cocaine use, and adolescent development Measuring Behavioral Disi nhibition Behavioral d isi nhibition refers to a lack of restraint in acting on impulses and desires which is manifested in several different types of behavior For the purposes of this dissertation the term behavioral disinhibition will be used to encompass both impulsivity and risk taking, which are strongly associated with drug use. Measures of Impulsivity in Humans Impul sivity, which has been described as rapid, unplanned behavior with little forethought of consequences ( Moeller et al., 2001 ) can be conceptually divided into two disti nct forms : impulsive action and impulsive choice (Evenden, 1999; Moeller et al., 2001) Impulsive action refers to an inability to withhold a proponent response and is (Winstanley et al., 2006) ) I mpulsive action can be measured by the Stop Signal Task in which participants are required to make a rapid response to a cue and then, on certain trials, without warning ing that they must inhibit that response (Greenberg and Waldman, 1993) Individuals who have difficulty successfully inhibiting their r es ponse after the stop signal is presented are said to display greater impulsive action. Impulsive choice is the preference for smaller, sooner rewards over larger, delayed rewards. Impulsive choice can be measured in the laboratory with delay discounting tasks, in which individuals are presented with choice s between smaller, more immediate reward s and la rger, but delayed reward s Individuals who would be considered impul sive or showing high levels of impulsive choice generally choose the smaller, sooner r eward more often than the larger delayed reward, especially when the
15 choice of the small reward seems (objectively) disadvantageous (e.g. choice of $100 today over $150 tomorrow could be considered disadvantageous as a relatively short delay of gratificati on w ould result in substantial ly greater gains ) ( Adriani and Laviola, 2003 ; Steinberg et al., 2009 ) (see Figure 1 1) Measures of Risk Taking in Humans In deciding from among an array of possible choices, favorable outcomes are ofte n associated with some risk of adverse consequences In order to make optimal decisions, one must be aware of t behavior accordingly. Risk taking is the choice of an action that has the potential to lead to a loss or other a dverse consequence. Two examples of laboratory tasks that measure risk taking are the Iowa Gambling Task ( IGT ) and the Cambridge Gambling Task (CGT) in which poor choices result in loss of earnings ( Bechara et al., 1997 ; Rogers et al., 1999 ) In the IGT, p articipants are presented with 4 virtual decks of cards on a computer screen. On each trial, they are required to choose a card from a deck. Most card choices will result in a loss The decks differ from each other in the number of trials over which the losses are distributed. Through feedback provided following choice of each card, participants learn which decks are "bad decks" ( larger gains per card, but costing more in intermittent losses ultimately resulting in net loss ) and which are "good decks" ( smaller gains per card but less frequent and smaller losses, ultimately resulting in net gain ) as greater Individuals who or greater gains regardless of loss are considered risk t aking. A study by Bechara et al. (2001) investigated IGT performance in substance dependent individuals and found that there was a wide range of individual variability, such that
16 some participants were able to perform the task on par with control participants whereas others were severely impaired, continuously selecting cards from the disadvantageous While this task is widely used, it has one maj or caveat such that optimal performance in this task requires one to be able to process and learn from negative feedback, such that any deficit in this learning ability can bias outcomes toward a more risk taking pattern of performance An additional task that can measure r isk taking is the CGT, which is different from the IGT in that it is simpler and requires minimal learning The CGT has two stages: a training stage and a gamblin g stage. In the training stage participants are presented with a row o f ten boxes across the top of a computer screen, some proportion of which are red and the rest blue The goal is to guess under which color a yellow token is hidden. For example, if 8 out of the 10 boxes are red and only 2 are blue, one might assume that the chances of the token being hidden under a red box is greater than that of a blue box and therefore, red would be the optimal choice In the gambling stage, participants start off with a certain number of points which are presented on the screen. Once the participant guesses whether the token is hidden under red or blue, they are box in which they select the number of points they would like to bet on their degree of confidence in their choice. Individuals who would be conside re d risk taking on this task might for example bet a larger n umber of points on a trial on which there are relatively equal numbers of blue and red boxes. For example, if there are 6 blue boxes and 4 red boxes at the top of the screen, which could be interp reted as a 60% chance that the yellow token is hidden under a blue box. A non
17 risk taker would bet fewer points on the probability that the token is under a blue box on this trial than they would on a trial on which there are 8 blue boxes Impulsivity and risk taking are difficult to disentangle in humans as there are many conditions such as attention defic it hyperactivity disorder and addiction, in which both present simultaneously Moreover, human decision making can be influenced by indi vidual differences in previous experiences, personal preferences, social cooperation, etc. (Glimcher and Rustichini, 2004; Brand et al., 2006; Lee, 2008; Kable and Glimcher, 2009) For example, smokers tend to display more impulsive choice, preferring smaller sooner rewards to larger, delayed ones (Reynolds et al., 2004) However, cigarette smoking is strongly related to educational status, such that individuals with lower education levels have a greater likelihood of smoking. Moreover, people with lower education levels will also most likely have lower paying jobs and people with lower income display greater rates of impulsive choice (Green et al., 1996) Therefore, the relationship between smoking and elevations in impulsive choice are unclear as they might be a result of education level and/or income level. Moreover, in smokers, impulsive choice might be a preexisting condition which may opensity to smoke (as opposed to smoking resulting in elevated impulsive choice) A nimal models of impulsivity and risk taking are particularly important for determining how these elements of behavioral disinhibition relate to each other and to the underly ing neural circuitry that may be mediating such behavior because confounds such as social environment and prior experience can be tightly controlled As a result, animal models are useful for disentangling cause/effect relationships in associations observ ed in humans.
18 Animal Measures of Impulsivity Impulsive action is most commonly measured in rodent s using the five choice serial reaction time task (5CSRTT) In this task, which was originally developed to assess visual attention, r odents are placed in oper ant chambers and are required to scan five apertures on one wall of the chamber s for the presentation of a brief target visual stimulus in one of them When the stimulus occurs, they are required to make a nosepoke response at that aperture to obtain a foo d reward. There are several types of erro r s the rodents can commit in this task (not all of which are linked to impulsivity), but for the purposes of this dissertation, the focus will be on p remature errors Premature errors are response s in an aperture before the tar get stimulus has been presented and are the measure of impulsive action (i.e. failure to wait for the appropriate signal to respond) (for review see (Dalley et al., 2004) ). Animals that are considered impulsive display a greater number of these premature responses Impulsive choice can also be assessed in animals using delay discounting tasks that are similar in design to those used in humans. In these tasks, rodents are placed in operant chambers and are presented with choices between a small er, sooner reward or a larger, but delayed reward (usually food or water) The delay to reward receipt at which an animal prefer s the smaller, sooner reward deter Th at is, an animal that shifts it s preference from the larger, delayed to the smaller, sooner reward at a short delay to delivery of the lar ge reward would be considered impulsi ve relative to an animal that i s willing to wait for long delays to obtain the large reward. G reater discounting of the large reward (e.g. steeper discounting), is indicative of a more impulsive animal.
19 Animal Measures of Risk Taking There are several animal models of risk based decision making that have been well characterized in the literature (Floresco et al., 2008; Zeeb et al., 2009; Jentsch et al., 2010b) For example, a commonly used assessment of risk taking is the probability d iscounting task, in which rodents are placed in operant chambers and are required to ch o ose b etween a small, certain reward and a large reward with uncertain delivery (i.e the large reward is associated with varying probabilities of reward delivery) A ra t would b e considered risk taking if it showed a greater preference for the large reward even when the probability of reward receipt was very low. While this and similar tasks do a good job of modeling some elements of real world decisions in humans, the a dverse outcomes are defined by reward omission which may not capture the full spectrum of adverse outcomes in humans For example, players a t a poker table must bet on their degree of confidence in the cards given to them and if they lose, t hey do not just fail to win, but encounter a financial loss as well. I t is difficult to employ such designs in animals due to the apparent difficulty of s (Hackenberg, 2009; Jentsch et al., 2010 a) ). However, tasks in which rewarding outcomes are combined with the risk of an explicitly punishing stimulus (Negus, 2005; Van Den Bos et al., 2006) have some advantages, in that they capture making in humans in which choi ces often result in both benefits (rewards) and risks of punishment. To model such decision making, we developed a task in our laboratory in which rat s are placed in operant chambers and must choose between two response levers, one whic h delivers a small, safe food reward (one food pellet) and
20 the other which delivers risky food reward (three food pellets) which is accompanied by a systematically increasing probability of punishment ( a mild footshock) (Figure 1 2 ) Sessions consist of blocks of 10 discrete choice trials each and as the task progresses the risk of punishment increases in each successive block of trials. Rats performing t his shift in preference from the risky to saf e reward as risk of punishment increases within test sessions (Figure 1 3 ) and choice performance remains consistent ( i.e rats preference for the large, risky reward does not change substantially ) over long periods of time (Simon et al., 2009b; Mitchell et al., 2011) Importantly as in humans, ra ts display individual variability in reward preference in preference for the risky reward), whereas other bias away from the risky reward) (Figure 1 4 ) This variability is minimally influenced by individual differences in several factors that could contribute to choice performance, such as appetitive motivation, consummat ory motivat ion, anxiety, and pain tolerance suggesting that risk taking in this task is a distinct behavioral construct Chronic Cocaine Use & Behavioral Disi nhibition This dissertation focuses on the effects of c ocaine because it is a powerf ully addictive stimulant drug and second only to marijuana in terms of prevalence of illicit drug use (NSDUH, 2011) It also is the best understood illicit drug from the perspective of animal models accounting for more than 40% of published research on drug self administration (Ahmed, 2010) ) Finally there is a substantial body of literature demonstrat ing long term cocaine related neurobiolog ical changes in brain structure and function that may have severe consequences for optimal decision making (for reviews
21 see (Bolla et al., 1998; Tucker et al., 2004; Beveridge et al., 2008; Thomas et al., 2008; Lucantonio et al., 2012) ). Cocaine Use is Associated with Behavioral Disi nhibition in Humans Cocaine users present with a range of neurobehavioral deficits including maladaptive decision making and the effects of cocaine on decision making in particular ha ve been studied at great length in both human s and animal model s (Holman et al., 1991; Fillmore and Rush, 2002; Schoenbaum et al., 2004; Tucker et al., 2004; Schoenbaum and Setlow, 2005; Colzato et al., 2007; Belin et al., 2008; Beveridge et al., 2008; Anker et al., 2009; Vadhan et al., 2009; Mendez et al., 2010; Cunha et al., 2011) It has consistently bee n shown that cocaine dependent patients show reliably greater impulsive choice in delay discounting tasks (i.e greater preference for smaller, sooner rewards than larger, but delayed rewards) and greater impulsive action as measu red by the Stop Signal tas k (i.e an inability to inhibit a proponent response ) than non users ( Bickel and Mar sch, 2001 ; Fillmore and Rush, 2002 ; Coffey et al., 2003 ; Heil et al., 2006 ; Li et al., 2006 ; Colzato et al., 2007 ; Johnson, 2012 ; Moreno Lopez et al., 2012 ) in addition to elevated risk taking as measured by the IGT (i.e (Bechara et al., 2001; Bolla et al. 2003; Tucker et al., 2004; Barry and Petry, 2008; Lane et al., 2010; Cunha et al., 2011) Importantly, maladaptive decision making associated with cocaine use can last well into abstinence. Heil et al. (2006) investigated impulsive choice using a delay discounting procedure and showed that there were no differences in impul sive choice between cocaine abstinent and cocaine dependent individuals, but that both of these groups were significantly more impulsive than control participants. These results suggest that cocaine users (prior and current) have greater impulsive choice t han non users and that this elevation in impulsive choic e exists long
22 into abstinence ; however it is unclear if greater impulsive choice is a preexisting condition or a consequence of cocaine use, nor is it clear what mechanisms may underlie relationship s between impulsive choice and cocaine use. Cocaine dependent and previous cocaine users present with robust neuro bio logical abnormalities such as reduced gray matter in the orbitofrontal cortex (OFC), insula, and cingulate cor tex (areas implicated in execut ive function and decision making) Neuroimaging studies in cocaine dependent patients show a range of f unctional abnormalities including as decreased blood flow in the OFC insula, and areas of the basal ganglia (all implicated in decision making, reward processing, and motivation) during normal conditions (Holman et al., 1991; Volkow et al., 1991; London et al., 2000; Bolla et al., 2003; Tucker et al., 2004) The regions which di splay decrease d gray matter in cocaine users overlap substantially with the regions that are found to have functional abnormalities, suggesting that differences in structure size could be causing the functional abnormalities However, in humans, it has bee n difficult to determine whethe r individuals have structural or functional abnormalities or demonstrate behavioral disinhibition prior to drug use or if such deficits are a result of the drug use itself. Animal models have helped to illuminate this issue as behavioral disinhibition can be measured prior to, during, and after drug use Cocaine Use Can Cause Increases in Behavioral Disi nhibition Animal studies have been utiliz ed to determine whether cocaine can cause the increa sed impulsivity observed in chr onic users There have be en mixed findings as to whether experimenter administered cocaine c auses increases in impulsiv ity (Logue et al., 1992; Paine et al., 2003; Bornovalova et al., 2005; Winstanley, 2007; Dandy and Gatch, 2009; Duva et al., 2011; Zuo et al., 2012) For example, Paine et al. (2003)
23 administered cocaine to rats for 14 days and tested them in a Stop Signal task and found no alterations in impulsive action. Moreover, Dalley et al. (2005) tested rats in the 5CSRTT after e xposure to cocaine and also found no a lterations in impulsive action. Therefore, there is little evidence to suggest that chronic cocaine increases impulsive action. However, there is evidence to suggest that experimenter administered cocaine can cause inc reases in impulsive choice in delay discounting tasks (Logue et al., 1992; Paine et al., 2003; Simon et al., 2007a; Dandy and Gatch, 2009; Zuo et al., 2012) For example, Simon et al. (2007a) tested impulsive choice followi ng 3 weeks of abstinence from chronic cocaine administration and found that cocaine exposed rats showed greater preference for smaller, more immediately available rewards which suggests that cocaine exposure can cause long lasting increases in impulsive c hoice. It is noteworthy to mention that there is ample evidence that the route of administration can have large impacts on the neurobiological consequences of cocaine administration which could potentially impact drug induced changes in impulsivity ( McFarland et al., 2003 ; Kalivas and Volkow, 2005 ) Intravenous (IV) s elf administration (SA) of cocaine is currently the best animal model of patterns of human drug intake as in this model, drugs are taken voluntarily (as in the case of humans) (Sanchis Segura and Spanagel, 200 6) In SA studies, a nimals are implanted with IV jugular catheters and allowed to SA cocaine directly into the blood stream by performing an instrumental response ( such as a lever press or nosepoke) Furthermore, f ollowing extended access to cocaine SA anima ls are more likely to escalate drug consumption (SA more drug in a given time period) which is thought to model the escalation of cocaine use observed in human chronic cocaine users (Ahmed and Koob, 1998; Roberts et al., 2007) Following
24 extended access to cocaine SA, animals will also work harder to obtain cocaine (Paterson and Markou, 2003) take more risks to seek and/or obtain cocaine (e.g. will continue to attempt to gain access to cocaine even when cocaine taking is punished ) (Vanderschuren and Everitt, 2004) and show an increased rate of reinstatement ( i.e. higher rates of relapse ) (Mantsch et al., 2004; Ahmed and Cado r, 2006; Kippin et al., 2006; Knackstedt and Kalivas, 2007) Therefore, cocaine SA in anim als can model several components of drug use in humans. O ur laboratory has shown that SA cocaine can also cause long term increases in impulsive choice comparable to those observed with experimenter administered cocaine ( Mendez et al., 2010 ) Broos et al. (2012) also investigated SA cocaine induced alterations i n delay discounting performance by measuring impulsive choice once a week throug h various stages of cocaine SA. Although they did not find that cocaine SA increased impulsive choice rats in their study consumed less cocaine than those in the Mendez et al. (2010) study Indeed recent data from our laboratory suggest that cocaine induced incre ases in impulsive choice depend on the amount of cocaine consumed show inc reased impulsive choice in a delay discounting task following SA, (Weiss et al., 2012) Behavioral Disi nhibition Can Predict Vulnerability to Cocaine Use Recent ly animal models have been employed to determine if individual differences in measures of behavio ral disinhibition can predict vulnerability to cocaine use. For example, Dalley et al. (2007) i nvestigated rela tionships between impulsive action as measured by the 5CSRTT and cocaine SA in rats. They found that individual variability in impulsive action p redicted cocaine SA such that those rats that displayed greater
25 impulsive action also showed greater escalation of cocaine SA compared to rats that displayed less impulsive action I mpulsive choice as measured by a delay discounting task also predicts acquisition and escalation of coca ine SA (Perry et al., 2005; Ank er et al., 2009) as well as persistence of cocaine seeking during extinction and propensity for relapse following cocaine SA ( Broos et al., 2012 ) In the wild, rats are required to explore new areas in search of food; however, doing so too quickly or without the necessary precautions can result in i n jury or death. As a result, novelty exploration in which researchers monitor how quickly and how much of a novel environment rats are willing to explore is sometim es used in the laboratory as a measure of risk taking Rats classified as high responders (those rats that display high novelty exploration) acquire cocaine SA at a faster rate than low responders (those rats that display low novelty exploration) which su ggests that increased risk taking may be predictive of cocaine SA (Belin et al., 2008; Davis et al., 2008) The data from animal studies described above suggest that there may be bidirectional relationships between components of behavioral disinhibition and cocaine SA, particular ly in the case of impulsivity, in which h igh levels of impulsive choice can predict the propensity to SA cocaine and cocaine SA in turn results in long lasting elevations in impulsive choice. Such findings could suggest that the elevated impulsive choice observed in chronic cocaine users may be both a cause and an effect of drug use. Cocaine use in humans is also as sociated with increased risk taking as assessed on the IGT and CGT however, there has yet to be a study directly investigating the relationship s between risk taking and cocaine use in an animal model both prior to use and after drug exposure Hence it i s unclear whether elevated risk taking is a
26 preexisting con dition that may influence place and/or if risk taking in cocaine users is a consequence of cocaine use Moreover, b ecause drug use may first present in adolescence and elevated risk taking is a hallmark of adolescent development, it is of great importance to determine the neurobiological mechanisms mediating the relationships between risk taking and drug use Adolescence & Behavioral Disi nhibition In o rder to investigate factors predictive of drug use, it makes sense to start with the adolescent period, as it is during this period when both behavioral disinhibition and drug use often first emerge. Adolescence, defined as ages 10 19 by the World Health O rganization ( WHO, 2008 ) is a time of substantial maturation. Adolescents are stuck in a stage between childhood and adulthood characterized by a desire to form intricate groups, companionship, and a sense of belonging ( Nelson et al., 2005 ) It is a period of transitions and behavioral changes, including increases ( across species ) in impulsivity ( Adriani and Laviola, 2003 ; Chambers et al ., 2003 ; Vaidya et al., 2004 ; Steinberg et al., 2009 ) novelty and sensation seeking (a personality trait defined by the search for experiences that are "varied, novel, comp lex and intense" and by the readiness to "take physical, social, legal, and financial risks for the sake of such experiences." (Leary and Hoyle, 2009) ) ( Zuckerman et al., 1978 ; Adriani et al., 1998 ; Douglas et al., 2003 ; Adriani and Laviola, 2004 ; Stansfield et al., 2004 ; Stansfield and Kirstein, 2006 ) and risk taking ( Spear, 2000 ; Steinberg, 2008 ) Luna et al (2001) state that impulsivity, risk taking behavior, and novelty seeking may provide a mechanism to expand the range of possibilities that will provide the appropriate feedback for optimal sculpting of t However, such impulsivity and risk taking may also promote maladaptive behavio r such
27 as substance abuse Adolescents are more likely than adults or children to experiment with tobacco, alcohol, and illicit drugs, as well as unprotected sex and r eckless driving (Arnett et al., 1997; Arnett, 1999; Spear, 2000; Chambers et al., 2003) By 12th gr ade tobacco, and 71% have sampled alcohol ( NIDA, 2010 ) Because of this adolescent vulnerability to drug use it is of high priority to understand the individual neural and cognitive differences present in adolescents that may increase propensity for drug use, in order to further the d evelopment of clinical and pharmacological based intervention. Evolutionarily, increased risk taking in adolescence may be adaptive as it would facilitate emigration from t he natal group and prevent in breeding (Spear, 2000) ; however, in modern society, these traits may lead to maladaptive behaviors such as increased likelihood to partake in drug use, reckless driving, and unprotected sex (Arnett et al., 1997; Arnett, 1999; Spear, 2000; Chambers et al., 20 03) While adolescent risk taking is well established within such social contexts adolescent risk taking in decision making tasks in the laboratory (which are useful for eliminating environmental factors such as social contexts, peer pressure, etc.) ha s been less well studied. In one of the few such studies Cauffman et al. (2010) tested children, adolescents, and adults on a modified version of the I GT and observed that while both adolescents and adults improved their decision making over ti me, adolescents did so more slowly than adults This suggests that adolescents may be less effect ive at processing relationships between rewards and adverse conseq uences such that their decision making is weighted more toward rewarding outcomes without appropriately accounting for the risk s involved.
28 Adolescent individual differences in preference for immediate rewards risk taking, and sensation seeking have been associated with an earlier age of alcohol and drug experimentation (Martin et al., 2002; Kollins, 2003; Laviola et al., 2003; Martin et al., 2004; Goudriaan et al., 2011) suggesting that adolescents who display high levels of behavioral disinhibition may be at an increased risk of substance use and misuse. For example, Kollins et al. (2003) investigated impulsive choice ( a s measured by a delay discounting task) among undergraduate students (mean age of 20) and found that greater preference for immediate rewards was associated with younger first use of marijuana, cigarettes, and alcohol and a higher total number of illicit drugs used in their lifetime. U sing a similar population, Goudriaan et al. (2011) investigated the degree to which IGT and Stop Signal performance predicted heavy alcohol use. They found that poorer IGT performance predict ed heavy drinking in males (but not females ), but found no relationship between heavy drinking and Stop Signal performance. The majority of studies investigating adolescent individual variabi lity i n behav ioral dis inhibition have used adolescents who are already using drugs (a s in the previous two examples) or children of drug users. For example, Bauman et al. (1986) compared preschool children of methadone maintaine d mothers to children of non addicted mothers and showed that children of methadone maintained mothers were more impulsive, immature, and irresponsible This could suggest that possible early life (in utero) drug exposure result ed in these elements of behavioral disinhibition However, there are caveats when investigating chi ldren of drug users. While it is clear that prenatal drug exposure, genetics, or environmental /social factors (e.g. poor parenting) may influence child behavior it is unclear to what extent each of these factors
29 influenced the behavior of the children stu died For example Bauman et al. (1986) also reported that methadone maintained mothers scored lower on tests of parenting behavior suggesting that the elevations in impulsivity, immaturity, and irresponsibility seen in their children could have resulted from environmental (or genetic) factors rather than solely from prenatal drug exposure Notably, Anokin et al. (2011) compared impulsive choice among t wins and found that twins displayed similar choice preference, providing support for a genetic basis of this aspect of impulsivity T he ability to model individual variability in decision making in animals can help to illuminate possible genetic/ neurobiological factors that may influence behavior al disinhibition by allowing relatively tight control over environmental factors. Dopamine The neurotransmitter dopamine is thought to play a central role in both behavioral disinhibition and drug use. A m etabolite of the amino acid tyrosine, 3 hydroxytyramine (dopamine) has become one of the most widely studied monoamines since the discovery of its physiological functions in 1957 (Carlsson et al., 1957) Dopamine generally exerts its effects by modulating the neurotransmission of GABA and glutamate. There are four main dopaminergic pathways in the mammalian brain: nigrostriatal (conn ecting the substantial nigra to the striatum), mesolimbic (connec ting the ventral tegmental area to the nucleus ac cumbens, amygdala, hippocampus, and medial prefrontal cortex [mPFC]), mesocortical (connecting the ventral tegmental area to the cerebral cortex (especially the prefrontal cortex) ) and tuberinfundibular (connecting the hypothalamus and median eminence) (Anden et al., 1964; Dahlstroem and Fuxe, 1964) These neurons are heavily implicated in mediating voluntary movement, feeding, reward, sleep, attention, working memory, and learning t o name
30 just a few of the roles ascribed to them (Snyder et al., 1970; Missale et al., 1998; Sibley, 1999; Carlsson et al., 2001; Iversen and Iversen, 2007) The actio ns of dopamine are mediated by five diffe rent G protein coupled receptor subtypes which can be classified as either D1 like (D1 & D5), which are excitatory as they are positively coupled to adenylyl cyclase or D2 like (D2, D3, & D4), which tend to be inhibitory as they are negatively coupled to adenylyl cyclase (Spano et al., 1978; Kebabian and Calne, 1979; Andersen et al., 1 990; Niznik and Van Tol, 1992; Sibley and Monsma, 1992; Sokoloff et al., 1992; Civelli et al., 1993; Vallone et al., 2000) D1 like receptors are primarily found postsynaptically whereas D2 like receptors are found both postsynaptically and presynaptically (as an autoreceptor) on dopaminerigc neurons (Sokoloff et al., 2006; Rankin et al., 2010; Rondou et al., 2010) D1 and D5 receptors share 80% of their homology whereas D 3 and D4 receptors share 75% and 53% homolo gy with D2 receptors, respectively (Gingrich and Caron, 1993; Missale et al., 1998) As a consequence of these similarities and differences, dopamine receptor subtypes differ in their sensitivity to dopam inergic agonist s and antagonists. Dopaminergic drugs distinguish well between D1 & D2 like receptors, but it has proven difficult to find ph armacological compounds that readily distinguish among the members of the D1 like or D2 like families (Missale et al., 1998; Sokoloff et al., 2006; Rankin et al., 2010; Rondou et al., 2010) Dopamin e receptors have very broad expression patterns within the brain, with D1 and D2 expression being most prominent. D1 receptors are highly expressed in three of the pathways mentioned earlier, the nigrostriatal, mesolimbic, and mesocortical, which include b rain regions such as the caudate putamen (dorsal striatum), nucleus
31 accumbens (ventral striatum ), substantia nigra, olfactory bulb, amygdal a and frontal cortex, with lower levels of expression in the cerebellum, hippocampus, thalamus, and hypothalamus. In contrast, D5 receptors are only expressed at low levels in the cortex, substantia nigra, hypothalamus, hippocampus and at even lower levels in the striatum (Missale et al., 1998; Gerfen, 2000; Sokoloff et al., 2006; Rankin et al., 2010) D2 receptors are expressed at very high levels in the striatum (b oth dorsal and ventral) and olfactory tubercle and a t high levels in the substantia nigra, ventral tegmental area, hypothalamus, cortex, septum, amygdala, and hippocampus (Missale et al., 1998; Gerfen, 2000; Vallone et al., 2000; Seeman, 2006) D3 receptors have limited expression in the brain with highest levels in the nucleus accumbens, olfactory tubercle, and the islands of Calleja (Sokoloff et al., 1992; Missale et al., 1998) D4 receptors have the lowest expression of any dopamine receptor and are found in the frontal cortex, amygdala, hypothalamus, substantia nigra, and thalamus (Missale et al., 1998; Rondou et al., 2010) (for comprehensive review on dopamine and dopamine receptors see ( Beaulieu and Gainetdinov, 2011 ) ) Dopamin ergic Regulation of Behaviora l Disi nhibition D ysr egulation of dopamine signaling has been strongly implicated in behavioral disinhibition For example, a cute pharmacological d opamine depletion in healthy people results in increases in risky choice in the IGT ( Sevy et al., 2006 ) possibly by interfering with the component s of the decision making process which bias attention toward m ore recent rather than long term outcomes. These data suggest that dopamine depletion can bias behavior toward a more risk taking pattern and that the same mechanisms might also bia s behavior tow ard sooner as opposed to delayed rewards Such findings are consistent with evidence that systemic administration of dopaminergic receptor
32 antagonists can increase impulsive choice (Setlow et al., 2009) Somewhat surprisingly, a dministration of dopaminergic agonists and precursors commo nly used in the treatment of PD can also result in behavioral disinhibition including impulse control disorders (Burn and Troster, 2004; Nirenberg and Waters, 2006) For example, Molina et al. (2000) first reported that some patients with PD develop pathological gambling an d that the behavior usually comes on or worsens with levadopa therapy (used to increas e dopamine availability throughou t the brain). Since then, the phenomenon has been observed in other PD patient groups ( (Giovannoni et al., 2000; Gschwandtner et al., 2001; Driver Dunckley et al., 2003) for review see (Lader, 2008) ) and has been studied in laboratory setting s. Pagonabarraga et al. (2007) investigated the ability of medi c ated PD patients to perform the IGT. They found that the PD group displayed worse performance on the task, by preferring the but ultimately long term losses. Other studies have found similar results in PD patients taking dopamine replacement therapies (Perretta et al., 2005; Pagonabarraga et al., 2007; Kobayakawa et al., 2008; Delazer et al., 2009; Ibarretxe Bilbao et al., 2009) suggesting that as with dopamine depletion increas es in dopaminergic signaling can also result in increases in b ehavioral disinhibition. One way to explain these seemingly contradictory results is that the influence of dopamine signaling on optimal behavioral performance may follow an inverted U shape d function such that levels of dopamine that are too low ( as a re sult of dopamine depletion ) or too high (as result of dopamine replacement therapy), can both result in suboptimal decision making capabilities (Kish et al., 1988; Cools et al., 2001) However, o ne major caveat in the PD literature described above is that measures of behavioral disinhibition are not taken prior to the
33 onset of PD symptoms. Therefore, it is possible that the in dividuals who present with behavioral disinhibition after PD o nset or dopamine replacement therapy may have exhibited behavioral disinhibition prior to PD onset or treatment A recent study using an animal model of PD in which dopamine te rminals in the striatum were lesioned found that the lesion alone did not alter performance on a probabilistic discounting task, but adminis tration of the D2/D3 agonist pramipexole (which is used to treat PD) resulted in increased preference for the large, risky reward in both le s i oned and control groups (Rokosik and Napier, 2012) These findings align with the clinical con dition (described above) in which PD patients undergoing dopamine replacement therapy tend to show increased risk taking but suggest that this effect is not specific to PD Studies investigating relations hips between dopamine receptor expression or function and behavioral disinhibition have provide d m ounting evidence which suggest s that D2 like dopamine receptors are particularly involved in mediating individual propensity for both behavioral disinhibition and addiction (Robbins and Everitt, 1999) (for review see ( Dagher and Robbins, 2009 ) ). For example, in humans, there are two gene polymorphisms that result in reduced striatal D2 receptor expressio n, TAQ 1A and C957T (Thompson et al., 1997; Jonsson et al., 1999; Hirvonen et al., 2004) P eople with these polymorphisms display a poorer ability to learn from negative feedback (Frank et al., 2007; Klein et al., 2007) elevated impulsivity and higher rates of addiction, and compulsive behaviors (Comings et al., 1996; Klein et al., 2007) Animal studies have shown that acute administration of D2 receptor agonists increase s and antagonists decrease s risk taking when the risk of an adverse consequence is reward omission (St Onge and Floresco, 2009a; Zeeb et al., 2009)
34 This result is in contrast to the human polymorphism studies mentioned earlier as D2 receptor activation would result in decreased risk taking in individuals who have decreased D2 receptor expression. H owever, as mentioned earlier, such cost benefit dec ision making tasks in rodents (e.g. probabilistic discounting) utilize reward omission as an adverse outcome. However, such rodent tasks may not capture the full spectrum tangible loss or in situations in which rewarding outcomes are combined with punishment. Simon et al. (2011) investigated the effects of acute systemic administration of D1 and D2 agonists and antagonists on preference for the large, risky rew ard in the RDT They found that neither a D1 agonist nor antagonist produced alterations in choice behavior ; howeve r, administration of a D2 agonist produced a dose dependent decrease in choice of the large, risky reward which is consistent with what is seen in humans Administration of a D2 antagonist did not alter choice behavior, which suggests that D2 receptor act ivation is not necessary but is sufficient to shift behavior toward a more risk averse pattern. In addition, expression of D2 receptors in t he striatum has also been linked to impulsive action in rats, such that lower levels of D2 receptor binding in the s triatum are associated with greater impulsive action as measured by the 5CSRTT (Dalley et al., 2007) Similar to these findings and the findings in the human s showing greater behavioral disinhibition in individuals with lower striatal D2 expression p revious work from our laboratory showed that D2 receptor mRNA levels in the dorsal striatum were negatively related to risk taking in the RDT, such that rats with high levels of risk taking displayed lower D2 receptor mRNA levels ( Simon et al., 2011 ) T aking these data together, it is clea r that dopamine plays a
35 substantial role in modul ating behavioral disinhibition although the exact nature of this relationship is unclear. Dopamine & Relationships between Behavioral Disinhibition and Cocaine Use There is growing eviden ce that dopamine si gnaling may mediate the relationship between behavioral disinhibition and cocaine use. G reater impulsive action as measured by the 5CSRTT and lower levels of D2 expression in the striatum are associated with high levels of cocaine SA (Nader et al., 2006; Dalley et al., 2007; Johnson and Kenny, 2010) C hronic stimulant users also display elevated risk taking and decreased D2 receptor expression in the striatum (Bechara et al., 2001; Nader et al., 2006; Volkow et al., 2007) As described above altered dopamine transmission is associated wi th maladaptive decision making. In rats, t here is a negative relationship between impulsive action and D2 like receptor binding in the striatum prior to cocaine SA such that rats with greater impulsive action displayed less receptor binding (Dalley et al., 2007) S uch findings suggest that the decrease in striatal D2 expression seen i n human cocaine addicts may be (at least in part) a predisposing trait and not solely a result of cocaine use. S tudies in animals report altered dopamine transmission (Franklin et al., 2002; Lane et al., 20 10) and decrease d dopamine receptor binding sites, espec ially in the striatum after cocaine SA (Moore et al., 1998; Nader et al., 2006) which is similar to what is seen in human patients in which D2 like receptor availability in the ventral striatum is decreased in chronic stimula nt users ( Volkow et al., 2001 ) In sum these data suggest a bi directional relationship between striatal D2 expression and cocaine SA, such that low striata l D2 receptor expression can predic t the propensity for cocaine SA, but may also be caused by cocaine SA (and possibly indicative of a greater propensity for relapse ) These data also suggest the existence of a bidirectional
36 relationship between cocaine us e and measures of behavioral disinhibition. Hence it is of great importance to determine the relationships between these three factors (D2 expression, cocaine SA, and behavioral disinhibition). Dopamine & Adolescen t Development The data desc ribed above li nking dopamine signaling to behavioral disinhibition suggest that s uboptimal decision making and engaging in possibly deleterious behavior (e.g. reckless driving, drug use, etc ) during adolescence may be a result of alterations in dopamine rgic signaling as this system matures throughout development (Seeman et al., 1987; Kalsbeek et al., 1988; Teicher et al., 1995; Tarazi et al., 1998, 1999; Spear, 2000) For example, a study in rats showed that dopamine inputs into the prefro ntal co rtex (implicated in decision making) increase in density during adolescence and into adulthood (Kalsbeek et al., 1988) Furthermore, both human and animal studies have shown a marked increase in d opamine receptor expression within the striatum (implicated in reward processing), which peaks in mid adolescence and then steadily declines into adulthood (Seeman et al., 19 87; Teicher et al., 1995; Tarazi et al., 1998, 1999) Importantly, these changes in dopamine expression during development occur in brain regions that are implicated in behavioral disinhibition (Bechara et al., 1994; Bechara et al., 1996; Bechara et al., 1999; Dalley et al., 2004; Balleine et al., 2007; Dalley et al., 2007; Eagle e t al., 2011) (for reviews see (Dalley et al., 2004; Chudasama and Robbins, 2006; Schultz, 2010) ) and reward valuation (Berridge and Robinson, 1998; Schultz, 1998) Taken together, individual differences in behavioral d isinhibition in adolescents may be influenced by structural and dopaminergic alterations throughout development within brain regions that are implicated in behavioral disinhibition Furthermore, since dopaminergic signaling is associated with risk taking a nd drug use, it
37 will therefore, be critical to determine if risk taking behavior, mediated by the dopaminergic system, in adolescence can predict the propensity for drug use in the future. Figure 1 1 Delay Discounting Curve. The curve on the left repr esents a non impulsive delay discounting curve in which preference for the large reward decreases as the delay to reward delivery increases (and preference shifts toward the smaller sooner rewards). The curve on the right represents what a delay discountin g curve may look like for an impulsive individual in which preference shifts very rapidly from the large, delayed reward to the smaller, sooner reward even at very short delays to reward receipt.
38 Figure 1 2 Risky Decision making Task. This schematic outlines the task performed by rats and contingencies associated with choice of either lever. Figure 1 3 Risky Decision making Task Performance. Mean group performance on the RDT shows that rats shift their preference from the large, risky reward (y axis) to the small, safe reward as the risk of punishment increases (x axis).
39 Figure 1 4 Individual Variability in Risky Decision making Task Performance. Each line on this graph represents an individual Importantly, some rats show a strong preference for the large, risky reward even when the risk of punishment is high and other rats show a strong bias away from the large, risky reward even when the risk of punishment is low.
40 CHAPTER 2 PURPOSE Overall Goal: The overall goal of this dissertation project was to determine the neurobiological mechanism s mediating relationships among adolescent risk taking, drug u se, and dopamine signaling The three main objectives of this research project, which combine d my research interests and experience in animal models of drug addiction, decision making, and adolescent development were as follows: Experiment 1: To test the hypothesis that adolescent risk taking is predictive of and also altered by cocaine self administration. Adolescence is a period characterized by high levels of risky behavior and vulnerability for drug use; however, it is unclear how these two factors are related. Experiment 1 used a rat model to determine whether risk taking in adolescence is a significant predictor of propensity to self administer cocaine in young adulthood. Rats were first characterized in the RDT during adolescence. U pon re aching adulthood, the relationships between acquisition of cocaine SA and risk taking w ere evaluated. In addition, because chronic cocaine can alter cognitive processes relevant to risk taking (suggesting that elevated risk taking in chronic cocaine users could also be due in part to effects of the drug itself hence the ere re tested in the RDT following cocaine SA to determine whether cocaine SA has long lasting effects on risk taking. Experiment 2: To characterize the hypothesi zed relationship between dopaminergic markers and r isky decision making. Researc h in both human s and animals has identified components of the dopaminergic system, particularly D2 like receptors, as important regulators of risk taking behavior. To determine whether these dopaminergic markers could mediate relationships between adolescent risk taking and
41 future cocaine self administration adolescent rats were trained in the RDT as in Experiment 1, followed by sacrifice during young adulthood Their brains we re processed for in situ hybridization for D1 and D2 mRNA and r egion specific mRNA expression in prefrontal and striatal areas implicated in decision making w as related to individual differences in risk taking ( Bizon et al., 2001 ) Experiment 3: To functionally test the hypothesized causal relationship between dopamine signaling in specific brain regions and individual variability in risky decision making. Experim ent 2 provide d novel data concerning relationships between components of the dopaminergic system and risk taking, but the nature of these studies does not allow explicit determination of causal roles. To begin to determine the functional relevance of relat ionships observed between individual differences in risk taking and dopaminergic markers we use d microinjections of quinpriole (a D2 like agonist) targeted at either the dorsal or ventral striatum to determine how D2 activation modulates choice behavior i n the RDT.
42 CHAPTER 3 EXPERIMENT 1 : TO TEST THE HYPOTH ESIS THAT ADOLESCENT RISK TAKING IS PREDICTIVE OF AND AL TERED BY COCAINE SEL F ADMINISTRATION. Introduction Adolescents generally have poor decision making capabilities, including across species elevations in impulsivity ( Adriani and Laviola, 2003 ; Chambers et al., 2003 ; Vaidya et al., 2004 ; Steinberg et al., 2009 ) novelty and sensation seeking ( Zuckerman et al., 1978 ; Adriani et al., 1998 ; Douglas et al., 2003 ; Adriani and Laviola, 2004 ; Stansfield et al., 2004 ; Stansfield and Kirstein, 2006 ) and risk taking ( Spear, 2000 ; Steinberg, 2008 ) compared to both adults and children. Moreover, there is some evidence that adolescent risky behavior is predic tive of future drug use (Laviola et al., 2003) The relationships between adolescent risk taking and the propensity for drug use are difficult to disentangle in humans; however, these relationships can be investigated experimentally using animal models (Laviola et al., 2003) Chronic c ocaine use is associated with maladaptive decision making such as increased risk taking; however it remains unclear whether elevated risk taking is a factor that predisposes some individuals to cocaine use and/or if cocaine use itself cause s elevations in risk taking. A growing body of data from animal models suggest s that chronic cocaine exposure can pro duce lasting impairments in other forms of dec ision making as well as cognitive processes relevant to risk taking (Schoenbaum and S etlow, 2005; Simon et al., 2007a; Setlow et al., 2009; Mendez et al., 2010) ; however, it is not clear whether chronic cocaine directly affects risk taking behavior. The goal of E xperiment 1 was to address these questions by determining whether adolescent risk taking predicts subsequent cocaine SA and whether cocaine SA causes elevations in risk taking. These questions are of considerable importance as adolescent risk taking
43 may predispose individual s to a greater vulnerability to drug us e and chronic drug induced elevations in risk taking have the potential to promo te further drug use and relapse. Methods Subjects Male Long Evans rats (n=42 P 26; Charles River Laboratories, Raleigh, NC) were individually housed and kept on a 12h light/da rk cycle (lights on at 0800 hours) with free access to food and water except as noted. During behavioral testing, rats were maintained at 85% of their free feeding weight, with allowances for growth. In adolescent rats free feeding weight was adjusted eve ry 4 days to account for growth using the Long Evans growth chart provided by Charles River. All animal procedures were conducted during the light cycle (0800 1700) and were approved by the University of Florida Institutional Animal Care and Use Committe e and follow ed NIH guidelines. Apparatus Testing was conducted in standard behavioral test chambers (Coulbourn Instruments, Whitehall, PA) housed within sound attenuating isolation cubicles. Each chamber was equipped with a recessed food pellet delivery trough fitted with a photobeam to detect head entries and a 1.12 W lamp to illuminate the food trough, which was located 2 cm above the floor in the center of the front wall. Forty five mg grain based food pellets (PJAI, Test Diet, Richmond, IN) could be delivered into the food trough. Two retractable levers were located to the left and right of the food trough, 11 cm above the floor. A 1.12 W house light was mounted on the rear wall of the isolation cubicle. The floor of the test chamber was composed of steel rods connected
44 to a shock generator that delivered scrambled footshocks. Locomotor activity was assessed thr oughout each session with an infrared activity monitor mounted on the ceiling of the test chamber. This monitor consisted of an array of infrared (body heat) detectors focused over the entire test chamber. Movement in the test chamber (in x, y, or z planes ) was defined as a relative change in the infrared energy falling on the different detectors. Test chambers were interfaced with a computer running Graphic State software (Coulbourn Instruments), which controlled task event delivery and data collection. Be havioral Procedures Shaping Shaping procedures followed those used previously (Cardinal et al., 2000; Simon et al., 2007b; Simon et al., 2009a) Following magazine training, rats were trained to press a single lever (either the left or the right, balanced across rats ; the other lever was retracted during this phase of training) to receive a single food pellet. After reaching a criterion of 50 lev er presses in 30 min, rats were then trained on the opposite lever under the same criterion. This was followed by further shaping sessions in which both levers were retracted and rats were shaped to nose poke into the food trough during simultaneous illumi nation of the trough and house lights. When a nose poke occurred, a single lever was extended (left or right), and a lever press resulted in immediate delivery of a single food pellet. Immediately following the lever press, the trough light was extinguishe d and the lever was retracted. Rats were trained to a criterion of 30 presses on each lever within 60 min.
45 Risky Decision Making Task Testing procedures were similar to Simon et al (2009a) and Mitchell et al (2011). The RDT was modified slightly by reducing trial numbe r to maintain attention and prevent satiation due to the smaller body size of adolescent rat s. Sessions were 48 min in duration and consisted of 5 blocks of trials Each 40 s trial began with a 10 s illumination of the food trough and house lights. A nose poke into the food trough extinguished the trough light and triggered extension of either a single lever (forced choice trials) or of both levers simultaneously ( free choice trials). If rats failed to nose poke within the 10 s time window, the lights were extinguished and the trial was scored as an omission. A press on one of the lever s (either left or right, balanced across rats ) resulted in one food pellet (the small safe reward) delivered immediately following the lever press. A press on the other lever resulted in immediate delivery of three food pe llets (the large, risky reward); h owever, selection of this lever was also accompanied immediately by a possible 1 s footshock contingent on a preset probability specific to each trial block. The large reward was delivered following every choice of the large reward lever, regardless of whether or not the footshock occurred. The probability of footshock accompanying the large reward was set at 0% during the first block of trials In subsequent blocks of trials the probability of footshock increased to 25, 50, 75, and 100%. Each trial block beg a n with 8 forced choice trials 4 for each lever (except for the first and last blocks in which only 4 forced choice trials 2 for each lever were presented) used to estab lish the punishment contingencies followed by 8 free choice trials (Cardinal and Howes, 2005; Simon et al., 2007b; Simon et al., 2009a; St Onge a nd Floresco, 2009b) Once either lever was pressed, both levers were immedi ately retracted. Food delivery was accompanied by re illumination of both the food trough and
46 house lights, which were extinguished upon entry to the food trough to collect the food or after 10 s, whichever occurred sooner. On the forced choice trials (in which only one lever was present) the probability of shock following a press on the large reward lever was dependent across the four trials in each block. For example, in the 25% risk block, one and only one of the four forced choice trials (randomly selec ted) always resulted in shock, and in the 75% risk block, three and only three of the four forced choice trials always resulted in shock. In contrast, the probability of shock on the free choice trials (in which both levers were present) was entirely indep endent, such that the probability of shock on each trial was the same, irrespective of shock delivery on previous trials in that block. Upon completion of the task (at age P55) rats were returned to their home cages and allowed to mature to young adulthood (60 days of age ( Odell, 1 990 ) ). Rats were separated into two groups based on performance in the RDT O ne underwent implantation of intravenous (IV) jugular catheters for cocaine SA and the other underwent sucrose SA procedures Each suc rose SA rat was matched with a cocaine SA rat based on performance in the RDT (f or example, two rats that chose the large, risky reward 100% of the time in all five blocks would be paired with each other ) Implantation of Intravenous Jugular Catheters Rats (n = 28 P70 ) were anesthetized using i soflurane gas. Using sterile techniques, a catheter w ere inserted into the right jugular vein and sutured to muscle tissue in the a rea of the vein. The catheter was then passed subcutaneously through the body and attached to a back mount cannula connector pedestal This plastic pedestal consisted of a threaded cylindrical top on a base molded around a stainless steel tube that projected upward, and was passed through a small incision in the skin over the scapulae. Rats were allowed at least 5 days of recove ry from surgery prior to
47 commencing cocaine SA During this recovery period, antibiotic ointment was applied to the incision sites, and catheters were flushed daily with heparinized saline and for the first seven days with an antibiotic solution to prevent occlusions ( Nation et al., 2004 ; Wellman et al., 2007 ) Catheters were also tested weekly for patency using an IV infusion of 0.1 mL propofol, which would anesthetize the rat briefly given the catheter was indeed patent. Cocaine Self Administration Group Cocaine SA was conducted in 12 identical standa rd rat test chambers (30.5 25.4 30.5 cm, Coulbourn Instruments, Whitehall, PA) housed in sound attenuating cubicles. Each chamber was equipped with two nosepoke holes located on the left and right side of the front wall of the test chamber, and which c ould be illuminated with a light located inside of the hole Twenty mL syr inges mounted on infusion pumps were used for IV drug delivery to rats in each test chamber. These syringes were connected via PE50 tubing to a fluid swivel and from there to a fluid line which mated to the back mount connector pedestal. The system was interfaced with a computer running Graphic S tate software to control drug d elivery and record data from each of the chambers. During SA sessions, only one of the two nosepoke holes was illuminated (the left/right position of the illuminated hole remained constant across all sessions ) Cocaine solution was delivered o n a fixed ratio 1 (FR1) schedule following a nosepoke into the illuminated ( active ) nosepoke hole in a volume of 0.16 mlL over 6 s. Responses at the non illuminated (inactive) nosepoke hole were recorded but had no programmed consequences. Following recovery from surgery, cocaine SA began with five daily 2 h sessions at 0.3 mg/kg/infusion followed by five 2 h sessions at 0.5 mg/kg/infusion. The goal of these relatively low dose and short access sessions was to try to accentuate
48 individual differences in the acquisition of cocaine SA. To assess escalation o f cocaine intake, session duration was increased to 6 h for an additiona l 14 sessions and the cocaine dose was increased to 1.0 mg/kg/infusion Escalation of intake (reflected by increased intake across sessions) during these long access conditions is thought to be related to the transition to drug addiction ( Ahmed and Koob, 1998 ; Roberts et al., 2007 ) Sucrose Self Administration Group (Control ) Another group of rats (n = 14) was trained to nosepoke (FR1) to obtain access to a 20% sucrose solution on a schedule such that the number of sucrose reinforc ers allowed to be earned by each rat was yoked to the number earned by its partnered cocaine rat. For ex ample, if a cocaine rat received 50 infusions, then his sucrose partner was allowed to self administer only 50 sucrose deliveries. These procedures control led for the total amount of instrumental learning experience and reward receipt. Sucrose reinforcers were delivered by a dipper cup located in a liquid trough positioned in the center of the front wall of the test chamber between the two nosepoke holes Sucrose SA was paired for each day of cocaine SA through out the entirety of the exp eriment (i.e. during both cocaine acquisition and escalation). Reassessment of Risky Decision making Following all SA procedures (both cocaine and sucrose), rats were left undisturbed in their home cages for 3 weeks to ensure adequate drug washout before returning to the RDT for retesting for an additional 20 sessions at which point stable performance was evident Data Analysis Raw data files were exported from Graphic State software and compiled using a custom macro written for Microsoft Excel (Dr. Jon athan Lifshitz, University of Kentucky).
49 Statistical analyses were conducted in SPSS 20 Stable performance was defined by the absence of a main effect of session, the absence of an interaction between session and trial block, and the presence of a main ef fect of trial block within a repeated measures ANOVA over a 5 session period (Winstanley et al., 2006; Simon et al., 2009a; Simon et al., 2010) In all cases, p values less than .05 were considered significant. adolescent performance on the RDT (mean percent choice of the large, risky reward) with the average daily of cocaine intake during the acquisition period P erformance in the RDT pre and post cocaine SA was examined using a repeated measures ANOVA ( drug condition x p re/post SA x punishment probability). Relationships between SA variables and pre and post cocaine RDT performance Results Rats achieved stable performance in the RDT during adolescence (21 26 sessions), with s ubstantial individual variability in reward preference (Figure 3 1). Rats were then assigned to one of two groups for cocaine or sucrose SA balanced for adolescent performance in the RDT Prior to SA experience, there were no differences in RDT performanc e between the rats assigned to the cocaine and sucrose groups ( main effect of block, F (4,84) = 50.33, p < 0.0001; main effect of group, F (1,21) = 0.33 p > 0 .5 7; block x group interaction F (4,84) = 1.84 p > 0 .1 3 ) (also see top graph in Figure 3 4) Adolescent Risk Taking as a Predictor of Future Cocaine Self Administration One of the primary goals of this experiment was to determine the relationship between adolescent risk taking and subsequent cocaine SA. Accordingly, t here was a significant positi ve bivariate correlation between adolescent risky decision making and
50 mean cocaine intake during the 5 day s of the 0.5 mg/kg/infusion dose, s uch that greater preference for the large, risky reward in adolescence was associated with greater cocaine intake ( r = 0.45 p < .05 ; Figure 3 2 ). Adolescent RDT performance was not correlated with mean c ocaine intake during the 5 days of 0.3 mg/kg/infusion (r = 0.36, n.s. ) n or with mean cocaine intake during the 14 days of 1.0 mg/kg/infusion (r = 0.25, n.s. ). Long term Alterations in Risky Decision making as a Result of Cocaine Self Administration Following cocaine (or sucrose) SA as described above, rats were r eturned to their home cages and remained abstinent for the remainder of the experiment. After 3 weeks they were food restricted and retrained in the RDT for an additional 20 daily sessions Final RDT performance was recorded during the last 5 RDT test sessions ( following 6 weeks of cocaine abstinence ) at which point rats had regained stable behavior (as described above) RDT data ( percent choice of the large, risky reward) were analyzed using a 3 f actor ANOVA (time [pre vs. post SA] x SA condition [cocaine vs. sucrose SA] x block). This analysis did not reveal m ain effect of time (F (1,21) = 1.52, p > 0.2 ), but did reveal main effects of SA condition (F (1,21) = 4.45, p < 0.05) and block (F (4,84) = 39.23, p < 0.0001) as well as interactions between SA condition and block ( F (4,84) = 3.12, p < 0.05 ) and between time, SA condition, and block ( F (4,84) = 5.29, p < 0.001). Most importantly, however, ther e was a significant interaction between time and SA condition ( F (1,21) = 6.48, p < 0.05 ), such that the difference between rats that underwent cocaine and sucrose SA was different in the pre vs. post SA periods. To further investigate these effects, follow up 2 factor ANOVAs (SA condition x block) were used to compare rats in each SA condition during the pre and post SA periods. Whereas
51 there was no difference between drug conditions pre SA (see statistics above) f ollowing SA, there was a significant main effect of SA condition such that cocaine SA rats chose the large, risky reward significantly more than sucrose SA rats (main effect of SA condition, F (1,22) = 8.51 p < .01 ; interaction between SA condition and block F (4,88) = 12.80 p < .0001 ) (Figure 3 3) Additional comparisons of pre vs. post SA performance within each SA condition revealed that rats in the cocaine SA group significantly increased their choice of the large, risky reward from pre to post SA (F (1,8) = 7.19 p < .05) whereas sucrose SA rats did not (F (1,13) = 0.99 p > 0.3) Interestingly within the sucrose SA group there was a significant interaction between time and block ( F (4,52) = 4.22 p < 0 .05) indicating that as adults rats shifted their preference to the small, safe reward more rapidly than they did in adolescence (Figure 3 4) To determine whether the elevated choice of the large, risky reward following cocaine SA was related to the amoun t of cocaine consumed a Pear was conducted between mean choice of the large, risky reward (post SA) and cumulative cocaine intake. There was no significant relationship between these two variables ( r = 0 .20 p > 0 .6). Activity Measures B aseline locomotor activity was measured during the inter trial intervals ( when no lights or levers were present ) during the choice sessions in the RDT There were no differences between cocaine and sucrose SA groups, either pre or post SA (Pre: t (21) = 1.31, n.s. ; Post: t (20) = 0. 45, n.s. ). Shock reactivity (measured as the locomotor activity during the 1 s shock period) was also compared between cocaine and sucrose SA groups. There were no differences between groups pre SA (t (21) = 0.38 n.s. ) or post SA (t( 20) = 0.16, n.s. ). Bas eline locomotor activity in cocaine SA rats post SA was near significantly correlated with the total amount of cocaine intake (r = 0.64, p = 0.06);
52 however s hock reactivity in cocaine SA rats post SA was not correlated with cocaine intake (r = 0.15 n.s. ) (see Table 3 3) Moreover, n either locomotion n or shock reactivity during adolescence correlated with cocaine intake ( locomotion: r = 0.10, n.s. ; shock reactivity: r = 0.47 n.s. ). Other Variables At no time point (during adolescence, during cocaine SA or during the post SA sessions) did body weight correlate with choice preference in the RDT or cocaine intake 0.34 to 0.36 ). Adolescent choice of the large, risky reward in the RDT was correlated with preference in the task as adults after sucros e SA (r = 0 61 p < 0 .05) but not after cocaine SA (r = 0.11, n.s. ) (see Tables 3 3 and 3 4) Omissions (omitted choice trials) were very low in both cocaine and sucrose SA rats upon return to the RDT (0.08% and 0.09% respectively). Discussion This stud y is the first to investigate trait like behaviors in adolescent rats that may predict future cocaine SA and to examine long term effects of cocaine SA on risky decision making. The results suggest that high levels of risk taking i n adolescence may be indicative of increase d vulnerability to cocaine use and that cocaine use itself in turn can cause long lasting elevat ions in risk taking that are present even after 6 weeks of abstinence. The finding that elevated risk taking in adolescence is a pre dictor of future cocaine SA is consistent with both human and animal literature m easuring behavioral disinhibition Human studies have shown that adolescents who display greater impulsivity, risk taking, and sensation seeking also display gre ater rates of substance use ( Adriani et al., 1998 ; Arnett, 1999 ; Spear, 2000 ; Adriani and Laviola, 2003 ;
53 Chambers et al., 2003 ; Stansfield et al., 2004 ; Stansfield and Kirstein, 2006 ) Studies in rats have shown that both impulsive action and impulsive c hoice in adults can predict cocaine SA (Perry et al., 2005; Dalley et al., 2007; Perry et al., 2008) For example, Anker et al. (2009) found that impuls ive choice, as measured by a delay discounting task, predict ed escalation o f cocaine SA, such that rats that preferred the smaller, immediate reward also escalated their cocaine intake when they were switched from short access (2 h/day) to long acces s (6 h /day) conditions, whereas rats that preferred the large, delayed reward did not. We did not observe evidence of escalation of cocaine intake in our rats, and hence this study cannot assess relationships between risk taking and escalation Moreover, we did not find any relationships between adolescent risk taking and cocaine self administration during the 0.3 mg/kg/infusion dose as the dose was too low to elicit continuous responding. Moreover, we did not see relationships between adolescent risk taking and the high 1.0 mg/kg/infusion dose as by time this both risk raking or risk averse rats were self administering cocaine at equivalent levels. The finding that cocaine SA can cause long lasting elevations in risk taking in the RDT may appear to contradict pr evious data from our laboratory w hich investigated the effects of cocaine SA in rats on another measure of risky decision making (the probability discounting task) In this task rats ch ose be tween a small, certain reward and a large uncertain reward. Prior cocaine SA had no effect on choice performance in this task and although it is not clear why chronic cocaine increased risk taking in the RDT but not the probability discounting task, this difference may be related to the form of the adverse consequ respectively). Importantly, however, the present finding that chronic cocaine SA
54 increased risk taking is consistent with a large body of literature showing that chronic cocaine causes lasting alterations in other forms of decision making in rats (particularly increases in impulsive choice (Simon et al., 2007a; Dandy and Gatch, 2009; Mendez et al., 2010) ). The present work is also consistent with studies using human s ubjects which have found that cocaine dependent individuals display increases in impulsivity in the Delay Discounting task ( Coffey et al., 2003 ) decreased inhi bition (impulsive action) in the Stop Signal task ( Fillmore and Rush, 2002 ; Li et al., 2006 ) and in creased risk taking in the IGT (Bechara et al., 2001; Bolla et al., 2003) suggesting that cocaine use can indeed result in maladaptive decision making. The cognitive mechanisms whereby chronic cocaine caused the lasting increase in choice of the large, risky reward are unclear. Numerous studies however, have show n that follo wing chronic drug use, the ability to rapidly adapt beh avior to changing task contingencies can be impaired, resulting in rigid, inflexible performance For example, reversal learning requires an individual to first learn one set of contingencies ( e.g A = X, B = Y), then the contingencies are reversed (e.g. A = Y, B = X) and the individual is adapt to the new contingencies. Studies in rats, monkeys, and humans have consistently shown that whereas the ability to learn the first set of contingencie s is unaffected by chronic cocaine administration, the ability to shift behavior when the contingencies are reverse d is impaired (Grant et al., 2000; Jentsch et al., 2002; Schoenbaum et al., 2004; Calu et al., 2 007; Krueger et al., 2009; Porter et al., 2011) Performance in the RDT cou ld b e argued to require some degree of behavioral flexibility and although such flexibility might not technically be considered
55 reversal learning, it will be interesting in future work to determine the relationships between cocaine induced alterations in RDT p erformance and reversal learning. A s adults, sucrose SA rats shifted their preference to the small, safe reward more rapidly over the course of the 5 blocks of trials than they did in adolescence This pattern of behavior, in which adults appear to show gr eater risk aversion than adolescents, is also found in humans (Doremus Fitzwater et al., 2012) ; however this fin ding should be interpreted with caution, as there was no main effect of age on choice, and the two test sessions were conducted 3 months apart It would be beneficial in future studies to further investigate this question by directly comparing adolescent a nd adult performance using a between subjects design. It will also be important in future work to determine whether risk taking in adulthood predict s subsequent acquisition of cocaine SA or whether the relationship between risk taking and cocaine SA is li mited to adolescence A growing literature has implicated D2 like receptors in both cocaine use and decision making. In p revious research i n our laboratory acute systemic administration of the D2 like agonist bromocriptine resulted in a dose dependent decrease in preference for the large, risky reward in the RDT (Simon et al., 2011) Impu lsive action (in the 5CSRTT) predicts acquisition of cocaine SA in rats and D2 like receptor availability in the ventral striatum is correlated with performance on the 5CSRTT suc h that rats with lower D2 like receptor availability show greater impulsive action ( Dalley et al., 2007 ) Furthermore, cocaine SA itself can cause long lasting decreases in D2 like receptor availability in the striatum in rhesus monkeys ( Nader et al., 2006 ) ; such decreases in striatal D2 receptor availability are similar to those seen in human cocaine
56 dependent patients ( Volkow et al., 2001 ) D2 like receptors in the striatum have also been implicated in mediating choice behavior in a rat version of the IGT and as well as in several form of behavioral flexibility (Winstanley et al., 2006; Drew et al., 2007; Haluk and Floresco, 2009; Laughlin et al., 2011; Markett et al., 2011) In addition, a recent pharmacological study show s that D2 receptor antagonists do not affect the ability to learn initial stimulus outcome associations (e.g. light = food reward) but impair subsequent reversal le arning (Lee et al., 2007) Mor eover, site specific microinjections of a D2 agonist into the nucleus accumbens results in deficits in reversal learning as well (Haluk and Floresco, 2009) Finally D2 availability in the striatum in monkeys correlates with performance on a reversal learning task, such that all animals learn the initial stimulus outcome paring s but animals with lower striatal D2 availability show poorer performance once the stimulus outcome contingencies are reversed (Groman et al., 2011) Taken together, these data suggest that D2 like receptors with in the striatum may both modulate choice be havior in the RDT and predict acquisition of cocaine SA In addition, c hronic c ocaine exposure can result in a reduction of D2 like receptors in the striatum which would be expected to result i n increased behavioral disinhibition and decreased behavioral flexibility. Such cocaine induced alterations in D2 like receptors could thus account for the long lasting elevations in risk tak ing seen after cocaine exposure. Limitations & Future Directions : This is the first animal study to investigate adolescent risk taking as a predictor of future drug SA. Because adolescent and adult risk taking are correlated, it would be predicted that adult risk taking would also be predictive of cocaine SA; however, it remains to be determined whether the relationship
57 found here is specific to adole scent development. Anker et al. (2009) and Broos et al. (2012) found that in adult rats impulsivity can predict several aspects cocaine SA in addition to acquisition, including escalation of cocaine intake, resistance to extinction, and propensity to relapse. Future studies will be needed to determine whether adolescent (or adult) risk taking is also a predictor of these factors. The results of Experiment 1 also demonstrate that cocaine SA can cause long lasting e levations in risk taking. L iterature investigating the effects of cocaine SA on another element of behavioral disinhibition (impulsive choice) have been mixed (e.g. (Anker et al., 2009; Mendez et al., 2010; Broos et al., 2012) ) with s ome studies reporting substantial increases in impulsive choice and others reporting no effects. These discrepancies may be due to the amount of cocaine consumed in these studies. For example, a recent study from our laboratory has shown that low levels of cocaine SA do not seem to alter impulsive choice whereas high levels of cocaine SA result in a sub stantial increase in impulsive choice (Weiss et al., 2012) With this in mind, it will be of interest in future work to determine if there is a similar relationship between the amount of cocaine consumed and risk taking, such that high but not low levels of cocaine intake result in increased risk taking. It w ill also be interesting in future work to investigate the relationships between other drugs of abuse and risk taking to determine w hether risk taking predict s their SA and/or whether consumption causes long term alterations in risk taking. Previous results from our laboratory showed that acute systemic administration of either nicotine or d amphetamine resulted in decreases in risk ta king (Mitchell et al., 2011) Preliminary data from our laboratory suggest that chronic experimenter administration of d
58 amphetamine does not result in alterations in risk taking (unpublished findings); however, as mentioned above, passive (experimenter administered) and active (SA) drug administration can have differential effects on behavior. Notably, t here is some evidence that the relations hips between components of behavioral disinhibition and drug SA may be different for different drugs of abuse; for example, impulsive action predicts high levels of cocaine SA (Dalley et al., 2007) whereas it does not predict heroin SA (McNamara et al., 2010) It will be important in future work to determine whether the se differences are present with risk taking as well. Finally, w hile this study investigated relationships between risk taking and cocaine SA solely at the behavioral level, it will be critical in future work to understand the underlying mechanisms which me diate these relationship s To that extent, i t would be of great interest to determine whether D2 like receptors play a role in modulating the relationships between risky decision making a nd cocaine SA. This question was addressed in Experiment 2.
59 Figure 3 1 Individ ual Variability in RDT Performance During Adolescence (Pre SA) Each line represents the adolescent performance of one rat in the RDT P ercent choice of the large, risky reward is s hown on the y axis; risk of p unishment is shown on the x axis.
60 Figure 3 2 Adolescent Risk Taking Predicts Cocaine S elf A dministration in Adulthood. Adolescent performance in the RDT averaged across the 5 choice blocks (x axis) significantly predicted the average cocaine intake per day ove r the 5 days of 0.5 mg/kg/infusion cocaine SA (y axis)
61 F igure 3 3 Cocaine Self Administration Causes Long Lasting Elevations in Risky Choice. The graph on top demonstrates that there were no differences in adolescent performance between groups prior to cocaine or sucrose SA. The graph the on bottom shows that there were long lasting (6 weeks into abstinence) elevations in risk taking after cocaine SA compared to sucrose SA.
62 Figure 3 4 Cocaine Self Administration Causes Long Lasting Elevations in Risky Choice. Cocain e SA rats (above) became significantly more risk taking even after 6 weeks of abstinence (closed circles) compared to their pre SA adolescent performance (open circles). Sucrose SA rats (bottom) did not shift their preference overall in adulthood (closed c ircles) in comparison to adolescence (open circles); however, they did shift their preference for the small, safe reward more rapidly (at lower levels of risk of punishment) in adulthood than they did in adolescence.
63 Table 3 1. Locomotion Values for Adole scent RDT Performance Locomotion Shock Reactivity Adolescent RDT Performance 188.67 (11.2) 2.98 (0.1) Pre Cocaine SA 170.58 (16.0) 2.9 (0.1) Pre Sucrose SA 200.29 (14.9) 3.02 (0.2) denotes a significant effect at p < 0.05. Standard error of the mean is in parenthesis. Table 3 2. Locomotion Values for Adult Post SA RDT Performance Locomotion Shock Reactivity Post Cocaine SA 289.21 (47.6) 3.52 (0.1) Post Sucrose SA 266.98 (24.4) 3.48 (0.2) denotes a significant effect at p < 0.05. Standard error of the mean is in parenthesis. Table 3 3. Correlations Summary Table for Cocaine Intake denotes a significant effect at p < 0.05. Table 3 4. Correlations Summary Table for Adolescent RDT Performance denotes a significant effect at p < 0.05.
64 CHAPTER 4 EXPERIMENT 2 : TO CHARACTERIZE THE HYPOTHESIZED RELATIO NSHIP BETWEEN D1 AND D2 RECEPTOR M RNA EXPESSION AND RISKY DECISION MAKING Introduction The results of E xperiment 1 demonstrate d that adolescent risk taking can predict the propensity for cocaine SA in adulthood. Understanding the mechanisms that may underlie this relationship may hold promise for reducing such behaviors through new developments in pharmacological or behavioral treatments. Dopaminergic signaling in both the prefrontal cortices and s triatum, has been implicated in mediating both risk taking behaviors (Bechara et al., 1994; Bechara et al., 1996; Bechara et al., 1997; Bechara et al., 1999; Bechara et al., 2001; Simon et al., 2011) and cocaine SA (Dalley et al., 2007) There are 5 different dopamine receptor subtypes, which can be c lassified as either D1 like (D1 & D5), which are excitatory or D2 like (D2, D3, & D4), which tend to be inhibitory D1 and D2 dopamine receptors are the most abundant subtype found in the brain and have been studied extensively (for comprehensive review see ( Beaulieu and Gainetdinov, 2011 ) ). Therefore investigating D1 and D2 mRNA expression within the prefrontal cortices (specifically the OFC and M PFC) and the striatum is a critical starting point in attempting to understand the u nderlying mechanisms that may be mediate the relationship between adolescent risk taking and the propensity for future cocaine SA in adulthood. Methods Subjects Male Long Evans rats (n=12, P 26; Charles River Laboratories, Raleigh, NC) were individually hou sed and kept on a 12h light/dark cycle (lights on at 0800 hours) with free
65 access to food and water except as noted. During behavioral testing, rats were maintained at 85% of their free feeding weight, with allowances for growth. In adolescent rats free f eeding weight was adjusted every 4 days to account for growth using the Long Evans growth chart provided by Charles River. All animal procedures were conducted during the light cycle (0800 1700) and were approved by the University of Florida Institutiona l Animal Care and Use Committee and follow ed NIH guidelines. R ats were trained as adolescents in the RDT as in Experiment 1 and were then sacrificed at P70 Isotopic in situ hybridization was performed to assess regio na l l y specific levels of D1 and D2 mRNA abundanc e, which was then compared with RDT performance. Tissue Preparation Rats were euthanized with 100 mg/kg sodium pentobarbital, then transcardially perfused with 0.1M phosphate buffer followed by 4% paraformaldehyde in 0.1 M phosphate buffer. Brain s were removed and stored in 4% paraformaldehyde solution overnight, then post fixed in 4% paraformaldehyde/20% sucrose for 24 h. Brains were then rapidly frozen on dry ice and stored at 80 until sectioning. Brains were sectioned in the coronal plane on a slidi ng microtome, and sections (30 m) collected in a 1 in 6 series beginning at the anterior portion of prefrontal cortex (5.2mm from B regma, according to (Paxinos and Watson, 2008) and ending posterior to the nucleus accumbens ( 0.26 mm Bregma). Probe preparation D1 and D2 receptor probes were targeted to transcript sequences with minimal homology to other dopamine receptor subtypes. The D1 probe spanned nucleotides 1625 to 1968 of t he D1 mRNA reference sequence (G enbank accession NM_012546).
66 The D2 probe spanned nucleotides 1630 to 2016 of the cor responding reference sequence (G enbank accession MN_ 012547). PCR amplified products from rat striatal cDNA were cloned into pGEM7zf+ plasmids as in (Haberman et al., 2011) The specificity of both probes was assessed through BLAST homology searches and in situ hybridization competition assays. The radiolabeled antisense cRNA probe was transcribed with T7 RNA polymerase in the presence of 35 S labelled UTP as per the MAXIscript in vitro transcription kit (Ambion). I n Situ Hybridization Free floating tissue sections were washed in 0.75% glycine in 0.1 M phosphate buffer pH 7.2 (PB) and 0.1 M PB alone to remove excess fixative. Sections were treated for 30 min at 37 C with proteinase K (1 mg/mL in 0.1 M Tris buffer containing 0.05% SDS), acetylated in 0.25% acetic anhydride in 0.1 M triethanolamine, pH 8.0, and rinsed twice in 2 saline sodiu m citrate buffer (SSC; 1 SSC = 0.15 M sodium chloride and 0.015 M sodium citrate, pH 7.0). Tissue was then hybridized for 20 h at 60 C in solution containing 50% formamide, 1 Denhardt's solution, 10% dextran sulphate, 4 SSC, 0.25 mg/mL yeast tRNA, 0 .3 mg/mL herring sperm DNA, 100 mm dithiothreitol and the 35 S labelled D1 or D2 cRNA at a final concentration of 1 10 7 CPM/mL. Following hybridization, sections were washed at 30 min intervals, twice in 4 SSC, once in 50% formamide/2 SSC at 60 C and then treated with ribonuclease A (20 mg/mL in 10 m M Tris saline buffer containing 1 m M ethylene diaminetetracetic acid) for 30 min at 37 C. Tissue sections were then washed further in descending concentr ations of SSC buffer containing 100 m dithiothreit ol to a final wash of 0.1 SSC and mounted onto gelatin coated slides for film autoradiography. Air dried sections of the sections were exposed along with 14 C standards (American Radiolabelled Chemicals Inc., St. Louis, MO, USA)
67 to Kodak max hyperfilm ( Perkin Elmer, Waltham MA ). Because dopamine receptor mRNA is less abundant in prefrontal cortex than in striatum, brain sections containing prefrontal cortex were exposed for 1 week while the tissue containin g striatum were exposed for 72 hours. Films wer e developed using Konica SRX 101A developer and fixed with Kodak rapid fixer Relative D1 and D2 mRNA abundance was quantified by densitometric analysis using Densita imaging software (MBF Biosciences, Williston, VT). Hybridization densities were linearized and calibrated relative to the 14 C labelled standards that were exposed to each film along with tissue sections. Multiple measures were obtained from 4 6 sections per brain region per rat For each brain structure analyzed, these values were ave raged to provide an individu al mean hybridization density (n Ci/ m g protein) per region in each rat These means were used for correlations and group comparisons. For regional analyses, prefront al cortex was divided into two subregions based on (Paxinos and Watson, 2008) : orbitofrontal (OFC) and medial prefrontal ( M PFC) (which included infralimbic, prelimbic, and anterior cingulate cortex. Dors olateral (DLS) and dorsomedial striatum (DMS) and nucleus accumbens core (NAC C ) and shell (NAC SH ) regions were also analyzed separately. Data Analysis Raw behavioral data files were exported from Graphic State software and compiled using a custom macro written for Microsoft Excel (Dr. Jonathan Lifshitz, University of Kentucky). Statistical analyses were conducted in SPSS 20 Stable performance in the RDT was defined by the absence of a main effect of session, the absence of an interaction between session and trial block, and the presence of a main effect of trial block within a repeated measures ANOVA over a 5 session period
68 (Winstanley et al., 2006; Simon et al., 2009a; Simon et al., 2010) In all cases, p values adolescent performance on the RDT (mean percent choice of the large, risky reward averaged across all 5 trial blocks ) with D1 and D2 hybridizatio n signals Results In order to begin to understand the underlying mechanisms mediating the relationships between adolescent risk taking and the propensity for future drug use, we investigated the expression of D1 and D2 mR NA in the prefr ontal cortex and st riatum (orbitofrontal cortex [OFC], medial prefrontal cortex [ M PFC], dorsomedial striatum [D M S], dorsolateral striatum [DLS], nucleus accumbens core [NAC C ], and nucleus accumbens shell [NAC SH ]) of rats behaviorally characterized in the RDT (see Figure 4 1 for behavioral characterization) Sample hemisections, as well as the regions analy zed, are displayed in Figure 4 2 Relationship s B etween D1 Dopamine Receptor Expression and Risky Decision making : There was a significant inverse linear correlation between adolescent performance in the RDT (mean percent choice and the large risky reward) and D1 mRNA expression in the DMS (r = 0 .62 p < 0 .05 Figure 4 3 [top] ) and a near significant inverse linear cor relation in the DLS (r = 0.57 p = 0 .053 Figure 4 3 [bottom] ). These d ata indicate that lower D1 mRNA expression in either the DMS or DLS is associated with a greater pre ference for the large, risky reward There were no significant relationships between adolescent RDT performance and D1 mRNA expression in the NAC C NAC SH M PFC, or OFC 0.31 ) Relationship s B etween D2 Dopamine Receptor Expression and Risky Decision making : There was a significant inverse linear correlation between
69 adolescent performance in the RDT (mean percent choice of t he large risky reward) and D2 mRNA expression in DLS (r = 0.75 p < 0 .01 Figure 4 4 [top] ) and in NAC SH (r = 0.72 p < 0 .01 Figure 4 4 [bottom] ). These data indicate that lo wer D2 mRNA expression in both the DLS and NAC SH is associated with a greater preference for the large, risky reward There were no relationships between adolescent RDT performance and D2 mRNA expression in the DMS, NAC C M 0.17 ) Discussion Striatal Dopaminergic Mediation of Risky Decision mak ing : There was a significant relationship between mean choice of the large, risky reward in the RDT in adolescence and D1 receptor mRNA expression in the DMS (and a near significant correlation in the DL S ) such that lower D1 expression in both of these regions was associated with greater preference for the large, risky reward. There were also significant relationships between mean choice of the large, risky reward in the RDT in adolescence and D2 receptor mRNA expression in the DLS and NAC SH such that l ower D2 expression in both of these regions was associated with greater preference for the large, risky reward. Therefore adolescent choice behavior in the RDT is inversely related to both D1 and D2 mRNA expression in the striatum suggesting that dopamin ergic signaling in the striatum may modulate risk taking behavior. T he dorsal striatum has been traditionally associated with habitual learning and memory rather than complex behavior or decision making based on multiple cues and contingencies ( Everitt et al., 2008 ; Packard, 2009 ) More recent evidence, however, suggests that the dorsal striatum may in fact contribute to action selection and flexible decision making ( Balleine et al., 2007 ; Johnson et al., 2007 ) For example rats with DMS lesions are able to learn action outcome associations, such as pressing a lever for
70 access to a sucrose solution; however, these rats lack the sensitivity to shift behavior when rewards are devalued or during extinction conditions (Yin et al., 2005) S uch findings, together with those from the current experiment, suggest the dorsal striatum as a region that may play a pivotal role in the cost benefit decision making process. Furthermore, the c urrent data are also consistent with previous findings from our laboratory in which dorsal striatal D2 mRNA expression was inversely related to performance in the RDT in adult rats (Simon et al., 2011) s uch that rats with lower D2 mRNA expression in the dorsal striatum also prefer riskier options in the RDT. The findings in the current study expand upon our previous wor k, by showing that dopamine signaling in both the dorsomedial (DMS) and dorsolateral (DLS) striatum are associated with risky decision making albeit through different receptor mechanisms within the two subregions The DMS is part of the neural circuitry that detects changes in action outcome contingencies and value based decision making (Samejima et al., 2005; Yin et al., 2006; Kim et al., 2009) and its ability to do s o is dopamine dependent (Lex and Hauber, 2010a, b) Dopaminergic signaling in the DMS is also involved in behavioral d isinhibition as site specific microinjections of a D1 antagonist into the DMS during a stop signal task in rats improved stop signal reaction time (Eagle et al., 2011) One important thing to note is that D1 receptors have been heavily implicated in mediating cocaine SA D1 receptor knockout mice do not SA cocaine (Caine et al., 2007) In addition dopamine transmission in the DMS is required for the initial preference or acquisition, of goal directed cocaine seeking (Murray et al., 2012) Considering these data together, it may be the case that D1 signaling within the DMS mediates the relationship between risky
71 decision making in adolescence and the propensity for cocaine SA in adulthood (i.e. D1 mRNA expression in the DMS was associated with adolescent risky decision mak ing and with the acquisition of SA) Importantly once preference for cocaine SA is acquired cocaine seeking is no longer dependent on the DMS, becomes dependent upon the DLS (Murray et al., 2012) In this light, i t would be of great interest to analyze the brains of the rats that underwent cocaine or sucrose SA to determine if there are cocaine induced changes in dopamine receptor mRNA expression in the DLS. D2 signaling in the DLS has been linked to avoidance learning, in a conditioned avoidanc e task (Boschen et al., 2011) in which rats are trained in a two chamber shuttle box and are required to cross into the opposite chamber to avoid shock. In this experiment, D2 receptors were activated via direct microinjection of the D2 agonist quinpirole both pre and post trainin g. A ctivation of D2 receptors in the DLS led to increased avoidance in test sessions (post training) but not training trials (pre training) The same study also investigated the role of D2 signaling within the nucleus accumbens and found that there was in creased avoidance with direct microinjections of quinpirole in both the training trials and the test session (Boschen et al., 2011) These findings suggest that D2 signaling in the nucleus accumbens is important for fast adaptation and response to unconditioned and conditioned aversive stimuli as pharmacological activation of D2 receptors caused alterations in avoidance in both training trials (fast adaptation) and test sessions (based on previous experiences) whereas D2 signaling in the DLS is important for a slower learning p rocess based on previous experiences as D2 activation only resulted in increased avoidance in the test sessions These data are particularly interesting because our results show that there is also a relationship
72 between D2 mRNA expression within the nucleu s accumbens (specifically the shell subregion) and adolescent choice of the large, risky reward. The previously mentioned study did not specify which region of the nucleus accumbens was involved in D2 mediated enhancement of avoidance response, but taken t ogether wit h our data it would suggest that D2 activation within the NAC SH away from adverse consequence s and toward the small, safe reward. The nucleus accumbens (as a whole) is involved in the representation of both rewarding and aversive outcomes (Schoenbaum and Setlow, 2003; Setlow et al., 2003; Sugam et al., 2012) both of which are factors in the RDT Additionally, the nucleus accumbens has been found to mediate perf ormance in several other cost benefit decision making tasks (Cardinal et al., 2001; Cardinal and Howes, 2005; Hauber and Sommer, 2009; Sugam et al., 2012) F or example, in a probabili ty discounting task, ( in which the delivery of the large reward becomes more uncertain as the task progresses, but the small reward is always delivered ) the nucleus accumbens plays a role in determining optimal responses when the reward outcome is uncertain (Stopper an d Floresco, 2011) The core subregion seems to play a role in mediating goal directed behavior in effort discounting tasks (in which rats must overcome an obstacle for a large reward verses cho osing a small reward with easier access) and in tasks measur ing impulsivity ( i.e. delay discounting) (Pothuizen et al., 2005; Pattij et al., 2007) In addition, a recent study by Besson et al. (2010) investigated the role of D2 receptors in both the NAC C and NAC SH in mediating impulsive action as measured by the 5CSRTT As mentioned previously, Dalley et al. (2007) found that individual variability in D2 like receptor availability in the ventral striatum corresponded to individual variability in
73 impulsive action such tha t rats with lower D2 availability showed greater impulsive action Besson et al. (2010) examined whether the individual variability in ventral striatal D2 expression and impulsive action was due to the NAC C or NAC SH by direct microinjections of a D2 like antagon ist into each sub region. They found that the antagonist infused into the NAC C produced a decrease in impulsive action but injections into the NAC SH pro duced an increase in impulsive action. These data suggest that lower D2 levels in the NAC SH are indicative of greater impulsive action which is similar to our finding that lower levels of D2 mRNA expression in the NAC SH are indicative of greater risk taking behavior in adolescence. Importantly low levels of D2 receptor availability in the ventr al striatum are associated with stimulant use (Volkow et al., 2001; Nader et al., 2006; Dalley et al., 2007) Considered together these data suggest that low D2 receptor availability within the ventral striatum ( which is possibly spe cific to the NAC SH based on the low D2 mRNA expression in the current study ) of risk preferring adolescent rats may also underlie their increased propensity to SA. Prefrontal Dopaminergic Mediation of Risky Decision making : T here were no significant relationship s between D1 and D2 receptor mRNA expression in two subregions of the prefrontal cortex (OFC and M PFC) and risky decision making. This was somewhat surprising as the OFC is a region implicated in representation of both reward and punishment as well as the integration of such information to guide complex decision making processes (McCabe et al ., In Press; Rolls, 2004; Schoenbaum et al., 2006; Schultz, 2007; Morrison and Salzman, 2009) In addition, p revious research from our l aboratory showed non linear relationship s between D2 mRNA expr ession within both the OFC and M PFC and individual variability in the RDT in adult rats (Simon et al.,
74 2011) such that either high (OFC) or low ( M PFC) levels of D2 mRNA expression were indicative of either risk preferring or risk averse performance respectively (i.e either extreme) Similar analyses of non linear relationships were conducted on the present dataset, but no such relationships were revealed (data not shown). This outcome suggests that although prefrontal cortical D1 and D2 receptors may be involved in modulating behavio r in this task in adult rats (Simon et al., 2011) their roles may be less important during adolescence. The prefrontal cortex undergo es substantial changes during late adolescence and into early adulthood across species including both rats and humans (Sowell et al., 1999; Spear, 2000; L una et al., 2001; Sowell et al., 2001; Sowell et al., 2002; Monk et al., 2003; Sowell et al., 2003; Nagy et al., 2004; Barnea Goraly et al., 2005; Bonekamp et al., 2007; Asato et al., 2010; Luna et al., 2010; Van Leijenhorst et al., 2010b; Van Leijenhorst et al., 2010a; Sturman and Moghaddam, 2011b, a) and recent electrophysiological evidence suggests that activity in the prefrontal cortex is more variable during adolescence than adulthood. Sturman et al. (2011a) has suggested that when rats are required to perform a simple reward driven tas k, in which a simple action (e.g nosepoke) results in a reward, neuronal activation at both the population and sin gle unit levels in the prefrontal cortex of adolescent animals is variable and uncoordinated compared to adults Therefore, it may be that these prefrontal regions are still developing at P70 (when brains were collected ) and as a result, prefrontal dopamine receptor expression is too variable to correlate with or predict adolesce nt risky decision making Limitations & Future Directions : While our data suggest that dopamine receptor mRNA expression is associated with risky decision making, mRNA expression does not
75 always correlate with protein levels or receptor availability and it w ill be critical to determine protein levels and binding potential for these receptors in b ehaviorally characterized rats in future studies Binding potential in particular preferably using autoradiographical techniques, will preserve anatomical specificity and allow comparable analyses between mRNA expression and receptor availability I t will also be important in future work to determine the functional relevan ce of the relationships identified here. This can be determined by performing site specific intracerebral microinjections of agonists ( such as in Experiment 3) or antagonists at dopamine receptors in a regionally specific manner, to determine how risky dec ision making is affected. In addition, the online functional activity of these brain regions during actual decision making performance could be investigated using in vivo electrophysiological recordings in behaving rats It will also be of interest to examine dopamine receptor mRNA expression in the same brain regions examined here following cocaine and sucrose SA to determine if changes in RDT performance following cocaine SA are associated with changes in dop aminergic signaling known to be induced by cocaine SA (particularly reductions in striatal D2 receptors) (Volkow et al., 1991; Moore et al., 1998; Volkow et al., 2001; Franklin et al., 2002; Nader et al., 2006; Lane et al., 2010; Moreno Lopez et al., 2012) Finally, b ecause in situ hybridization requires postmortem tissue, determining the m echanisms that underlie relationships between adolescent risk taking and future cocaine SA must necessarily use a between subjects design in which only inferenc es can be drawn between dopamine receptor mRNA expression, risk taking, and cocaine SA I t would be ideal to be able to visualize dopamine r eceptor s within subjects across
76 the course of RDT training, cocaine SA, and RDT retraining Such data would require the use of positron emission tomography (PET) which would allow examination of dopamine receptor binding in live animals, and which would allow truly predictive relationships bet ween receptor binding and subsequent behavioral performance to be determined. Figure 4 1 RDT Performance of Adolescent Rats Used for In Situ Hybridization Analyses. This figure shows the individual variability seen in adolescent rats that were characterized in the RDT then sacrificed for in situ hybridization analyses for D1 and D2 mRNA expression. Each line represents data from a single rat.
77 Figure 4 2 Hybridization of R adiolabeled Dopamine mRNA in Prefrontal C ortex and S triatum Images fr om film autoradiograms show dopamine receptor mRNA exp ression in coronal sections through the prefrontal cortex (OFC & M PFC) (left) and striatum (DMS, DLS, NAC C NAC SH ) (right) Note the preferential expression of dopamine mRNA is in deeper layers of prefrontal cortex (Santana et al., 2009)
78 Figure 4 3 D1 mRNA Expression is Related to Adolescent RDT Performance. There was a significant negative correlation between mean choice of the large, risky reward in adolescence and D1 mRNA expression in the DMS (top) and a near significant negative correlation bet ween these two variables in the DLS (bottom).
79 Figure 4 4 D2 mRNA Expression is Related to Adolescent RDT Performance There were significant negative correlations between mean choice of the large, ri sky reward in adolescence and D2 mRNA expression in the DLS (top) and NAC SH (bottom), such that lower D2 mRNA expression is indicative of greater preference for the large, risky reward.
80 C HAPTER 5 E XPERIMENT 3 : TO FUNCTIONALLY TE ST HYPOTHESIZED CAUSAL RELA TIONSHIP BETWEEN DOP AMINE SIGNALING IN S PECIFIC BRAIN REGION S AND RISKY DECISION MAKING. Introduction The r esults from Experiment 1 show ed that adolescent risk taking is a predictor of future cocaine use in adulthood and results from Experiment 2 show ed associations between D1 and D2 dopamine receptor m RNA and adolescent risk taking behavior, ( specifically between D1 in the DMS and D2 in the DLS and NAC SH ). Previous work from our laboratory investigated the effects of acute systemic administration of D1 and D2 agonists and antagonists in the RDT and found that only the D2 agonist, bromocriptine, produce d alterations in choice behavior (specifically reductions in risk taking) (Simon et al., 2011) Other work suggests that D2 receptors specifically within the dorsal striatum are important for risky decision making (Simon et al., 2011) avoidance learning (Boschen et al., 2011) and behavioral flexibility (Winstanley et al., 2006; Lee et al., 2007; Groman et al., 2011) a nd therefore could mediate the relationship between adolescent risk taking and the propensity for cocai ne SA. Still o ther work suggest s that D2 receptors in the ventral striatum are important for mediating individual differences in impulsive action in the 5CSRTT and the relationship between ventral striatal D2 and impulsive action predicts the acquisition of cocaine SA (Dalley et al., 2007; Besson et al., 2010) ; hence, ventral striatal D2 receptors may also play a role in the relationship betwee n adolescent risk taking and pro pensity for cocaine SA. In order to begin to determine the functional relevance of the findings from Experiment 2 and to determine the role of striatal D2 receptors in modulating risk taking in the RDT, the D2 agonist quinpirole was directly microinjected into either the dorsal or ventral
81 striatum to determine the effects of direct activation of striatal D2 like receptors on risk taking. Methods Subjects Male Long Evans rats (n= 2 3 P 26; Charles River Laboratories, Raleigh, NC) were individually housed and kept on a 12h light/dark cycle (lights on at 0800 hours) with free access to food and water except as noted. During behavioral testing, rats were maintained at 85% of their free feeding weight, with allowances for growth. In adolescent rats free feeding weight was adjusted every 4 days to account for proper growth using the Long Evans growth chart provided by Charles River. All animal procedures were conducted during the light cycle (0800 1700) and were approved by the University of Flori da Institutional Animal Care and Use Committee and follow ed NIH guidelines. Experimental Design Rats were trained in the RDT as desc ribed in Experiment 1 (Chapter 3 ) until stable performance was achieved. They were then allowed to eat ad libitum for 5 da ys prior to surgery to implant bilateral guide cannuale targeting either the dorsal or ventral striatum (described in detail below) After surgery, t hey were allowed 5 days to recover before beginning retraining in the RDT and returning to 8 5% of their fre e feeding weight ( with allowances for growth ). Upon reestablishing stable performance in the task, rats received intra striatal injections of the D2 like agonist quinpirole prior to RDT testing to determine the involvement of D2 like receptors in modulatin g risky decision making.
82 Implantation of Bilateral Cranial Cannulae Ra ts were anesthetized with isofl u o rane gas and secured into a stereotaxic frame (Kopf Instruments; Tujunga, CA) fitted with atraumatic earbars, with the incisor bar set at 3.3 mm relativ e to the interaural line to provide a flat skull position. Bilateral guide cannulae (Plastics One, Roanoke, VA), which consisted of a plastic body holding two 22 gauge stainless steel cannulae 3.6 mm apart, were i mplanted relative to B regma (AP +1.5 mm, ML 1.8 mm,) and DV 2.8 mm for dorsal s triatum ( n = 11 ) and 4.8 mm for ventral s triatum (n = 1 2 ) from dura (Paxinos and Watson, 2008) Cannulae were secured to the skull with dental acrylic and stainless steel screws, and wire stylets (Plastics One, Roanoke, VA) were inserted to occlude the guide cannulae to prevent infection. Following surgery, rats recovered in their home cages for 5 days before retraining in the RDT Microinfusion P rocedure Stable performance (as described below ) was reestablished on the RDT before intracerebral infusions were performed. All rats received the D2 agonist quinpirole (0.1, 1.0, and 10 g in 0.5 L per hemisphere ) (Tocris, United Kingdom) or vehicle (artificial cerebral spinal fluid [ACSF] Harvard Apparatus, Holliston, MA) in a randomized counterbalanced order such that each rat received each dose of the drug Drugs were prepared fresh each test day. The infusion experiments were run on a cycle of baseline, drug, baseline, drug, baseline, drug, baseline, drug, baseline with one session per day Prior to the first int racerebral injection day, each rat was habituated t o cannula insertion procedures Rats received a 1 min (0.5 L ) infusion per hemisphere and the injector was left in place for a n additional 1 min after infusion to allow time for drug diffusion. Microinjections were delive red through bilateral 28 gauge inj ector s (Pla stics One,
83 Roanoke, VA) that were inserted through the guide cannulae and extended 2 mm beyond the tip s of the guide cannulae. Data Analysis Raw data files were exported from Graphic State software and compiled using a custom macro written for Microsoft Excel (Dr. Jonathan Lifshitz, University of Kentucky). Statistical analyses were conducted in SPSS 20. Stable behavior was defined by the absence of a main effect of session, the absence of an interaction between session and trial block, and the presence of a main effect of trial block within a repeated measures ANOVA over a 5 session period (Winstanley et al., 2006; Simon et al., 2009a; Simon et al., 2010) The effects of drug manipulat ions were assessed using two way repeated measures ANOVA, with both drug dose and trial block (i.e. risk of footshock ) as repeated measures variables. In all cases, p values less than .05 were considered significant. Assessment of Cannula Placement After behavioral testing was completed, rats were euth anized by intraperiotoneal injection of 100mg/kg sodium pentobarbital. Brains we re removed and stored in 4% formaldehyde solution for 48 hours, then post fixed in 4% formaldehyde/20% sucrose solution until sectioning. Tissue was sectioned in the coronal pl ane on a sliding microtome, and sections (6 0 m) were collected in a 1 in 2 series and mounted on slides. Sections were stained with Cresyl Violet coverslipped, and visualized using a microscope under conventional bright field illumination. Cannula tip pl acements were verified for both dorsal and ventral striatal infusion sites and mapped onto standardized coronal sections of the rat brain (Paxinos and Watson, 2008)
84 Results Rats were trained extensively in the RDT and were then implanted with cannula directed at either the dorsal or ventral striatum. Upon recovery, rats were retrained in the RDT and achie ved stable performance before dr ug testing began. T here were no main effects or interactions involving the factor of session across the test sessions interposed between drug testing days (Fs < 1.877 and p s > 0.133 ) suggesting that there were no carryover e ffects of t he drugs on choice performance ( i.e. performance remained stable across the baseline sessions ) Data from t he 10 g dose were excluded after analyses revealed that rats in both the dorsal and ventral striata l cannulation groups omitted over 45% and 38 % of all trials, respectively. Additionally, four rats were exclud ed after histological analysis revealed that their cannula placements were outside of the desired location (dorsal: n = 2, ventral n= 2) Microinjections of th e D2 like agonist quinpirole into the dorsal striatum did not alter choice of the large, risky reward in the RDT ( main effect of drug: F (2,16) = 0.97 n.s. ; drug x block interaction: F (8,64) = 0.87, n.s. Figure 5 1 ). However, microinjections into the vent ral striatum resulted in a dose dependent decrease in choice of the large, risky reward (main effect of drug: F (2,18) = 3.87 p < .05,drug x block interaction: F (8,72) = 0. 22 n.s. Figure 5 2 ), suggesting that D2 like receptors in the ventral striatum may modulate risk taking behavior and that an increase in D2 like receptor activity may bias behavior toward greater risk aversion There were no drug induced changes in locomotor activity during the shock period (shock reactivity) in either dorsal or ventral cannulated rats ( d orsal: F (2,14 ) = 1.24 n.s. ; v entral: F (2,16 ) = 0.39 n.s. ) (see Table 5 1) There was a significant change in baseline locomotion (locomotor activity measured during the pe riod between active trials ) in
85 ventral and a near significant change in dorsally cannulated rats ( ventral: F (2,18) = 3.77, p < 0.05 ; dorsal: F (2,16) 3.28, p = 0.06). Pair wise comparisons show ed a significant increase in baseline locomotion from vehicle injections compared with admi nistration of the low dose (0.1 g ) of quinpirole in both groups (dorsal and ventral) ( dorsal: t (8) = 2.74 p < 0.5; ventral: t (9) = 2.75 p < 0.5); however, there was no change in baseline locomotion between vehicle injections and the medium dose (1.0 g) (dorsal: t (8) = 0.80 n.s. ; ventral: t (9) = 0.69 n.s. ). Furthermore, there were no differences in baseline locomotion between the low (0.1ug) and medium (1.0 g) doses of quinpirole (dorsal: t (8) = 1.87 n.s. ; ventral: t (9) = 1.80 n.s. ). Discussion This is the first study to inv estigate the involv ement of striatal dopamine D2 like receptors in modulating choice behavior in the RDT. The results suggest that activation of D2 like receptors in the ventral striatum bia se s choic e behavior toward a more risk a verse pattern This findin g is consistent with the results of Experiment 2, which showed that rats with greater preference for the large, risky reward had lower D2 mRNA levels in the NAC SH It is also consistent with evidence that individuals with lower D2 like receptor availabili ty in the striatum ha ve higher rates of risk taking as measured by the IGT (Linnet et al., 2011a, b) a s well as with, previous work from our laboratory showing that acute systemic administration of the D2 agonist bromocriptine b iased choice behavior toward greater risk aversion (Simon et al., 2011) Finally, these data are consistent with findin gs that direct microinjections of the D2 like antagonis t nafadotride into the NAC SH produce an increase in impulsivity (Be sson et al., 2010) Moreover, these data are also consistent with findings that direct microinjections of quinpirole into the nucleus accumbens show that ve ntral striatal D2 receptors are critical for fast
86 adaptation to responding to aversive stimuli (Boschen et al., 2011) In the current experiment quinpirole was not infused into the NAC C or NAC SH subregions specifically; it will be of interest to conduct such studies in the future to dissociate the role of these subregions in modulating risky decision making. There were no alterations in risk taking with quinpirole administration into the dorsa l striatum which is surprising as previous data from our laboratory as we ll as data from Experiment 2 indicate that low levels of D2 mRNA in the dorsal striatum (especially the DLS) are associated with increased choice of the large, risky reward Inject ions of quinpirole into the DLS have also been shown to reduce nociception a nd increase avoidance behavior (Magnusson and Fisher, 2000; Boschen et al., 2011) Had quinpirole reduced nociception, one might suggest that preference for the large, risky reward would have increased as the shock might have become less noxious; however, q uinpirole injections into the dorsal striatum did not affect risky decision making or shock reactivity. However the injections in the present study did not target the DLS dir ectly, and thus more specific infusions into this subr egion of the dorsal striatum could have different effects. Importantly, these results were unlikely to have been due to drug induced alterations in food motivation, locomotor activity, or shock reactivity. We have shown previously that preference for the large risky reward is not affected by either 1 or 24 h of pr e feeding prior to testing (Simon et al., 2009a) and the effects of the drugs on locomotion and shock reactivity in the current experiments did not track their effects on reward preference in any obvious way (see Table 6 1) suggesting that the effects of quinpirole on these
87 preference For example, the lowest dose of quinpiro le (0.1 g/0.5 L per hemisphere ) resulted in an increase in locomotor activity in both the dorsal and ventral cannulated groups; however, there were no detectable alterations in risky decision making at this dose Moreover, there were no changes in locomo tion with administration of the medium dose of quinpirole (1.0 g/0.5 L per hemisphere ), but this dose resulted in reduced choice of the large, risky reward in the ventrally cannulated rats. Notably, the results obtained here stand in contrast to the incr ease in risk taking behavior produced by acute systemic administration of dopaminergic agonists and antagonists in oth er rodent tests of risk taking, in which reward omission (rather than For example, Zeeb et al. (2009) found that acute systemic administration of the D2 anta gonist eticlopride resulted in improved performance in a rat gambling task (designed to mimic the human IGT), such that rats biased their choice s away from high risk options This difference in the effects of dopaminergic agonists and antagonists likely reflects in part the nature of the costs associated with the large rewards i n these tasks. Although both reward omission and punishment have similar effects on choice behavior (reducing choice of the rewards with which they are associated), it is likely that punishment (even a mild footshock) is a more salient cost than reward omi ssion and that this underlies the difference in D2 modulation of risk taking within these two tasks (see also (St Onge and Floresco, 2009a) In conclusion, t he results of direct microinjections of the D2 like agonist quinpirole into the ventral striatum further support our previous behavioral and receptor mRNA ex pression data, by showing that activation of ventral striatal D2 like receptors
88 can reduce risk taking and that low levels of ventral striatal D2 receptors may play a causal role in high levels of risk taking Notably, c ocaine SA (which can cause reductio ns in striatal D2 receptors (Nader et al., 2006) ) caused long lasting elevations in risk taking (Experiment 1) Such cocaine induced decreases in D2 receptor expression could result in behavioral inflexibility (Groman et al., 2011) which could lead to a bias toward the large risky reward in cocaine SA rats (Lucantonio et al., 2012) Limitations and Future Directions : This study determined that administration of the D2 like agonist quinpirole into the ventral striatum resulte d in a decrease in preference for the large, risky reward I t will be interesting in future studies to determine whether this effect is mediated by the NAC C or NAC SH Preliminary analyses in which the cannula placements in the current study were separated by whether they were located in the core or shell suggest that placements in the shell were more effective than those in the core at reducing risk taking (data not shown) This observatio n is particularly interesting as results from Experiment 2 suggest that D2 mRNA expression especially in the NAC SH is related to preference for the large, risky reward in a dolescent rats, whereas there was no relationship between D2 receptor expression in the NAC C and adolescent preference for the large, risky reward. It would also be interesting to investigate the relationship between D3 recep tors and risk taking, as quinpirole can activate both D2 and D3 receptors. Within the ventral striatum, D3 receptor s are located specifically in the NAC SH Therefore, if the NAC SH is more important for mediating risk taking than the NAC C then quinpirole may be exerting its effects through both D2 and D3 receptors in this region. In addition i t would be of great inter est to perform direct microinjections of a D2 like antagonist into the ventral striatum to determine whether it
89 mimics the increase in risky decision making seen in the cocaine SA rats after SA. Such data wou ld help to determine whether nucleus accumbens D 2 like activity is sufficient or necessary for mediating risk taking behavior. The preponderance of published data linking risk taking, cocaine SA, and adolescent development, concerns the D2 receptor. R esults from Experiment 2 also showed relationship s b etween striatal D1 receptor mRNA expression in the DMS and adolescent preference for the large, risky reward, however and D1 receptors in the DMS have been implicated in mediating the initial preference for cocaine SA (Murray et al., 2012) Accor dingly, it will be of great interest to determine if D1 receptors within the DMS can modulate risk taking behavior. It may be that D2 receptors within the ventral striatum and D1 receptor s within the dorsal striatum mediate risk taking in a differential (o r complementary) manner Therefore, it will be of interest to determine the effects on risk taking if intra striatal microinjection s o f D1 receptor acting drugs.
90 Figure 5 1 RDT Performance After Dorsal Striatal Microinjection s of Quinpirole. Microinjections of the D2 agonist quinpirole had no effect on risky decision making.
91 Figure 5 2 RDT Performance After Ventral Striatal Microinjections of Quinpirole. Microinjections of the D2 agonist quinpiro le shifted choice behavior, in a dose dependent manner, toward a greater preference for the small, safe reward.
92 Table 5 1. Omissions, Locomotion, and Shock Reactivity during Quinpirole Microinjections Drug Percent of Choice Trials Omitted Locomotion (Locomotor units/ITI) Shock Reactivity (Locomotor units/1 s shock) Dorsal ACSF 22.5 (9.0) 186.28 (41.4) 2.66 (0.3) 0.1ug/side 7.8 (2.5) 339.36* (37.3) 2.57 (0.4) 1.0ug/side 18.6 (3.9) 243.64 (54.7) 2.88 (0.2) 10ug/side 45.3 (8.7) 107.81 (46.4) 3.25 (0.6) Ventral ACSF 13.0 (2.6) 261.42 (49.1) 2.80 (0.1) 0.1ug/side 15.0 (5.6) 456.91* (59.0) 3.09 (0.2) 1.0ug/side 27.0 (8.8) 308.99 (56.4) 2.80 (0.3) 10ug/side 38.0 (7.2) 132.74* (49.4) 2.13 (0.4) denotes a significant difference from the ACSF condition at p < .05. Standard error of the mean is in parenthesis.
93 CHAPTER 6 SUMMARY AND CONCLUSI ONS C hronic drug users display maladaptive decision making, including elevated risk taking. However i t h as been difficult to determine whether elevations in risk taking are a pre exist ing condition that might increase propensity for drug use or if they are caused by chronic d rug use. Experiment 1 used a rat model to demonstrate t hat adolescent risk taking predict s future cocaine SA in adulthood such that rats that preferred the large, risky reward in adolescence had greater cocaine intake during a cocaine SA acquisition parad igm In addition, this experiment demonstrated that cocaine SA itself can cause long lasting elevations in preference for the large, risky reward Thus, these data suggest that the elevated risk taking observed in chronic drug users may be both a pre exist ing condition and a consequence of drug (at least cocaine) use. In future work it would be of great interest to investigate the behavioral mechanisms that may underlie the individual differences in preference for the large, risky reward in the RDT. For exa mple, in delay discounting tasks, choice behavior can be influenced by two behavioral mechanis ms: sensitivity to del ay and sensitivity to reward These behavioral mechanisms can be differentially modulated by pharmacological agents (e.g. acute systemic nic otine administration results in increased impulsive choice in a delay discounting task, but when behavioral mechanisms are investigated independently, it is revealed that the increase in impulsivity is not a result of alterations in sen sitivit y to delay, b ut rather due to a decrease in sensitivity to the magnitude s of the reward s used in the task ) (Dallery and Locey, 2005; Locey and Dallery, 2009, 2011) However, as tasks become more complex, it becomes more difficult to disentangle the underlying behavioral mechanisms. In the RDT there are (at
94 least) three behavioral mechanisms that may influence choice: sensitivity to reward, sensitivity to probability, and sen sitivity to punishment. P revious work from our laboratory has investigated individual differences in reward motivation (willingness to exert effort to obtain reward) and pain tolerance (sensitivity to shock) (refer to Figure 1 12), and found that they are not correlated with RDT choice performance (Simon et al., 2011) However, the value of the small and large rewards in the RDT do differ (1 vs. 3 pellets respectively) and hence variation in sensitivity to the differences in reward magnitudes could still influence choice behavior In addit ion, as mentioned above, RDT performance could be influenced by sensitivity to the probability of shock delivery or the ability to detect the changes in probability across trial blocks Rats that are unable to detect the se changes in probability, but that are still sensitive to reward magnitude and punishment might show greater choice of the large, risky reward because they are less able to detect/respond to the increasing probability of punishment across trial blocks Finally, while pain sensitivity is no t associated with preference for the large, risky reward in the RDT (Simon et al., 2011) this does not rule out an in fluence of individual differences in sensitivity to pun ishment (i.e. the ability to process and respond to negative feedback ) For example, people with frontal cortical lesions have deficits in their ability to process negative feedback such that during IGT performance, they do not shift their behavior to choose safer decks even when they are consistently presented with loss, and more frequently choose risky decks in the IGT (Bechara et al., 1994; Bechara et al., 1996; Bechara et al., 1997; Bechara et al., 1999; Bechara et al., 2001) Each one of these factors may contribute to the individual differences shown in ado lescent RDT performance and different factors could contribute differentially in
95 different individuals After sucrose SA, rats in this group still show ed considerable v ariabilit y as was observed in adolescence and post sucrose SA perfo rmance was correlated with adolescent performance. A fter cocaine SA, however, the va riability was decreased dramatica lly such that all of the rats showed a strong bias toward the large ri sky reward. This result might narrow the behavioral mechanisms that may strongly drive RDT choice behavior after cocaine SA In particular there is a mounting body of lit erature suggesting that cocaine dependent subjects are insensitive to punishment (in that it has a reduced influence on their behavior) and display deficits in processing negative feedback similar to those found in patients with prefrontal cortex damage (Bechara et al., 2001; Bolla et al., 2003; Tucker et al ., 2004; Barry and Petry, 2008; Lane et al., 2010; Cunha et al., 2011) Suc h data suggest that under normal circumstances (e.g. prior to cocaine SA), several dif ferent behavioral mechanisms might influence choice behavior, whereas after cocaine SA, insensitivity to punishment might p lay a leading role in driving strong preference for the large, risky reward. Future studies that explicitly investigate associations between individual differences in RDT performance and sensitivity to reward, probability, and punishment will be useful for determining which of these behavio ral mechanis ms might drive choice behavior under different conditions Previous data from our laboratory and elsewhere suggest that both risk taking and drug use are strongly influenced by dopamine signaling (Volkow et al., 2001; Nader et al., 2006; Dalley et al., 2007; Simon et al., 2009a; Mitchell et al., 2011; Simon et al. 2011) Experiment 2 investigated how dopamine signaling may mediate the relationship between adolescent risk taking and cocaine SA by assessing D1 and D2 dopamine
96 receptor mRNA expression in sub reg ions of the prefrontal cortex and striatum in rats characterized in the RDT during adolescence. D1 mRNA expression in the DMS was negatively related to adolescent preference for the large, risky reward such that rats with less D1 mRNA expression in the DMS had greater preference for the large, risky reward. Interestingly, D1 signaling in the DMS has also been associated with early SA cocaine seeking (i.e. initial motivation to obtain cocaine) (Murray et al., 2012) The data from Murray et al. (2012) suggest that a decrease in D1 signaling attenuates cocaine seeking which stands in contrast to the findings in the pre sent study It is also important to note that unlike the present work, Simon et al. (2011) found a pos itive relationship between D1 receptor mRNA expression in the NAC SH and preference for the large, risky reward in the RDT (such that greater D1 mRNA expression was associated with greater risk taking). U nfortunately there are very few data available to pr ovide a context to better understand these effects (e.g. there has been little or no PET imaging of D1 receptors in the context of decision making or chronic drug use) Simon et al. (2011) recently showed that dorsal striatal D2 receptor mRNA expression was negatively correlated with adult preference for the large, risky reward in the RDT such that rats that showed greater preference for the large, risky reward had less D2 receptor mRNA expression in the dorsal striatum. Results from Experiment 2 are consistent with these previous data and expand upon them by narrowing the dorsal stria tal effect to the DLS (i.e. DLS D2 mRNA expression is inversely related to choice of the large, risky reward ) D2 receptor activity within the DLS has been implicated in avoidance learning in that DLS D2 activation enhances such learning (Boschen et al., 2011) These data suggest then that low levels of DLS D2 receptor expression m ay
97 result in reduced avoidance behavior and consequently increased choice of the large, risky reward. The results of Experiment 2 also show an inverse relationship between NAC SH D2 mRNA expression and adolescent preference for the large, risky reward Thi s result is particularly interesting as the NAC SH is part of the ventral striatum, which has been implicated in both risk taking and drug use. It was previously unclear in human studies (Volkow et al., 2001; Lee et al., 2009) whether low levels of striatal D2 binding in chronic drug users were a result of stimulant use or were a preexisting condition; however, Nader et al. (Nader et al., 2006) showed that ventral striatal D2 binding dec reased after cocaine SA in rhesus monkeys suggesting that low D2 like receptor availability in human cocaine users may be due in part to effects of cocaine itself Moreover, Dalley et al. (Dalley et al., 2007) found that D2 bindin g in the ventral striatum predict ed both trait im pulsivity and high rates of cocaine SA. Taken together with our data, it appears that low D2 expression in the ventral striatum, specifically the NAC SH may render individuals more vulnerable to both risk taking and cocaine use. Previous data from our labo r atory showed that acute systemic administration of a D2 like agonist, but not a D1 like agonist, shifted choice behavior toward a more risk averse pattern in the RDT. To investigate this further and to determine the functional and anatomical relevance of the D2 mRNA expression data from Experiment 2, in Experiment 3 the D2 like agonist quinpirole was microinjected into either the dorsal or ventral striatum prior to performance in the RDT to determine how D2 like receptor activation in these areas modulate s choice behavior. Consistent with the mRNA data from Experiment 2 D2 like receptor activation within the ventral striatum dose
98 dependently decreased preference for the large, risky reward, shifting behavior toward a more risk averse patter n. Thes e data further support the idea that low D2 expression within the ventral striatum may modulate choice behavior toward elevated risk taking and a greater propensity for cocaine use. Considered together, these data suggest that low levels of striatal dopam ine receptor act ivity, particularly during late adolescence/early adulthood may be a feature of several forms of maladaptive behavior, and furthermore that increasing striatal dopamine receptor activity may hold promise for reducing such behaviors. Howeve r, more work needs to be done not only to determine the role of striatal D1 receptor signaling in mediating the relationship between risky decision making and cocaine SA but also to determine how chronic cocaine alters dopaminergic signaling, which could play a causal role in cocaine induced elevations in risk taking. Variation in dopamine signaling (either preexisting individual differences or cocaine induced changes in dopamine) within the s triatum can have implications for various other structures and signaling pathways as the striatum is a major component of the basal ganglia. The basal ganglia are a group of nuclei which work together to form a functional c ircuit which underlies a variety of processes including cognition (e.g. behavioral disinhibition) (for reviews on the basal ganglia and its circuitry see (Nauta and Domesick, 1984; Gerfen, 2004; Chakravarthy et al., 2010; Sesack and Grace, 2010) ) The prima ry components of the basal ganglia are the striatum, globus pallidus, substantia nigra, and subthalamic nucleus. The basal ganglia also have a subsector which mediates limbic functions made up of the nucleus accumbens, ventral palladium, and ventral tegmen tal area. These circuits connect to the th alamus and from there to
99 the prefrontal cortex, where they can influence executive functions including decision making processes. The striatum is the first stage of the basal ganglia circuitry and receives inputs f rom various regions of the brain including the pre frontal cortex In turn, it s ends outputs through the basal ganglia/thalamic circuitry bac k to the prefrontal cortex via two routes characterized as the direct indirect pathway s It is widely accept ed that striatal D1 receptors largely influen ce the direct pathway and D2 receptors largely influence the indirect pathway. Activation of D1 receptors in the d irect pathway results in the activation of the thalamic output to the prefrontal cortex, which is thought to reinforce behavior (i.e to encourage repetition of behavior) (Hollerman and Schultz, 1998; Schultz, 1998; Schultz and Dickinson, 2000; Goto and Grace, 2008; Sesack and Grace, 2010) The circuitry of the indirect pathway inhibits th e thalamic output to the cortex; however, activation of inhibitory D2 receptor s with in the indirect pathway results in the disinhibition of the thalamus ultimately resulting in in creased thalamic o utput to the prefrontal cortex ( see Figure 6 1) Such D2 receptor activation in striatum (and consequent reduction in indirect pathway influence on the thalamus) is thought to be important for inhibiting reward directed behavior (Caine et al., 2002; Drew et al., 2007; Floresco, 2007; Welter et al., 2007; Durieux et al., 2009; Chakravarthy et al. 2010; Johnson and Kenny, 2010; Sesack and Grace, 2010; Xue et al., 2011) As mentioned previously, striatal D2 receptors have been heavily implicated in behavioral disinhibition and drug use, such that lower D2 expression is associated with elevations in behavioral disinhibition and an increased propensity for drug use. Reductions in D2 receptor activation resul ting from lower D2 receptor expression within the striatum might result in less inhibition of risk taking and drug use by inhibiting the
100 thalamic output to the prefrontal cortex and possibly consequent greater reinforcement of these behaviors through activ ation of the D1 (direct) pathway (Lobo et al., 2010) In studies mentioned earlier in which D2 receptor availability is measured using PET (Volkow et al., 2001; Lee et al., 2009) because of the nature of the technique it is unclear whether the lower D2 receptor availability is a result of reduced D2 receptor density if the reduction in receptor availability is post or pre synaptic (or both) or if there is an increase in dopamine release competing with the ligand. Moreover, it still remains unclear if the relationships between D2 recepto r expression or availability (including cocaine induced alterations in receptor expression) and behavioral dis inhib ition are associated with pr e or postsynaptic receptors or both ( radiolabeled ligands currently do not distinguish between the two) In regard to the current study, the mRNA receptor expression lev els reported in Experiment 2 do reflect postsynaptic D2 receptor mRNA expr ession (i.e. D2 receptor mRNA is known to be expressed in striatal neurons) but it is unknown if they also reflect presynaptic receptor expression as well (i.e. it is not clear whether D2 mRNA is present in presynaptic terminals) Pot entially shedding some light on this issue, h owever, a recent study by Bello et al. (2011) developed a selective D2 recepto r knockout mouse that lacks presynaptic D2 au toreceptors within the striatum. These mice were hypersen sitive to the locomotor effects of cocaine and show ed increased sensitivity to the moti vational effects of cocaine as they were willing to press a lever more times to gain access to cocaine compared to wild type mice. Moreover, the se mice worked harder to obtain a food reward and show ed a greater locomotor response to a novel environment (a possible measure of risk taking). These data suggest that lower D2 autoreceptor expression can
101 result in increases in sensitivity to cocaine and reward motivation (pote ntial elements of behavioral disinhibition) and that, therefore, the relationships between reduced striatal D2 receptors, elevated behavioral disinhibition, and propensity for cocaine use might be due to reductions in presynaptic D2 receptors There are s everal caveats to this conclusion however D ecreases in presynaptic D2 autoreceptor levels would result in increase d dopamine release, such that the behavioral phenotype of these mice could b e a result of hyperdopaminergia. In addition, c hronic excessive d opamine release could lead to compensatory mechanism s such as decreased postsynaptic dopamine receptor expression Regardless of the exact mechanism, the results from the Bello et al. (2011) study suggest that loss of D2 pres ynaptic autoreceptors h as the potential to play a causal role in some elements of behavioral disinhibition and cocaine use. Low striatal D2 receptor expression may be a preexisting condition that can increase propensity for cocaine use, but it is still uncle ar how cocaine use causes elevated risk taking. A recent study investigated the effects of acute cocaine administration in mice on neuronal intracellular calcium levels in vivo using optical microprobe imaging (changes in intracellular calcium can be used as a marker of postsynaptic neuronal activation) (Luo et al., 2011) Cocaine administration resulted in a rapid increase in intracellular calcium in D1 receptor expressing neurons, whereas intracellular calcium d ecreased continuously over the course of 30 m inutes in post synaptic D2 receptor expressing neurons. These data suggest that acute cocaine administration results in rapid activation of D1 expressing neurons within the direc t pathway of the basal ganglia a nd a slower, longer acti ng deactivation of D2 expressing neurons within the indirect pathway. While D2 receptors within the indi rect pathway
102 would normally act to suppress the r einforcement of cocaine taking (Caine et al., 2002; Welter et al., 2007; Lobo et al., 2010) ( although it should be noted that it remains unclear how D2 receptors within the indirect pathway exert this effect ) the cocaine induc ed reduction in D2 activation in indirect pathway neurons would be expected to allow for greater reinforcement of cocaine taking by resulting in the in hibition of the thalamus and therefore, less output to the prefrontal cortex. T he effects of chronic cocaine administration on changes in intracellular ca lcium remain unclear ; however, Thompson et al. (2010) found that chronic cocaine exposure resulted in the downregulation of D2 receptors in the striatum as measured by radioligand binding (as described above these alterations in D2 receptor binding could be either pre or postsynaptic) further supporting the idea that cocain e administration reduces the influence of D2 receptors within the indirect pathway, which normally act to suppress such behavior (Caine et al., 2002; Welter et al., 2007; Lobo et al., 2010) Considering all of these data together, repeated c ocaine administration might result in deactivation of the indirect pathway and a downregulation of dopamine D2 rec eptors (Thompson et al., 2010) p ossibly including presynaptic D2 autoreceptors. Such alterations in receptor expression may then mimic many of the findings regarding the D2 autoreceptor knockout mice (Bello et al. 2011) s uch that cocaine exposed subjects display a sensitized r (amplified by the decrease in D2 autoreceptors) and even increased risk taking. In conclusion i t could be argued that low D2 receptor expre ssion ( possibly both pre and postsynaptic) in the striatum can be a preexisting factor resulting in elevated behavioral disinhibition, including risk taking. This elevation in risk taking (particularly in
103 adolescence) can predict the propensity for cocain e SA. As striatal D2 receptors have been associated with both risk taking and drug use, it is pos sible that the low expression of D2 receptors underlies elevated risk taking by causing dampened thalamic output to the prefrontal cortex Chronic cocaine admi nistration might then further dampen the thalamic output to the prefrontal cortex via the indirect pathway ( through further decreases in D2 expression) and increase activation in the direct pathway, which would result in further reinforcement of cocaine ta king, and ultimately risk taking forming a Figure 6 1 Dopaminergic Modulation of the Direct and Indirect Pathways. This figure shows the circuitry between the prefrontal cortex, striatum, and basal ganglia/thalamic circuitry to produce voluntary movement, procedural learning, and some cognitive functions. The green arrows represent excitatory connections and the red a rrows represent inhibitory connections.
104 LIST OF REFERENCES Adriani W, Chiarotti F, Laviola G (1998) Elevated novelty seeking and peculiar d amphetamine sensitization in periadolescent mice compared with adult mice. Behavioral neuroscie nce 112:1152 1166. Adriani W, Laviola G (2003) Elevated levels of impulsivity and reduced place conditioning with d amphetamine: two behavioral features of adolescence in mice. Behavioral neuroscience 117:695 703. Adriani W, Laviola G (2004) Windows of vul nerability to psychopathology and therapeutic strategy in the adolescent rodent model. Behav ioural pharmacology 15:341 352. Ahmed SH (2010) Validation crisis in animal models of drug addiction: beyond non disordered drug use toward drug addiction. Neuroscience and biobehavioral reviews 35:172 184. Ahmed SH, Koob GF (1998) Transition from moderate to excessive drug intake: change in hedonic set point. Science 282:298 300. Ahmed SH, Cador M (2006) Dissociation of psychomotor sensitization from compuls ive cocaine consumption. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 31:563 571. Anden NE, Carlsson A, Dahlstroem A, Fuxe K, Hillarp NA, Larsson K (1964) Demonstration and Mapping out of Nigro Neostriat al Dopamine Neurons. Life Sci 3:523 530. Andersen PH, Gingrich JA, Bates MD, Dearry A, Falardeau P, Senogles SE, Caron MG (1990) Dopamine receptor subtypes: beyond the D1/D2 classification. Trends Pharmacol Sci 11:231 236. Anker JJ, Perry JL, Gliddon LA, C arroll ME (2009) Impulsivity predicts the escalation of cocaine self administration in rats. Pharmacol Biochem Behav 93:343 348. Anokhin AP, Golosheykin S, Grant JD, Heath AC (2011) Heritability of delay discounting in adolescence: a longitudinal twin stud y. Behav Genet 41:175 183. Arnett JJ (1999) Adolescent storm and stress, reconsidered. The American psychologist 54:317 326. Arnett JJ, Offer D, Fine MA (1997) Reckless driving in adolescence: 'state' and 'trait' factors. Accident; analysis and prevention 29:57 63. Asato MR, Terwilliger R, Woo J, Luna B (2010) White matter development in adolescence: a DTI study. Cereb Cortex 20:2122 2131.
105 Balleine BW, Delgado MR, Hikosaka O (2007) The Role of the Dorsal Striatum in Reward and Decision Making. J Neurosci 27 :8161 8165. Barnea Goraly N, Menon V, Eckert M, Tamm L, Bammer R, Karchemskiy A, Dant CC, Reiss AL (2005) White matter development during childhood and adolescence: a cross sectional diffusion tensor imaging study. Cereb Cortex 15:1848 1854. Barry D, Petry NM (2008) Predictors of decision making on the Iowa Gambling Task: independent effects of lifetime history of substance use disorders and performance on the Trail Making Test. Brain Cogn 66:243 252. Bauman PS, Levine SA (1986) The development of children of drug addicts. Int J Addict 21:849 863. Beaulieu JM, Gainetdinov RR (2011) The physiology, signaling, and pharmacology of dopamine receptors. Pharmacological reviews 63:182 217. Bechara A, Damasio AR, Damasio H, Anderson SW (1994) Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50:7 15. Bechara A, Damasio H, Tranel D, Damasio AR (1997) Deciding advantageously before knowing the advantageous strategy. Science 275:1293 1295. Bechara A, Damasio H, Damasio AR, Lee G P (1999) Different contributions of the human amygdala and ventromedial prefrontal cortex to decision making. The Journal of neuroscience : the official journal of the Society for Neuroscience 19:5473 5481. Bechara A, Dolan S, Denburg N, Hindes A, Anderson SW, Nathan PE (2001) Decision making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia 39:376 389. Bechara A, Tranel D, Damasio H, Damasio AR (1996) Failure to respond autonomic ally to anticipated future outcomes following damage to prefrontal cortex. Cereb Cortex 6:215 225. Belin D, Mar AC, Dalley JW, Robbins TW, Everitt BJ (2008) High impulsivity predicts the switch to compulsive cocaine taking. Science 320:1352 1355. Bello EP, Mateo Y, Gelman DM, Noain D, Shin JH, Low MJ, Alvarez VA, Lovinger DM, Rubinstein M (2011) Cocaine supersensitivity and enhanced motivation for reward in mice lacking dopamine D2 autoreceptors. Nat Neurosci 14:1033 1038. Berridge KC, Robinson TE (1998) Wh at is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res Brain Res Rev 28:309 369.
106 Besson M, Belin D, McNamara R, Theobald DE, Castel A, Beckett VL, Crittenden BM, Newman AH, Everitt BJ, Robbins TW, Dalley JW (2010) Dissociable control of impulsivity in rats by dopamine d2/3 receptors in the core and shell subregions of the nucleus accumbens. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 35:560 569. Beveridge TJ, Gill KE, Hanlon CA, Porrino LJ (2008) Review. Parallel studies of cocaine related neural and cognitive impairment in humans and monkeys. Philos Trans R Soc Lond B Biol Sci 363:3257 3266. Bickel WK, Marsch LA (2001) Toward a behavioral economic understa nding of drug dependence: delay discounting processes. Addiction 96:73 86. Bizon JL, Helm KA, Han JS, Chun HJ, Pucilowska J, Lund PK, Gallagher M (2001) Hypothalamic pituitary adrenal axis function and corticosterone receptor expression in behaviourally ch aracterized young and aged Long Evans rats. Eur J Neurosci 14:1739 1751. Bolla KI, Cadet JL, London ED (1998) The neuropsychiatry of chronic cocaine abuse. J Neuropsychiatry Clin Neurosci 10:280 289. Bolla KI, Eldreth DA, London ED, Kiehl KA, Mouratidis M, Contoreggi C, Matochik JA, Kurian V, Cadet JL, Kimes AS, Funderburk FR, Ernst M (2003) Orbitofrontal cortex dysfunction in abstinent cocaine abusers performing a decision making task. Neuroimage 19:1085 1094. Bonekamp D, Nagae LM, Degaonkar M, Matson M, Abdalla WM, Barker PB, Mori S, Horska A (2007) Diffusion tensor imaging in children and adolescents: reproducibility, hemispheric, and age related differences. Neuroimage 34:733 742. Bornovalova MA, Daughters SB, Hernandez GD, Richards JB, Lejuez CW (2005) Differences in impulsivity and risk taking propensity between primary users of crack cocaine and primary users of heroin in a residential substance use program. Exp Clin Psychopharmacol 13:311 318. Boschen SL, Wietzikoski EC, Winn P, Da Cunha C (2011) The role of nucleus accumbens and dorsolateral striatal D2 receptors in active avoidance conditioning. Neurobiol Learn Mem 96:254 262. Brand M, Labudda K, Markowitsch HJ (2006) Neuropsychological correlates of decision making in ambiguous and risky situations Neural Netw 19:1266 1276. Broos N, Diergaarde L, Schoffelmeer AN, Pattij T, De Vries TJ (2012) Trait impulsive choice predicts resistance to extinction and propensity to relapse to cocaine seeking: a bidirectional investigation. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 37:1377 1386.
107 Burn DJ, Troster AI (2004) Neuropsychiatric complications of medical and surgical therapies for Parkinson's disease. J Geriatr Psychiatry Neurol 17:172 180. Caine SB, Ne gus SS, Mello NK, Patel S, Bristow L, Kulagowski J, Vallone D, Saiardi A, Borrelli E (2002) Role of dopamine D2 like receptors in cocaine self administration: studies with D2 receptor mutant mice and novel D2 receptor antagonists. The Journal of neuroscien ce : the official journal of the Society for Neuroscience 22:2977 2988. Caine SB, Thomsen M, Gabriel KI, Berkowitz JS, Gold LH, Koob GF, Tonegawa S, Zhang J, Xu M (2007) Lack of self administration of cocaine in dopamine D1 receptor knock out mice. The Jou rnal of neuroscience : the official journal of the Society for Neuroscience 27:13140 13150. Calu DJ, Stalnaker TA, Franz TM, Singh T, Shaham Y, Schoenbaum G (2007) Withdrawal from cocaine self administration produces long lasting deficits in orbitofrontal dependent reversal learning in rats. Learn Mem 14:325 328. Cardinal R, Howes N (2005) Effects of lesions of the nucleus accumbens core on choice between small certain rewards and large uncertain rewards in rats. BMC Neurosci 6:37. Cardinal RN, Robbins TW, Everitt BJ (2000) The effects of d amphetamine, chlordiazepoxide, alpha flupenthixol and behavioural manipulations on choice of signalled and unsignalled delayed reinforcement in rats. Psychopharmacology 152:362 375. Cardinal RN, Pennicot DR, Sugathapala C L, Robbins TW, Everitt BJ (2001) Impulsive choice induced in rats by lesions of the nucleus accumbens core. Science 292:2499 2501. Carlsson A, Lindqvist M, Magnusson T (1957) 3,4 Dihydroxyphenylalanine and 5 hydroxytryptophan as reserpine antagonists. Natu re 180:1200. Carlsson A, Waters N, Holm Waters S, Tedroff J, Nilsson M, Carlsson ML (2001) Interactions between monoamines, glutamate, and GABA in schizophrenia: new evidence. Annu Rev Pharmacol Toxicol 41:237 260. Cauffman E, Shulman EP, Steinberg L, Clau s E, Banich MT, Graham S, Woolard J (2010) Age differences in affective decision making as indexed by performance on the Iowa Gambling Task. Dev Psychol 46:193 207. Chakravarthy VS, Joseph D, Bapi RS (2010) What do the basal ganglia do? A modeling perspect ive. Biol Cybern 103:237 253. Chambers RA, Taylor JR, Potenza MN (2003) Developmental neurocircuitry of motivation in adolescence: a critical period of addiction vulnerability. The American journal of psychiatry 160:1041 1052.
108 Chudasama Y, Robbins TW (2006 ) Functions of frontostriatal systems in cognition: comparative neuropsychopharmacological studies in rats, monkeys and humans. Biol Psychol 73:19 38. Civelli O, Bunzow JR, Grandy DK (1993) Molecular diversity of the dopamine receptors. Annu Rev Pharmacol Toxicol 33:281 307. Coffey SF, Gudleski GD, Saladin ME, Brady KT (2003) Impulsivity and rapid discounting of delayed hypothetical rewards in cocaine dependent individuals. Exp Clin Psychopharmacol 11:18 25. Colzato LS, van den Wildenberg WP, Hommel B (2007 ) Impaired inhibitory control in recreational cocaine users. PLoS One 2:e1143. Comings DE, Rosenthal RJ, Lesieur HR, Rugle LJ, Muhleman D, Chiu C, Dietz G, Gade R (1996) A study of the dopamine D2 receptor gene in pathological gambling. Pharmacogenetics 6: 223 234. Cools R, Barker RA, Sahakian BJ, Robbins TW (2001) Enhanced or impaired cognitive function in Parkinson's disease as a function of dopaminergic medication and task demands. Cereb Cortex 11:1136 1143. Cunha PJ, Bechara A, de Andrade AG, Nicastri S (2011) Decision making deficits linked to real life social dysfunction in crack cocaine dependent individuals. Am J Addict 20:78 86. Dagher A, Robbins TW (2009) Personality, addiction, dopamine: insights from Parkinson's disease. Neuron 61:502 510. Dahlstroem A, Fuxe K (1964) Evidence for the Existence of Monoamine Containing Neurons in the Central Nervous System. I. Demonstration of Monoamines in the Cell Bodies of Brain Stem Neurons. Acta Physiol Scand Suppl:SUPPL 232:231 255. Dallery J, Locey ML ( 2005) Effects of acute and chronic nicotine on impulsive choice in rats. Behavioural pharmacology 16:15 23. Dalley JW, Cardinal RN, Robbins TW (2004) Prefrontal executive and cognitive functions in rodents: neural and neurochemical substrates. Neuroscience and biobehavioral reviews 28:771 784. Dalley JW, Fryer TD, Brichard L, Robinson ES, Theobald DE, Laane K, Pena Y, Murphy ER, Shah Y, Probst K, Abakumova I, Aigbirhio FI, Richards HK, Hong Y, Baron JC, Everitt BJ, Robbins TW (2007) Nucleus accumbens D2/3 r eceptors predict trait impulsivity and cocaine reinfo rcement. Science 315:1267 1270.
109 Dalley JW, Laane K, Pena Y, Theobald DE, Everitt BJ, Robbins TW (2005) Attentional and motivational deficits in rats withdrawn from intravenous self administration of cocaine or heroin. Psychopharmacology 182:579 587. Dandy KL, Gatch MB (2009) The effects of chronic cocaine exposure on impulsivity in rats. Behavioural pharmacology 20:400 405. Davis BA, Clinton SM, Akil H, Becker JB (2008) The effects of novelty seeking phenotypes and sex differences on acquisition of cocaine self administration in selectively bred High Responder and Low Responder rats. Pharmacology, biochemistry, and behavior 90:331 338. Delazer M, Sinz H, Zamarian L, Stockner H, Seppi K, Wenning GK, Ben ke T, Poewe W (2009) Decision making under risk and under ambiguity in Parkinson's disease. Neuropsychologia 47:1901 1908. Doremus Fitzwater TL, Barreto M, Spear LP (2012) Age Related Differences in Impulsivity Among Adolescent and Adult Sprague Dawley Rat s. Behav Neurosci. Douglas LA, Varlinskaya EI, Spear LP (2003) Novel object place conditioning in adolescent and adult male and female rats: effects of social isolation. Physiology & behavior 80:317 325. Drew MR, Simpson EH, Kellendonk C, Herzberg WG, Lipa tova O, Fairhurst S, Kandel ER, Malapani C, Balsam PD (2007) Transient overexpression of striatal D2 receptors impairs operant motivation and interval timing. The Journal of neuroscience : the official journal of the Society for Neuroscience 27:7731 7739. Driver Dunckley E, Samanta J, Stacy M (2003) Pathological gambling associated with dopamine agonist therapy in Parkinson's disease. Neurology 61:422 423. Durieux PF, Bearzatto B, Guiducci S, Buch T, Waisman A, Zoli M, Schiffmann SN, de Kerchove d'Exaerde A (2009) D2R striatopallidal neurons inhibit both locomotor and drug reward processes. Nat Neurosci 12:393 395. Duva SM, Silverstein SM, Spiga R (2011) Impulsivity and risk taking in co occurring psychotic disorders and substance abuse. Psychiatry Res 186:3 51 355. Eagle DM, Wong JC, Allan ME, Mar AC, Theobald DE, Robbins TW (2011) Contrasting roles for dopamine D1 and D2 receptor subtypes in the dorsomedial striatum but not the nucleus accumbens core during behavioral inhibition in the stop signal task in ra ts. The Journal of neuroscience : the official journal of the Society for Neuroscience 31:7349 7356. Evenden J (1999) Impulsivity: a discussion of clinical and experimental findings. J Psychopharmacol 13:180 192.
110 Everitt BJ, Belin D, Economidou D, Pelloux Y, Dalley JW, Robbins TW (2008) Neural mechanisms underlying the vulnerability to develop compulsive drug seeking habits and addiction. Philosophical Transactions of the Royal Society B: Biological Sciences 363:3125 3135. Fillmore MT, Rush CR (2002) Impair ed inhibitory control of behavior in chronic cocaine users. Drug and alcohol dependence 66:265 273. Floresco SB (2007) Dopaminergic regulation of limbic striatal interplay. J Psychiatry Neurosci 32:400 411. Floresco SB, St. Onge JR, Ghods Sharifi S, Winsta nley CA (2008) Cortico limbic striatal circuits subserving different forms of cost benefit decision making. Cogn Affect Behav Neurosci 8:375 389. Frank MJ, Moustafa AA, Haughey HM, Curran T, Hutchison KE (2007) Genetic triple dissociation reveals multiple roles for dopamine in reinforcement learning. Proceedings of the National Academy of Sciences of the United States of America 104:16311 16316. Franklin TR, Acton PD, Maldjian JA, Gray JD, Croft JR, Dackis CA, O'Brien CP, Childress AR (2002) Decreased gray matter concentration in the insular, orbitofrontal, cingulate, and temporal cortices of cocaine patients. Biol Psychiatry 51:134 142. Gerfen CR (2000) Molecular effects of dopamine on striatal projection pathways. Trends Neurosci 23:S64 70. Gerfen CR (2004 ) Basal Ganglia. In: The Rat Nervous System, 3rd Edition (Paxinos G, ed), pp 458 494. San Diego, CA: Elsevier Academic Press. Gingrich JA, Caron MG (1993) Recent advances in the molecular biology of dopamine receptors. Annu Rev Neurosci 16:299 321. Giovann oni G, O'Sullivan JD, Turner K, Manson AJ, Lees AJ (2000) Hedonistic homeostatic dysregulation in patients with Parkinson's disease on dopamine replacement therapies. J Neurol Neurosurg Psychiatry 68:423 428. Glimcher PW, Rustichini A (2004) Neuroeconomics : the consilience of brain and decision. Science 306:447 452. Goto Y, Grace AA (2008) Limbic and cortical information processing in the nucleus accumbens. Trends Neurosci 31:552 558. Goudriaan AE, Grekin ER, Sher KJ (2011) Decision making and response inhi bition as predictors of heavy alcohol use: a prospective study. Alcoholism, clinical and experimental research 35:1050 1057.
111 Grant S, Contoreggi C, London ED (2000) Drug abusers show impaired performance in a laboratory test of decision making. Neuropsycho logia 38:1180 1187. Green L, Myerson J, Lichtman D, Rosen S, Fry A (1996) Temporal discounting in choice between delayed rewards: the role of age and income. Psychol Aging 11:79 84. Greenberg LM, Waldman ID (1993) Developmental normative data on the test o f variables of attention (T.O.V.A.). Journal of child psychology and psychiatry, and allied disciplines 34:1019 1030. Groman SM, Lee B, London ED, Mandelkern MA, James AS, Feiler K, Rivera R, Dahlbom M, Sossi V, Vandervoort E, Jentsch JD (2011) Dorsal stri atal D2 like receptor availability covaries with sensitivity to positive reinforcement during discrimination learning. The Journal of neuroscience : the official journal of the Society for Neuroscience 31:7291 7299. Gschwandtner U, Aston J, Renaud S, Fuhr P (2001) Pathologic gambling in patients with Parkinson's disease. Clin Neuropharmacol 24:170 172. Haberman RP, Colantuoni C, Stocker AM, Schmidt AC, Pedersen JT, Gallagher M (2011) Prominent hippocampal CA3 gene expression profile in neurocognitive aging. Neurobiol Aging 32:1678 1692. Hackenberg TD (2009) Token reinforcement: a review and analysis. J Exp Anal Behav 91:257 286. Haluk DM, Floresco SB (2009) Ventral striatal dopamine modulation of different forms of behavioral flexibility. Neuropsychopharmaco logy : official publication of the American College of Neuropsychopharmacology 34:2041 2052. Hauber W, Sommer S (2009) Prefrontostriatal Circuitry Regulates Effort Related Decision Making. Cereb Cortex In Press. Heil SH, Johnson MW, Higgins ST, Bickel WK (2006) Delay discounting in currently using and currently abstinent cocaine dependent outpatients and non drug using matched controls. Addict Behav 31:1290 1294. Hirvonen M, Laakso A, Nagren K, Rinne JO, Pohjalainen T, Hietala J (2004) C957T polymorphism o f the dopamine D2 receptor (DRD2) gene affects striatal DRD2 availability in vivo. Mol Psychiatry 9:1060 1061. Hollerman JR, Schultz W (1998) Dopamine neurons report an error in the temporal prediction of reward during learning. Nat Neurosci 1:304 309. Hol man BL, Carvalho PA, Mendelson J, Teoh SK, Nardin R, Hallgring E, Hebben N, Johnson KA (1991) Brain perfusion is abnormal in cocaine dependent polydrug users: a study using technetium 99m HMPAO and ASPECT. J Nucl Med 32:1206 1210.
112 Ibarretxe Bilbao N, Junqu e C, Tolosa E, Marti MJ, Valldeoriola F, Bargallo N, Zarei M (2009) Neuroanatomical correlates of impaired decision making and facial emotion recognition in early Parkinson's disease. The European journal of neuroscience 30:1162 1171. Iversen SD, Iversen L L (2007) Dopamine: 50 years in perspective. Trends Neurosci 30:188 193. Jentsch JD, Olausson P, De La Garza R, 2nd, Taylor JR (2002) Impairments of reversal learning and response perseveration after repeated, intermittent cocaine administrations to monkeys Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 26:183 190. Jentsch JD, Woods JA, Groman SM, Seu E (2010a) Behavioral characteristics and neural mechanisms mediating performance in a rodent version of the Balloon Analog Risk Task. Neuropsychopharmacology 35:1797 1806. Jentsch JD, Woods JA, Groman SM, Seu E (2010b) Behavioral characteristics and neural mechanisms mediating performance in a rodent version of the Balloon Analog Risk Task. Neuropsychopharm 35: 1797 1806. Johnson A, van der Meer MAA, Redish AD (2007) Integrating hippocampus and striatum in decision making. Current Opinion in Neurobiology 17:692 697. Johnson MW (2012) An Efficient Operant Choice Procedure for Assessing Delay Discounting in Humans: Initial Validation in Cocaine Dependent and Control Individuals. Exp Clin Psychopharmacol. Johnson PM, Kenny PJ (2010) Dopamine D2 receptors in addiction like reward dysfunction and compulsive eating in obese rats. Nat Neurosci 13:635 641. Jonsson EG, Not hen MM, Grunhage F, Farde L, Nakashima Y, Propping P, Sedvall GC (1999) Polymorphisms in the dopamine D2 receptor gene and their relationships to striatal dopamine receptor density of healthy volunteers. Mol Psychiatry 4:290 296. Kable JW, Glimcher PW (200 9) The neurobiology of decision: consensus and controversy. Neuron 63:733 745. Kalivas PW, Volkow ND (2005) The neural basis of addiction: a pathology of motivation and choice. Am J Psychiatry 162:1403 1413. Kalsbeek A, Voorn P, Buijs RM, Pool CW, Uylings HB (1988) Development of the dopaminergic innervation in the prefrontal cortex of the rat. The Journal of comparative neurology 269:58 72. Kebabian JW, Calne DB (1979) Multiple receptors for dopamine. Nature 277:93 96.
113 Kim H, Sul JH, Huh N, Lee D, Jung MW (2009) Role of striatum in updating values of chosen actions. The Journal of neuroscience : the official journal of the Society for Neuroscience 29:14701 14712. Kippin TE, Fuchs RA, See RE (2006) Contributions of prolonged contingent and noncontingent coca ine exposure to enhanced reinstatement of cocaine seeking in rats. Psychopharmacology 187:60 67. Kish SJ, Shannak K, Hornykiewicz O (1988) Uneven pattern of dopamine loss in the striatum of patients with idiopathic Parkinson's disease. Pathophysiologic and clinical implications. N Engl J Med 318:876 880. Klein TA, Neumann J, Reuter M, Hennig J, von Cramon DY, Ullsperger M (2007) Genetically determined differences in learning from errors. Science 318:1642 1645. Knackstedt LA, Kalivas PW (2007) Extended acces s to cocaine self administration enhances drug primed reinstatement but not behavioral sensitization. J Pharmacol Exp Ther 322:1103 1109. Kobayakawa M, Koyama S, Mimura M, Kawamura M (2008) Decision making in Parkinson's disease: Analysis of behavioral and physiological patterns in the Iowa gambling task. Movement Disorders 23:547 552. Kollins SH (2003) Delay discounting is associated with substance use in college students. Addict Behav 28:1167 1173. Krueger DD, Howell JL, Oo H, Olausson P, Taylor JR, Nairn AC (2009) Prior chronic cocaine exposure in mice induces persistent alterations in cognitive function. Behavioural pharmacology 20:695 704. Lader M (2008) Antiparkinsonian medication and pathological gambling. CNS Drugs 22:407 416. Lane SD, Steinberg JL, Ma L, Hasan KM, Kramer LA, Zuniga EA, Narayana PA, Moeller FG (2010) Diffusion tensor imaging and decision making in cocaine dependence. PLoS One 5:e11591. Laughlin RE, Grant TL, Williams RW, Jentsch JD (2011) Genetic dissection of behavioral flexibility: reversal learning in mice. Biol Psychiatry 69:1109 1116. Laviola G, Macri S, Morley Fletcher S, Adriani W (2003) Risk taking behavior in adolescent mice: psychobiological determinants and early epigenetic influence. Neurosci Biobehav Rev 27:19 31. Leary MR Hoyle RH (2009) Handbook of individual differences in social behavior. New York: Guilford Press.
114 Lee B, Groman S, London ED, Jentsch JD (2007) Dopamine D2/D3 receptors play a specific role in the reversal of a learned visual discrimination in monkeys. Ne uropsychopharmacology : official publication of the American College of Neuropsychopharmacology 32:2125 2134. Lee B, London ED, Poldrack RA, Farahi J, Nacca A, Monterosso JR, Mumford JA, Bokarius AV, Dahlbom M, Mukherjee J, Bilder RM, Brody AL, Mandelkern MA (2009) Striatal dopamine d2/d3 receptor availability is reduced in methamphetamine dependence and is linked to impulsivity. The Journal of neuroscience : the official journal of the Society for Neuroscience 29:14734 14740. Lee D (2008) Game theory and n eural basis of social decision making. Nat Neurosci 11:404 409. Lex B, Hauber W (2010a) Disconnection of the entorhinal cortex and dorsomedial striatum impairs the sensitivity to instrumental contingency degradation. Neuropsychopharmacology : official publ ication of the American College of Neuropsychopharmacology 35:1788 1796. Lex B, Hauber W (2010b) The role of dopamine in the prelimbic cortex and the dorsomedial striatum in instrumental conditioning. Cereb Cortex 20:873 883. Li CS, Milivojevic V, Kemp K, Hong K, Sinha R (2006) Performance monitoring and stop signal inhibition in abstinent patients with cocaine dependence. Drug and alcohol dependence 85:205 212. Linnet J, Moller A, Peterson E, Gjedde A, Doudet D (2011a) Dopamine release in ventral striatum during Iowa Gambling Task performance is associated with increased excitement levels in pathological gambling. Addiction 106:383 390. Linnet J, Moller A, Peterson E, Gjedde A, Doudet D (2011b) Inverse association between dopaminergic neurotransmission and Iowa Gambling Task performance in pathological gamblers and healthy controls. Scand J Psychol 52:28 34. Lobo MK, Covington HE, 3rd, Chaudhury D, Friedman AK, Sun H, Damez Werno D, Dietz DM, Zaman S, Koo JW, Kennedy PJ, Mouzon E, Mogri M, Neve RL, Deisserot h K, Han MH, Nestler EJ (2010) Cell type specific loss of BDNF signaling mimics optogenetic control of cocaine reward. Science 330:385 390. Locey ML, Dallery J (2009) Isolating behavioral mechanisms of intertemporal choice: nicotine effects on delay discou nting and amount sensitivity. J Exp Anal Behav 91:213 223. Locey ML, Dallery J (2011) Nicotine and the behavioral mechanisms of intertemporal choice. Behav Processes 87:18 24.
115 Logue AW, Tobin H, Chelonis JJ, Wang RY, Geary N, Schachter S (1992) Cocaine dec reases self control in rats: a preliminary report. Psychopharmacology 109:245 247. London ED, Ernst M, Grant S, Bonson K, Weinstein A (2000) Orbitofrontal cortex and human drug abuse: functional imaging. Cereb Cortex 10:334 342. Lucantonio F, Stalnaker TA, Shaham Y, Niv Y, Schoenbaum G (2012) The impact of orbitofrontal dysfunction on cocaine addiction. Nat Neurosci 15:358 366. Luna B, Padmanabhan A, O'Hearn K (2010) What has fMRI told us about the development of cognitive control through adolescence? Brain Cogn 72:101 113. Luna B, Thulborn KR, Munoz DP, Merriam EP, Garver KE, Minshew NJ, Keshavan MS, Genovese CR, Eddy WF, Sweeney JA (2001) Maturation of widely distributed brain function subserves cognitive development. Neuroimage 13:786 793. Luo Z, Volkow ND, Heintz N, Pan Y, Du C (2011) Acute cocaine induces fast activation of D1 receptor and progressive deactivation of D2 receptor striatal neurons: in vivo optical microprobe [Ca2+]i imaging. The Journal of neuroscience : the official journal of the Societ y for Neuroscience 31:13180 13190. Magnusson JE, Fisher K (2000) The involvement of dopamine in nociception: the role of D(1) and D(2) receptors in the dorsolateral striatum. Brain Res 855:260 266. Mantsch JR, Yuferov V, Mathieu Kia AM, Ho A, Kreek MJ (200 4) Effects of extended access to high versus low cocaine doses on self administration, cocaine induced reinstatement and brain mRNA levels in rats. Psychopharmacology 175:26 36. Markett S, Montag C, Walter NT, Plieger T, Reuter M (2011) On the molecular ge netics of flexibility: the case of task switching, inhibitory control and genetic variants. Cogn Affect Behav Neurosci 11:644 651. Martin CA, Kelly TH, Rayens MK, Brogli BR, Brenzel A, Smith WJ, Omar HA (2002) Sensation seeking, puberty, and nicotine, alco hol, and marijuana use in adolescence. Journal of the American Academy of Child and Adolescent Psychiatry 41:1495 1502. Martin CA, Kelly TH, Rayens MK, Brogli B, Himelreich K, Brenzel A, Bingcang CM, Omar H (2004) Sensation seeking and symptoms of disrupti ve disorder: association with nicotine, alcohol, and marijuana use in early and mid adolescence. Psychological reports 94:1075 1082. McCabe C, Mishor Z, Cowen PJ, Harmer CJ Diminished Neural Processing of Aversive and Rewarding Stimuli During Selective Ser otonin Reuptake Inhibitor Treatment. Biological Psychiatry In Press, Corrected Proof.
116 McFarland K, Lapish CC, Kalivas PW (2003) Prefrontal glutamate release into the core of the nucleus accumbens mediates cocaine induced reinstatement of drug seeking behavior. The Journal of neuroscience : the official journal of the Society for Neuroscience 23:3531 3537. McNamara R, Dalley JW, Robbins TW, Everitt BJ, Belin D (2010) Trait like impulsivity does not predict escalation of heroin self administration in the rat. Psychopharmacology 212:453 464. Mendez IA, Simon NW, Hart N, Mitchell MR, Nation JR, Wellman PJ, Setlow B (2010) Self administered cocaine causes long lasting increases in impulsive choice in a delay discounting task. Behav Neurosci 124:470 477. Miss ale C, Nash SR, Robinson SW, Jaber M, Caron MG (1998) Dopamine receptors: from structure to function. Physiol Rev 78:189 225. Mitchell MR, Vokes CM, Blankenship AL, Simon NW, Setlow B (2011) Effects of acute administration of nicotine, amphetamine, diazepa m, morphine, and ethanol on risky decision making in rats. Psychopharmacology 218:703 712. Moeller FG, Barratt ES, Dougherty DM, Schmitz JM, Swann AC (2001) Psychiatric aspects of impulsivity. The American journal of psychiatry 158:1783 1793. Molina JA, Sa inz Artiga MJ, Fraile A, Jimenez Jimenez FJ, Villanueva C, Orti Pareja M, Bermejo F (2000) Pathologic gambling in Parkinson's disease: a behavioral manifestation of pharmacologic treatment? Mov Disord 15:869 872. Monk CS, McClure EB, Nelson EE, Zarahn E, B ilder RM, Leibenluft E, Charney DS, Ernst M, Pine DS (2003) Adolescent immaturity in attention related brain engagement to emotional facial expressions. Neuroimage 20:420 428. Moore RJ, Vinsant SL, Nader MA, Porrino LJ, Friedman DP (1998) Effect of cocaine self administration on striatal dopamine D1 receptors in rhesus monkeys. Synapse 28:1 9. Moreno Lopez L, Catena A, Fernandez Serrano MJ, Delgado Rico E, Stamatakis EA, Perez Garcia M, Verdejo Garcia A (2012) Trait impulsivity and prefrontal gray matter re ductions in cocaine dependent individuals. Drug and alcohol dependence. Morrison SE, Salzman CD (2009) The Convergence of Information about Rewarding and Aversive Stimuli in Single Neurons. J Neurosci 29:11471 11483. Murray JE, Belin D, Everitt BJ (2012) D ouble Dissociation of the Dorsomedial and Dorsolateral Striatal Control Over the Acquisition and Performance of Cocaine Seeking. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology.
117 Nader MA, Morgan D, Gage HD, Nader SH, Calhoun TL, Buchheimer N, Ehrenkaufer R, Mach RH (2006) PET imaging of dopamine D2 receptors during chronic cocaine self administration in monkeys. Nat Neurosci 9:1050 1056. Nagy Z, Westerberg H, Klingberg T (2004) Maturation of white matter is associated with the development of cognitive functions during childhood. Journal of cognitive neuroscience 16:1227 1233. Nation JR, Smith KR, Bratton GR (2004) Early developmental lead exposure increases sensitivity to cocaine in a self administration para digm. Pharmacology Biochemistry and Behavior 77:127 135. Nauta WJ, Domesick VB (1984) Afferent and efferent relationships of the basal ganglia. Ciba Found Symp 107:3 29. Negus S (2005) Effects of punishment on choice between cocaine and food in rhesus monk eys. Psychopharmacology (Berl) 181:244 252. Nelson EE, Leibenluft E, McClure EB, Pine DS (2005) The social re orientation of adolescence: a neuroscience perspective on the process and its relation to psychopathology. Psychological medicine 35:163 174. NIDA (2010) InfoFacts: High School and Youth Trends. In. Nirenberg MJ, Waters C (2006) Compulsive eating and weight gain related to dopamine agonist use. Mov Disord 21:524 529. Niznik HB, Van Tol HH (1992) Dopamine receptor genes: new tools for molecular psych iatry. J Psychiatry Neurosci 17:158 180. Odell WD (1990) Sexual maturation in the rat. Baltimore, MD: Williams and Wilkins. Packard MG (2009) Exhumed from thought: Basal ganglia and response learning in the plus maze. Behavioural Brain Research 199:24 31. Pagonabarraga J, Garcia Sanchez C, Llebaria G, Pascual Sedano B, Gironell A, Kulisevsky J (2007) Controlled study of decision making and cognitive impairment in Parkinson's disease. Mov Disord 22:1430 1435. Paine TA, Dringenberg HC, Olmstead MC (2003) Effe cts of chronic cocaine on impulsivity: relation to cortical serotonin mechanisms. Behav Brain Res 147:135 147. Paterson NE, Markou A (2003) Increased motivation for self administered cocaine after escalated cocaine intake. Neuroreport 14:2229 2232.
118 Pattij T, Janssen MC, Vanderschuren LJ, Schoffelmeer AN, van Gaalen MM (2007) Involvement of dopamine D1 and D2 receptors in the nucleus accumbens core and shell in inhibitory response control. Psychopharmacology 191:587 598. Paxinos G, Watson C (2008) The rat br ain in stereotaxic corrdinates: Compact, sixth edition, 6 Edition: Academic Press. Perretta JG, Pari G, Beninger RJ (2005) Effects of Parkinson disease on two putative nondeclarative learning tasks: probabilistic classification and gambling. Cogn Behav Neu rol 18:185 192. Perry JL, Nelson SE, Carroll ME (2008) Impulsive choice as a predictor of acquisition of IV cocaine self administration and reinstatement of cocaine seeking behavior in male and female rats. Exp Clin Psychopharmacol 16:165 177. Perry JL, Larson EB, German JP, Madden GJ, Carroll ME (2005) Impulsivity (delay discounting) as a predictor of acquisition of IV cocaine self administration in female rats. Psychopharmacology 178:193 201. Porter JN, Olsen AS, Gurnsey K, Dugan BP, Jedema HP, Bradberr y CW (2011) Chronic cocaine self administration in rhesus monkeys: impact on associative learning, cognitive control, and working memory. The Journal of neuroscience : the official journal of the Society for Neuroscience 31:4926 4934. Pothuizen HH, Jongen Relo AL, Feldon J, Yee BK (2005) Double dissociation of the effects of selective nucleus accumbens core and shell lesions on impulsive choice behaviour and salience learning in rats. The European journal of neuroscience 22:2605 2616. Rankin ML, Hazelwood L A, Free RB, Namkung Y, Rex EB, Roof RA, Sibley DR (2010) Molecular pharmacology of dopamine receptors. In: Dopamaine Handbook (Iversen LL, Dunnett SB, Iversen SD, Bjorklund A, eds), pp 63 87. New York: Oxford University Press. Reynolds B, Richards JB, Horn K, Karraker K (2004) Delay discounting and probability discounting as related to cigarette smoking status in adults. Behav Processes 65:35 42. Robbins TW, Everitt BJ (1999) Drug addiction: bad habits add up. Nature 398:567 570. Roberts DC, Morgan D, Liu Y (2007) How to make a rat addicted to cocaine. Prog Neuropsychopharmacol Biol Psychiatry 31:1614 1624. Rogers RD, Owen AM, Middleton HC, Williams EJ, Pickard JD, Sahakian BJ, Robbins TW (1999) Choosing between small, likely rewards and large, unlikely rewa rds activates inferior and orbital prefrontal cortex. J Neurosci 19:9029 9038.
119 Rokosik SL, Napier TC (2012) Pramipexole induced increased probabilistic discounting: comparison between a rodent model of Parkinson's disease and controls. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 37:1397 1408. Rolls ET (2004) The functions of the orbitofrontal cortex. Brain and Cognition 55:11 29. Rondou P, Haegeman G, Van Craenenbroeck K (2010) The do pamine D4 receptor: biochemical and signalling properties. Cell Mol Life Sci 67:1971 1986. Samejima K, Ueda Y, Doya K, Kimura M (2005) Representation of action specific reward values in the striatum. Science 310:1337 1340. Sanchis Segura C, Spanagel R (200 6) Behavioural assessment of drug reinforcement and addictive features in rodents: an overview. Addiction biology 11:2 38. Santana N, Mengod G, Artigas F (2009) Quantitative analysis of the expression of dopamine D1 and D2 receptors in pyramidal and GABAer gic neurons of the rat prefrontal cortex. Cereb Cortex 19:849 860. Schoenbaum G, Setlow B (2003) Lesions of nucleus accumbens disrupt learning about aversive outcomes. The Journal of Neuroscience 23:9833 9841. Schoenbaum G, Setlow B (2005) Cocaine makes ac tions insensitive to outcomes but not extinction: implications for altered orbitofrontal amygdalar function. Cereb Cortex 15:1162 1169. Schoenbaum G, Roesch MR, Stalnaker TA (2006) Orbitofrontal cortex, decision making, and drug addiction. Trends in Neuros ciences 29:116 124. Schoenbaum G, Saddoris MP, Ramus SJ, Shaham Y, Setlow B (2004) Cocaine experienced rats exhibit learning deficits in a task sensitive to orbitofrontal cortex lesions. The European journal of neuroscience 19:1997 2002. Schultz W (1998) P redictive reward signal of dopamine neurons. Journal of neurophysiology 80:1 27. Schultz W (2007) Behavioral dopamine signals. Trends in Neurosciences 30:203 210. Schultz W (2010) Subjective neuronal coding of reward: temporal value discounting and risk. T he European journal of neuroscience 31:2124 2135. Schultz W, Dickinson A (2000) Neuronal coding of prediction errors. Annu Rev Neurosci 23:473 500. Seeman P (2006) Targeting the dopamine D2 receptor in schizophrenia. Expert Opin Ther Targets 10:515 531.
120 Se eman P, Bzowej NH, Guan HC, Bergeron C, Becker LE, Reynolds GP, Bird ED, Riederer P, Jellinger K, Watanabe S, et al. (1987) Human brain dopamine receptors in children and aging adults. Synapse 1:399 404. Sesack SR, Grace AA (2010) Cortico Basal Ganglia rew ard network: microcircuitry. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 35:27 47. Setlow B, Schoenbaum G, Gallagher M (2003) Neural encoding in ventral striatum during olfactory discrimination learning Neuron 38:625 636. Setlow B, Mendez IA, Mitchell MR, Simon NW (2009) Effects of chronic administration of drugs of abuse on impulsive choice (delay discounting) in animal models. Behavioural pharmacology 20:380 389. Sevy S, Hassoun Y, Bechara A, Yechiam E, Napolitano B, Burdick K, Delman H, Malhotra A (2006) Emotion based decision making in healthy subjects: short term effects of reducing dopamine levels. Psychopharmacology 188:228 235. Sibley DR (1999) New insights into dopaminergic receptor function using antisense and genetically altered animals. Annu Rev Pharmacol Toxicol 39:313 341. Sibley DR, Monsma FJ, Jr. (1992) Molecular biology of dopamine receptors. Trends Pharmacol Sci 13:61 69. Simon NW, Mendez IA, Setlow B (2007a) Cocaine exposure causes l ong term increases in impulsive choice. Behav Neurosci 121:543 549. Simon NW, Mendez IA, Setlow B (2007b) Cocaine exposure causes long term increases in impulsive choice. Behavioral Neuroscience 121:543 549. Simon NW, Gilbert RJ, Mayse JD, Bizon JL, Setlow B (2009a) Balancing risk and reward: a rat model of risky decision making. Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology 34:2208 2217. Simon NW, Gilbert RJ, Mayse JD, Bizon JL, Setlow B (2009b) Balancing risk and reward: a rat model of risky decision making. Neuropsychopharm 34:2208 2217. Simon NW, LaSarge CL, Montgomery KS, Williams MT, Mendez IA, Setlow B, Bizon JL (2010) Good things come to those who wait: attenuated discounting of delayed rewards in a ged Fischer 344 rats. Neurobiol Aging 31:853 862. Simon NW, Montgomery KS, Beas BS, Mitchell MR, LaSarge CL, Mendez IA, Banuelos C, Vokes CM, Taylor AB, Haberman RP, Bizon JL, Setlow B (2011) Dopaminergic modulation of risky decision making. The Journal of neuroscience : the official journal of the Society for Neuroscience 31:17460 17470.
121 Snyder SH, Taylor KM, Coyle JT, Meyerhoff JL (1970) The role of brain dopamine in behavioral regulation and the actions of psychotropic drugs. Am J Psychiatry 127:199 207. Sokoloff P, Andrieux M, Besancon R, Pilon C, Martres MP, Giros B, Schwartz JC (1992) Pharmacology of human dopamine D3 receptor expressed in a mammalian cell line: comparison with D2 receptor. Eur J Pharmacol 225:331 337. Sokoloff P, Diaz J, Le Foll B, Gu illin O, Leriche L, Bezard E, Gross C (2006) The dopamine D3 receptor: a therapeutic target for the treatment of neuropsychiatric disorders. CNS Neurol Disord Drug Targets 5:25 43. Sowell ER, Thompson PM, Tessner KD, Toga AW (2001) Mapping continued brain growth and gray matter density reduction in dorsal frontal cortex: Inverse relationships during postadolescent brain maturation. The Journal of neuroscience : the official journal of the Society for Neuroscience 21:8819 8829. Sowell ER, Trauner DA, Gamst A Jernigan TL (2002) Development of cortical and subcortical brain structures in childhood and adolescence: a structural MRI study. Developmental medicine and child neurology 44:4 16. Sowell ER, Thompson PM, Holmes CJ, Batth R, Jernigan TL, Toga AW (1999) Localizing age related changes in brain structure between childhood and adolescence using statistical parametric mapping. Neuroimage 9:587 597. Sowell ER, Peterson BS, Thompson PM, Welcome SE, Henkenius AL, Toga AW (2003) Mapping cortical change across the human life span. Nat Neurosci 6:309 315. Spano PF, Govoni S, Trabucchi M (1978) Studies on the pharmacological properties of dopamine receptors in various areas of the central nervous system. Adv Biochem Psychopharmacol 19:155 165. Spear LP (2000) The ado lescent brain and age related behavioral manifestations. Neuroscience and biobehavioral reviews 24:417 463. St Onge JR, Floresco SB (2009a) Dopaminergic modulation of risk based decision making. Neuropsychopharmacology : official publication of the America n College of Neuropsychopharmacology 34:681 697. St Onge JR, Floresco SB (2009b) Dopaminergic modulation of risk based decision making. Neuropsychopharmacology 34:681 697. Stansfield KH, Kirstein CL (2006) Effects of novelty on behavior in the adolescent a nd adult rat. Developmental psychobiology 48:10 15. Stansfield KH, Philpot RM, Kirstein CL (2004) An animal model of sensation seeking: the adolescent rat. Annals of the New York Academy of Sciences 1021:453 458.
122 Steinberg L (2008) A Social Neuroscience Pe rspective on Adolescent Risk Taking. Developmental review : DR 28:78 106. Steinberg L, Graham S, O'Brien L, Woolard J, Cauffman E, Banich M (2009) Age differences in future orientation and delay discounting. Child development 80:28 44. Stopper CM, Floresco SB (2011) Contributions of the nucleus accumbens and its subregions to different aspects of risk based decision making. Cogn Affect Behav Neurosci 11:97 112. Sturman DA, Moghaddam B (2011a) Reduced neuronal inhibition and coordination of adolescent prefro ntal cortex during motivated behavior. The Journal of neuroscience : the official journal of the Society for Neuroscience 31:1471 1478. Sturman DA, Moghaddam B (2011b) The neurobiology of adolescence: changes in brain architecture, functional dynamics, and behavioral tendencies. Neuroscience and biobehavioral reviews 35:1704 1712. Substance Abuse and Mental Health Administration (2011) Results from the 2010 National Survey on Drug Use and Health: National Findings (Office of Applied Studies, NSDUH Series H 41, DHHS Publication No. SMA 11 4658). Rockville, MD: Substance Abuse and Mental Health Services Administration. Sugam JA, Day JJ, Wightman RM, Carelli RM (2012) Phasic nucleus accumbens dopamine encodes risk based decision making behavior. Biol Psychiat ry 71:199 205. Tarazi FI, Tomasini EC, Baldessarini RJ (1998) Postnatal development of dopamine and serotonin transporters in rat caudate putamen and nucleus accumbens septi. Neurosci Lett 254:21 24. Tarazi FI, Tomasini EC, Baldessarini RJ (1999) Postnatal development of dopamine D1 like receptors in rat cortical and striatolimbic brain regions: An autoradiographic study. Dev Neurosci 21:43 49. Teicher MH, Andersen SL, Hostetter JC, Jr. (1995) Evidence for dopamine receptor pruning between adolescence and a dulthood in striatum but not nucleus accumbens. Brain Res Dev Brain Res 89:167 172. Thomas MJ, Kalivas PW, Shaham Y (2008) Neuroplasticity in the mesolimbic dopamine system and cocaine addiction. Br J Pharmacol 154:327 342. Thompson D, Martini L, Whistler JL (2010) Altered ratio of D1 and D2 dopamine receptors in mouse striatum is associated with behavioral sensitization to cocaine. PLoS One 5:e11038.
123 Thompson J, Thomas N, Singleton A, Piggott M, Lloyd S, Perry EK, Morris CM, Perry RH, Ferrier IN, Court JA (1997) D2 dopamine receptor gene (DRD2) Taq1 A polymorphism: reduced dopamine D2 receptor binding in the human striatum associated with the A1 allele. Pharmacogenetics 7:479 484. Tucker KA, Potenza MN, Beauvais JE, Browndyke JN, Gottschalk PC, Kosten TR (2 004) Perfusion abnormalities and decision making in cocaine dependence. Biol Psychiatry 56:527 530. Vadhan NP, Hart CL, Haney M, van Gorp WG, Foltin RW (2009) Decision making in long term cocaine users: Effects of a cash monetary contingency on Gambling ta sk performance. Drug and alcohol dependence 102:95 101. Vaidya JG, Grippo AJ, Johnson AK, Watson D (2004) A comparative developmental study of impulsivity in rats and humans: the role of reward sensitivity. Ann N Y Acad Sci 1021:395 398. Vallone D, Picetti R, Borrelli E (2000) Structure and function of dopamine receptors. Neuroscience and biobehavioral reviews 24:125 132. Van Den Bos R, Lasthius W, Den Heijer E, Van Der Harst J, Spruijt B (2006) Toward a rodent model of the Iowa gambling task. Behav Res Met hods 38:470 478. Van Leijenhorst L, Zanolie K, Van Meel CS, Westenberg PM, Rombouts SA, Crone EA (2010a) What motivates the adolescent? Brain regions mediating reward sensitivity across adolescence. Cereb Cortex 20:61 69. Van Leijenhorst L, Gunther Moor B, Op de Macks ZA, Rombouts SA, Westenberg PM, Crone EA (2010b) Adolescent risky decision making: neurocognitive development of reward and control regions. Neuroimage 51:345 355. Vanderschuren LJ, Everitt BJ (2004) Drug seeking becomes compulsive after prolo nged cocaine self administration. Science 305:1017 1019. Volkow ND, Fowler JS, Wolf AP, Hitzemann R, Dewey S, Bendriem B, Alpert R, Hoff A (1991) Changes in brain glucose metabolism in cocaine dependence and withdrawal. Am J Psychiatry 148:621 626. Volkow ND, Wang GJ, Newcorn J, Telang F, Solanto MV, Fowler JS, Logan J, Ma Y, Schulz K, Pradhan K, Wong C, Swanson JM (2007) Depressed dopamine activity in caudate and preliminary evidence of limbic involvement in adults with attention deficit/hyperactivity diso rder. Archives of general psychiatry 64:932 940. Volkow ND, Chang L, Wang GJ, Fowler JS, Ding YS, Sedler M, Logan J, Franceschi D, Gatley J, Hitzemann R, Gifford A, Wong C, Pappas N (2001) Low level of brain dopamine D2 receptors in methamphetamine abusers : association with metabolism in the orbitofrontal cortex. Am J Psychiatry 158:2015 2021.
124 Weiss VG, Mitchell MR, Vokes CM, Setlow B (2012) High Cocaine Intake Causes Long Lasting Elevations in Impulsive Choice in a Delay Discounting Task. In: Society for N euroscience. New Orleans, LA. Wellman PJ, Nation JR, Davis KW (2007) Impairment of acquisition of cocaine self administration in rats maintained on a high fat diet. Pharmacology, Biochemistry, and Behavior 88:89 93. Welter M, Vallone D, Samad TA, Meziane H Usiello A, Borrelli E (2007) Absence of dopamine D2 receptors unmasks an inhibitory control over the brain circuitries activated by cocaine. Proceedings of the National Academy of Sciences of the United States of America 104:6840 6845. WHO (2008) 10 Fact s on Adolescent Health. In: WHO. Winstanley CA (2007) The orbitofrontal cortex, impulsivity, and addiction: probing orbitofrontal dysfunction at the neural, neurochemical, and molecular level. Ann N Y Acad Sci 1121:639 655. Winstanley CA, Eagle DM, Robbins TW (2006) Behavioral models of impulsivity in relation to ADHD: translation between clinical and preclinical studies. Clin Psychol Rev 26:379 395. Xue Y, Steketee JD, Rebec GV, Sun W (2011) Activation of D(2) like receptors in rat ventral tegmental area i nhibits cocaine reinstated drug seeking behavior. The European journal of neuroscience 33:1291 1298. Yin HH, Knowlton BJ, Balleine BW (2006) Inactivation of dorsolateral striatum enhances sensitivity to changes in the action outcome contingency in instrume ntal conditioning. Behav Brain Res 166:189 196. Yin HH, Ostlund SB, Knowlton BJ, Balleine BW (2005) The role of the dorsomedial striatum in instrumental conditioning. The European journal of neuroscience 22:513 523. Zeeb FD, Robbins TW, Winstanley CA (2009 ) Serotonergic and dopaminergic modulation of gambling behavior as assessed using a novel rat gambling task. Neuropsychopharm 34:2329 2343. Zuckerman M, Eysenck S, Eysenck HJ (1978) Sensation seeking in England and America: cross cultural, age, and sex com parisons. Journal of consulting and clinical psychology 46:139 149. Zuo Y, Wang X, Cui C, Luo F, Yu P (2012) Cocaine induced impulsive choices are accompanied by impaired delay dependent anticipatory activity in basolateral amygdala. Journal of cognitive n euroscience 24:196 211.
125 BIOGRAPHICAL SKETCH Marci Mitchell was born and raised in Flint, Michigan and is the middle of three children. She graduated high school in 2004 and enrolled at the University of Michigan in Ann Arbor the following fall. While studying, Marci gained valuable experience and her love of research in the laboratories of Dr. Kent Berridge and Dr. Jill Becker. She graduated from the University of Michigan in the spring of 2008 with a Bachelor of Science in Brain, Behavior, and Cognitive Sciences. The following fall, she enrolled in a Ph.D. program at Texas A&M University under the guidance of Dr. Barry Setlow The summer of 2010, Dr. Setlow and his wife, Dr. Jennifer Bizon were recruited to the Un iversity of Florid a, to which Marci followed them Marci received her PhD from the University of Florida in the fall of 2012 and is currently a postdoctoral fellow at Yale University in New Haven, Connecticut working with Dr. Marc Potenza.