Baseline studies in cerebral blood flow : reproducibility and density effects associated with a simple visuospatial task

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Baseline studies in cerebral blood flow : reproducibility and density effects associated with a simple visuospatial task
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Thesis (Ph. D.)--University of Florida, 1985.
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Includes bibliographical references (leaves 51-55).
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BASELINE STUDIES IN CEREBRAL BLOOD FLOW:
REPRODUCIBILITY AND DENSITY EFFECTS ASSOCIATED
WITH A SIMPLE VISUOSPATIAL TASK









By

JANET COPELAND FALGOUT


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


1985























To my family and my friends,
who have cared for me throughout
this most solitary of pursuits.















ACKNOWLEDGEMENTS


It is generally true that the motivation to identify oneself as a member of

any profession derives in no small part from contact with-and certainly from

respect and admiration for-those individuals who represent that profession

with distinction and integrity. I am fortunate to be able to claim several of

these individuals as members of my supervisory committee: Dr. Eileen Fennell

(chair), Dr. Hugh Davis, Dr. Jacquelin Goldman, Dr. Russell Bauer, and Dr.

Edward Valenstein. These people-each in his or her unique capacity-have

been my teachers in many different ways for many years. Without their

influence and support, I would not have been able to reach this point in my

education. Without their personal attributes, I would not have wanted to. I am

glad to have the opportunity, in these formal acknowledgments, to publicly

recognize their influence in my personal and professional development, and to

express my very sincere and deeply felt gratitude.

There are other individuals, as well, from among my graduate faculty,

whom I would like to recognize as influential in shaping the focus of my

professional training and research. Among them are: Dr. Nathan Perry, who

trained me in electrophysiologic research and served for many years as a role

model for the research/clinical practitioner; Dr. Mary McCaulley, whose

respect for individual differences permeates her interpersonal relationships as

well as her research; and Dr. Kenneth Heilman, who initially introduced me









(with Dr. Fennell's very capable assistance) to the clinical study of human

neuropsychology. In this vein, I would also like to mention a fondly-

remembered professor from my undergraduate years, Dr. Brad Bunnell, who

initially kindled my interest in physiological psychology, and facilitated my

earliest research efforts.

In more recent years, I have been fortunate to have the professional

guidance and personal friendship of my supervisor and colleague, Dr. Dano Leli,

Clinical Neuropsychologist in Neurology at UAB. I am indebted to him in many

ways for the opportunity to develop this dissertation research. He has been

generous with his encouragement and support, and has never failed to serve as

an advocate in times of need. I am grateful for the association with Dr. Julia

Hannay, of Auburn University, who has served as a role model, teacher, and

friend in the past several years of collaborative work at the UAB Stroke

Research Center, and who did not hesitate to serve also as advocate when that

was needed. Likewise, I am grateful to Dr. C. J. Rosecrans, Director of

Training during my clinical internship at UAB, for his concern and advocacy at

a critical time in my graduate career. I hope his faith in me-as well as that of

my committee and my colleagues-has been justified.

There are many others whose contributions to this research are greatly

appreciated. I would like to thank Dr. J. H. Halsey, Jr., Chairman of Neurology

and Director of the Stroke Research Center at UAB, for his tutelage in the area

of cerebral blood flow measurement and for support of my research in his rCBF

Laboratory. I want to acknowledge the helpful collaboration of two of our

Graduate Research Assistants, Ms. Carol Me Lain and Ms. Susan Wolfe, in

conceptual development and implementation of these reliability studies. I have









also needed and greatly appreciate the efforts and expertise of Mr. Audie

White, rCBF Laboratory Manager, and his assistants, Ms. Tina Davis (now Mrs.

E. Berg) and Ms. Sandra Shodja, in collecting the data for these studies. I

appreciate the assistance of several Stroke Research Center staff members in

developing the stimulus-control instrumentation. I would like to acknowledge

the statistical consultation of Dr. C. R. Katholi, Dept. of Biostatistics at UAB,

who has long been affiliated with the cerebral blood flow studies issuing from

the Stroke Research Center. And finally, I would like to acknowledge and

commend the excellent work of a very talented and tolerant typist and friend,

Ms. Carol Smitherman, in shaping up this manuscript from beginning to end.

In addition to those whose names I have mentioned, there remain more

than a few very special friends, relatives, and colleagues who have consistently

encouraged and supported me over the course of my studies, who will remain

unnamed but not unappreciated. They know who they are and that I will always

be grateful.

Research funding for these studies has been provided by NINCDS Grant

NS 08802, by NIA Grant AG05014, and by private grants from the Anna and

Seymour Gitenstein Foundation and the Virginia J. Cosper Fund.















TABLE OF CONTENTS

Page

ACKNOWLEDGEMENTS .......................................... iii

ABSTRACT ..................................................... vii

LIST OF TABLES ................................................ viii

LIST OF FIGURES ............................................... ix

INTRODUCTION ................................................. 1

DEFINITION OF PROBLEM ....................................... 5

LITERATURE REVIEW .......................................... 10

MATERIALS AND METHODS ..................................... 15

Sample Characteristics ..................................... 15
Apparatus ................................... .............. 15
Procedures ................................................ 16
Statistical Methods .......................................... 22

RESULTS ....................................................... 25

Study 1: Task Effects ...................................... 25
Study 2: Density Effects..................................... 29
Summary of Results ........................................ 37

DISCUSSION .................................................... 38

Study 1: Task Effects ...................................... 38
Study 2: Density Effects..................................... 46
General Issues ............................................. 48
Sum mary .................................................. 50

REFERENCES .................................................. 51

BIOGRAPHICAL SKETCH ......................................... 56






vi















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

BASELINE STUDIES IN CEREBRAL BLOOD FLOW:
REPRODUCIBILITY AND DENSITY EFFECTS ASSOCIATED
WITH A SIMPLE VISUOSPATIAL TASK

By

Janet Copeland Falgout

August, 1985

Chairman: Eileen B. Fennell, Ph.D.
Major Department: Clinical Psychology

Repeated measurements of cerebral blood flow (rCBF) were made using

the 133-xenon inhalation technique in two within-group studies: (1) under

normal resting (NR) and visuomotor task conditions, and (2) during performance

of the visuomotor task at two different rates. Twelve healthy right-handed

males ages 19-35 served as subjects in each study. Analysis of variance

revealed substantial reduction in run-to-run variability of rCBF during the

visuomotor task as compared to the non-task condition. While no major

differences in level of flow were indicated by comparisons between visuomotor

and NR measures, significant individual differences were associated with rate

of task presentation. The hypothesized stabilizing function of a "controlled-

rest" condition in sequential studies-and of its alias, the sensorimotorr control

task" in studies of complex cognitive processes-is validated by these studies.















LIST OF TABLES


Table Page

1 F1 (ml 100 g-1 min-1) Means and Standard Deviations
for Task Effects Group at Detector Locations
Identified in Figure 1. ..................................... 26

2 Comparison of Mean Run-to-run (Error) Variance
Components for VMf and NR Conditions in the Task
Effects Study............................................. 30

3 F1 (ml 100 g-1 min-l) Means and Standard Deviations
for Rate Effects Group at Detector Locations
Identified in Figure 1. ..................................... 31

4 Comparison of Mean Run-to-run (Error) Variance
Components for VMf and NR Conditions in the Density
Effects Study ............................................. 36

5 Comparison Between Two Studies: Run-to-run (Error)
Variance for the VMf Task ................................. 40
















LIST OF FIGURES


Figure Page

1 Schematic representation of approximate detector location
over eight regions of the left hemisphere. ................... 17

2 Examples of stimulus slides for the visuomotor tasks. ......... 19

3 Results of Task Effects study for left hemisphere
regions .................................................. 27

4 Results of Task Effects study for right hemisphere
regions ................................................. 28

5 Results of Density Effects study for left hemisphere
regions.................................................. 32

6 Results of Density Effects study for right hemisphere
regions .................................................. 33

7 Example of change in flow as a function of initial level
on low-rate visuomotor task. .............................. 35
















INTRODUCTION


In the study of brain-behavior relationships there are very few ways in

which the physiologic correlates of cognitive or sensorimotor behaviors can be

directly assessed in healthy, alert individuals. Most common among these

methods are the electrophysiologic techniques (EEG and its computer-assisted

derivatives, e.g., averaged evoked potential and power spectrum analysis) and

the radioisotopic techniques, including the older two-dimensional cerebral blood

flow methodologies and the newer three-dimensional tomographic methods of

estimating cerebral metabolic activity. These techniques, each with its

respective limitations and strengths, offer us the opportunity to observe certain

parameters of the intact human brain in various functional states.

While certainly less sophisticated than the three-dimensional physiologic

imaging techniques now becoming clinically accessible, the two-dimensional

autoradiographic methods have proven both adequate and useful in the

elucidation of brain function dependent on cortical gray-matter activity.

Among these two-dimensional techniques, the 133Xe inhalation method of

measuring cerebral blood flow has been widely used in the study of normal brain

function. Its nontraumatic attributes and utility in assessment of both cerebral

hemispheres simultaneously have made it much preferable to the injection

methods for use with healthy human subjects. Its relative cost efficiency and

the capacity for repeated metabolic measurements over a relatively brief span

of time give it more versatility than most other radioisotopic methods. It







2

remains an important tool in establishing refined experimental procedures

which can be constructively adapted to studies utilizing more modern and costly

tomographic techniques.

With the 133Xe inhalation technique, the cerebral circulation is measured

by introducing a trace amount of diffusible radioactive isotope into the

bloodstream and recording its rate of clearance through the skull by external

radiation detectors. The gaseous isotope is introduced through a rebreathing

system which allows for monitoring the expired-air concentration of

radioactivity, in order to correct for recirculation factors in the head clearance

curve. Computation of cortical or gray matter flow parameters is based on

mathematical models developed by Mallett and Veall (1965; Veall & Mallett,

1966), improved by Obrist and Risberg (Obrist et al., 1967; 1975; Risberg et al.,

1975) and reformulated by Hazelrig et al. (1981) to utilize the total head

clearance curve.

The inhalation method has been shown to correspond closely to the

intracarotid injection method of measuring cerebral blood flow (Reivich et al.,

1975). The injection method has been shown to reflect metabolic changes

related to functional neuronal activity levels (Raichle et al., 1976). Both

methods have been shown to be sensitive to changes in cerebral blood flow

associated with sensorimotor or complex cognitive tasks (Halsey et al., 1979,

1980; Ingvar & Risberg, 1965, 1967; Larsen et al., 1977; Maximilian, 1980;

Risberg & Ingvar, 1972, 1973; Wood et al., 1980). The total curve method of

analysis (Hazelrig et al., 1981) has been found to be particularly sensitive to

blood flow changes associated with simple sensorimotor tasks (Leli et al., 1985).

The standard procedure for obtaining a measurement of regional cerebral

blood flow (rCBF) for an individual has required that the subject lie quietly at

rest with eyes closed while the face mask and detectors are adjusted, 133Xe is







3

administered, and isotope uptake and clearance is monitored for 10 minutes

following a one-minute inhalation period. This so-called "normal rest" measure

is often repeated as a validity check, or the subject may be required to perform

an "activation" task during a subsequent inhalation and clearance period in

order to obtain a measure of task-related cerebral blood flow. Such task-

related measures have the potential for significantly increasing our fund of

information in both clinical/diagnostic and neuropsychologic applications. In

clinical application, for instance, it is reasonable to expect that the

measurement of a person's ability to efficiently mobilize his metabolic

resources (blood flow) on demand would yield more predictive information than

simple determination of flow rate during an ill-defined or uncontrolled state of

rest. In neuropsychologic research, the utility of physiologic data relating to

localization or specialization of function is of obvious value in refining our

understanding of brain-behavior relationships and individual variability.

However, the optimal use of rCBF measurements-whether resting or activated,

and whether for clinical or research application-requires that we obtain

reproducible measurements of flow in relation to well defined behavioral states.

The importance of reproducible measurements becomes apparent when

one notes that the run-to-run variability of the regional resting flow for the

133Xe inhalation method averages about 7 percent across all detector locations

in normal subjects (Blauenstein et al., 1977; Meyer et al., 1978). Individual

regional values, however, ranging up to 50 or 100 percent from one

measurement to the next are not uncommon, particularly in sleep-deprived

subjects (Falgout et al., 1983). When such extreme variability is observed

between two measures taken during a single session for an individual subject,

the practical informational value of the rCBF measured in this "normal resting

state" must be questioned. The uncontrolled variability becomes even more







4

problematic when measures are made over extended periods in patients for

clinical purposes, or when resting baseline values are used for evaluation of

task-related cognitive activation effects. These task-related rCBF activation

effects typically range from 5 to 20 percent greater than the resting baseline-

with a range similar to that of the run-to-run variability of the resting

measures.

In an effort to reduce some of the extremes of state-related run-to-run

variability in the measures of resting flow, the concept of a "controlled rest"

measure has been introduced (Stump et al., 1978; Falgout et al., 1983, 1984) and

is currently being tested in our laboratory. Such a measurement requires that

the subject engage in a low-demand task which requires a continual (though

minimal) focus of attention and a minimal motoric response throughout the

inhalation period. Additionally, the sensorimotor control task, a low-demand

task utilizing the same input and output modalities as the primary complex

activation task under study (Wood, 1980; Leli et al., 1984), has been

incorporated into our experimental design as a standard against which to

measure cognitively mediated rCBF activation associated with the complex

task (Leli et al., 1982, 1983; Hannay et al., 1983; McLain et al., 1984). It is

with the aim of refining our knowledge of these baseline tasks that the

following studies are presented.















DEFINITION OF PROBLEM


The hypothetical utility of a minimal-effort, controlled rest task in rCBF

studies can be intuitively appreciated: A person who is continuously engaged in

a simple, nearly automatic task-but one which requires an overt, observable

response-is less likely to drift into those ill-defined dreamlike states which

border on sleep than one who is asked merely to remain alert but silent and

motionless, with eyes closed, for the 15-20 minutes necessary to complete a

measurement of cerebral blood flow. Therefore, the psychophysiologic

conditions under which a measurement is made are much more easily defined,

since we have some idea of what the subject is doing, in addition to what he is

not doing. In providing a continuous performance task to engage even a

minimal portion of his attentional and motivational capacity, we are setting

both implicit and explicit limits on the behavior we expect to observe during

the course of the measurements. The more explicitly the task is defined, the

more confident we will be in predicting the behavioral response to the testing

situation, both within and between persons; we would hope that the associated

physiologic responses would also reflect that predictability. To date, however,

the stabilizing effect of such minimal-demand tasks on baseline rCBF measures

has been hypothesized, but not demonstrated.

In our own laboratory, studies have been designed to assess reproducibility

issues within same-session and split-session paradigms for controlled-rest tasks,

and to evaluate the stability of the controlled-rest flow when a complex







6

activation-task measurement is interposed between control measures (McLain

et al., 1984). Preliminary analysis suggests that the use of a simple visuomotor

controlled-rest task may limit the extremes of variability associated with the

normal rest measurement: The run-to-run variance of rCBF for the controlled-

rest task is generally lower than that found in analogous normal-rest paradigms.

However, the variability inherent in small-group samples limits the

generalizability of these between-group findings. That is, an apparent decrease

in variability attributed to the use of a controlled rest task may be due more to

sampling artifact than to task effects. The more rigorous test of these

preliminary findings requires that we administer both types of baseline

conditions ("normal" rest and "controlled" rest) to the same sample of

individuals. We will then be in a better position to evaluate the effects of a

controlled rest task on regional cerebral blood flow measurements, in regard to

both mean level of flow and reliability of the measures.

There is in addition a need to begin to define the effects of rate of task

presentation on cerebral blood flow parameters. Our understanding of rCBF

changes associated with complex cognitive activity is otherwise limited. An

interpretational problem encountered in one of our own rCBF studies may be

useful in illustrating this point.

For several practical reasons, the sensorimotor control tasks used as a

reference baseline for the cognitive activation tasks in our first studies (Leli et

al., 1982; Hannay et al., 1983; McLain et al., 1984) have been presented at a

constant rate for all subjects, while the activation task has been self-paced.

The necessity of using a counterbalanced design to minimize potential order

effects was the major design factor precluding an equal rate of presentation of

the control and activation tasks: in half the cases, an individual's average rate

of activation task performance would not be known until after the control task







7

had been administered. It was assumed that a rate of control task presentation

which was estimated to equal or exceed the average activation task

performance would provide the most conservative estimate of rCBF effects

associated with the sensorimotor components of the activation task. It was

assumed, in other words, (a) that rCBF would increase in direct proportion to

the number of task items completed per unit time, and (b) that this relationship

would hold true both for simple sensorimotor and for complex cognitive tasks.

Task-related blood flow changes associated with the cognitive components

specific to the complex task, then, could be sorted out by comparing rCBF

activation during complex task performance to the levels obtained during

sensorimotor task performance.

In fact, in an initial study of a right-left discrimination task (Leli et al.,

1982), when correlations were computed based on relative rCBF change scores

(rCBF for activation compared to control) versus measures of task accuracy or

total number of problems solved, the relationship was found to be an inverse

one: individuals who completed more problems showed a smaller rCBF increase

than those who worked more slowly. By design, as explained above, all

individuals had completed a preset number of control tasks, which equaled or

exceeded the number of self-paced activation tasks completed. Reasoning that

the sensorimotor components of the complex activation task, if nothing else,

would require cumulatively more neuronal activity (and therefore increased

rCBF) for those subjects who performed a greater number of the complex task

items, it seemed clear that the inverse relationship between rCBF and task

performance measures could not be attributed to the sensorimotor differences

between the two tasks: the correlation in that case would have to be a positive

one. Consequently, an "effort" hypothesis was generated, among other

possibilities, to account for the inverse relationship. Note again, however, that







8
this interpretation was grounded on an untested assumption: that more

input/output per given period of time results in higher measured rCBF levels,

even for simple sensorimotor tasks.

We actually know very little about what we can expect and what we can

count on in measurements of rCBF in human subjects either at rest or while

performing an imposed sensorimotor or cognitive task. The current series of

studies continue to examine various parameters of the baseline measurement in

rCBF. In particular, the two studies presented here examine the hemispheric

and regional cerebral blood flow effects of a simple visuomotor task at two

different rates (VMf and VMs) with respect to the following null hypotheses:

(1) Task effects: VMf mean flow is not different from resting mean flow.

(2) Rate effects: VMf mean flow is not different from VMs mean flow.

(3) Reproducibility: (a) Mean run-to-run variability of the resting flow is

not different from mean variability of VMf flow, and (b) Mean run-to-run

variability of VMf flow is not different from mean variability of VMs flow.

The visuomotor task rates selected for study represent the extremes of

those achieved by individual subjects in previous self-paced cognitive activation

studies, the faster (VMf) averaging 7 sec. between stimuli, the slower (VMs)

having an average interstimulus interval of 14 sec. By comparing the effects of

the higher-rate task to normal rest measures in the same group of subjects, one

would ideally document an increased run-to-run reliability of the visuomotor

task without a significant change in mean level of flow. By comparing the two

rates of task presentation within a second group of subjects, one would hope to

document minimal differences in both level and variability of flow between the

two task rates. The findings of increased rCBF stability, combined with








9
minimal change in mean level of flow, would verify the utility of controlled rest

or sensorimotor tasks in both clinical and experimental studies of human brain

function.















LITERATURE REVIEW


In reviewing published research which might aid in formulation of

predictions regarding the studies, there are three areas of particular relevance:

(1) task effects; (2) reproducibility; and (3) rate-of-presentation, or density

effects.

In the evaluation of task effects the primary question is whether the rCBF

measures associated with performance of a simple visuospatial task differ

significantly from those associated with the eyes-closed, resting state. There is

every reason to expect that they should. There are several 133Xe cerebral

blood flow studies which have used visual stimuli in activation tasks of varying

complexity (Risberg et al., 1977; Gur & Reivich, 1980; Roland & Skinhoj, 1981;

Leli et al., 1982). In general, the results have shown bilateral activation-

relative to eyes-closed rest-of the visual associative and posterior parietal

cortex for simple, diffuse stimulation, with increased frontal involvement as

task complexity and the need for focused attention increase. There is in

addition the suggestion from studies using positron emission tomography to

estimate glucose metabolism that right hemisphere activation (again in

comparison to the eyes-closed resting state) may be relatively greater than left

for tasks requiring attention to extra-personal space (Gur et al., 1983).

However, among the visual activation tasks reported in the research literature

which have required an overt response, most have used the verbal, spoken

modality. Since the expected mode of response is likely to be critical in the







11
organization of a whole set of psychophysiologic behaviors, we would expect

response modality to affect the organization of neural activity as well. Indeed,

Leli et al. (1984), in attempting to assess the effects of spoken vs. manual

response modalities using the inhalation technique, have demonstrated major

differences in regional blood flow activation dependent on response modality.

The visuomotor task used for the Leli et al. (1984) study, in fact, serves as the

closest approximation to the visuospatial task at issue here, and may serve as

the best model for predictions of task effects for the present study.

In the Leli et al. (1984) study, a simple number-recognition task utilizing a

manual (button-press) response and presented at a 7-second rate produced

significant rCBF increases (vs. rest) averaging 8 to 11 percent at bilateral

temporo-occipital and posterior parietal detector locations. While the task

induced flow increases in both cerebral hemispheres, the right hemisphere

increases were on the average higher than those for the left, even for these

numerical stimuli requiring a right-handed response. We might expect, then,

similar results from performance of a visual task requiring simple pattern

recognition and using the same motoric response mode and a similar rate of

task presentation.

In making any task-to-rest comparisons of rCBF measures, of course, we

are glossing over the whole issue of intrinsic run-to-run variability in the

resting measures which led to the search for more reliable baseline or reference

measures in the first place. Thus, the evaluation of task effects relative to rest

may be of interest only if, and to the extent that, the effects are strong and

consistent across individuals. A more basic concern may be the question of run-

to-run variability of the resting and task-related rCBF measures.

Although reproducibility-or reliability, as it is more often called-has

been evaluated in many rCBF studies under resting, non-stimulated conditions







12

in normal subjects (Obrist et al., 1975; Blauenstein et al., 1977; Stump et al.,

1978; Larsen et al., 1977; McHenry et al., 1978; Meyer et al., 1978), only a few

have addressed this issue using activation or task-related measures. With

subjects who underwent two rCBF measurements while working on parallel

forms of a complex reasoning task (Raven's Progressive Matrices), Risberg et

al. (1977) reported a mean relative decrease in cerebral blood flow in frontal

regions on second testing, while activation in posterior regions persisted.

Maximilian (1980) also reported an initial activation to simple auditory (verbal)

stimulation which disappeared upon second testing.

Studies in progress in our own laboratory have begun to evaluate task-

repetition effects both within the same rCBF session and between sessions

separated by a week or more, using both simple and complex tasks. Preliminary

results for the visuomotor task under discussion suggest that same-session

level-of-flow effects are reproducible: that is, the regional and hemispheric

means are not significantly different from each other when the task is repeated

up to four times on the same day, whether or not a more difficult cognitive task

is interposed. In order to more accurately assess the relative run-to-run

reliability of the rCBF associated with the visuomotor task in comparison to

resting measures of rCBF, however, we are obliged to obtain both sets of

measures from the same individuals. If successful, the major effect of a simple

task such as the visuomotor task under study would be to stabilize run-to-run

variability of the rCBF measures as compared to the normal resting state

(Stump et al., 1978; Falgout et al., 1983, 1984). This effect would be obtained

regardless of the task effects defined by rate or level of flow relative to resting

baseline.

The final topic of interest here, task rate effects on cerebral blood flow,

is an issue which is very nearly independent of, though certainly complementary







13

to, the assessment of task vs. rest effects. The primary question involves the

comparison of rCBF effects associated with the same task at two different

rates: Would task presentation differing in rate by a factor of two have a

significant, consistent or predictable effect on hemispheric or regional rCBF?

The only systematic investigation of rate effects on rCBF was reported by Fox

and Raichle (1984) using the H2150 tracer method with positron emission

tomography (PET). Patterned photic stimuli were presented at rates ranging

from 0.0 to 61 Hz to obtain eight sequential rCBF measures from each subject.

The subjects were not required to make stimulus-related responses. A

monotonic rCBF increase at the primary visual cortex was noted, linear

between 1.0 and 7.8 Hz, and declining thereafter. Since stimulus rates below

1.0 Hz were not evaluated, and since the combination of sensory, motor, and

volitional factors requisite to a sensorimotor control task were not present, we

are not able to gain much information from this study about the expected rate

effects in one of our cognitive activation studies. We can hope, but cannot

presume, that rate effects will be negligible at low rates of presentation.

The purpose of this research is twofold: (1) to examine the effect of a

minimal-effort, sustained-attention, visual-motor task on the level of flow and

within-session reproducibility of regional cerebral blood flow (rCBF)

measurements, and (2) to examine the rCBF changes related to a high vs. low

rate of repetition of that task, i.e., task rate effects. These studies focus

directly on the question of what rCBF effects we can reliably obtain in a young,

healthy, non-patient population. Moreover, they examine assumptions that are

central to the interpretation of rCBF effects attributed to complex cognitive

tasks. Their import lies both in the predictive utility of the 133Xe inhalation

technique as a clinical tool, and in the theoretical utility of the method in

neurobehavioral research. We would hope that these findings would be of value







14
as well in establishing experimental paradigms for research using the newer

three-dimensional radioisotopic techniques to study the working brain.















MATERIALS AND METHODS


Sample Characteristics


Twenty-four healthy, right-handed, nonsmoking men ages 18 to 35 were

selected from volunteers within the local community. They were interviewed

to rule out major medical or psychiatric disorders, head trauma or other

neurologic disorders, history of learning disability, hypertension, asthma, or

allergic or sinus disorders that might impair normal breathing. They were

informed of risks and procedures in conformance with guidelines for human use

issued by the Institutional Review Board for the University of Alabama at

Birmingham. The 24 men were randomly assigned to one of two experimental

studies: a Task Effects study and a Density or Rate Effects study. They were

paid $20-$30 each for their participation, depending on the amount of time

involved.


Apparatus


rCBF data collection system. The rCBF data collection system has been

described in detail for our laboratory by Wilson et al. (1977). In brief, there are

three major components:

(1) A rebreathing system for administering 133Xe and monitoring the

expired-air concentration of CO2 (PeCO2).

(2) A collimated Nal scintillation detector system with amplifiers for

monitoring the rate of 133Xe clearance through the skull and one








16

for monitoring the expired air concentration of 133Xe. The head

detectors are arranged in two sets of eight and mounted on guide

tracks to assure replicable placement close against the lateral sides

of the subject's head (see Fig. 1).

(3) A computer system for processing of 133Xe data. For each rCBF

measurement, the air curve is sampled at 0.2 sec intervals, while

counts from the head detectors are sampled at 2.0 sec intervals for

11 minutes after inhalation begins.

Stimulus-response system. The stimulus-response system for the

administration of visual tasks during rCBF measurement consists of a Kodak

Carousel projector connected to an auxiliary timer, a projection screen located

approximately 5.5 feet above the subject (who lies supine), and a set of four

small red indicator lights located horizontally under the screen, which are

activated by a thumb depression switch held in the subject's right hand.


Procedures


General. Four separate 11-minute measurements of rCBF were obtained

during one 2-hour session for each individual. Before undergoing the rCBF

measurements, each person had the procedures and purpose of the study

explained in detail, signed an informed consent, and filled out standard

questionnaires relating to personal history and habits.

rCBF measurement. The measurement of rCBF requires the subject to

recline on a hospital bed with his head resting between two adjustable detector

blocks. He breathes through an oxygen-type molded rubber mask fitted

securely over his nose and mouth during the rCBF measurements. The

computer operator and technician work beyond his range of view, and room

lighting is subdued during the measures. There is constant low-frequency noise



















































Figure 1. Schematic representation of approximate detector location over
eight regions of the left hemisphere. The detector montage is duplicated over
the right hemisphere.








18

from a large exhaust fan and the various equipment fans, so that the sound of

the projector's advance is masked considerably.

Task descriptions. There are two basic types of tasks these subjects are

asked to perform during the rCBF measurements: the 'normal-rest' (NR) task

and the visuomotor (VM) task. The visuomotor task is presented at one of two

rates as explained below, so that effectively there are three conditions under

which rCBF measurements may be made: NR, VM-fast (VMf) or VM-slow (VMs).

Each subject in fact undergoes four rCBF measurements under only two

different conditions, depending on the study to which he is assigned.

Stimuli. The NR condition requires no external stimulus presentation.

The VM task uses a series of slide-projected black-on-white line drawings as

stimuli. Each slide presents an array of four horizontal and four vertical lines

in which one of the vertical lines is crossed at the top, as in an upper-ease

"typed T" (see Fig. 2 for two examples). These slides are advanced at 5 to 9

second intervals (averaging 7 seconds) in the VM-fast condition, and at 10 to 18

second intervals (averaging 14 seconds) in the VM-slow condition. The stimuli

are projected onto an overhead screen using the high intensity setting of the

Kodak projector in a darkened room. The size of the illuminated field is 40 cm

wide x 30 cm high, at a distance of 140 cm from the subject's eyes, and

subtending a visual angle of approximately 16 degrees.

Instructions. For the NR condition the subject is instructed: "Just relax,

with your eyes closed, and try not to move around during the blood flow

measurement. We want you to remain alert but comfortable, and to breathe as

normally as possible throughout the measurements." The resting condition is

begun one minute before the rCBF measurement begins.

For the VM conditions, the subject is instructed: "For each slide you must

indicate, by moving the light with this thumb-press button, which vertical line





















































Figure 2. Examples of stimulus slides for the visuomotor tasks. In each slide,
one of the four vertical lines is crossed at the top. Recognition of this 'target'
must be indicated by illuminating the red indicator light beneath it, using a
thumb-press trigger held in the right hand. The slides are presented with an
average interstimulus interval of 7 seconds (range = 5 to 9) for the high-rate
visuomotor task (VMf), and at an average interstimulus interval of 14 seconds
(range = 10 to 18) for the low rate task (VMs).







20

is crossed by a horizontal one. The light will clear itself as the slide changes.

There are no hidden problems or patterns you need to notice, the purpose is

merely to give you a simple visual-motor task to work on during the blood flow

measurement. Let your eyes scan the visual pattern and use the least motion

necessary to press the button with your thumb. Breathe as normally and

regularly as you can, and try not to move around during the measurement." The

subject is allowed to practice on four slides, and begins the VM task one minute

before the CBF measurement begins.

Order of tasks. Since the 133Xe inhalation technique is a costly one (and

healthy, non-smoking volunteers are at a premium), only those temporal

permutations of the measurement conditions which are most relevant to

interpretation of our other rCBF studies were used. Due to the limitation of

four rCBF measurements per year for non-patient volunteer subjects, two

studies were required for the evaluation of three measurement conditions and

associated run-to-run variability. Each study used one group of 12 subjects.

The first study, designated the Task Effects study, allows for comparison

of the differential effects of the normal resting vs. the visuomotor task on (a)

level (or rate) of hemispheric and regional cerebral blood flow, and (b)

variability of flow from one measurement to the next.

The second study, designated the Density Effects study,1 allows for

comparison of the effects of the visuomotor task at two different rates of

presentation on (a) level of hemispheric and regional flow, and (b) variability of

flow from one measurement to the next.



1A note regarding terminology is in order here vis-a-vis the distinction
between "rate" and "density" effects in rCBF studies. If two rates of stimulus
presentation are to be compared, one double the other, a simple "rate" effect is
one which would be obtained by monitoring rCBF for an equal number of
stimulus/response cycles at each rate of presentation; that is, by halving the








21

Within each study, subjects were randomly assigned to one of four orders

of task performance:

Order Study 1 Study 2
Model Task Effects Study Density Effects Study

A-B-B-A VMf-NR-NR-VMf VMf-VMs-VMs-VMf
B-A-A-B NR-VMf-VMf-NR VMs-VMf-VMf-VMs
A-B-A-B NR-VMf-NR-VMf VMf-VMs-VMf-VMs
B-A-B-A VMf-NR-VMf-NR VMs-VMf-VMf-VMs


Thus, each subject underwent four rCBF measurements (twice for each of

two different task conditions) during one 2- to 21-hour session. These

permutations permit the evaluation of task effects, rate effects, and

reproducibility effects related to both task and task rate, according to the

hypotheses stated above.

Blood flow index. The blood flow index of interest here is f l, representing

primarily the fastest-clearing tissue in the brain, or gray matter flow (Obrist et

al., 1975), and expressed in ml 100 g-1 min.-1 It is derived according to the

total head curve method of analysis (Hazelrig et al., 1981) for eight detector

locations over each hemisphere (Fig. 1).

Physiologic data. Arterial CO2 is estimated from end-expired air

concentrations (PeCO2). Blood pressure is recorded with a manual

sphygmomanometer before each rCBF measurement. The estimated mean



time period of task performance while presenting a constant or equal number of
stimuli. Such studies are possible in physiologic studies (such as EEG) which
have a sufficiently brief or variable period of data analysis. However, since the
sampling window is set in rCBF studies to encompass a period of 10-12 minutes,
doubling the rate of stimulus presentation also doubles the total number of
stimulus/response cycles which are sampled in that window. Therefore, the
term "density" is more accurate than "rate" in describing the effects which are
addressed in this study. Having recognized this distinction, however, I will
proceed to use the two terms interchangeably, and have even favored the use of
"rate" in most instances, because I believe this is the concept most readily
appreciated by most readers.







22

arterial blood pressure (MABP) is calculated from systolic (SBP) and diastolic

(DBP) pressures according to the formula MABP = DBP + 1/3 (SBP + DBP).


Statistical Methods


Statistical analysis of the rCBF data is approached in two ways. First is

the standard analysis of variance (ANOVA) approach used in previous studies to

test for task-related effects on mean level of flow. Second is a variance

components analysis to assess run-to-run variability of rCBF under different

task conditions. The general procedures are outlined below.

(A) To assess for task and task rate effects on mean level of flow:

(1) The data from each study are examined for normality and

homogeneity of variance.

(2) The data are screened by covariate analysis for each detector

location to determine whether age, PeCO2, or MABP account for a significant

portion of the variance in a one factor, mixed model, repeated measures

ANOVA which treats Subject as a random between-subjects variable and

Treatment as a two-level within-subject factor (Myers, 1972, Ch. 7). The GLM

Procedures developed by SAS Institute, Inc. (1982) are used for the analyses of

variance and covariance.

(3) If covariates do not add significantly to the fit of the model, a

reduced-model repeated-measures ANOVA is run for each detector location

with fl as the dependent variable. Again, Subject serves as a random between-

subjects factor that adjusts for those individual differences in initial or average

level of flow which invariably account for the greater portion of variance in

rCBF studies. The Treatment factor is a within-subject factor with two levels

for each study.








23

(4) When uncertainty exists regarding assumptions of normality or

homogeneity of variance, rank order ANOVAs are computed to verify

significant findings (Winer, 1971, p. 301).

(B) To assess for within-subject run-to-run variability of one task vs.

another, the VARCOMP procedure (SAS, 1982) is applied to the rCBF data (fl)

from each study after sorting by type of task. Thus, the total test-retest

Subject variance for the two NR measurements in the Task Effects study can be

partitioned into between-subject and within-subject (or error) components for

that task, and the error component can be compared (by F-ratio computation)

to the error variance component from the VMf task for that study.

In anticipation of the results to be presented, it should be noted that the

application of F-tests to comparison of the within-subject variance components

computed for each type of task produces results similar to those of Cochran's C

or Hartley's Fmax statistics for testing homogeneity of variance (Winer, 1971,

p. 205). In this sense, the discovery that within-subject error (i.e., test-retest)

variance is significantly different depending on type of task (Study 1) should,

strictly speaking, raise questions about application of analysis of variance

techniques to those data. However, the F-ratios obtained in this study, while

certainly significant within the context of a response-variability assessment,

are not of sufficient magnitude to create a major methodologic concern among

those who espouse the ANOVA techniques (Myers, 1972, pp. 72-76). The

practical effects of a difference in error variance, in any case, should be to

inflate 4l, the probability of a Type 1 error; that is, the probability of rejecting

a true null hypothesis. This distortion is minimized when sample sizes are

equal.

One suggested method of handling the problem (if it is one) of

heterogeneity of variance prior to ANOVA is by corrective transformation of








24
the data to achieve homogeneity. While such preliminary transformation seems

appropriate when sample sizes are larger and trends are apparent, consistent, or

physiologically meaningful, an arbitrary, ad hoe transformation does not seem

to be indicated when sample size is limited and trends are not evident.

Likewise, in following up those analyses where ANOVA results indicated non-

additivity in the model (Study 2), attempts at corrective data transformation

were avoided. Regression/correlation analysis was applied, instead, in an

attempt to define the nature of the interaction effects.















RESULTS


Study 1: Task Effects


The first study compares regional and hemispheric rCBF measures

obtained during normal rest (NR) and visuomotor task (VMf) conditions in a

group of 12 right-handed males.

Table 1 contains the means and standard deviations of fl values for the

NR and VMf tasks at each detector location (LOC) and for the left and right

hemispheric means (LM and RM). The flj value for each task represents a group

average over two rCBF measures for each subject. Figures 3 and 4 graphically

present the fl means and standard errors of the means for the NR and VMf

tasks. The means of the physiologic measures, MABP and PeCO2, did not differ

significantly between NR and VMf measurement conditions.

Analysis of covariance for each region revealed no significant or

systematic effects of age, PeCO2, or MABP which were not adequately

accounted for by the Subject factor. Reduced-model repeated measures

ANOVAs for each region to test for mean differences due to task effects

revealed no significant F-ratios for Task at any region except RF, the right

hemisphere inferior temporal detector (p('F) = .03). At RF, the mean flow for

the VMf task is 5% higher than that for the NR condition. Most of the variance

in the model at all regions is accounted for by the random Subject factor, and

there are no significant Subject x Task interactions.










TABLE 1. F1 (ml 100 g-1 min-1) Means and Standard Deviations
for Task Effects Group at Detector Locations Identified in Figure 1.


LEFT HEMISPHERE


RIGHT HEMISPHERE


LOCa TASK MEANb S.D. LOCa TASK MEANb


VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR


VMf
NR


77.2
78.7

77.5
77.7

67.0
67.7

73.0
71.8

66.7
67.9

64.0
62.3

69.9
68.5

63.4
61.4


70.7
70.5


12.8
15.4

12.3
14.5

9.4
12.8

11.8
13.7

8.4
12.6

8.9
10.6

10.6
11.4

8.2
11.1


VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR


9.8
12.5


VMf
NR


78.7
80.0

78.6
79.4

68.7
68.4

71.9
73.3

68.6
68.3

65.1
62.0

71.1
68.8

64.2
61.9


71.7
71.5


S.D.

14.1
16.0

13.0
14.9

9.8
12.9

12.2
14.5

9.6
12.7

9.0
9.7

11.6
11.7

6.4
10.7


10.4
12.7


a Detector location as identified in Figure 1. LM and RM represent left and
right hemispheric averages over the eight detector locations.
b The F1 value for each task represents a group average over two rCBF
measures for each of 12 subjects.

















80 -


75-


70 -


65 -,


if ii


uI


60-O
i


I I I
I I I I I I I l~~I I


Task
Location


a I -
0-i a-


fn fn fn fn fn fn fn fn


LA LB LC LD LE


LF LG LH = LM


Figure 3. Results of Task Effects study for left hemisphere regions. Detector
location is identified in Figure 1; LM represents the hemispheric mean. The
high-rate visuomotor task (f) is indicated by triangles, the normal rest measure
(n) by circles. Flow value for each task represents the fl (ml 100 g-1 min-l)
group average over two rCBF measures for 12 subjects. Standard error of the
mean is indicated for each point.


Ut


- -- J -














dlii


Ii0


Ii


- a I S a a a I I * I a a a J
1a1a11aaaaa1aa


Task
Location


fn fn fn fn


RA RB RC


fn fn


RD RE


fn fn


RF RG RH


Figure 4. Results of Task Effects study for right hemisphere regions. Detector
location is identified in Figure 1; RM represents the hemispheric mean. The
high-rate visuomotor task (f) is indicated by triangles, the normal rest measure
(n) by circles. Flow value for each task represents the fj (ml 100 g-1 min-1)
group average over two rCBF measures for 12 subjects. Standard error of the
mean is indicated for each point.


U


C
E



0
.L
IL


80-i


75-


70-

65 -4


60-,


fn
RM








29

Assessment of within-subject variance for each task was achieved by

partitioning the total variance (now pooled into a Subject factor) into between-

subject and within-subject (i.e., error) variance components, using the SAS

(1982) VARCOMP Procedure. Table 2 contains the mean within-subject

variance components for each type of task and each detector location.

Comparison of the error components for each task (NR vs. VMf) by F-ratio

computation revealed significant reduction (p( F12,2) .05) of run-to-run

variability at 12 of the 16 regions during performance of the visuomotor task.

Most pronounced reduction was obtained at detector locations LE and RH.


Study 2: Density Effects

The second study compares regional and hemispheric rCBF measures

obtained during performance of the visuomotor task at high and low rates (VMf

and VMs) in a second group of 12 right-handed males.

Table 3 contains the means and standard deviations of fl values for the

VMf and VMs tasks at each detector location (LOC) and for the left and right

hemisphere means (LM and RM). The fl value for each task rate represents a

group average over two rCBF measures for each subject. Figures 5 and 6

present the means and standard errors of the means graphically for each

hemisphere. The means of the physiologic measures, PeCO2 and MABP, did not

differ significantly between the VMf and VMS measurement conditions.

Covariate analysis for each region revealed no significant or systematic

effects of age, PeCO2, or MABP which were not adequately subsumed under the

SUBJECT factor. Reduced-model ANOVAs for each region to test for mean

flow differences due to Rate of task presentation and response (i.e., density

effects) revealed significant Subject x Rate interaction at detector locations

LB, RC, RG, and for left and right hemisphere means (LM and RM), along with










TABLE 2. Comparison of Mean Run-to-run (Error) Variance
Components for VMf and NR Conditions in the Task Effects Study


LEFT HEMISPHERE


RIGHT HEMISPHERE


ERROR
LOCa TASK VARIANCE


VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR


VMf
NR


18.0
42.4

15.2
43.8

18.2
57.8

32.9
25.3

11.3
81.5

20.2
48.5

11.6
35.9

16.6
47.1


8.6
33.2


F-RATIOb


2.36


2.84C


3.17c


1.30


2.40


3.09c


2.84c


3.86C


LOCa TASK


VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR

VMf
NR


VMf
NR


ERROR
VARIANCE

21.4
39.1

26.3
55.1

22.5
56.0

16.6
73.7

15.8
74.2

24.8
49.9

20.3
64.2


8.4
56.4


8.5
47.8


a Detector location as identified in Figure 1. LM and RM represent left and
right hemispheric averages over the eight detector locations.

b Ratios are computed by dividing the larger variance by the smaller one,
regardless of direction of difference.


c p(>F12, 12)'C.05

d p-.005


F-RATIOb


1.82


2.10


2.48


4.44c


4.70c


2.01


3.16c










TABLE 3. F1 (ml 100 g-1 min-1) Means and Standard Deviations
for Rate Effects Group at Detector Locations Identified in Figure 1.


LEFT HEMISPHERE


RIGHT HEMISPHERE


LOCa TASK MEANb S.D. LOCa TASK MEANb S.D.


VMf
VMS

VMf
VMs

VMf
VMS

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs


VMf
VMs


77.3
78.9

76.5
78.3

66.7
67.3

72.4
74.3

67.1
68.2

62.7
63.5

70.3
71.6

63.0
63.5


7.4
11.2

6.7
10.5

5.9
8.8

4.5
6.7

4.6
6.8

5.8
7.4

4.8
6.3

5.2
7.1


VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs


70.5
71.7


VMf
VMs


8.4
10.2


78.4
78.1

77.3
77.9

68.2
69.8

72.3
73.5

68.9
69.2

64.1
64.5

70.2
70.7

62.6
62.3


71.1
71.7


a Detector location as identified in Figure 1. LM and RM represent left and
right hemispheric averages over the eight detector locations.

b3 The F1 value for each task represents a group average over two rCBF
measures for each of 12 subjects.



















E
0)
0
0

E

_0
LL


80-


75-


70-


65 -4


if


4


if


60 -

L..
Task
Location


- I I 1 I I
:I I I I 1 1 1-- 1--1
fs fs fs fs fs
LA LB LC LD LE


- ,-, :- : - J
fs fs fs fs
LF LG LH LM


Figure 5. Results of Density Effects study for left hemisphere regions.
Detector location is identified in Figure 1; LM represents the hemispheric
mean. The high-rate visuomotor task (f) is indicated by triangles pointing up,
the low-rate task(s) by triangles pointing down. Flow value for each task
represents the fl (ml 100 g-I min-1) group average over two rCBF measures for
12 subjects. Standard error of the mean is indicated for each point.



















c7
E

o
0)
0

C
0
L-
U.


80 -:


75-


70-


65 -


60--
"L.

Task
Location


Iii'


if


I


fs


Ip


1


* a a a a a a a a a a
a ~ a a a


fs fs fs fs


RA RB RC RD RE


fs fs fs fs
RF RG RH RM


Figure 6. Results of Density Effects study for right hemisphere regions.
Detector location is identified in Figure 1; RM represents the hemispheric
mean. The high-rate visuomotor task (f) is indicated by triangles pointing up,
the low-rate task(s) by triangles pointing down. Flow value for each task
represents the fi (ml 100 g-1 min-1) group average over two rCBF measures for
12 subjects. Standard error of the mean is indicated for each point.


a a a J.
I a a








34
marginal effects at LD and RD. Inspection of the nonsignificant F-ratios for

Rate effects revealed a suspicious number of fractional values, suggesting that

the assumptions underlying the ANOVA model had not been met. Since tests

for homogeneity of variance and inspection for normality of error distribution

were essentially non-productive the assumption of independence of

observations was examined by correlation analysis.

At those detector locations marked by significant interaction effects, the

means of fl (within-subject) observations under the VMf condition were not

significantly related to the means of fl observations associated with the VMs

task. However, differences between the mean fl values for VMf and the mean

fl values for VMs were highly and negatively correlated (r> -.80, p4.001) with

the mean fl values for the VMS task. This relationship is illustrated in Figure 7

for the right posterior parietal area, RG. Since the correlations between the

VMf-VMs difference scores and the mean fl values for the VMf task did not

reach significant levels, the dependence is such that mean level of flow on the

slow-rate visuomotor task becomes a useful predictor of amount of change

expected with the high-rate task (VMf), but not vice versa. These results

suggest a functional dependence between the rCBF responses to the two

measurement conditions which differed only in rate (or density) of task

performance.

Partitioning of the total variance for each task into between- and within-

subject components to obtain estimates of relative run-to-run variability

revealed significant F-ratios (p(> F12,12)-.05) for comparison of VMf to VMs

at detector locations LH and RC, where variability was smaller for VMf, the

high-density task. The mean within-subject variance components for each task

are displayed in Table 4 for each detector location.







35
















15 -

> 10-,

S 05 0

M 00- 00

-o -05

o 10-
LL
15-
60 65 70 75 80 85

Flow in ml l00oog-1 min-1



Figure 7. Example of change in flow as a function of initial level on low-rate
visuomotor task. Flow change is indicated in ml 100 g-1 rmin-1 as the mean fl
difference for each subject between measures during the high-rate and low-rate
visuomotor tasks (VMf VMs). Initial flow level for the slower, VMs, task is
indicated on the horizontal axis. Change in flow is positive at low initial VMs
levels, and negative at extremely high initial levels.









TABLE 4. Comparison of Mean Run-to-run (Error) Variance Components
for VMf and VMs Conditions in the Density Effects Study.


LEFT HEMISPHERE


RIGHT HEMISPHERE


ERROR
LOCa TASK VARIANCE


VMf
VMs

VMf
VMs

VMf
VMS

VMf
VMs

VMf
VMS

VMf
VMs

VMf
VMs

VMf
VMs


VMf
VMs


24.5
44.1

24.3
13.7

10.1
22.2

11.6
21.3

14.7
13.9

18.2
29.2

14.2
19.9

9.8
27.4


F-RATIOb


1.80


1.77


2.19


1.84


1.06


1.60


1.40


2.79c


1.21


LOCa TASK


VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs

VMf
VMs


VMf
VMs


ERROR
VARIANCE

31.2
40.2

29.1
13.7

8.1
27.1

20.1
12.8

18.1
20.5

31.0
48.8

13.3
8.5

8.1
18.7


a Detector location as identified in Figure 1. LM and RM represent left and
right hemispheric averages over the eight detector locations.

b Ratios are computed by dividing the larger variance by the smaller one,
regardless of direction of difference.


c p(>F12, 12)<.05


F-RATIOb


1.29


2.12


3.35c


1.57


1.13


1.57


1.56


2.30


1.11








Summary of Results


No treatment differences in mean level of flow due to task or task rate

effects are evident in either study, except for region RF in the Task Effects

(NR vs. VMf) group. However, a marked reduction in run-to-run variability is

achieved by the VMf task in comparison to the NR condition. Significant

individual differences are evident in the relative effects of the high and low

rate visuomotor tasks on level of flow at several detector locations. At these

regions, the mean level of flow (f1) associated with the low-rate task is

inversely correlated with the mean difference in flow between the two tasks.














DISCUSSION


The results of the first study presented here have validated two of our

working hypotheses: (1) that baseline data can be stabilized by having a subject

perform a simple, minimal attention task in place of an eyes-closed, "non-task,"

"resting" baseline; and (2) that such tasks can be appropriately selected so as to

create minimal regional changes of flow, in keeping with the requirements of a

"good" baseline task (Stump et al., 1978). The second study has elaborated on

the results of the first by examining the effects of presenting the same

visuomotor controlled-rest task at two different speeds. These results

demonstrate, if nothing else, the salience of individual differences in

physiologic studies of brain function. They also lead us to continue to question

some of the other working hypotheses upon which we build our studies.


Study 1: Task Effects

The most important results from the first study relate to the stabilization

of baseline data by use of a minimal-attention visuomotor task. It is evident

from the results presented in Table 2 that the VMf task significantly reduces

run-to-run variability of regional cerebral blood flow in comparison to the

normal rest condition when both are given to the same subjects. Eight regions

and both hemispheric means show significant reduction in variability for the

visuomotor task as compared to the normal rest. The areas showing the highest

variance component ratios (RH and LE) are associated with sensory-related






39
aspects of the stimulus presentation and task performance: Detectors "E"f

reflect, no doubt, metabolic activity related to sounds associated with

presentation of the visual stimulus, while the right temporo-occipital detector

(RH) most likely reflects the neuronal activity required for processing the

visuospatial task. It is possible that, for group data, those cortical areas which

are most "engaged" by the simple task may reflect this neuronal processing by a

more restricted range of activity, as opposed to an overall increase in level of

flow. This effect would certainly be consistent with the rationale for

implementation of a sensorimotor control task in the first place. The failure to

find improved reproducibility for the left perisylvian region (LD)-which should

also be engaged by the right-hand thumb-press response-however, raises some

question about this hypothesis. It is indeed puzzling that this area (LD) is less

variable for the normal rest condition than for the visuomotor task condition.

Inspection of Table 2 reveals that, for some reason, the NR error variance is

particularly small at this region. Whether this is a random artifact of sampling,

or a task-related phenomenon reflecting, for instance, task carryover effects, is

a question which can be addressed only with further experimentation.

Since the variability across tasks and regions is on the whole greater for

the Task Study group than for the Density Study group (see Tables 1 and 3), one

might suspect that the apparent stabilization of run-to-run variability by the

VMf task which is notable in the Task Effects study might be simply an artifact

of greater total variance for that group. However, between-group comparison

of the VMf error variance for the two groups suggests that the task itself

provides run-to-run stability for repeated measures, regardless of other

variability inherent in the groups. For illustration, the VMf error variance

components from the two studies are compared in Table 5, and F-ratios are

computed as an index of distribution similarity. Only two regions (LD and RC)














LOCa

L LA
E
F LB
T
LC
H
E LD
M
I LE
S
P LF
H
E LG
R
E LH


LM


RA

RB

RC

RD

RE

RF

RG

RH


RM


TABLE 5. Comparison Between Two Studies:
Run-to-run (Error) Variance for the VMf Task

Density Task
Effects Effects
Group Group

24.5 18.0

24.3 15.4

10.1 18.2

11.6 32.9

14.7 11.3

18.2 20.2

14.2 11.6

9.8 16.6


8.1 8.7


31.2

29.1

8.1

20.1

18.1

31.0

13.3

8.1


7.4


21.4

26.2

22.5

16.6

15.8

24.8

20.3

8.4


8.5


Between-group
F-Ratiosb
(df = 12, 12)

1.36

1.58

1.80

2.84C

1.30

1.11

1.23

1.69


1.07


1.48

1.11

2.78c

1.21

1.14

1.25

1.53

1.04


1.15


a Detector location for left and right hemisphere regions A-H as indicated in
Fig. 1, and for the hemispheric means (LM and RM).
b Ratios are computed by dividing the larger variance by the smaller one, and
therefore are non-directional.
c p(>F)<.05







41

show significant distributional differences (p(>F)< .05). The general

equivalence of the repeated measures variance components between the two

studies adds weight to the conclusion that a visuomotor control task of this kind

can achieve a more reliable baseline for repeated measures studies than the

eyes-closed, non-directed, normal rest condition.

The predominantly negative regional CBF findings re: task effects on

mean level of flow for the first study are not totally consistent with previous

findings, even from our own laboratory. The study by Leli et al. (1985) which

compared a visuomotor number-recognition task to normal rest conditions did

find rCBF activation effects at bilateral posterior channels G and H, as well as

right hemisphere channel C, using the full curve method of analysis. That study

differed from the present one in several ways, however: (1) the temporal

ordering of the visuomotor task in relation to control conditions was not

completely counterbalanced, (2) the visual stimuli were numeric as opposed to a

spatial array of lines, (3) the stimuli were presented at an automated 7-sec.

interstimulus interval versus pseudorandom 5 to 9 sec. intervals used in the

current study. An earlier study (Leli et al., 1982) which used an even simpler

control condition (blank slides presented automatically every 7 sec. and

requiring a delayed alternation button-press response) reported control

activation effects (vs. rest) at all locations except LB, LH and RD, using the

partial curve method of analysis. Again, the temporal ordering of the tasks was

such that the activation and control tasks were counterbalanced at positions

two and three, while normal rest conditions were placed first and last.1 Results



1This experimental paradigm had been implemented in order to allow
adjustment for potential habituation effects over the course of the CBF session.
The use of first- and fourth-position rests along with activation tasks
counterbalanced at positions two and three is not criticized. It serves as an







42

from a recent study (judgment of line orientation) issuing from our laboratory

(Hannay et al., unpublished manuscript) are more congruent with the current

findings. The control task consisted of a repetitive spatial array of lines

presented at a 5 to 9 sec. interstimulus rate, as in the current study, and

requiring a two-choice button-press, delayed alternation response. The

activation task, control task, and normal rest condition were completely

counterbalanced. As in the current study, no significant changes in level of

flow were found between the (visuomotor) control task and the resting baseline

at any region. Of course, in all of these studies the sample size has been quite

small, making generalization hazardous at best. Furthermore, the

unpredictable variance of resting flow measures makes its use as a baseline

condition particularly problematic under any circumstances, and makes

negative results (i.e., failure to reject the null hypothesis) more likely.

However, it is heartening to find a similar result using a different control task

but similar experimental paradigms, even if from our own laboratory.

The possibility of differential findings between this and earlier studies due

to differences in counterbalancing procedures is difficult to evaluate, since

other task parameters differed as well, and the small sample size in all studies

reduces predictive reliability. However, several recent studies from our

laboratory have led us to suspect a non-linear trend in normal-rest

measurements which is not so obvious in controlled-rest trials, but which may

bias task-to-rest comparisons made solely to first and last positions.

In order to examine the possibility of mean differences in flow due to

temporal position in the current task effects study, the fl data for each region



adequate paradigm for assessing cognitive-task activation effects relative to
the control task, and was not designed to rigorously assess the control tasks per
se.







43

were further evaluated using a two-factor (Treatment x Run) repeated-

measures ANOVA. The F-tests for overall effect of measurement were

significant (p(> F)4.05) at left-hemisphere regions C and E, and at right-

hemisphere regions C, D, E, F, and G. Post-hoc comparisons revealed the

second measurement to be the highest in all regions when NR and VMf

conditions are pooled. These findings were confirmed by non-parametric

analysis.

The data, then, would tend to support a second-measurement

enhancement of flow across both types of measurements, a finding consistent

with the recent four-normal-rest study from this laboratory (Falgout et al.,

1983). The source of this effect is not clear. Prohovnik et al. (1980), using

essentially the same inhalation techniques, has reported a different pattern of

sequential-flow effects during same-session normal rest studies, with first and

last measures tending to show the higher flow levels. Larsen et al. (1977), using

the 133Xe intracarotid injection procedure, reported first-run enhancement of

flow which was attributed to psychophysiologic activation. Thus the sequential

flow patterns may be unique both to a particular methodology as well as to a

particular laboratory. We are currently examining our own calibration data as

well as available physiologic and psychologic indices in an effort to increase our

information regarding these "run" effects.

In continuing the comparison of Study 1 results to findings of previous

studies from our laboratory, it should be noted that in addition to the

differences in counterbalancing between studies, a second salient factor may lie

in the nature of the two-task repeated measures (test-retest) paradigm itself:

In this study, the evaluation of mean treatment effects is based on the average

of two measurements under the same condition. A test given twice is not

actually expected to impact upon the test-taker in the same way both times. A







44

plethora of explanations come to mind, among these being expectation or

mental set of the subject, learning and habituation effects, changes in

endogenous physiologic state, first-test apprehension or second-test boredom,

contrast effects contingent on task order, and related to this, physiologic

carryover or recovery effects from previous activities. Thus, aside from the

fact that comparing a mean of two measurements under one condition to the

mean of two measurements under a second condition certainly offers the most

conservative measure of differences between treatment a priori, there is the

further possibility that both level of engagement and variability in task

performance are influenced by the subject's initial (informed) expectations

regarding same-task repetition. The "boredom factor," for example, may be

enhanced by the expectation of performing a pair of monotonous and low-

demand tasks not once but twice during a two-hour session, and may result in

individual (creative) responses which further mask any "task" effects per se.

Whatever the mechanism, it seems likely that counterbalancing

contributes to the obfuscation of otherwise identifiable, though evidently not

robust, task effects, and conversely, that sensorimotor "task" effects may

become most apparent when other parameters are set. It may be argued of

course that "task" effects obtained under such standardized conditions are not

"task" effects at all, but perhaps "order" effects or "contrast" effects, or "run-

two" effects, for example. And in a certain scientific sense, that argument

would be accepted. However, in an equally pure and irreproachable scientific

sense, the opposite argument may be true: in order to demonstrate certain

lawful phenomena which might otherwise escape our notice, certain other

influential factors must be controlled. Thus, the constant effects of "gravity"

on a falling mass are more apparent under a variety of atmospheric conditions

when a stone is the object observed falling, as opposed to a feather. If the









constancy of gravitational effect is to be demonstrated with a feather, certain

relevant environmental parameters must be rigorously controlled.2

For the sake of completeness, the one positive finding from the first study

regarding visuomotor task effects on mean level of flow as compared to normal

rest must be addressed: the finding of VMf versus NR activation over the right

inferior temporal region. Our other studies have typically not reported results

from this detector location (F), since its relative placement in the fixed-

detector montage makes it the most vulnerable to positioning artifact, and

because it has sometimes shown high variability relative to other detectors.

However, the means and variances obtained from the "F" detectors in this study

are compatible with those from the contiguous temporo-occipital detectors (H)

in the eyes-closed (resting) condition (see Table 1 and Fig. 1), so the data

cannot be discarded lightly as artifactual. The location of the detector over

the middle and inferior aspects of the temporal lobe, moreover, puts it in a

position to monitor cortical areas which have been shown in lesion studies to

affect complex spatial learning tasks in the monkey (Cowey & Gross, 1970).

There is neuroanatomical evidence that suggests these regions may be involved

in automatic scanning and identification of spatial stimuli which will be acted

upon by other components of the spatial memory system (Pandya & Yeterian,

1984). This positive finding, then, though interpreted cautiously dueto the high

probability of spurious effects related to multiple comparison procedures and

small sample size, must nevertheless be recognized as plausible and held up for

possible verification from other studies.


21 am indebted to Hays (1962, p. 42) for reminding me of Galileo's
insightful disregard of appearance in his search for constancy. Lesser scientists
among us depend more heavily on demonstration than on logic. To such minds,
the "proof" of the relationship depends, in the end, on strict "experimental"
control, not on counterbalancing or other methods for distributing the variance.









Study 2: Density Effects


As for the effects of task rate on level of flow, the results from the

second study are clear: (a) individual differences in response to rate of task

presentation are of considerable importance, and (b) there is apparently an

inverse relationship between regional flow values at the lower task rate and

differential rCBF response to the higher rate of performance. In other words,

those subjects with the highest flow rates for the VMs task tended to show the

smallest mean increases-or even to show decreases in flow levels-when

presented with the high-rate VMf task; those subjects with the lowest flow

rates for the VMs task showed the largest mean increases to the high-rate task.

The individual variation in rCBF responses to the two rates of task

presentation are by no means surprising. Some of the spontaneous comments

made by the subjects as they completed the four task-related rCBF measures

illustrate the very individualized reactions elicited by the two rates of task

presentation: Two subjects were irritated by the high-rate task, as it interfered

with their ongoing ideational or imaginal processes; another much preferred

that task as it held his attention better than the slower one; a fourth used the

changing visual array as an aid in self-initiated meditation; still another created

his own test paradigm by trying to guess what stimulus pattern would turn up

next. It is attractive to believe that these creative and idiosyncratic responses

to what could otherwise be considered a pair of "cold" cognitive tasks would be

reflected in physiologic measures of brain work, if we but knew how to ferret

out the information. Alternatively, it is certainly plausible and potentially

more useful, to hypothesize that the physiologic response may inform us

regarding the prediction of individual differences.






47

The Law of Initial Value, first described by Wilder (1931, cited by Wilder,

1957) and elaborated by Lacey (1956) appears to accurately describe the pattern

of these rCBF responses to differing task rates. Loosely defined, this law

states that higher initial levels of activation in a given physiologic system are

associated with smaller changes in response to additional stimulation. A

corollary is that at extreme levels of activation, the response to stimulation is

more likely to be a "paradoxical" one, reversing its typical direction. Recently,

Rogers et al. (1985) have demonstrated the application of the Law of Initial

Value to the vasomotor reactivity of the cerebrovascular system as measured

by rCBF.

It is notable that the initial-value relationship is not apparent in the first

of these studies, comparing the NR to the VMf task. In that comparison,

knowledge of the average level of flow during the NR condition does not

facilitate prediction of the change in flow due to visuomotor stimulation. It is

possible that the greater intrinsic variability of resting measures obscures the

subtle effects of changes due to the minimally-demanding visuomotor task. If

this is true, then stabilization of the regional blood flow measures by use of the

controlled rest task allows these individual differences in task response to

become manifest and measurable.

The results of the variance component analysis of the Density study

suggest that there is little additional gain in stability of rCBF measures when

the high-rate visuomotor task is compared to the low-rate task (see Table 4);

only two detector locations (LH and RC) show significantly lower variability

under the more demanding conditions. It is speculative but reasonable to

interpret these focal results (along with other areas showing near-significant

variance ratios) as reflecting increased stimulus-bound attentional and

visuospatial activity.






48

The finding that individual differences are paramount in prediction of

rCBF responses to differing rates of task performance-even for these very

simple visuomotor tasks-demands that we re-assess both our experimental

design and our interpretation of task-related activation effects in studies

evaluating higher cognitive processing. Although some tasks may be easily

designed so that the sensorimotor control condition very nearly duplicates the

sensory and motor requirements of the test condition (except, naturally, for

level of difficulty), other tasks (such as Miller Analogies) are not nearly so

amenable to matched-rate sensorimotor control stimulation. In these cases, it

may be necessary to impose a form of statistical control, such as partial

correlation, in order to sort out the higher cognitive from the more purely

sensorimotor aspects of task performance.


General Issues


Several points remain to be made about the methods of data analysis used

in this study. The evaluation of task-related changes in level of flow and run-

to-run reproducibility of flow has been done on a region-by-region basis; that is,

the question addressed is whether focal flow in a given region "X" changes

significantly as a result of type of task administered during the rCBF

measurement. No consideration is given to definition of that region's relative

flow level with respect to another. Thus, an fj increase in region "X"

associated with performance of the visuomotor task may reflect any of several

phenomena of interest. This "isolationist" approach does not allow

discrimination between (a) a general hemispheric or global change in level of

flow reflected at all or most detector locations, and (b) a local and specific

change in flow which may or may not be correlated-inversely or directly-with

changes in other regions of interest. Nor does this approach allow a definition







49

of any particular pattern or profile of flow across the regions of interest which

might be associated with a particular type of task, or with person x task

interactions. Although such patterns may be more readily ascertained by the

implementation of three-dimensional visual displays such as the tomographic

maps available with P.E.T. technology, the assessment of relevant task-related

changes must still rely on application of appropriate statistical (decision-

making) procedures as well as comparison to relevant baseline or normative

data.

The difficulties inherent in application of common statistical procedures

to a set of data which may be both restricted in quantity and highly

intercorrelated are not unique to the 133Xe methodology. Several recent

publications in the three-dimensional physiologic imaging literature have begun

to address these issues. Multivariate procedures dependent on regression

approaches (including ANOVA) suffer from the common problem, in these

radioisotopic studies, of inadequate sample sizes. As the quantity of data per

individual is increased, however, the adaptation and application of Q-type

factor-analytic methods may provide a more promising approach to data

definition and analysis (Clark et al., 1985).

In focusing on the task-related aspects of run-to-run variability in these

studies, I have ignored the more general issue relating to other sources of

extraneous variability in rCBF measurement by the 133Xe inhalation technique.

This issue has not been ignored in the rCBF literature, however (e.g., Ingvar &

Lassen, 1982; McHenry et al., 1978; Prohovnik et al., 1980), nor is it overlooked

in the rapidly expanding literature of the various three-dimensional imaging

technologies. The sources of variance are broad, ranging from fluctuating

detector sensitivity to mathematical modeling algorithms to respiratory

efficiency to circadien and ultradien fluctuations in level of arousal. The most







50

powerful and uncontrolled determinant of level of flow, however, appears to

relate to the intrinsically determined physiologic (cognitive/emotive) state of

the individual (Blauenstein et al., 1977; Mchedlishvili, 1980), and this influence

appears to be most evident and unpredictable in normal subjects in the various

states of arousal associated with sleep and dreaming. Thus the decision to

consider these sources of variance as non-random is the first step toward

gaining control over them. The use of alternative baseline tasks-instead of or

in addition to the non-directed "normal rest"-is seen as instrumental in

bringing this important source of variance under some degree of experimental

control.


Summary


The results of these two within-group, within-subject studies have

demonstrated the effectiveness of a simple visuomotor task in reducing run-to-

run variability of regional and hemispheric blood flow measures as compared to

the standard eyes-closed resting baseline condition, and have highlighted the

importance of individual differences in response to differing rates of task

presentation. The use of a within-subject experimental design enables the

assignment of a degree of credibility to these findings which would not be as

definitive in a small-sample, between-group reliability study. These findings

certainly have implications for other physiologic methodologies used in the

investigation of metabolic parameters related to human brain function, as well

as for the 133Xe inhalation technique of measuring cerebral blood flow in

particular. The hypothesized stabilizing function of a controlled rest condition

in sequential studies-and of its alias, the sensorimotor control task in studies

of complex cognitive processes-is validated by these studies.














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BIOGRAPHICAL SKETCH


Janet Copeland Falgout was born July 21, 1942, and raised in West

Florida. She earned both her baccalaureate and master's degrees from the

University of Florida in 1967 and 1975, respectively, specializing in physiologic

and experimental psychology. Her doctoral studies in the University of

Florida's Department of Clinical Psychology and her clinical internship at the

University of Alabama at Birmingham Medical School have culminated in a

major research and clinical focus on physiologic and neuropsychologic aspects

of human behavior. Since her internship, she has completed a predoctoral

fellowship in the UAB Department of Neurology/Division of Neuropsychology

and is currently employed there as a Research Associate.

Working for a number of years at the University of Florida's Visual

Science Laboratory under Drs. N. W. Perry and D. G. Childers, Ms. Falgout

gained some expertise in electrophysiologic measures of perception and

development. Her affiliation with the UAB Stroke Research Center has allowed

her to acquire some experience with the cerebral blood flow methodology as a

tool in neurobehavioral research. At UAB, she has collaborated with Dano Leli,

Ph.D., James Halsey, Jr., M.D., and Julia Hannay, Ph.D. (Auburn University), in

refining experimental paradigms for the application of cerebral blood flow

methodology to the study of human cognitive processes.









I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope
and quality, as a dissertation for the degree of Doctor of Philosophy.


Eileen B. Fennell, Chair
Associate Professor of Clinical Psychology

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope
and quality, as a dissertation for the degree of Doctor of Philosophy.
j ^-X ^^^--^-^-

Jacquelin R. Goldman
Professor of Clinical Psychology

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope
and quality, as a dissertation for the degree of Doctor of Philosophy.


Russell M. Bauer /
IAssociate Professor of Clinical Psychology

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope
and quality, as a dissertation for the degree of Doctor of Philosophy.


Hugh C. vis) "
Professor of Clinical Psychology

I certify that I have read this study and that in my opinion it conforms to
acceptable standards of scholarly presentation and is fully adequate, in scope
and quality, as a dissertation for the de ee of Doctor of Philosophy.


/ Edward Valenstein
Professor of Neurology









This dissertation was submitted to the Graduate Faculty of the College of
Health Related Professions and to the Graduate School and was accepted as
partial fulfillment of the requirements for the degree of Doctor of Philosophy.


August, 1985


Dean, College of Health Related Professions



Dean, Graduate School