Group Title: BMC Neuroscience
Title: Temporal spike pattern learning
Full Citation
Permanent Link:
 Material Information
Title: Temporal spike pattern learning
Physical Description: Book
Language: English
Creator: Talathi, Sachin
Abarbanel, Henry
Ditto, William
Publisher: BMC Neuroscience
Publication Date: 2008
General Note: Start page P4
General Note: M3: 10.1186/1471-2202-9-S1-P4
 Record Information
Bibliographic ID: UF00099978
Volume ID: VID00001
Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: Open Access:
Resource Identifier: issn - 1471-2202


This item has the following downloads:


Full Text

BMC Meuroscience

BioMled Central

Poster presentation

Temporal spike pattern learning
Sachin S Talathi* 1, Henry DI Abarbanel2 and William L Ditto'

Address: 1J Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, FL 32611, USA and 2Marine Physical Laboratory,
Scripps Institution of Oceanography, Department of Physics and Institute for Nonlinear Science, University of California San Diego, La Jolla, CA
92093, USA
Email: Sachin S Talathi*
* Corresponding author

from Seventeenth Annual Computational Neuroscience Meeting: CNS*2008
Portland, OR, USA. 19-24 July 2008

Published: II July 2008
BMC Neuroscience 2008, 9(Suppl I):P4 doi: 10.1186/1471-2202-9-SI -P4
This abstract is available from: I/P4
2008 Talathi et al; licensee BioMed Central Ltd.

Sensory systems pass information about an animal's envi-
ronment to higher nervous system units through
sequences of action potentials. When these action poten-
tials have essentially equivalent waveforms, all informa-
tion is contained in the interspike intervals (ISIs) of the
spike sequence. The question then is, how do neural cir-
cuits recognize and read these ISI sequences? We address
this issue of temporal sequence learning with a neuronal
system utilizing spike timing dependent plasticity

Motivated through recent work by [ 1 ] using spike timing
dependent plasticity rules observed in inhibitory syn-
apses, we present a very general architecture of neural cir-
cuitry that can perform the task of ISI recognition. The
essential ingredients of this neural circuit, which we refer
to as "interspike interval recognition unit" (IRU) are, (i) A
spike selection unit, the function of which is to selectively
distribute input spikes to downstream IRU circuitry, (ii) A
time delay unit that can be tuned by STDP, (iii) A detec-
tion unit, which is the output of the IRU and a spike from
which indicates successful ISI recognition by the IRU (Fig
la). We present two distinct configurations for the time
delay circuit within the IRU using excitatory and inhibi-
tory synapses respectively to produce a delayed output
spike at time to + t(R) in response to an input spike
received at time to (Fig 1b, c). R is the tunable parameter
of the time delay circuit that controls the timing of the
delayed output spike. We discuss the forms of STDP rules
for excitatory and inhibitory synapses respectively, which
allows for modulation of R for the IRU to perform its task
of ISI recognition. We then present two architectures for

the IRU circuitry that can both learn the ISIs of a training
sequence and then recognize the same ISI sequence when
it is presented on the subsequent occasion.

Page 1 of 2
(page number not for citation purposes)

a Interpike interval Leaming Unit (IRU)

IRU4110101111y LhsMIMh

-I eiieWM

Figure I
(a) Schematic diagram of the Interspike interval Recognition Unit (IRU). The IRU will respond with an output spike if it is tuned
to detect the input interspike interval T. The key circuit elements of the IRU are, (1) a spike selection unit (SSU), whose func-
tion is to split the incoming spike train into sequence of individual spikes to be fed into the downstream IRU circuitry, (2) a
time delay unit (TDU), which can produce a delayed spike output at time to + t(R) in response to input spike at time to, tuned
through either an excitatory or inhibitory spike timing dependent learning rule, (3) a detection unit (DU), which triggers a
spike output if it receives coincident spike input through the TDU. (b) Schematic circuitry for the IRU constructed with a TDU
that can be tuned through spike timing dependent plasticity of an inhibitory synapse (iSTDP). (c) Schematic diagram of the IRU
constructed using a TDU that can be tuned through spike timing dependent plasticity of an excitatory synapse (eSTDP).

This work was funded through the grant from the office of Naval research
(Grant Number N00014-02-1-1)

I. Abarbanel HDI, Talathi SS: Neural circuitry for recognizing inter Publish with BioMed Central and every
spike intervals. Phys Rev Lett 2006, 96:148104. scientist can read your work free of charge
"BioMed Central will be the most significant development for
disseminating the results of biomedical research in our lifetime."
Sir Paul Nurse, Cancer Research UK
Your research papers will be:
available free of charge to the entire biomedical community
peer reviewed and published immediately upon acceptance
cited in PubMed and archived on PubMed Central
yours you keep the copyright
Submit your manuscript here: BioMedcentral adv.asp -

Page 2 of 2
(page number not for citation purposes)

BMC Neuroscience 2008, 9(Suppl 1): P4

University of Florida Home Page
© 2004 - 2010 University of Florida George A. Smathers Libraries.
All rights reserved.

Acceptable Use, Copyright, and Disclaimer Statement
Last updated October 10, 2010 - - mvs