Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains
Thorpe SJ (2008) Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike
Trains. PLoS ONE 3(1): e1377. doi:10.1371/journal.pone.0001377
Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains
Timothe e Masquelier 0 1
Rudy Guyonneau 0 1
Simon J. Thorpe 0 1
0 Academic Editor: Olaf Sporns, Indiana University , United States of America
1 1 Centre de Recherche Cerveau et Cognition, Universite Toulouse 3, Centre National de la Recherche Scientifique (CNRS), Facult e de Me decine de Rangueil , Toulouse, France, 2 SpikeNet Technology SARL, Prologue 1 La Pyre ne enne, Labe`ge , France
Experimental studies have observed Long Term synaptic Potentiation (LTP) when a presynaptic neuron fires shortly before a postsynaptic neuron, and Long Term Depression (LTD) when the presynaptic neuron fires shortly after, a phenomenon known as Spike Timing Dependant Plasticity (STDP). When a neuron is presented successively with discrete volleys of input spikes STDP has been shown to learn 'early spike patterns', that is to concentrate synaptic weights on afferents that consistently fire early, with the result that the postsynaptic spike latency decreases, until it reaches a minimal and stable value. Here, we show that these results still stand in a continuous regime where afferents fire continuously with a constant population rate. As such, STDP is able to solve a very difficult computational problem: to localize a repeating spatio-temporal spike pattern embedded in equally dense 'distractor' spike trains. STDP thus enables some form of temporal coding, even in the absence of an explicit time reference. Given that the mechanism exposed here is simple and cheap it is hard to believe that the brain did not evolve to use it.
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INTRODUCTION
Electrophysiologists report the existence of repeating
spatiotemporal spike patterns with millisecond precision, both in vitro
and in vivo, lasting from a few tens of ms to several seconds[13].
In this study we assess the difficult problem of detecting them, and
suggest how neurons could solve it. The problem is made
particularly difficult when only a fraction of the recorded neurons
are involved in the pattern. Fig. 1 illustrates such a situation. There
is a pattern of spikes (indicated by the red dots) that repeats at
irregular intervals, but is hidden within the variable background
firing of the whole population (shown in blue). The problem is
made hard because nothing in terms of population firing rate
characterizes the periods when the pattern is present, nor is there
anything unusual about the firing rates of the neurons involved in
the pattern. In such a situation detecting the pattern clearly
requires taking the spike times into account. However direct
comparison of each spike time to one another over the entire
recording period and across the entire set of afferents is extremely
computationally expensive. In this article we will see how a single
neuron equipped with STDP can solve the problem in a different
manner, taking advantage of the fact that a pattern is a succession
of spike coincidences.
STDP is now a widely accepted physiological mechanism of
activity-driven synaptic regulation. It has been observed
extensively in vitro[47], and more recently in vivo in Xenopuss visual
system[8,9], in the locusts mushroom body[10], and in the rats
visual cortex[11] and barrel cortex[12]. An exponential update
rule fits well the synaptic modifications observed
experimentally[13] (see Fig. 2). Very recently, it has also been shown that
cortical reorganization in cat primary visual cortex is in
accordance with STDP[14]. Note that STDP is in agreement
with Hebbs postulate because it reinforces the connections with
the presynaptic neurons that fired slightly before the postsynaptic
neuron, which are those that took part in firing it. It thereby
reinforces causality links.
When a neuron is presented successively with similar volleys of
input spikes STDP is known to have the effect of concentrating
synaptic weights on afferents that consistently fire early, with the
result that the postsynaptic spike latency decreases[1518]. This
theoretical observation is in accordance with recordings in rats
hippocampus showing that the so called place cells fire earlier
relative to the cycle of the theta oscillation in hippocampus after
the animal has repeatedly traversed the corresponding area[19].
STDP has also been studied in an oscillatory mode, and was
shown to be able to select only phase-locked inputs among a broad
population with random phases, turning the postsynaptic neuron
into a coincidence detector[20].
The main limitation of these studies is the assumption that the
input spikes arrive in discrete volleys (sometimes also called spike
waves). They assume an explicit time reference usually the
presentation of a stimulus[15,17,18], or the maximum (or
minimum) of an oscillatory drive[20,21] that allows the
specification (...truncated)