spike timing dependent plasticity finds the start of repeating patterns in continuous spike trains高峰时间依赖性可塑性发现列车重复模式在连续上涨的开始.pdf

Spike Timing Dependent Plasticity Finds the Start of Repeating Patterns in Continuous Spike Trains ´ 1,2 1,2 1,2 Timothee Masquelier *, Rudy Guyonneau , Simon J. Thorpe ´ ´ ´ 1 Centre de Recherche Cerveau et Cognition, Universite Toulouse 3, Centre National de la Recherche Scientifique (CNRS), Faculte de Medecine de ´ ´ ` Rangueil, Toulouse, France, 2 SpikeNet Technology SARL, Prologue 1 La Pyreneenne, Labege, 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. Citation: Masquelier T, Guyonneau R, Thorpe SJ (2008) Spike Timing Dependent Plasti