Temporal Structure of Incoming Spike Trains Modulate Structure Formation by STDP

Abstract

Event Abstract Back to Event Temporal Structure of Incoming Spike Trains Modulate Structure Formation by STDP Pipa Gordon1*, Marta Castellano1, Raul Vicente1 and Bertram Scheller2 1 Max Planck Institute for Brain Research, Frankfurt Institute for Advanced Studies, Germany 2 Johann Wolfgang Goethe University, Clinic for Anesthesia, Intensive Care Medicine and Pain Therapy, Germany In order to understand cognitive processes through the cortex it is necessary to have an understanding of its information processing, which depends on the self organization and structure formation on the network. Rich auto-structure has been recorded in spiking activity, ranging from bursty to regular renewal processes and involving very complex spiking patterns. Here we explore the influence of non-Poissonian renewal activity on structure formation by Spike Time Dependent Plasticity (STDP). We study the impact on non-Poissonian renewal activity on structure formation by STDP. To this end we simulated a conductance based integrate and fire neuron that receives input from 200 up to 2500 neurons, both excitatory and inhibitory. The presynaptic activity was modeled by a renewal process with gamma distributed inter-spike interval distribution (ISI). Using such a gamma process, allowed us to systematically vary the regularity, ranging from Poissonian firing for a gamma process with a shape factor of 1 (coefficient of variation of the ISI distribution CVISI = 1) to extremely regular firing with a shape factor of 100 (CVISI = 0.1). In the first step we show that the auto-structure of the presynaptic activity (even in the order of thousands mutually independent spike trains) can induce temporal structure in the post synaptic firing, in particular we show an interplay between the pre-synaptic auto-structures which implies a modulation by the rate of the individual processes. This finding raises the question to which degree this dependence between the pre-post synaptic activity can also modulate synaptic plasticity. Thus, in the second step we analyze this impact by using STDP as a synaptic plasticity paradigm. To this end we show that not only the regularity or auto-structure of the renewal process but also the rate of the individual processes modulate the dynamics of the synaptic weights. Both the speed and strength of structural changes induced by STDP can be modulated by the temporal structure of mutually independent spiking activity (i.e. the regularity of the presynaptic activity and its rate). Our findings give rise to the possibility that the temporal auto-structure of large groups of independent neurons could be used to modulate the sensitivity for spontaneous structure formation in recurrent networks, a novel modulatory effect on structure formation by STDP. Both effects are observed in neuronal recording and had been associated with cognitive tasks. Thus, our findings might be understood as a link between neuronal plasticity and task-modulation of learning and structure formation in recurrent networks.