Modulation of STDP by the structure of pre-post synaptic spike times
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1
MPI for Brain Research, Germany
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2
J. W. Goethe Univ, Clinic for Anaesthesiology, Germany
Spiking activity recorded in vitro and in vivo preparations often contains rich auto structure. This auto structure can range from bursty to regular renewal processes, and can be even non renewal involving very complex temporal spiking pattern. Despite the fact that such auto-structure has been discussed to be involved in encoding information it is mostly ignored in modeling studies. Instead, modeling often assumes that spiking activity can be described by Poissonian firing. Here we studied the impact of non Poissonian renewal activity on structure formation by spike timing dependent synaptic plasticity. To this end we simulated a conductance based integrate and fire neuron that received input from 200 to 2500 inhibitory and excitatory neurons. This presynaptic activity was modeled by renewal processes with gamma distributed inter-spike interval (ISI) distributions. Using such a gamma process allowed us to systemically vary the regularity, ranging from Poissonian firing for a gamma processes with a shape factor on 1 (coefficient of variation of the ISI distribution, CV=1 ) to extremely regular firing with a shape factor of 100 (CV=0.1). In a first step we show that the temporal structure of post synaptic firing depends critically on the auto structure of the presynaptic activity even if the presynaptic population contain on the order of a couple of thousands mutually independently firing neurons. This clearly counter argues the assumption that a large enough presynaptic population can be modeled as Poissonian population activity, and raises the question to what degree this dependence of the post synaptic firing onto the pre-synaptic auto structure also modulated synaptic plasticity. In a second step we investigate this impact. We show that the auto-structure of the pre-synaptic activity first changes the steady state distribution of synaptic weights. Second, that the learning rate, that is the speed with which the distribution of weights is changing over time, is substantially higher than in the case of regular firing neurons than in the case of Poissonian firing. Third, that the impact of non-Poissonian firing is also modulated by the rate distribution of the presynaptic population, as well as by the rate relation between the populations of excitatory and inhibitory neurons. If both the excitatory and inhibitory population fires with a regular gamma process the learning rate is highest when the rate of the excitatory and inhibitory scales as n:1 with n being an integer number. Our findings give rise to new modulatory effects of synaptic learning due to STDP. Such that the learning rate of STDP can be regulated by a modulation of the autostructure of the spike trains, i.e. the regularity of presynaptic firing and its rate (in case that firing is not Poissonian). Both effects are frequently observed in neuronal recording and had been associated with attention, learning, short term memory and other cognitive tasks. In this light our findings might establish a link between neuronal activity changes and task or behavioral modulation of learning and structure formation in recurrent networks. Acknowledgements: Research was funded by the European Community GABA project (FP6-NEST No. 043309)
Conference:
Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010.
Presentation Type:
Poster Presentation
Topic:
Poster session III
Citation:
Pipa
G,
Castellano
M,
Vicente
R and
Scheller
B
(2010). Modulation of STDP by the structure of pre-post synaptic spike times.
Front. Neurosci.
Conference Abstract:
Computational and Systems Neuroscience 2010.
doi: 10.3389/conf.fnins.2010.03.00262
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Received:
05 Mar 2010;
Published Online:
05 Mar 2010.
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Correspondence:
Gordon Pipa, MPI for Brain Research, Frankfurt, Germany, gpipa@uos.de