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University of Cambridge > Talks.cam > Computational Neuroscience > Learning sensory and spatial representations from interacting excitatory and inhibitory synaptic plasticity
Learning sensory and spatial representations from interacting excitatory and inhibitory synaptic plasticityAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Guillaume Hennequin. Cortical neurons receive excitatory and inhibitory currents that are correlated both in time and in stimulus selectivity. The mechanisms by which this “balance” of excitation and inhibition arises is not fully understood. In the first part of the talk, I will present our recent suggestion that Hebbian plasticity of inhibitory synapses (ISP) can establish a self-organized excitation-inhibition balance in both feedforward “sensory” and recurrent “memory” networks (Vogels et al., 2011). In sensory networks, ISP causes an balance in the stimulus tuning of the excitatory and inhibitory currents. ISP also balances excitatory and inhibitory currents in recurrent spiking networks and thereby leads to the self-organized formation of an asynchronous irregular state that resembles the irregular activity found in cortical networks. In the second part of the talk, I will present an analysis of the interaction of Hebbian (“balancing”) ISP with concurrent Hebbian synaptic plasticity of excitatory synapses, with a focus on feedforward networks. For inhibitory inputs with a weak stimulus-specificity, ISP establishes a sliding threshold similar to that of Bienenstock-Cooper-Munro learning rules and thereby allows the self-organized formation of neuronal stimulus-selectivity. For highly stimulus-specific inhibition, the precise excitation-inhibition balance arising from the inhibitory plasticity acts against the formation of a stimulus selectivity in the excitation. In the intermediate regime, where inhibitory inputs have a wider stimulus tuning than their excitatory counterparts, the system generates periodic solutions, which arise from a Turing bifurcation. When the input encodes the animal’s position in a 2-dimensional environment, this intermediate regime reliably generates neuronal responses with a hexagonal grid pattern as observed in grid cells in entorhinal cortex. Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner H. Inhibitory plasticity balances excitation and inhibition in sensory pathways and memory networks. Science 334:1569-1573 (2011) This talk is part of the Computational Neuroscience series. This talk is included in these lists:
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