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PLoS Computational BiologyNeurosciencePeer-reviewed journal article

Stability and learning in excitatory synapses by nonlinear inhibitory plasticity

Christoph MiehliD, Julijana GjorgjievaiD

PDFDOIPreprint

Abstract

Synaptic changes underlie learning and memory formation in the brain. But synaptic plasticity of excitatory synapses on its own is unstable, leading to unlimited growth of synaptic strengths without additional homeostatic mechanisms. To control excitatory synaptic strengths we propose a novel form of synaptic plasticity at inhibitory synapses. We identify two key features of inhibitory plasticity, dominance of inhibition over excitation and a nonlinear dependence on the firing rate of postsynaptic excitatory neurons whereby inhibitory synaptic strengths change in the same direction as excitatory synaptic strengths. We demonstrate that the stable synaptic strengths realized by this novel inhibitory plasticity achieve a fixed excitatory/inhibitory set-point in agreement with experimental results. Applying a disinhibitory signal can gate plasticity and lead to the generation of receptive fields and strong bidirectional connectivity in a recurrent network. Hence, a novel form of nonlinear inhibitory plasticity can simultaneously stabilize excitatory synaptic strengths and enable learning upon disinhibition.

Citations
42
FWCI
3.64
Field percentile
top 5%

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