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NatureNeurosciencePeer-reviewed journal article

Recurrent interactions in local cortical circuits

Simon PeroniD, Ravi PancholiiD, Bettina VoelckeriD, Jason D. WittenbachiD, H. Freyja ÓlafsdóttiriD, Jeremy FreemaniD, Karel SvobodaiD

PDFDOIPreprint

Abstract

The majority of cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing for pattern completion and other computations1. Cortical circuits contain subnetworks, consisting of neurons with similar receptive fields and elevated connectivity relative to the network average2,3. Understanding the computations performed by these subnetworks during behavior has been hampered by the fact that cortical neurons encoding different types of information are spatially intermingled and distributed over large brain volumes 4,5. We used computational modeling, optical recordings and manipulations to probe the function of recurrent coupling in layer (L) 2/3 of the somatosensory cortex during tactile discrimination. A model of L2/3 dynamics revealed that recurrent excitation enhances sensory signals via amplification, but only for subnetwork with elevated connectivity. Networks with high amplification were sensitive to damage: loss of a few subnetwork members degraded stimulus encoding. We tested this prediction experimentally by mapping neuronal selectivity5 and photoablating6,7 neurons with specific selectivity. In L2/3 of the somatosensory cortex, ablating a small proportion (10-20, < 5 % of the total) of neurons representing touch dramatically reduced responses in the spared touch representation, but not other representations. Network models further predicted that degradation following ablation should be greatest among spared neurons with stimulus responses that were most similar to the ablated population. Consistent with this prediction, ablations most strongly impacted neurons with selectivity similar to the ablated population. Our data shows that recurrence among cortical neurons with similar selectivity can drive input-specific amplification during behavior.

Citations
119
FWCI
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top 1%

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