Mechanisms underlying sharpening of visual response dynamics with familiarity.

Sukbin Lim

doi:10.7554/elife.44098

Abstract

Experience-dependent modifications of synaptic connections are thought to change patterns of network activities and stimulus tuning with learning. However, only a few studies explored how synaptic plasticity shapes the response dynamics of cortical circuits. Here, we investigated the mechanism underlying sharpening of both stimulus selectivity and response dynamics with familiarity observed in monkey inferotemporal cortex. Broadening the distribution of activities and stronger oscillations in the response dynamics after learning provide evidence for synaptic plasticity in recurrent connections modifying the strength of positive feedback. Its interplay with slow negative feedback via firing rate adaptation is critical in sharpening response dynamics. Analysis of changes in temporal patterns also enables us to disentangle recurrent and feedforward synaptic plasticity and provides a measure for the strengths of recurrent synaptic plasticity. Overall, this work highlights the importance of analyzing changes in dynamics as well as network patterns to further reveal the mechanisms of visual learning.

Highlights

Experience-dependent changes in neural responses have been suggested to underlie the more efficient and rapid processing of stimuli with learning
Using a mean-field analysis, we identify the conditions on synaptic plasticity and negative feedback to reproduce changes in response dynamics consistently observed in different experimental settings
We summarize the effects of visual experience on response dynamics obtained from three different laboratories comparing the visual response to novel and familiar stimuli in the monkey ITC (Lim et al, 2015; McKee et al, 2013; Meyer et al, 2014; Woloszyn and Sheinberg, 2012)

Summary

Introduction

Experience-dependent changes in neural responses have been suggested to underlie the more efficient and rapid processing of stimuli with learning. A repeated encounter of a stimulus would elicit a particular activity pattern in the network, which in turn modifies synaptic connections depending on pre- and post-synaptic activities Such modifications of synaptic connections lead to changes in neural responses that can be a substrate to differentiate learned and unlearned stimuli. The previous modeling works investigated the relationship between synaptic plasticity and changes in network activity to find a synaptic plasticity rule that can account for sharpening of stimulus selectivity observed with learning (Dayan and Abbott, 2005; Gerstner and Kistler, 2002) Whether such rules can explain temporal changes in neural responses is in question

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