Mechanisms underlying sharpening of visual response dynamics with familiarity
- New York University, Shanghai, China
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.
Data availability
All data and codes used in the manuscript have been provided as Source code files. Please note that the original data was generated in Sheinberg's and Freedman's labs, and the uploaded data is a processed one used for network simulations and fitting.
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Funding
National Natural Science Foundation of China (Fund for International Young Scientists, 31650110468)
- Sukbin Lim
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Lim
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Mechanisms underlying sharpening of visual response dynamics with familiarity
eLife 8:e44098.
https://doi.org/10.7554/eLife.44098
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