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Fast Recurrent Processing Via Ventral Prefrontal Cortex is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition

37 Pages Posted: 12 Jun 2020 Publication Status: Review Complete

See all articles by Kohitij Kar

Kohitij Kar

Massachusetts Institute of Technology (MIT) - McGovern Institute for Brain Research

James J. DiCarlo

Massachusetts Institute of Technology (MIT) - McGovern Institute for Brain Research; Massachusetts Institute of Technology (MIT) - Department of Brain and Cognitive Sciences

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Abstract

Distributed neural population spiking patterns in macaque inferior temporal (IT) cortex that support core visual object recognition require additional time to develop for specific (“late-solved”) images suggesting the necessity of recurrent processing in these computations. Which brain circuit motifs are most responsible for computing and transmitting these putative recurrent signals to IT? To test whether the ventral prefrontal cortex (vPFC) is a critical recurrent circuit node in this system, here we pharmacologically inactivated parts of the vPFC and simultaneously measured IT population activity, while monkeys performed object discrimination tasks. Our results show that vPFC inactivation deteriorated the quality of the late-phase (>150 ms from image onset) IT population code, along with commensurate, specific behavioral deficits for “late-solved” images. Finally, silencing vPFC caused the monkeys’ IT activity patterns and behavior to become more like those produced by feedforward artificial neural network models of the ventral stream. Together with prior work, these results argue that fast recurrent processing through the vPFC is critical to the production of behaviorally-sufficient object representations in IT.

Keywords: Ventral PFC, inferior temporal cortex, core object recognition, muscimol, deep neural networks, population codes

Suggested Citation

Kar, Kohitij and DiCarlo, James J., Fast Recurrent Processing Via Ventral Prefrontal Cortex is Needed by the Primate Ventral Stream for Robust Core Visual Object Recognition. Available at SSRN: https://ssrn.com/abstract=3606801 or http://dx.doi.org/10.2139/ssrn.3606801
This is a paper under consideration at Cell Press and has not been peer-reviewed.

Kohitij Kar (Contact Author)

Massachusetts Institute of Technology (MIT) - McGovern Institute for Brain Research ( email )

Cambridge, MA
United States

James J. DiCarlo

Massachusetts Institute of Technology (MIT) - McGovern Institute for Brain Research ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Massachusetts Institute of Technology (MIT) - Department of Brain and Cognitive Sciences

Cambridge, MA 02139
United States

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