Rate and timing of cortical responses driven by separate sensory channels

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Abstract

The sense of touch comprises multiple sensory channels that each convey characteristic signals during interactions with objects. These neural signals must then be integrated in such a way that behaviorally relevant information about the objects is preserved. To understand this integration process, we implement a simple computational model that describes how the responses of neurons in somatosensory cortex - recorded from awake, behaving monkeys - are shaped by the peripheral input, reconstructed using simulations of neuronal populations that reproduce natural spiking responses in the nerve with millisecond precision. First, we find that the strength of cortical responses is driven by one population of nerve fibers (rapidly adapting) whereas the timing of cortical responses is shaped by another (Pacinian). Second, we show that input from these sensory channels is integrated in an optimal fashion that exploits the disparate response behaviors of the different fiber types.

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Hannes P Saal

Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States

Competing interests
The authors declare that no competing interests exist.
Michael A Harvey

Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States

Competing interests
The authors declare that no competing interests exist.
Sliman J Bensmaia

Department of Organismal Biology and Anatomy, University of Chicago, Chicago, United States

For correspondence
sliman.bensmaia@gmail.com

Competing interests
The authors declare that no competing interests exist.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to protocol #72042, which was approved by the institutional animal care and use committee (IACUC) of the University of Chicago and the Johns Hopkins University.

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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.