Title:
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The encoding of decision difficulty and movement time in the primate premotor cortex
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Author:
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Martínez-García, Marina; Insabato, Andrea; Pannunzi, Mario; Pardo-Vazquez, Jose L.; Acuña, Carlos; Deco, Gustavo
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Abstract:
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Estimating the difficulty of a decision is a fundamental process to elaborate complex and adaptive behaviour. In this paper, we show that the movement time of behaving monkeys performing a decision-making task is correlated with decision difficulty and that the activity of a population of neurons in ventral Premotor cortex correlates with the movement time. Moreover, we found another population of neurons that encodes the discriminability of the stimulus, thereby supplying another source of information about the difficulty of the decision. The activity of neurons encoding the difficulty can be produced by very different computations. Therefore, we show that decision difficulty can be encoded through three different mechanisms: 1. Switch time coding, 2. rate coding and 3. binary coding. This rich representation reflects the basis of different functional aspects of difficulty in the making of a decision and the possible role of difficulty estimation in complex decision scenarios. |
Abstract:
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MMG was supported by the FP7-ICT BrainScales. AI was supported by the FI/AGAUR fellowship and FP7-ICT Coronet (n. 269459). MP was supported by the CONSOLIDER-INGENIO 2010 Program CSD2007-00012. JLPV was supported by the Human Frontier Science Programme (LT000442/2012). GD was supported by the ERC Advanced Grant: DYSTRUCTURE (n. 295129), the FP7- FET-Flagship Human Brain Project (n. 604102) and the Plan Estatal de Fomento de la investigación Científica y Técnica de Excelencia (PSI2013-42091-P). |
Rights:
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© 2015 Martinez-Garcia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
http://creativecommons.org/licenses/by/4.0/ |
Document type:
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Article Article - Published version |
Published by:
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Public Library of Science (PLoS)
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