Literature DB >> 16624994

Neural representation of information measure in the primate premotor cortex.

Kiyohiko Nakamura1.   

Abstract

Animals seek information to reduce their efforts to receive rewards and perform actions that enable them to gain more information. The ability of seeking information subserves higher cognition processes such as planning and reasoning. There exists limited information on how the brain measures and seeks information. In this study, I discuss results indicating that the brain quantifies information by using the information-theoretic measure. The monkeys were trained to perform saccadic eye movement to one of the visual targets. When required to choose from the targets that included varying amounts of information regarding the goal, the animals selected the most informative target. While making a choice, the neurons in the dorsal premotor cortex exhibited activity that reflected the corresponding information value. The population response of these neurons was examined using the following three measures: the information-theoretic measure, probability gain, and absolute change in beliefs. Changes in this response exhibited relatively similar proportionality to the three measures. An analysis of two intuitive conditions for information measures, decreasing monotonicity on probability and additivity between independent events, showed that only the information-theoretic measure satisfies both the conditions. These results suggest that in comparison with the other measures, the information-theoretic measure is more plausible for information measure in the brain.

Mesh:

Year:  2006        PMID: 16624994     DOI: 10.1152/jn.01326.2005

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  5 in total

1.  Parietal neurons encode expected gains in instrumental information.

Authors:  Nicholas C Foley; Simon P Kelly; Himanshu Mhatre; Manuel Lopes; Jacqueline Gottlieb
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-03       Impact factor: 11.205

2.  Midbrain dopamine neurons signal preference for advance information about upcoming rewards.

Authors:  Ethan S Bromberg-Martin; Okihide Hikosaka
Journal:  Neuron       Date:  2009-07-16       Impact factor: 17.173

3.  Experience matters: information acquisition optimizes probability gain.

Authors:  Jonathan D Nelson; Craig R M McKenzie; Garrison W Cottrell; Terrence J Sejnowski
Journal:  Psychol Sci       Date:  2010-06-04

4.  Brain cells in the avian 'prefrontal cortex' code for features of slot-machine-like gambling.

Authors:  Damian Scarf; Kirby Miles; Amanda Sloan; Natalie Goulter; Matt Hegan; Azade Seid-Fatemi; David Harper; Michael Colombo
Journal:  PLoS One       Date:  2011-01-25       Impact factor: 3.240

5.  Influence of uncertainty and surprise on human corticospinal excitability during preparation for action.

Authors:  Sven Bestmann; Lee M Harrison; Felix Blankenburg; Rogier B Mars; Patrick Haggard; Karl J Friston; John C Rothwell
Journal:  Curr Biol       Date:  2008-05-20       Impact factor: 10.834

  5 in total

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