Literature DB >> 25185818

Intelligence moderates reinforcement learning: a mini-review of the neural evidence.

Chong Chen1.   

Abstract

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence.
Copyright © 2015 the American Physiological Society.

Entities:  

Keywords:  intelligence; model based; prediction error; reinforcement learning

Mesh:

Year:  2014        PMID: 25185818      PMCID: PMC4455485          DOI: 10.1152/jn.00600.2014

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


  14 in total

1.  Brain function during probabilistic learning in relation to IQ and level of education.

Authors:  Wouter van den Bos; Eveline A Crone; Berna Güroğlu
Journal:  Dev Cogn Neurosci       Date:  2011-10-06       Impact factor: 6.464

2.  Mining the posterior cingulate: segregation between memory and pain components.

Authors:  Finn Arup Nielsen; Daniela Balslev; Lars Kai Hansen
Journal:  Neuroimage       Date:  2005-09       Impact factor: 6.556

3.  Individual differences and the neural representations of reward expectation and reward prediction error.

Authors:  Michael X Cohen
Journal:  Soc Cogn Affect Neurosci       Date:  2007-03       Impact factor: 3.436

Review 4.  Valuation and decision-making in frontal cortex: one or many serial or parallel systems?

Authors:  Matthew F S Rushworth; Nils Kolling; Jérôme Sallet; Rogier B Mars
Journal:  Curr Opin Neurobiol       Date:  2012-05-07       Impact factor: 6.627

Review 5.  The neuroscience of human intelligence differences.

Authors:  Ian J Deary; Lars Penke; Wendy Johnson
Journal:  Nat Rev Neurosci       Date:  2010-02-10       Impact factor: 34.870

Review 6.  The role of the human ventral striatum and the medial orbitofrontal cortex in the representation of reward magnitude - an activation likelihood estimation meta-analysis of neuroimaging studies of passive reward expectancy and outcome processing.

Authors:  Esther Kristina Diekhof; Lisa Kaps; Peter Falkai; Oliver Gruber
Journal:  Neuropsychologia       Date:  2012-02-18       Impact factor: 3.139

7.  Neural computations underlying arbitration between model-based and model-free learning.

Authors:  Sang Wan Lee; Shinsuke Shimojo; John P O'Doherty
Journal:  Neuron       Date:  2014-02-05       Impact factor: 17.173

8.  Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence.

Authors:  Florian Schlagenhauf; Michael A Rapp; Quentin J M Huys; Anne Beck; Torsten Wüstenberg; Lorenz Deserno; Hans-Georg Buchholz; Jan Kalbitzer; Ralph Buchert; Michael Bauer; Thorsten Kienast; Paul Cumming; Michail Plotkin; Yoshitaka Kumakura; Anthony A Grace; Raymond J Dolan; Andreas Heinz
Journal:  Hum Brain Mapp       Date:  2012-02-17       Impact factor: 5.038

9.  Model-based influences on humans' choices and striatal prediction errors.

Authors:  Nathaniel D Daw; Samuel J Gershman; Ben Seymour; Peter Dayan; Raymond J Dolan
Journal:  Neuron       Date:  2011-03-24       Impact factor: 17.173

10.  Disruption of dorsolateral prefrontal cortex decreases model-based in favor of model-free control in humans.

Authors:  Peter Smittenaar; Thomas H B FitzGerald; Vincenzo Romei; Nicholas D Wright; Raymond J Dolan
Journal:  Neuron       Date:  2013-10-24       Impact factor: 17.173

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  5 in total

1.  Probabilistic Category Learning and Striatal Functional Activation in Psychosis Risk.

Authors:  Nicole R Karcher; Jessica P Y Hua; John G Kerns
Journal:  Schizophr Bull       Date:  2019-03-07       Impact factor: 9.306

2.  Predictive Movements and Human Reinforcement Learning of Sequential Action.

Authors:  Roy de Kleijn; George Kachergis; Bernhard Hommel
Journal:  Cogn Sci       Date:  2018-03-02

3.  Reinforcement learning as an intermediate phenotype in psychosis? Deficits sensitive to illness stage but not associated with polygenic risk of schizophrenia in the general population.

Authors:  Marcella Montagnese; Franziska Knolle; Joost Haarsma; Juliet D Griffin; Alex Richards; Petra E Vertes; Beatrix Kiddle; Paul C Fletcher; Peter B Jones; Michael J Owen; Peter Fonagy; Edward T Bullmore; Raymond J Dolan; Michael Moutoussis; Ian M Goodyer; Graham K Murray
Journal:  Schizophr Res       Date:  2020-05-07       Impact factor: 4.939

4.  Sex difference in the weighting of expected uncertainty under chronic stress.

Authors:  Huijie Lei; Yasuhiro Mochizuki; Chong Chen; Kosuke Hagiwara; Masako Hirotsu; Toshio Matsubara; Shin Nakagawa
Journal:  Sci Rep       Date:  2021-04-22       Impact factor: 4.379

5.  The Effect of Brief Stair-Climbing on Divergent and Convergent Thinking.

Authors:  Karin Matsumoto; Chong Chen; Kosuke Hagiwara; Natsumi Shimizu; Masako Hirotsu; Yusuke Oda; Huijie Lei; Akiyo Takao; Yuko Fujii; Fumihiro Higuchi; Shin Nakagawa
Journal:  Front Behav Neurosci       Date:  2022-01-28       Impact factor: 3.558

  5 in total

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