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

Journal of Neurophysiology

Volumn 113, Issue 10, 2015, Pages 3459-3461

  Chen, Chong ^a  

^a HOKKAIDO UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

Author keywords

Intelligence; Model based; Prediction error; Reinforcement learning

Indexed keywords

ARTICLE; BOLD SIGNAL; BRAIN FUNCTION; COGNITION; CORPUS STRIATUM; DORSAL ANTERIOR CINGULATE CORTEX; DORSOLATERAL PREFRONTAL CORTEX; EMOTION; FEEDBACK SYSTEM; HUMAN; INTELLIGENCE; INTELLIGENCE QUOTIENT; MEASUREMENT ERROR; NERVE POTENTIAL; PREDICTION; PRIORITY JOURNAL; REINFORCEMENT; REWARD; TASK PERFORMANCE; BRAIN; BRAIN MAPPING; PHYSIOLOGY;

BRAIN; BRAIN MAPPING; HUMANS; INTELLIGENCE; REINFORCEMENT (PSYCHOLOGY);

EID: 84930854843     PISSN: 00223077     EISSN: 15221598     Source Type: Journal    
DOI: 10.1152/jn.00600.2014     Document Type: Article

References (15)

1. Bomyea J, Risbrough V, Lang AJ. A consideration of select pre-trauma factors as key vulnerabilities in PTSD. Clin Psychol Rev 32: 630–641, 2012.
2. Bookheimer S. Functional MRI of language: new approaches to understanding the cortical organization of semantic processing. Annu Rev Neurosci 25: 151–188, 2002.
3. Cohen MX. Individual differences and the neural representations of reward expectation and reward prediction error. Soc Cogn Affect Neurosci 2: 20–30, 2007.
4. Daw ND, Gershman SJ, Seymour B, Dayan P, Dolan RJ. Model-based influences on humans’ choices and striatal prediction errors. Neuron 69: 1204–1215, 2011.
5. Deary IJ, Penke L, Johnson W. The neuroscience of human intelligence differences. Nat Rev Neurosci 11: 201–211, 2010.
6. Diekhof EK, Kaps L, Falkai P, Gruber O. 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. Neuropsychologia 50: 1252–1266, 2012.
7. Hawes DR, DeYoung CG, Gray JR, Rustichini A. Intelligence moderates neural responses to monetary reward and punishment. J Neurophysiol 111: 1823–1832, 2014.
8. Lee SW, Shimojo S, O’Doherty JP. Neural computations underlying arbitration between model-based and model-free learning. Neuron 81: 687–699, 2014.
9. MacDonald PA, Ganjavi H, Collins DL, Evans AC, Karama S. Investigating the relation between striatal volume and IQ. Brain Imaging Behav 8: 52–59, 2014.
10. Nielsen FA, Balslev D, Hansen LK. Mining the posterior cingulate: segregation between memory and pain components. Neuroimage 27: 520–532, 2005.
11. Nisbett RE. Intelligence and How to Get It: Why Schools and Cultures Count. New York: Norton, 2009.
12. Rushworth MF, Kolling N, Sallet J, Mars RB. Valuation and decisionmaking in frontal cortex: one or many serial or parallel systems? Curr Opin Neurobiol 22: 946–955, 2012.
13. Schlagenhauf F, Rapp MA, Huys QJ, Beck A, Wüstenberg T, Deserno L, Buchholz HG, Kalbitzer J, Buchert R, Bauer M, Kienast T, Cumming P, Plotkin M, Kumakura Y, Grace AA, Dolan RJ, Heinz A. Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence. Hum Brain Mapp 34: 1490–1499, 2013.
14. Smittenaar P, FitzGerald TH, Romei V, Wright ND, Dolan RJ. Disruption of dorsolateral prefrontal cortex decreases model-based in favor of modelfree control in humans. Neuron 80: 914–919, 2013.
15. Van den Bos W, Crone EA, Guroglu B. Brain function during probabilistic learning in relation to IQ and level of education. Dev Cogn Neurosci 2, Suppl 1: S78–S89, 2012.