Behavioural and neural characterization of optimistic reinforcement learning

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How unrealistic optimism is maintained in the face of reality

Ray Dolan, Tali Sharot, Christoph W. Korn … (2011)

Unrealistic optimism is a pervasive human trait influencing domains ranging from personal relationships to politics and finance. How people maintain unrealistic optimism, despite frequently encountering information that challenges those biased beliefs, is unknown. Here, we provide an explanation. Specifically, we show a striking asymmetry, whereby people updated their beliefs more in response to information that was better than expected compared to information that was worse. This selectivity was mediated by a relative failure to code for errors that should reduce optimism. Distinct regions of the prefrontal cortex tracked estimation errors when those called for positive update, both in highly optimistic and low optimistic individuals. However, highly optimistic individuals exhibited reduced tracking of estimation errors that called for negative update within right inferior prefrontal gyrus. These findings show that optimism is tied to a selective update failure, and diminished neural coding, of undesirable information regarding the future.

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Neural mechanisms mediating optimism bias.

Tali Sharot, Alison M Riccardi, Candace M Raio … (2007)

Humans expect positive events in the future even when there is no evidence to support such expectations. For example, people expect to live longer and be healthier than average, they underestimate their likelihood of getting a divorce, and overestimate their prospects for success on the job market. We examined how the brain generates this pervasive optimism bias. Here we report that this tendency was related specifically to enhanced activation in the amygdala and in the rostral anterior cingulate cortex when imagining positive future events relative to negative ones, suggesting a key role for areas involved in monitoring emotional salience in mediating the optimism bias. These are the same regions that show irregularities in depression, which has been related to pessimism. Across individuals, activity in the rostral anterior cingulate cortex was correlated with trait optimism. The current study highlights how the brain may generate the tendency to engage in the projection of positive future events, suggesting that the effective integration and regulation of emotional and autobiographical information supports the projection of positive future events in healthy individuals, and is related to optimism.

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VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data

Jean Daunizeau, Vincent Adam, Lionel Rigoux (2014)

This work is in line with an on-going effort tending toward a computational (quantitative and refutable) understanding of human neuro-cognitive processes. Many sophisticated models for behavioural and neurobiological data have flourished during the past decade. Most of these models are partly unspecified (i.e. they have unknown parameters) and nonlinear. This makes them difficult to peer with a formal statistical data analysis framework. In turn, this compromises the reproducibility of model-based empirical studies. This work exposes a software toolbox that provides generic, efficient and robust probabilistic solutions to the three problems of model-based analysis of empirical data: (i) data simulation, (ii) parameter estimation/model selection, and (iii) experimental design optimization.

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Title: Nature Human Behaviour

Abbreviated Title: Nat. hum. behav.

Publisher: Springer Nature

ISSN (Electronic): 2397-3374

Publication date Created: March 20 2017

Publication date (Print): March 20 2017

Volume: 1

Issue: 4

Page: 0067

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DOI: 10.1038/s41562-017-0067

SO-VID: a8ffe3f6-d81f-4237-ac9e-6db8506c0dc1

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Behavioural and neural characterization of optimistic reinforcement learning

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Asian Journal of Behavioural Studies (AjBeS)

Most cited references 27

How unrealistic optimism is maintained in the face of reality

Neural mechanisms mediating optimism bias.

VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data

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