Literature DB >> 23476024

Neural evidence for adaptive strategy selection in value-based decision-making.

Sebastian Gluth1, Jörg Rieskamp2, Christian Büchel1.   

Abstract

In everyday life, humans often encounter complex environments in which multiple sources of information can influence their decisions. We propose that in such situations, people select and apply different strategies representing different cognitive models of the decision problem. Learning advances by evaluating the success of using a strategy and eventually by switching between strategies. To test our strategy selection model, we investigated how humans solve a dynamic learning task with complex auditory and visual information, and assessed the underlying neural mechanisms with functional magnetic resonance imaging. Using the model, we were able to capture participants' choices and to successfully attribute expected values and reward prediction errors to activations in the dopaminoceptive system (e.g., ventral striatum [VS]) as well as decision conflict to signals in the anterior cingulate cortex. The model outperformed an alternative approach that did not update decision strategies, but the relevance of information itself. Activation of sensory areas depended on whether the selected strategy made use of the respective source of information. Selection of a strategy also determined how value-related information influenced effective connectivity between sensory systems and the VS. Our results suggest that humans can structure their search for and use of relevant information by adaptively selecting between decision strategies.
© The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  model-based fMRI; reinforcement learning; reward; ventral striatum

Mesh:

Year:  2013        PMID: 23476024     DOI: 10.1093/cercor/bht049

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  7 in total

1.  Value-based attentional capture affects multi-alternative decision making.

Authors:  Sebastian Gluth; Mikhail S Spektor; Jörg Rieskamp
Journal:  Elife       Date:  2018-11-05       Impact factor: 8.140

2.  Neural representation of expected value in the adolescent brain.

Authors:  Emily Barkley-Levenson; Adriana Galván
Journal:  Proc Natl Acad Sci U S A       Date:  2014-01-13       Impact factor: 11.205

3.  Dysfunctional insular connectivity during reward prediction in patients with first-episode psychosis.

Authors:  André Schmidt; Lena Palaniyappan; Renata Smieskova; Andor Simon; Anita Riecher-Rössler; Undine E Lang; Paolo Fusar-Poli; Philip McGuire; Stefan J Borgwardt
Journal:  J Psychiatry Neurosci       Date:  2016-10       Impact factor: 6.186

4.  Disentangling choice value and choice conflict in sequential decisions under risk.

Authors:  Laura Fontanesi; Amitai Shenhav; Sebastian Gluth
Journal:  PLoS Comput Biol       Date:  2022-10-07       Impact factor: 4.779

5.  Stochastic model predicts evolving preferences in the Iowa gambling task.

Authors:  Miguel A Fuentes; Claudio Lavín; L Sebastián Contreras-Huerta; Hernan Miguel; Eduardo Rosales Jubal
Journal:  Front Comput Neurosci       Date:  2014-12-19       Impact factor: 2.380

6.  Neural Underpinnings of Decision Strategy Selection: A Review and a Theoretical Model.

Authors:  Szymon Wichary; Tomasz Smolen
Journal:  Front Neurosci       Date:  2016-11-08       Impact factor: 4.677

7.  Neural Signatures of Rational and Heuristic Choice Strategies: A Single Trial ERP Analysis.

Authors:  Szymon Wichary; Mikołaj Magnuski; Tomasz Oleksy; Aneta Brzezicka
Journal:  Front Hum Neurosci       Date:  2017-08-18       Impact factor: 3.169

  7 in total

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