PortalPublikationenHeuristic and optimal policy computations in the human brain...

Heuristic and optimal policy computations in the human brain during sequential decision-making

Standard

Heuristic and optimal policy computations in the human brain during sequential decision-making. / Korn, Christoph; Bach, Dominik R.

in: NAT COMMUN, Jahrgang 9, Nr. 1, 23.01.2018, S. 325.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Korn, C & Bach, DR 2018, 'Heuristic and optimal policy computations in the human brain during sequential decision-making', NAT COMMUN, Jg. 9, Nr. 1, S. 325. https://doi.org/10.1038/s41467-017-02750-3

APA

Korn, C., & Bach, D. R. (2018). Heuristic and optimal policy computations in the human brain during sequential decision-making. NAT COMMUN, 9(1), 325. https://doi.org/10.1038/s41467-017-02750-3

Vancouver

Korn C, Bach DR. Heuristic and optimal policy computations in the human brain during sequential decision-making. NAT COMMUN. 2018 Jan 23;9(1):325. https://doi.org/10.1038/s41467-017-02750-3

Bibtex

@article{a0bde72b7c61453b8e06a49cc07c9223,
title = "Heuristic and optimal policy computations in the human brain during sequential decision-making",
abstract = "Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.",
keywords = "Adult, Brain/physiology, Brain Mapping, Choice Behavior/physiology, Decision Making/physiology, Feeding Behavior/physiology, Female, Heuristics/physiology, Humans, Magnetic Resonance Imaging, Male, Photic Stimulation, Prefrontal Cortex/physiology, Reaction Time/physiology, Reward, Uncertainty, Young Adult",
author = "Christoph Korn and Bach, {Dominik R}",
year = "2018",
month = jan,
day = "23",
doi = "10.1038/s41467-017-02750-3",
language = "English",
volume = "9",
pages = "325",
journal = "NAT COMMUN",
issn = "2041-1723",
publisher = "NATURE PUBLISHING GROUP",
number = "1",

}

RIS

TY - JOUR

T1 - Heuristic and optimal policy computations in the human brain during sequential decision-making

AU - Korn, Christoph

AU - Bach, Dominik R

PY - 2018/1/23

Y1 - 2018/1/23

N2 - Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

AB - Optimal decisions across extended time horizons require value calculations over multiple probabilistic future states. Humans may circumvent such complex computations by resorting to easy-to-compute heuristics that approximate optimal solutions. To probe the potential interplay between heuristic and optimal computations, we develop a novel sequential decision-making task, framed as virtual foraging in which participants have to avoid virtual starvation. Rewards depend only on final outcomes over five-trial blocks, necessitating planning over five sequential decisions and probabilistic outcomes. Here, we report model comparisons demonstrating that participants primarily rely on the best available heuristic but also use the normatively optimal policy. FMRI signals in medial prefrontal cortex (MPFC) relate to heuristic and optimal policies and associated choice uncertainties. Crucially, reaction times and dorsal MPFC activity scale with discrepancies between heuristic and optimal policies. Thus, sequential decision-making in humans may emerge from integration between heuristic and optimal policies, implemented by controllers in MPFC.

KW - Adult

KW - Brain/physiology

KW - Brain Mapping

KW - Choice Behavior/physiology

KW - Decision Making/physiology

KW - Feeding Behavior/physiology

KW - Female

KW - Heuristics/physiology

KW - Humans

KW - Magnetic Resonance Imaging

KW - Male

KW - Photic Stimulation

KW - Prefrontal Cortex/physiology

KW - Reaction Time/physiology

KW - Reward

KW - Uncertainty

KW - Young Adult

U2 - 10.1038/s41467-017-02750-3

DO - 10.1038/s41467-017-02750-3

M3 - SCORING: Journal article

C2 - 29362449

VL - 9

SP - 325

JO - NAT COMMUN

JF - NAT COMMUN

SN - 2041-1723

IS - 1

ER -