Evidence map›Paper›PMID 35525242›Full record

ArticleNeuron2022

Fast and slow contributions to decision-making in corticostriatal circuits.

Zuzanna Z Balewski, Eric B Knudsen, Joni D Wallis

Abstract read
In one paragraph

Article in Neuron, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Zuzanna Z BalewskiHelen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA 94720, USA.
Eric B KnudsenHelen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA 94720, USA.
Joni D WallisHelen Wills Neuroscience Institute, University of California at Berkeley, Berkeley, CA 94720, USA; Department of Psychology, University of California at Berkeley, Berkeley, CA 94720, USA. Electronic address: wallis@berkeley.edu.

Funding

Neuroscience Training Program at UC BerkeleyT32NS095939 · NINDS · UNIVERSITY OF CALIFORNIA BERKELEY · PI BATEUP, HELEN S. · 2016 to 2025
$6.3M
Hippocampal-orbitofrontal interactions and reward learningR01MH121448 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI WALLIS, JONI D · 2020 to 2024
$2.3M
Frontostriatal Rhythms Underlying Reinforcement Learning.R01MH117763 · NIMH · UNIVERSITY OF CALIFORNIA BERKELEY · PI WALLIS, JONI D · 2018 to 2022
$2.3M
NIMH NIH HHS R01 MH117763NIMH NIH HHS R01 MH121448NINDS NIH HHS T32 NS095939
6 · The paper itself

Abstract

We make complex decisions using both fast judgments and slower, more deliberative reasoning. For example, during value-based decision-making, animals make rapid value-guided orienting eye movements after stimulus presentation that bias the upcoming decision. The neural mechanisms underlying these processes remain unclear. To address this, we recorded from the caudate nucleus and orbitofrontal cortex while animals made value-guided decisions. Using population-level decoding, we found a rapid, phasic signal in caudate that predicted the choice response and closely aligned with animals' initial orienting eye movements. In contrast, the dynamics in orbitofrontal cortex were more consistent with a deliberative system serially representing the value of each available option. The phasic caudate value signal and the deliberative orbitofrontal value signal were largely independent from each other, consistent with value-guided orienting and value-guided decision-making being independent processes.

Indexed as

Prefrontal CortexAnimalsCaudate NucleusCerebellar CortexDecision MakingEye Movementscaudate nucleuscorticostratial circuitneurophysiologynon-human primateorbitofrontal cortexvalue-based decision-making

Identifiers

PMID35525242
PMCPMC9262822

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.