Evidence map›Paper›PMID 33596433›Full record

ReviewBehavioural brain research2021

Prediction errors and valence: From single units to multidimensional encoding in the amygdala.

Adam T Brockett, Daniela Vázquez, Matthew R Roesch

Abstract readReview
In one paragraph

Review in Behavioural brain research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Adam T BrockettDepartment of Psychology, University of Maryland, College Park, MD, 20742, United States; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, 20742, United States. Electronic address: brockett@umd.edu.
Daniela VázquezDepartment of Psychology, University of Maryland, College Park, MD, 20742, United States; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, 20742, United States.
Matthew R RoeschDepartment of Psychology, University of Maryland, College Park, MD, 20742, United States; Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, 20742, United States.

Funding

Restoration and Further Assessment of the Actor-Critic Circuit and Connected Areas After Cocaine Self-AdministrationR01DA031695 · NIDA · UNIV OF MARYLAND, COLLEGE PARK · PI MATTHEW R ROESCH · 2011 to 2026
$4.8M
Investigating the Role of ACC in the Regulation and Maintenance of Response InhibitionF32MH117836 · NIMH · UNIV OF MARYLAND, COLLEGE PARK · PI BROCKETT, ADAM T · 2019 to 2021
$199k
NIDA NIH HHS R01 DA031695NIMH NIH HHS F32 MH117836
6 · The paper itself

Abstract

The amygdala-one of the primary structures of the limbic system-is comprised of interconnected nuclei situated within the temporal lobe. It has a well-established role in the modulation of negative affective states, as well as in fear processing. However, its vast projections with diverse brain regions-ranging from the cortex to the brainstem-are suggestive of its more complex involvement in affective or motivational aspects of cognitive processing. The amygdala can play an invaluable role in context-dependent associative learning, unsigned prediction error learning, influencing outcome selection, and multidimensional encoding. In this review, we delve into the amygdala's role in associative learning and outcome selection, emphasizing its intrinsic involvement in the appropriate context-dependent modulation of motivated behavior.

Indexed as

AmygdalaAnimalsDecision MakingFearHumansLearningRewardAmygdalaDecision makingLearningPrediction error

Identifiers

PMID33596433
PMCPMC7946750

What OpenQuestion holds

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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.