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Record W3012504197 · doi:10.1089/brain.2020.0742

Cognition and Learning in Decision-Making as Compensatory Mechanism for Emotional Processing Deficit

2020· article· en· W3012504197 on OpenAlexaff
Rowena Kong

Bibliographic record

VenueBrain Connectivity · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyMechanism (biology)CognitionIowa gambling taskCognitive psychologyPrefrontal cortexAmygdalaVentromedial prefrontal cortexNeglectNeuroscienceWorking memoryCognitive science

Abstract

fetched live from OpenAlex

The functional roles of ventromedial prefrontal cortex (VMPF) and amygdala in affecting emotional processing in decision-making have been raised in support of the somatic marker hypothesis. However, later studies demonstrated challenges to such support based on preserved cognition in the form of reversal learning in VMPF damaged patients tested with a shuffled variant of Iowa Gambling Task. This finding provides implications for cognitive neglect in somatic marker hypothesis with its magnified emphasis on the link between somatic markers and emotion-guided decision-making. It also suggests that cognition could compensate for emotion impairment in the absence of crucial prefrontal cortical region needed for low-risk choice and decision-making. Emotional somatic marker signaling is proposed to be an assistive initiation mechanism for choice decision-making between gains and losses instead of a fixated necessity in the process, and that it works in concert with concurrent conscious knowledge and cognition of the situation, building upon the nature of close connections between the VMPF and other brain region(s).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.493

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.127
GPT teacher head0.375
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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