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Record W1979326603 · doi:10.1177/1534582304273251

The Cognitive Neuroscience of Human Decision Making: A Review and Conceptual Framework

2004· review· en· W1979326603 on OpenAlexaff
Lesley K. Fellows

Bibliographic record

VenueBehavioral and Cognitive Neuroscience Reviews · 2004
Typereview
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMontreal Neurological Institute and Hospital
FundersNational Institute of Neurological Disorders and Stroke
KeywordsCognitive neurosciencePsychologyCognitionCognitive scienceCultural neuroscienceAddictionConceptual frameworkNeuroscienceCognitive psychologySociologySocial science

Abstract

fetched live from OpenAlex

Decision making, the process of choosing between options, is a fundamental human behavior that has been studied intensively by disciplines ranging from cognitive psychology to economics. Despite the importance of this behavior, the neural substrates of decision making are only beginning to be understood. Impaired decision making is recognized in neuropsychiatric conditions such as dementia and drug addiction, and the inconsistencies and biases of healthy decision makers have been intensively studied. However, the tools of cognitive neuroscience have only recently been applied to understanding the brain basis of this complex behavior. This article reviews the literature on the cognitive neuroscience of human decision making, focusing on the roles of the frontal lobes, and provides a conceptual framework for organizing this disparate body of work.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0010.002
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.389
GPT teacher head0.516
Teacher spread0.127 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations260
Published2004
Admission routes1
Has abstractyes

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