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Record W2128444742 · doi:10.1111/nyas.12467

Case studies continue to illuminate the cognitive neuroscience of memory

2014· review· en· W2128444742 on OpenAlexafffund
R. Shayna Rosenbaum, Asaf Gilboa, Morris Moscovitch

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2014
Typereview
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBaycrest HospitalHeart and Stroke FoundationUniversity of TorontoYork University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchAlfred P. Sloan Foundation
KeywordsNeurocognitivePsychologyFunctional neuroimagingNeuroimagingEpisodic memoryCognitive psychologyCognitive scienceNeuroscienceCognitive neuroscienceRecallCognitionVentromedial prefrontal cortexPrefrontal cortex

Abstract

fetched live from OpenAlex

The current ubiquity of functional neuroimaging studies, and the importance they have had in elucidating brain function, obscures the fact that much of what we know about brain-behavior relationships derives largely from the study of single- and multiple-patient cases. A major goal of the present review is to describe how single cases continue to uniquely and critically contribute to cognitive neuroscience theory. With several recent examples from the literature, we demonstrate that single cases can both challenge accepted dogma and generate hypotheses and theories that steer the field in new directions. We discuss recent findings from case studies that specify critical functions of the hippocampus in episodic memory and recollection, and clarify its role in nonmnemonic abilities. Although we focus on the hippocampus, we discuss other regions and the occurrence of new associative learning, as well as the involvement of the ventromedial prefrontal and parietal cortices in memory encoding and retrieval. We also describe ways of dealing with the shortcomings of case studies, and emphasize the partnership of patient and neuroimaging methods in constraining neurocognitive models of memory.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.952
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.003
Science and technology studies0.0010.005
Scholarly communication0.0000.000
Open science0.0040.001
Research integrity0.0000.001
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 head0.491
GPT teacher head0.475
Teacher spread0.016 · 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.

Study designOther design
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

Citations76
Published2014
Admission routes2
Has abstractyes

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