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Record W2154401572 · doi:10.1162/jocn.2008.20105

Patterns of Autobiographical Memory Loss in Medial-Temporal Lobe Amnesic Patients

2008· article· en· W2154401572 on OpenAlexafffund
R. Shayna Rosenbaum, Morris Moscovitch, Jonathan K. Foster, David M. Schnyer, Fuqiang Gao, Natasha Kovacevic, Mieke Verfaellie, Sandra E. Black, Brian Levine

Bibliographic record

VenueJournal of Cognitive Neuroscience · 2008
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreBaycrest HospitalUniversity of TorontoYork University
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUniversity of TorontoJohns Hopkins University
KeywordsAutobiographical memoryPsychologyTemporal lobeAmnesiaEpisodic memoryCognitive psychologyNeuroscienceRecallCognitionEpilepsy

Abstract

fetched live from OpenAlex

The issue of whether the hippocampus and related structures in the medial-temporal lobe (MTL) play a temporary or permanent role in autobiographical episodic memory remains unresolved. One long-standing belief is that autobiographical memory (AM), like semantic memory, is initially dependent on the MTL but ultimately can be retained and recovered independently of it. However, evidence that hippocampal amnesia results in severe loss of episodic memory for a lifetime of personally experienced events suggests otherwise. To test the opposing views, we conducted detailed investigations of autobiographical episodic memory in people with amnesia resulting from MTL lesions of varying extent. By combining precise quantification of MTL and neocortical volumes with sensitive measures of recollection of one's personal past, we show that the severity of episodic, but not semantic, AM loss is best accounted for by the degree of hippocampal damage and less likely related to additional neocortical compromise.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.313
Teacher spread0.282 · 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 designObservational
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

Citations207
Published2008
Admission routes2
Has abstractyes

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Same venueJournal of Cognitive NeuroscienceSame topicIdentity, Memory, and TherapyFrench-language works237,207