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Record W2025205333 · doi:10.1002/hipo.20871

Detailed descriptions of routes traveled, but not map‐like knowledge, correlates with tests of hippocampal function in older adults

2010· article· en· W2025205333 on OpenAlexafffundabout
Marnie Hirshhorn, Leorra Newman, Morris Moscovitch

Bibliographic record

VenueHippocampus · 2010
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsBaycrest HospitalToronto Rehabilitation InstituteUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsPsychologyCognitive psychologyHippocampal formationFluencyHippocampusPerceptionEpisodic memoryCognitive mapSpatial memoryCognitionNeuroscienceWorking memory

Abstract

fetched live from OpenAlex

We examined hippocampal contribution to remote spatial memory in older adults by correlating their performance on tests sensitive to hippocampal damage with their description of routes they traversed many times or only once, and with their map-like knowledge of downtown Toronto. We found that performance on table-top tests of spatial location (Smith and Milner (1981) Neuropsychologia 19:781-793) and on paired-associate learning, and the number of Internal Details on the Autobiographical Interview (Levine et al., (2002) Psychol Aging 17:677-689), all correlated significantly with the number and type of perceptual details used in describing routes one has traversed, but not with map-like knowledge of Toronto. No significant correlations were found with performance on tests of frontal function (WCST, phonemic fluency, and backward digit span). We conclude that the hippocampus is implicated in vivid re-experiencing of a familiar route, but not with map-like knowledge of a large-scale environment. These findings are interpreted as consistent with Multiple Trace Theory's prediction that it is the degree of detail of a retrieved memory that is crucially dependent on the hippocampus.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.255
Teacher spread0.229 · 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

Citations27
Published2010
Admission routes3
Has abstractyes

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