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Record W4402423352 · doi:10.24908/iqurcp17964

Understanding the Contributions of the Hippocampus

2024· article· en· W4402423352 on OpenAlexaffvenue
Heather Reid

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2024
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsHippocampusNeurosciencePsychology

Abstract

fetched live from OpenAlex

The hippocampus plays an important role in human memory, with its anterior portion contributing to coarse-grained representations and its posterior portion contributing to fine-grained ones (Poppenk et al., 2013). My USRA project is focused on understanding the role of the hippocampus in a potential third type of memory representation; a general synthesis of stimuli. Beyond memory, the hippocampus has also been hypothesize to influence clinical disorders. For instance, preliminary research in our lab has found meta-cognitive memory abilities to be organized into factors resembling clinical disorders, when organized by variance in brain structure. My USRA project also aims to understand the contribution of the hippocampus to clinical disorders. My role in this project has been to develop administrative and experimental structure for the protocol, which involves extensive testing. Participants will complete approximately 27 hours of memory tasks, designed to evaluate the nature of their memory, and whether it is oriented towards detail, gist, or a synthesis of all stimuli. To do so, I have developed an extensive task of reading and evaluating reviews, as well as a recall task of lab-generated stories. Participants will also complete approximately 3-4 hours of online questionnaires, administered through Qualtrics. Over the summer, I conducted research to identify validated questionnaires that assess metacognitive abilities, in the domains of memory, attention, language, motor control, social cognition and perception. Results on these questionnaires will be used to validate preliminary findings on the relationship between metacognitive memory, brain variance and sub-threshold levels of clinical disorders, and to investigate whether these findings expand to other forms of metacognition. Finally, participants will complete a number of structural and functional MRI scans (including DTI). This work may help us understand the pure science of the function of human memory, as well as the nature of clinical disorders.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0020.005
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.364
GPT teacher head0.422
Teacher spread0.058 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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