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Schizophrenia diagnosis and anterior hippocampal volume make separate contributions to sensory gating

2008· article· en· W2051113915 on OpenAlexaff
Robert J. Thoma, Helen Petropoulos, Gregory A. Miller, Sandra N. Moses, Ashley K. Smith, Lauren Parks, S. Laura Lundy, Natalie M. Sanchez, Aaron P. Jones, Mingxiong Huang, Michael P. Weisend, José M. Cañive

Bibliographic record

VenuePsychophysiology · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsBaycrest Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on AgingNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthNational Institute on Alcohol Abuse and Alcoholism
KeywordsGatingSensory gatingHippocampal formationPsychologySchizophrenia (object-oriented programming)NeuroscienceHippocampusAudiologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Impaired P50 gating is thought to reflect a core deficit in schizophrenia, but the relevant neural network is not well understood. The present study used EEG and MEG to assess sensory gating and volumetric MRI to measure hippocampal volume to investigate relationships between them in 22 normal controls and 22 patients with schizophrenia. In the schizophrenia group, anterior but not posterior hippocampal volume was smaller, and both the P50 and M50 gating ratios were larger (worse) than in controls. Independent of group, left-hemisphere M50 gating ratio correlated negatively with left anterior hippocampal volume, and right-hemisphere M50 gating ratio correlated negatively with right anterior hippocampal volume. Schizophrenia diagnosis predicted M50 gating independent of hippocampal volume. These results are consistent with the finding that hippocampus is a critical part of a fronto-temporal circuit involved in auditory gating.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.039
GPT teacher head0.325
Teacher spread0.286 · 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

Citations29
Published2008
Admission routes1
Has abstractyes

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