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Distinct M50 and M100 auditory gating deficits in schizophrenia

2005· article· en· W2027994730 on OpenAlexaff
Gregory A. Miller, Robert J. Thoma, Aaron P. Jones, Sandra N. Moses, Mingxiong Huang, Michael P. Weisend, Kim Paulson, J. Christopher Edgar, Lawrence E. Adler, José M. Cañive

Bibliographic record

VenuePsychophysiology · 2005
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsBaycrest Hospital
FundersNational Institute of Mental Health
KeywordsGatingSensory gatingMagnetoencephalographyPsychologyLateralization of brain functionSchizophrenia (object-oriented programming)AudiologyCognitionAssociation (psychology)NeuroscienceCognitive psychologyElectroencephalographyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The time course of the schizophrenia auditory gating deficit may provide clues to mechanisms of impaired cognition. Magnetoencephalography was recorded during a standard paired-click paradigm. Using source strength of the M50 and M100 components for each click, calculated from dipole locations identified as underlying each component for the first click, a ratio of the second divided by the first was used to measure gating. Patients showed a left-hemisphere gating deficit in M50 and a bilateral gating deficit in M100. Hypothesizing that an early deficit may affect later processing, hierarchical regression was used to examine variance shared between the components. A left-hemisphere M100 gating deficit was coupled with the left M50 gating deficit. In contrast, a right-hemisphere M100 gating deficit was unrelated to M50 gating in either hemisphere. Investigations of interhemisphere gating relations may clarify group differences in regional connectivity and their role in 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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.026
GPT teacher head0.291
Teacher spread0.264 · 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

Citations74
Published2005
Admission routes1
Has abstractyes

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