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Auditory Hypergnosia as an Example of Psychic Tonus in the Temporal Lobes: Multiple Case Analyses

2005· review· en· W2085082318 on OpenAlexaff
Claude M. J. Braun, Julie Duval, Anik Guimond

Bibliographic record

VenueCritical Reviews in Neurobiology · 2005
Typereview
Languageen
FieldNeuroscience
TopicHallucinations in medical conditions
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychicPsychologyCognitionAuditory hallucinationTemporal lobeElectroencephalographyEnergy (signal processing)AudiologyCognitive psychologyNeuroscienceMedicinePsychosisEpilepsyPsychiatry

Abstract

fetched live from OpenAlex

In 2006, Braun proposed a new model of hemispheric specialization of energy management by the brain, which he termed the "psychic tonus" model of hemispheric specialization. The term "psychic tonus" is deliberately general. It invites further investigation designed to incorporate various behavioral and cognitive modalities. At present, any cognitive operation or behavior likely to require energy expenditure, such as cardiovascular or metabolic, is considered to be at one extreme while any cognitive operation or behavior likely to reduce energy expenditure is considered to be at the other extreme. The model states that the left hemisphere of the brain is specialized to increase psychic tonus and the right to decrease it. The model predicts that the tonus of auditory representation ought to also manifest these hemispheric specializations in the temporal lobes. Specifically, it was predicted that pathological positive auditory tonus (auditory hallucination) ought to be associated more frequently with right temporal lobe lesions. Our analysis of a large number of previously published cases of patients with unilateral lesions supports the prediction.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.414
GPT teacher head0.525
Teacher spread0.111 · 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 designCase report
Domainnot available
GenreReview

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

Citations5
Published2005
Admission routes1
Has abstractyes

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