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Record W1996668729 · doi:10.1111/bdi.12173

Disturbances of visual motion perception in bipolar disorder

2014· article· en· W1996668729 on OpenAlexaff
Rebecca A. O'Bryan, Colleen A. Brenner, William P. Hetrick, Brian F. O’Donnell

Bibliographic record

VenueBipolar Disorders · 2014
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Mental Health
KeywordsBipolar disorderPsychologyCognitionSchizophrenia (object-oriented programming)Motion perceptionVisual perceptionAudiologyMoodPerceptionVisual processingCognitive psychologyNeurosciencePsychiatryMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: While cognitive deficits have been well documented in patients with bipolar disorder, visual perception has been less well characterized. Such deficits appear in schizophrenia, which shares genetic risk factors with bipolar disorder, and may contribute to disturbances in visual cognition and learning. METHODS: The present study investigated visual perception in bipolar disorder using psychophysical tests of contrast sensitivity, dot motion discrimination, and form discrimination. The relationship of these measures to mood state, medication status, and cognitive function was investigated. Sixty-one patients with type I bipolar disorder and 67 comparison subjects were tested. RESULTS: Results indicated a deficit in dot motion trajectory discrimination in both euthymic and ill individuals with bipolar disorder, as well as a global deficit in moving grating contrast sensitivity. Ill individuals with bipolar disorder were impaired in psychomotor processing, but this finding was not related to visual processing performance. CONCLUSIONS: These findings could be due to disturbances in specific visual pathways involved in the processing of motion properties, or to a more general deficit which impairs processing of temporally modulated stimuli.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.938

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 studies0.0000.000
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 head0.007
GPT teacher head0.256
Teacher spread0.249 · 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 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

Citations52
Published2014
Admission routes1
Has abstractyes

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