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Record W4404636922 · doi:10.1503/jpn.240060

Altered use of extraretinal information during sequential saccadic eye movements among people with schizophrenia and bipolar disorder with psychotic features

2024· article· en· W4404636922 on OpenAlexvenueno aff
Dominic Roberts, Beier Yao, Martin Rolfs, Rachael Slate, Jessica Fattal, Jacqueline Bao, Eric D. Achtyes, Ivy F. Tso, Vaibhav A. Diwadkar, Katharine N. Thakkar

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2024
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsnot available
FundersNational Institutes of HealthH. Lundbeck A/SDeutsche ForschungsgemeinschaftEuropean Commission
KeywordsSaccadic maskingSchizophrenia (object-oriented programming)Eye movementPsychologyBipolar disorderCognitive psychologyAudiologyNeurosciencePsychiatryMedicineCognition

Abstract

fetched live from OpenAlex

Background Impaired corollary discharge (CD) signalling disrupts the ability to predict the sensory consequences of one’s own actions; impaired CD signalling may be specific to schizophrenia or it may also be a transdiagnostic mechanism of psychosis. We sought to assess whether disruptions in oculomotor CD signalling are equally present in schizophrenia and bipolar disorder (BD) with psychotic features, and whether these putative CD disruptions relate to anomalous self-experiences. Methods We recruited patients with schizophrenia and patients with BD with psychotic features, as well as healthy controls, to complete a double-step saccade task. On each trial, 2 visual targets (T1 and T2) flashed in rapid succession. For half of the trials, participants could use visual information to look at T2. For the other half, looking correctly at T2 required CD. Results We included 66 patients with schizophrenia, 43 patients with BD with psychotic features, and 37 healthy controls. On trials requiring CD, patient groups were significantly less accurate than controls in localizing T2 ( F2,131 = 8.40, p < 0.001). This reduced accuracy was related to difficulty in compensating for variability in the first saccade ( F2,131 = 9.11, p < 0.001). Among controls, anomalous self-experiences predicted worse performance ( F1, 57 = 14.23, p < 0.001). Limitations Our sample comprised stable outpatients with relatively low symptom scores, which may limit the generalizability of our results. Conclusion These results suggest CD impairments may be a marker of predisposition for psychosis. However, observed inconsistencies suggest that this relationship is nuanced.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.293
Teacher spread0.265 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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