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Record W4390084601 · doi:10.1017/s1355617723011360

54 The Influence of Sex on Cognitive Control Performance and Frontoparietal Network Integrity in First-Episode Psychosis

2023· article· en· W4390084601 on OpenAlexaff
Kaitlyn M. Greer, Sierra Jarvis, Ben Graul, Colt M. Halter, Aaron Clouse, Madeleine Reading, Braydon Lee, Karteek Popuri, Mirza Faisal Beg, Derin Cobia

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsSimon Fraser UniversityMemorial University of Newfoundland
Fundersnot available
KeywordsPsychologyPsychosisCognitionMiddle frontal gyrusSuperior frontal gyrusStatistical parametric mappingNeuropsychologyThalamusAudiologyNeuroscienceSuperior temporal gyrusFunctional magnetic resonance imagingPsychiatryMedicineMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

Objective: Cognitive deficits in first-episode psychosis (FEP) are well documented, particularly aspects of cognitive control, which is one of the primary hypothesized functions of the frontoparietal network (FPN). The clinical features of psychotic disorders are known to differ between men and women, but little work has systematically studied neurobiological differences between the sexes, particularly in FEP. The current study aimed to examine sexual dimorphisms in structural integrity of the frontoparietal network (FPN) and its role in cognitive control in FEP. Participants and Methods: A total of 111 FEP patients (68 male, 43 female) and 55 healthy control participants (35 male, 20 female) from the Human Connectome Project for Early Psychosis underwent T1-weighted magnetic resonance imaging and neuropsychological testing were included in the study. Regions of interest (ROIs) included: left and right superior frontal gyrus, left and right middle frontal gyrus, left inferior frontal gyrus, left and right inferior parietal gyrus, right caudate and left thalamus. Using high-dimensional brain mapping procedures, surface shape of the caudate and thalamus was characterized using Large Deformation Diffeomorphic Metric Mapping, and cortical thickness of frontal and parietal regions was estimated using the FreeSurfer toolkit. Cognitive control was assessed using the Fluid Cognition Composite score from the NIH Toolbox Cognition Battery. Multivariate ANOVA models tested group differences, separated by sex, in cortical thickness ROIs, in addition to a whole-brain vertex-wise analysis. Vertex-wise statistical surface t-maps evaluated differences in subcortical surface shape, and Pearson correlations tested relationships between brain regions and Fluid Cognition performance. Results: Results of deep brain region comparisons between schizophrenia males (SCZM) and schizophrenia females (SCZF) groups revealed significant outward deformation at the tail of the right caudate and significant inward deformation along the dorsal aspects of the right caudate. Additionally, significant inward deformation in multiple nuclei of the left thalamus were revealed. Significant negative relationships between Fluid Cognition and the left superior/middle frontal gyrus (r = -0.24, p = 0.05) in the male FEP group were observed. Additionally, significant positive relationships between Fluid Cognition and left inferior frontal gyrus (r = 0.35, p = 0.02) and left inferior parietal gyrus (r = 0.35, p = 0.02) in the female FEP group were found. Conclusions: Overall, findings revealed significant brain differences of the FPN in deep-brain structures only, including abnormal caudal and thalamic shape, in male FEP compared to female FEP, providing evidence of the importance to examine sex differences in deep-brain regions at the first episode. Differential brain relationships with cognitive control also highlight sex-specific presentations that may aid in clinical management and further characterization of the illness in early stages.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0040.000

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 head0.037
GPT teacher head0.295
Teacher spread0.258 · 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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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