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Record W4400981299 · doi:10.3390/brainsci14080742

Resting-State Functional Connectivity Profile of Insular Subregions

2024· article· en· W4400981299 on OpenAlexafffund
Jimmy Ghaziri, Phillip Fei, Alan Tucholka, Sami Obaïd, Olivier Boucher, Isabelle Rouleau, Dang Khoa Nguyen

Bibliographic record

VenueBrain Sciences · 2024
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversité de SherbrookeCentre Hospitalier de l’Université de MontréalUniversité du Québec à Montréal
FundersCanadian Institutes of Health ResearchRéseau en Bio-Imagerie du QuebecNatural Sciences and Engineering Research Council of CanadaFondation du CHUM
KeywordsTractographyInsulaFunctional connectivityConnectomeNeuroscienceResting state fMRIInsular cortexBrain mappingStereoelectroencephalographyConcordancePsychologyDiffusion MRIBiologyElectroencephalographyMedicineMagnetic resonance imagingBioinformatics

Abstract

fetched live from OpenAlex

The insula is often considered the fifth lobe of the brain and is increasingly recognized as one of the most connected regions in the brain, with widespread connections to cortical and subcortical structures. As a follow-up to our previous tractography work, we investigated the resting-state functional connectivity (rsFC) profiles of insular subregions and assessed their concordance with structural connectivity. We used the CONN toolbox to analyze the rsFC of the same 19 insular regions of interest (ROIs) we used in our prior tractography work and regrouped them into six subregions based on their connectivity pattern similarity. Our analysis of 50 healthy participants confirms the known broad connectivity of the insula and shows novel and specific whole-brain and intra-connectivity patterns of insular subregions. By examining such subregions, our findings provide a more detailed pattern of connectivity than prior studies that may prove useful for comparison between patients.

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)0.001
metaresearch head score (Gemma)0.021
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.001
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 head0.092
GPT teacher head0.308
Teacher spread0.216 · 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.

Study designBench or experimental
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

Citations10
Published2024
Admission routes2
Has abstractyes

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