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Stability of resting fMRI interregional correlations analyzed in subject-native space: A one-year longitudinal study in healthy adults and premanifest Huntington's disease

2011· article· en· W2010117446 on OpenAlexaboutno aff
Tyler M. Seibert, D.S. Adnan Majid, Adam R. Aron, Jody Corey‐Bloom, James B. Brewer

Bibliographic record

VenueNeuroImage · 2011
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersNational Institute of Neurological Disorders and StrokeNational Institute of General Medical SciencesNational Institutes of HealthCHDI Foundation
KeywordsStability (learning theory)PsychologyHuntington's diseaseResting state fMRIFunctional connectivitySpace (punctuation)DiseaseCognitive psychologyPhysical medicine and rehabilitationMedicineNeuroscienceComputer scienceMachine learningInternal medicine

Abstract

fetched live from OpenAlex

The pattern of interregional functional MRI correlations at rest is being actively considered as a potential noninvasive biomarker in multiple diseases. Before such methods can be used in clinical studies it is important to establish their usefulness in three ways. First, the long-term stability of resting correlation patterns should be characterized, but there have been very few such studies. Second, analysis of resting correlations should account for the unique neuroanatomy of each subject by taking measurements in native space and avoiding transformation of functional data to a standard volume space (e.g., Talairach-Tournox or Montreal Neurological Institute atlases). Transformation to a standard volume space has been shown to variably influence the measurement of functional correlations, and this is a particular concern in diseases which may cause structural changes in the brain. Third, comparisons within the patient population of interest and comparisons between patients and age-matched controls, should demonstrate sensitivity to any disease-related disruption of resting functional correlations. Here we examine the test-retest stability of resting fMRI correlations over a period of one year in a group of healthy adults and in a group of cognitively intact individuals who are gene-positive for Huntington's disease. A recently-developed method is used to measure functional correlations in the native space of individual subjects. The utility of resting functional correlations as a biomarker in premanifest Huntington's disease is also investigated. Results in control and premanifest Huntington's populations were both highly consistent at the group level over one year. We thus show that when resting fMRI analysis is performed in native space (to reduce confounds in registration between subjects and groups) it has good long-term stability at the group level. Individual-subject level results were less consistent between visit 1 and visit 2, suggesting further work is required before resting fMRI correlations can be useful diagnostically for individual patients. No significant effect of premanifest Huntington's disease on prespecified interregional fMRI correlations was observed relative to the control group using either baseline or longitudinal measures. Within the premanifest Huntington's group, though, there was evidence that decreased striatal functional correlations might be associated with disease severity, as gauged by estimated years to symptom onset or by striatal volume.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.099
GPT teacher head0.315
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 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

Citations48
Published2011
Admission routes1
Has abstractyes

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