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Record W2157245735 · doi:10.1002/hbm.20300

Stabilities of negative correlations between blood oxygen level‐dependent signals associated with sensory and motor cortices

2007· article· en· W2157245735 on OpenAlexaff
Lixia Tian, Tianzi Jiang, Meng Liang, Xiaobo Li, Yong He, Kun Wang, Bingli Cao, Tao Jiang

Bibliographic record

VenueHuman Brain Mapping · 2007
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsMcGill UniversityMontreal Neurological Institute and Hospital
FundersBeijing University of Technology
KeywordsCorrelationResting state fMRIPsychologySensory systemMotor cortexNeuroscienceAuditory cortexVisual cortexBlood-oxygen-level dependentCortex (anatomy)AudiologyTask (project management)Negative correlationFunctional magnetic resonance imagingMedicineMathematicsInternal medicine

Abstract

fetched live from OpenAlex

Compared with positive correlations, negative correlations of blood oxygen level-dependent (BOLD) signals (NCOBSs) have been much less studied. In most related studies, the NCOBSs have been accepted as stable without further consideration. To investigate the stabilities of NCOBSs associated with the auditory, motor, and visual cortices, we evaluated the negative correlation maps of each brain region under different "task-backgrounds" within the same subject-group, as well as within different subject-groups during a conscious resting state. These "task-backgrounds" refer to tasks not expected to activate the specific ROI under consideration and are in some sense analogous to "resting states." We found that the negative correlation maps of the motor and visual cortices were quite variable between either different task-backgrounds or different subject-groups, whereas those of the auditory cortex exhibited some similarities. These results indicate that the NCOBSs associated with the motor and visual cortices were unstable both under task-backgrounds and during the conscious resting state. The auditory cortex tended to have stable NCOBSs during these "resting states" (but scanner noise could make the auditory cortex "less resting"). This study highlights the importance of paying attention to the influence of the stabilities of NCOBSs in related studies and establishes the need for further studies on NCOBSs.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.115
GPT teacher head0.288
Teacher spread0.173 · 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

Citations18
Published2007
Admission routes1
Has abstractyes

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