Detection of inter-hemispheric functional connectivity in motor cortex with coherence analysis
Bibliographic record
Abstract
Functional near-infrared spectroscopy (fNIRS) is showing promise as an alternate method to fMRI for studying cortical function. Resting state studies in both methods are showing functional linkages. The strength of functional connections is typically quantified by the level of significance of the temporal synchrony between brain regions, termed resting-state functional connectivity. Coherence analysis of resting state allows for phase insensitive and frequency specific analysis. This paper provides a detailed method for undertaking fNIRS in combination with resting-state coherence analysis. We show that maps of inter-hemispheric resting-state functional connectivity between the motor cortices can be reliably generated, and the frequency responses (to 50 Hz) for both oxy- and deoxyhemoglobin. Frequencies of 0-0.1 Hz provide robust data as have been shown previously. Higher frequencies (up to 5 Hz) also exhibit high coherence. Deoxyhemoglobin also shows high coherence above 10Hz. Coherence is similar during both resting and task activated states. fNIRS allows for mapping cortical function and, in combination with coherence analysis, allows one to study variations in frequency response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".