Specific functional asymmetries of the human visual cortex revealed by functional Near-Infrared Spectroscopy
Bibliographic record
Abstract
Over the past decades, the animal and human visual systems have been widely studied. Based on multiple invasive reports and neuroimaging studies, it is now well established that the cytoarchitecture of the visual cortex is related to its functional organization, which is the called retinotopic organization of the visual cortex. The present study aims to investigate retinotopic mapping as well as specific vertical and horizontal functional asymmetries within the human visual cortex using functional near-infrared spectroscopy (fNIRS). Black and white wedge checkerboard stimuli were randomly presented to the four visual fields (VF) quadrants of eight healthy adults in order to quantify and compare the localization and the amplitude of hemodynamic visual cortex responses to each stimulated VF quadrant. As expected, results showed a stronger visual cortical activation in the controlateral hemisphere and in the inverse upper/lower quadrant to the stimulation. We also measured significant stronger activations in the upper visual cortex when lower hemifield stimuli were presented compared to activations in the lower visual cortex when upper hemifield stimuli were showed. This confirms the vertical asymmetry of the visual cortex previously reported by neuroimaging and behavioural studies. The present work constitutes the first study showing functional asymmetries in the visual cortex using fNIRS and confirms the reliability of this non-invasive technique for functional mapping of the human brain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".