Speeding up the brain: when spatial facilitation translates into latency shortening
Bibliographic record
Abstract
Waves of activity following a focal stimulation are reliably observed to spread across the cortical tissue. The origin of these waves remains unclear and the underlying mechanisms and function are still debated. In this study, we ask whether waves of activity modulate the magnetoencephalography (MEG) signals recorded in humans during visual stimulation with Gabor patches sequentially flashed along a vertical path, eliciting a perception of vertical apparent motion. Building upon the functional properties of long-rang horizontal connections, proposed to contribute to spreading activity, we specifically probe the amplitude and latency of MEG responses as a function of Gabor contrast and orientation. The results indicate that in the left hemisphere the response amplitude is enhanced and the half height response latency is shortened for co-aligned Gabor as compared to misaligned Gabor patches at a low but not at a high contrast. Building upon these findings, we develop a biologically plausible computational model that performs a "spike time alignment" of the responses to elongated contours with varying contrast, endowing them with a phase advance relative to misaligned contours.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".