Motion mechanisms and cortical areas in human vision : psychophysics and fMRI
Bibliographic record
Abstract
Our visual world contains both luminance- (first-order) and contrast-defined (second-order) information. Distinct mechanisms underlying the perception of first-order and second-order motion have been proposed from electrophysiological, psychophysical and neurological studies. In this thesis psychophysical and human brain imaging (fMRI) experiments are described that support the notion of distinct mechanisms, but extend the previous studies by providing evidence for a functional dissociation and a relative cortical specialization for first- and second-order motion. Using psychophysical methods, a directional anisotropy was found for second-order but not first-order motion in peripheral vision. This anisotropy is interpreted as a functional dissociation implicating the second-order mechanism in optic flow processing. Identification of early visual cortical areas is a prerequisite to any functional assessment of these visual areas. To this aim a novel human brain mapping method has been developed which automatically segments early human retinotopic visual areas. Unlike previous methods this procedure does not depend on a cortical surface reconstruction and thereby greatly simplifies the analysis. In a combined psychophysical and fMRI study, distinct cortical regions, in occipital and parietal lobes, were preferentially activated by either first- or second-order motion. These results provide evidence for the idea that first-order motion is computed in V1 and second-order motion in later occipital visual areas. In addition the results suggest a functional dissociation of the two kinds of motion beyond the occipital lobe consistent with a role for the second-order mechanism in optic flow analysis.
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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) | 0.002 | 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".