Neural correlates of speed-tuned differences in global motion and motion-defined form perception
Bibliographic record
Abstract
A popular view of the human visual system is that it comprises at least two somewhat parallel pathways: the ventral stream for form and colour, and the dorsal stream for motion. There is also support for a modified view in which slow speeds of motion are processed ventrally. We recently reported speed-tuned psychophysical differences in the typical and atypical development (due to amblyopia) of global motion and motion-defined form perception (Hayward et al., 2011; Narasimhan & Giaschi, 2012). Specifically, immaturities and deficits were reported for slow but not fast speeds. These different developmental patterns may reflect different cortical systems mediating slow and fast motion perception. The current study used functional MRI in adults with normal vision to examine the neural correlates of our psychophysical tasks. The tasks included global motion direction discrimination and motion-defined rectangle orientation discrimination, each at slow (0.1 deg/s) and fast (5 deg/s) speeds. Stimuli were random-walk dot fields presented using a block design with four conditions: high motion coherence, low motion coherence, 0% motion coherence and stationary dots. Coherence levels were adjusted to match the difficulty level across speeds. We examined each task using a whole-brain voxelwise analysis and a 2 (Speed: Fast, Slow) x 3 (Coherence: High, Low, 0%) within-subjects ANOVA. For both tasks, there were significant main effects of Speed and Coherence, and no interaction between the two. On the global motion task, pairwise comparisons between fast and slow speeds showed activation in occipital and parietal regions, with stronger dorsal activation for fast speeds. On the motion-defined form task, comparisons showed activation in occipital regions, with stronger activation in ventral occipital areas for slow speeds. These results demonstrate differences in the cortical systems activated by fast and slow motion, and suggest a role for the ventral stream in the processing of slow speeds. Meeting abstract presented at VSS 2013
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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 | 0.001 | 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".