Subcortical and cortical responses to local biological motion as revealed by fMRI and MEG
Bibliographic record
Abstract
We report findings from both human fMRI (n = 35), and MEG (n = 10) experiments that tested neural responses to dynamic ("local", acceleration) cues in biological motion. We measured fMRI responses (3T Siemens Trio, 1.5 mm3) to point-light stimuli that were degraded according to: 1. spatial coherency (intact, horizontally scrambled with vertical order retained, horizontally scrambled with vertical order inverted); 2. local motion (intact, constant velocity); and 3. temporal structure (intact, scrambled). Results from MVPA decoding analyses revealed surprising sensitivity of subcortical (non-visual) thalamic area ventral lateral nucleus (VLN) for discriminating local naturally-accelerating biological motion from constant velocity motion, in addition to a wide cortical network that extends dorsally through the IPS and ventrally, including the STS. Retaining the vertical order of the local trajectories resulted in higher accuracies than inverting it, but phase-randomization did not affect (discrimination) responses. In a separate experiment, different subjects were presented with the same stimuli while magnetic responses were measured using a 360 channel whole head MEG system (Neuromag 360, Elekta; 1000 Hz sampling frequency). Results revealed responses in much of the same cortical network identified using fMRI, peaking at 100-150 ms, and again at 350-500 ms after stimulus onset during which we also observed important functional differences with greater activity in hMT+, LO, and STS for structure-from-motion versus the local natural acceleration stimulus, and greater early (V1-V3) and IPS activity for the local natural acceleration versus constant velocity motion. We also observed activity along the medial surface by 200 ms. The fact that medial activity arrives distinctly following early cortical activity (100-150 ms), but before the 350-500 ms window suggests that the implication of thalamic VLN for biological motion perception observed with fMRI may have arisen from early cortical responses, but not higher order extrastriate cortex. Meeting abstract presented at VSS 2017
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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 | 0.000 | 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".