Shared functional connectivity between the dorso-medial and dorso-ventral streams in macaques
Bibliographic record
Abstract
Manipulation of an object requires us to transport our hand towards the object (reach) and close our digits around that object (grasp). In current models, reach-related information is propagated in the dorso-medial stream from posterior parietal area V6A to medial intraparietal area, dorsal premotor cortex, and primary motor cortex. Grasp-related information is processed in the dorso-ventral stream from the anterior intraparietal area to ventral premotor cortex and the hand area of primary motor cortex. However, recent studies have cast doubt on the validity of this separation in separate processing streams. We investigated in 10 male rhesus macaques the whole-brain functional connectivity of these areas using resting state fMRI at 7-T. Although we found a clear separation between dorso-medial and dorso-ventral network connectivity in support of the two-stream hypothesis, we also found evidence of shared connectivity between these networks. The dorso-ventral network was distinctly correlated with high-order somatosensory areas and feeding related areas, whereas the dorso-medial network with visual areas and trunk/hindlimb motor areas. Shared connectivity was found in the superior frontal and precentral gyrus, central sulcus, intraparietal sulcus, precuneus, and insular cortex. These results suggest that while sensorimotor processing streams are functionally separated, they can access information through shared areas.
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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 | 0.001 |
| 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".