Is That within Reach? fMRI Reveals That the Human Superior Parieto-Occipital Cortex Encodes Objects Reachable by the Hand
Bibliographic record
Abstract
Macaque neurophysiology and human neuropsychology results suggest that parietal cortex encodes a unique representation of space within reach of the arm. Here, we used slow event-related functional magnetic resonance imaging (fMRI) to investigate whether human brain areas involved in reaching are more activated by objects within reach versus beyond reach. In experiment 1, graspable objects were placed at three possible locations on a platform: two reachable locations and one beyond reach. On some trials, participants reached to touch or grasp objects at the reachable location; on other trials participants passively viewed objects at one of the three locations. A reach-related area in the superior parieto-occipital cortex (SPOC) was more activated for targets within reach than beyond. In experiment 2, we investigated whether this SPOC response occurred when visual and motor confounds were controlled and whether it was modulated when a tool extended the effective range of the arm. On some trials, participants performed grasping and reaching actions to a reachable object location using either the hand alone or a tool; on other trials, participants passively viewed reachable and unreachable object locations. SPOC was significantly more active for passively viewed objects within reach of the hand versus beyond reach, regardless of whether or not a tool was available. Interestingly, these findings suggest that neural responses within brain areas coding actions (such as SPOC for reaching) may reflect automatic processing of motor affordances (such as reachability with the hand).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".