Characterization of neurons in the primate medial intraparietal area reveals a joint representation of intended reach direction and amplitude
Bibliographic record
Abstract
To support accurate memory-guided reaching, the brain must represent both the direction and amplitude of reaches in a movement plan. Several cortical areas have been shown to represent the direction of a planned reaching movement, but the neuronal representation of reach amplitude is still unclear, especially in sensory-motor integration areas. To investigate this, we recorded from neurons in the medial intraparietal area (MIP) of monkeys performing a variable amplitude memory reach task. In one monkey, we additionally recorded from the dorsal premotor cortex (PMd) for direct cross-area comparisons. In both areas, we found modest but significant proportions of neurons with movement-planning activity sensitive to reach amplitude. However, reach amplitude was under-represented relative to direction in the neuronal population, with approximately one third as many selective neurons. We observed an interaction between neuronal selectivity for amplitude and direction; neurons in both areas exhibited significant modulation of neuronal activity by reach amplitude in some but not all directions. Consistent with an encoding of reach goals as a position in visual space, the response patterns of MIP/PMd neurons were best predicted by 2D Gaussian position encoding model, in contrast to a number of alternative direction and amplitude tuning models. Taken together, these results suggest that amplitude and direction jointly modulate activity in MIP, as in PMd, to form representations of intended reach position.
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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".