Specificity of Human Cortical Areas for Reaches and Saccades
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Bibliographic record
Abstract
Electrophysiological studies in monkeys have identified effector-related regions in the posterior parietal cortex (PPC). The lateral intraparietal area, for example, responds preferentially for saccades, whereas the parietal reach region responds preferentially for arm movements. However, the degree of effector selectivity actually observed is limited; each area contains neurons selective for the nonpreferred effector, and many neurons in both areas respond for both effectors. We used functional magnetic resonance imaging to assess the degree of effector preference at the population level, focusing on topographically organized regions in the human PPC [visual area V7, intraparietal sulcus 1 (IPS1), and IPS2]. An event-related design adapted from monkey experiments was used. In each trial, an effector cue preceded the appearance of a spatial target, after which a Go signal instructed subjects to produce the specified movement with the specified effector. Our results show that the degree of effector specificity is limited in many cortical areas and transitions gradually from saccade to reach preference as one moves through the hierarchy of areas in the occipital, parietal, and frontal cortices. Saccade preference was observed in visual cortex, including early areas and V7. IPS1 exhibited balanced activation to saccades and reaches, whereas IPS2 showed a weak but significant preference for reaches. In frontal cortex, areas near the central sulcus showed a clear and absolute preference for reaches, whereas the frontal eye field showed little or no effector selectivity. Although these results contradict many theoretical conclusions about effector specificity, they are compatible with the complex picture arising from electrophysiological studies and also with previous imaging studies that reported mostly overlapping saccade- and arm-related activation. The results are also compatible with theories of efficient coding in cortex.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 it