Neural Substrates of Visual Spatial Coding and Visual Feedback Control for Hand Movements in Allocentric and Target-Directed Tasks
Bibliographic record
Abstract
Neuropsychological evidence suggests that different brain areas may be involved in movements that are directed at visual targets (e.g., pointing or reaching), and movements that are based on allocentric visual information (e.g., drawing or copying). Here we used fMRI to investigate the neural correlates of these two types of movements in healthy volunteers. Subjects (n = 14) performed right hand movements in either a target-directed task (moving a cursor to a target dot) or an allocentric task (moving a cursor to reproduce the distance and direction between two distal target dots) with or without visual feedback about their hand movement. Movements were monitored with an MR compatible touch panel. A whole brain analysis revealed that movements in allocentric conditions led to an increase in activity in the fundus of the left intra-parietal sulcus (IPS), in posterior IPS, in bilateral dorsal premotor cortex (PMd), and in the lateral occipital complex (LOC). Visual feedback in both target-directed and allocentric conditions led to an increase in activity in area MT+, superior parietal-occipital cortex (SPOC), and posterior IPS (all bilateral). In addition, we found that visual feedback affected brain activity differently in target-directed as compared to allocentric conditions, particularly in the pre-supplementary motor area, PMd, IPS, and parieto-occipital cortex. Our results, in combination with previous findings, suggest that the LOC is essential for allocentric visual coding and that SPOC is involved in visual feedback control. The differences in brain activity between target-directed and allocentric visual feedback conditions may be related to behavioral differences in visual feedback control. Our results advance the understanding of the visual coordinate frame used by the LOC. In addition, because of the nature of the allocentric task, our results have relevance for the understanding of neural substrates of magnitude estimation and vector coding of movements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".