Neural substrates for allocentric‐to‐egocentric conversion of remembered reach targets in humans
Bibliographic record
Abstract
Targets for goal-directed action can be encoded in allocentric coordinates (relative to another visual landmark), but it is not known how these are converted into egocentric commands for action. Here, we investigated this using a slow event-related fMRI paradigm, based on our previous behavioural finding that the allocentric-to-egocentric (Allo-Ego) conversion for reach is performed at the first possible opportunity. Participants were asked to remember (and eventually reach towards) the location of a briefly presented target relative to another visual landmark. After a first memory delay, participants were forewarned by a verbal instruction if the landmark would reappear at the same location (potentially allowing them to plan a reach following the auditory cue before the second delay), or at a different location where they had to wait for the final landmark to be presented before response, and then reach towards the remembered target location. As predicted, participants showed landmark-centred directional selectivity in occipital-temporal cortex during the first memory delay, and only developed egocentric directional selectivity in occipital-parietal cortex during the second delay for the 'Same cue' task, and during response for the 'Different cue' task. We then compared cortical activation between these two tasks at the times when the Allo-Ego conversion occurred, and found common activation in right precuneus, right presupplementary area and bilateral dorsal premotor cortex. These results confirm that the brain converts allocentric codes to egocentric plans at the first possible opportunity, and identify the four most likely candidate sites specific to the Allo-Ego transformation for reaches.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".