Allocentric vs. Egocentric Coding of Remembered Saccade Targets in Human Cortex
Bibliographic record
Abstract
A remembered visual target can be defined in allocentric or egocentric coordinates, but the neural mechanisms for allocentric saccade coding in humans are essentially unknown. Here we employed an event-related fMRI design to investigate the brain areas involved in these two types of representation in twelve participants. A saccade target and an additional landmark were always presented for 2s, but at the beginning of each trial, a recorded voice instructed participants to remember target location relative to the landmark (Allo saccade) or ignore the landmark and remember target location (Ego saccade). During the following delay phase of 12s participants had to remember the target location in the appropriate coordinates. In a non-spatial control task (Color), participants remembered and reported target color later. At the end of the delay the landmark re-appeared at its original or a novel location for 2s, followed by a response of saccade or target color report. In the Ego task, participants were signaled to saccade toward or opposite to the target. We found that during the delay phase Ego and Allo tasks elicited higher activation in bilateral frontal eye fields, left midposterior intraparietal sulcus (mIPS) and superior parieto-occipital cortex, right amIPS and pmIPS as compared to the Color control. The Ego task produced higher activation in inferior parietal cortex as compared to the Allo task, whereas temporal and occipital cortex showed higher activation for Allo vs. Ego. Egocentric directional selectivity was observed in superior and inferior occipital cortex in the Ego task, whereas allocentric directional selectivity was observed in precuneus and mIPS in the Allo task. Our results indicate different cortical mechanisms for allocentric vs. egocentric target memory for saccade. Comparing this to our recent reaching study (Chen et al. Journal of Neuroscience 2014), the detailed mechanisms also depend on the motor effector (eye vs. hand). Meeting abstract presented at VSS 2016
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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".