Strength of Retinotopic Representation of Visual Memories is Modulated by Strategy
Bibliographic record
Abstract
Human visual cortex shows retinotopic organization during both perception and attention, but whether this remains true for visual short-term memory (VSTM) is uncertain. In 2 functional magnetic resonance imaging experiments, we separated retinotopic activation during perception, attention, and VSTM maintenance. The 2 experiments differed in whether spatial encoding of the VSTM stimuli and prospective attention to the locations of the remembered items was encouraged or discouraged. Using multivoxel pattern analysis to extract a measure of spatial coding in early visual cortex, we saw sensory and attentional retinotopic coding in both experiments. However, significant spatial coding during memory maintenance was only seen where a spatial strategy was encouraged. Furthermore, individual differences in attentional spatial coding predicted performance in both experiments, while individual differences in maintenance spatial coding predicted performance in neither. We conclude that retinotopic coding in the early visual cortex during VSTM maintenance is not obligatory, that attentional processes during stimulus perception modulate memory performance, and that different attentional strategies are used depending on the task in hand.
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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 | 0.004 |
| 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 | 0.001 | 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".