Working memory requirements influence the strength of visual motion direction representations in dorsolateral prefrontal cortex neurons
Bibliographic record
Abstract
When presented with a moving visual stimulus, neurons in macaque area MT encode its motion direction. When the stimulus disappears and its direction is held in working memory, these neurons no longer encode motion direction. In contrast, neurons in the dorsolateral prefrontal cortex (dlPFC) encode motion direction both during the stimulus presentation and during working memory maintenance in the absence of visual input. One question that has not yet been systematically addressed is whether motion direction representations in dlPFC are stronger when the stimulus remains visually available or when it disappears and its direction is remembered. To examine this, we recorded the activity of 155 dlPFC neurons from two macaques while they performed two alternative conditions of a match-to-sample task requiring the comparison between the motion directions of a sample stimulus and a subsequent test stimulus. In the memory condition, the sample was presented for 1 s and, after a delay, followed by the test. In the no-memory condition, the sample remained visible until and during the test presentation, and therefore working memory was not required. For each neuron, we quantified sample direction representation strength using ROC analysis and compared it between the delay period of the memory condition and the equivalent period of the no-memory condition. We found that in approximately half of the direction-selective neurons, representation strength was higher when the sample remained visually available than when it was remembered. Interestingly, in the remaining half, representations were stronger when the sample direction was remembered than when the sample remained present. Our results show not only that dlPFC neurons can encode visual representations in the absence of sensory input, but also that in many neurons, the strength of these representations is in fact reduced in the presence of sensory input, when working memory is not required. Meeting abstract presented at VSS 2012
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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 | 0.002 |
| 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 | 0.001 |
| 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".