Sharp emergence of working memories along the primate dorsal visual pathway
Bibliographic record
Abstract
The temporary storage of visual information in the absence of retinal inputs is known as visual working memory. It is long established that in primates, visual working memory representations are encoded in the sustained spiking activity of neurons in high-order cortical areas far downstream along the visual processing pathways, such as the lateral prefrontal cortex (LPFC). Several studies have recently argued that these representations are also encoded in the spiking activity of neurons in early visual cortical areas. Where along the visual stream working memory representations emerge remains highly controversial. Here we show that in macaque monkeys, working memories of visual motion direction are not encoded in the spiking activity of direction-selective neurons in early visual area middle temporal (MT). Surprisingly, these memories robustly emerge immediately downstream, in multimodal association area medial superior temporal (MST). Working memories in MST were as strong as (mean auROC, P = 0.13, t-test) and lasted longer than (% significant bins, P = 0.03, t-test), those found in LPFC. On the other hand, activity during working memory maintenance was more predictive of task performance in lPFC than in MST (mean choice probability, cp = 0.61 in LPFC; cp = 0.55 in MST; P = 0.02, t-test). Our findings reveal a sharp functional boundary between early visual areas, mainly encoding sensory inputs, and downstream association areas, additionally encoding the contents of working memory. Moreover, we found that local field potential oscillations in MT encoded the memorized directions and, in the low frequencies, were phase-coherent with spikes from LPFC neurons in 12.5% (14 of 112) of the recorded LPFC-MT pairs. This suggests that LPFC modulates synaptic activity in MT, a putative top-down mechanism by which working memory signals influence sensory processing in early visual cortex. Meeting abstract presented at VSS 2014
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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".