Divergent roles of early visual cortex and inferior frontal junction in visual working memory
Bibliographic record
Abstract
BACKGROUND: Recent studies indicate that both prefrontal and visual regions play critical roles in visual working memory (VWM), with prefrontal regions mainly associated with executive functions, and visual cortices linked to representations of memory contents. VWM involves the selective filtering of irrelevant information, yet the specific contributions of the prefrontal regions and visual cortex in this process remain unclear. OBJECTIVE: To understand the dynamic causal roles of prefrontal and visual regions in VWM. METHODS: The differentiation of VWM components was achieved using a computational model that incorporated a swap rate for non-target stimuli. Single-pulse magnetic transcranial stimulation (spTMS) was delivered to the early visual cortex (EVC) and the inferior frontal junction (IFJ) across different phases of an orientation recall task that with or without distractors. RESULTS: Our results indicate that spTMS over the EVC and IFJ influences VWM particularly when distractors are present. VWM precision can be impacted by spTMS applied to either region during the early retention, while spTMS effect is especially prominent when EVC is stimulated during the late retention phase and when directed at the ipsilateral EVC. Conversely, the probability of accurately recalling the target exhibited comparable patterns when spTMS was administered to either the EVC or IFJ. CONCLUSIONS: We highlight the "sensory recruitment" of VWM characterized by critical involvement of EVC particularly in the information-filtering process within VWM. The maintenance of memory content representations necessitates ongoing communication between the EVC and IFJ throughout the entirety of the VWM process in a dynamic pattern.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".