Unimodal and Bimodal Access to Sensory Working Memories by Auditory and Visual Impulses
Bibliographic record
Abstract
It is unclear to what extent sensory processing areas are involved in the maintenance of sensory information in working memory (WM). Previous studies have thus far relied on finding neural activity in the corresponding sensory cortices, neglecting potential activity-silent mechanisms, such as connectivity-dependent encoding. It has recently been found that visual stimulation during visual WM maintenance reveals WM-dependent changes through a bottom-up neural response. Here, we test whether this impulse response is uniquely visual and sensory-specific. Human participants (both sexes) completed visual and auditory WM tasks while electroencephalography was recorded. During the maintenance period, the WM network was perturbed serially with fixed and task-neutral auditory and visual stimuli. We show that a neutral auditory impulse-stimulus presented during the maintenance of a pure tone resulted in a WM-dependent neural response, providing evidence for the auditory counterpart to the visual WM findings reported previously. Interestingly, visual stimulation also resulted in an auditory WM-dependent impulse response, implicating the visual cortex in the maintenance of auditory information, either directly or indirectly, as a pathway to the neural auditory WM representations elsewhere. In contrast, during visual WM maintenance, only the impulse response to visual stimulation was content-specific, suggesting that visual information is maintained in a sensory-specific neural network, separated from auditory processing areas. SIGNIFICANCE STATEMENTWorking memory is a crucial component of intelligent, adaptive behavior. Our understanding of the neural mechanisms that support it has recently shifted: rather than being dependent on an unbroken chain of neural activity, working memory may rely on transient changes in neuronal connectivity, which can be maintained efficiently in activity-silent brain states. Previous work using a visual impulse stimulus to perturb the memory network has implicated such silent states in the retention of line orientations in visual working memory. Here, we show that auditory working memory similarly retains auditory information. We also observed a sensory-specific impulse response in visual working memory, while auditory memory responded bimodally to both visual and auditory impulses, possibly reflecting visual dominance of working memory.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".