The Interplay of Stimulus Modality and Response Latency in Neural Network Organization for Simple Working Memory Tasks
Bibliographic record
Abstract
We used functional magnetic resonance imaging to examine how modality of input affects functional network organization beyond the sensory cortices for simple working memory tasks. The stimuli were auditory or visual bandpass-filtered white noise. On a given trial, three stimuli, each with differing center frequencies, were presented in succession. For temporal sequencing tasks, participants indicated when the stimulus with the highest frequency content appeared. For comparison tasks, participants indicated whether the frequency content of the last stimulus was lower, intermediate, or higher than the first two stimuli. Task difficulty was equated by establishing equivalent accuracy thresholds across subjects. We used behavioral spatiotemporal partial-least squares (ST-bPLS) analysis to identify neural patterns capturing the optimal association between brain images and reaction time. Because of statistical instabilities, subjects were divided into a SLOW group and a FAST group based on the median split of reaction times. ST-bPLS identified a significant interaction between stimulus modality and task demands for both groups, indicating that task-dependent brain-behavior correlations changed with stimulus modality. The large-scale activity pattern associated with this effect included prefrontal cortex and parietal cortex for the SLOW group and parietal cortex and cingulate for the FAST group. For the FAST group only, ST-bPLS also identified a significant main effect that differentiated tasks independent of modality. The pattern associated with this effect included prefrontal cortex and parietal cortex. These results confirm that modality of input affects network configuration even outside of the sensory cortices but that network configuration may vary with behavior.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".