The frontoparietal multiple demand network interacts with the dual pathways in auditory working memory
Bibliographic record
Abstract
The frontoparietal multiple demand (MD) network has been proposed as a control network that regulates processing demands while enabling goal-directed actions. This study tested the MD network account in auditory working memory (AWM) and identified its functional role and relationship with the dual pathways model in AWM, where segregation of function was based on the sound domain. Forty-one healthy young adults performed an n-back task consisting of an orthogonal combination of the sound domain (spatial versus nonspatial) and cognitive operation (low load versus high load). Functional connectivity and correlation analyses were performed to assess the connectivity of the MD network and the dual pathways. Our results confirmed the contribution of the MD network to AWM and identified its interactions with the dual pathways in both sound domains and during high and low load levels. At high loads, the strength of connectivity with the MD network correlated with task accuracy, indicating the key role of the MD network in supporting successful performance as cognitive load increases. This study contributed to the auditory literature by showing that both the MD network and dual pathways collaborate with each other to support AWM, and neither of them alone is adequate to explain auditory cognition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".