Direct Cortical Recordings Suggest Temporal Order of Task-Evoked Responses in Human Dorsal Attention and Default Networks
Bibliographic record
Abstract
The past decade has seen a large number of neuroimaging studies focused on the anticorrelated functional relationship between the default mode network (DMN) and the dorsal attention network (DAN). Due principally to the low temporal resolution of functional neuroimaging modalities, the fast-neuronal dynamics across these networks remain poorly understood. Here we report novel human intracranial electrophysiology data from six neurosurgical patients (four males) with simultaneous coverage of well characterized nodes of the DMN and DAN. Subjects performed an arithmetic processing task, shown previously to evoke reliable deactivations (below baseline) in the DMN, and activations in the DAN. In this cohort, we show that DMN deactivations lag DAN activations by approximately 200 ms. Our findings suggest a clear temporal order of processing across the two networks during the current task and place the DMN further than the DAN in a plausible information-processing hierarchy. SIGNIFICANCE STATEMENTThe human brain contains an intrinsic and strictly organized network architecture. Our understanding of the interplay across association networks has relied primarily on the slow fluctuations of the hemodynamic response, and as such it has lacked essential evidence regarding the temporal dynamics of activity across these networks. The current study presents evidence from high spatiotemporal methods showing that well studied areas of the default mode network display delayed task-induced activity relative to divergent responses in dorsal attention network nodes. This finding provides direct and critical evidence regarding the temporal chronology of neuronal events across opposing brain networks.
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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) | 0.002 | 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".