Intrinsic neural timescales attenuate information transfer along the uni-transmodal hierarchy
Bibliographic record
Abstract
Abstract The brain’s intrinsic timescales are organized in a hierarchy with shorter timescales in sensory regions and longer ones in associative regions. This timescale hierarchy overlaps with the timing demands of sensory information. Our question was how does this timescale hierarchy affect information transfer. We used a model of the timescale hierarchy based on connected excitatory and inhibitory populations across the cortex. We found that a hierarchy of information transfer follows the hierarchy of timescales with higher information transfer in sensory areas while it is lower in associative regions. Probing the effect of changes in timescale hierarchy on information transfer, we changed various model parameters which all, through, the loss of hierarchy, induced increased information transfer. Finally, the steepness of the timescale hierarchy relates negatively to total information transfer. Human MEG data confirmed our results. In sum, we demonstrate a key role of the brain’s timescale hierarchy in mediating information transfer.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".