Routing States Transition During Oscillatory Bursts and Attentional Selection
Bibliographic record
Abstract
Abstract Neural information routing relies on spatiotemporal activity dynamics across interconnected brain areas. However, it remains unclear how routing states emerge at fast spiking timescales and interact with the slower activity dynamics of larger networks during cognitive processes. Here, we show that localized neural spiking events generate long-range directional routing states with spiking activity in distant brain areas that dynamically switch or amplify during oscillatory bursts, selective attention, and decision-making. Computational modeling and neural recordings from lateral prefrontal cortex (LPFC), anterior cingulate cortex (ACC), and striatum of nonhuman primates revealed that cross-areal, directional routing states arise within ∼20 ms around spikes of single neurons. On average, LPFC spikes led activity in the ACC and striatum by few milliseconds. The routing state was amplified during LPFC beta bursts between the LPFC and striatum and switched direction during ACC theta/alpha bursts between ACC and LPFC. Selective attention amplified the lead of these theta/alpha-specific lead-ensembles in the ACC, while decision-making amplified the lead of ACC and LPFC spiking output over the striatum. Notably, the fast lead/lag relationships of cross-areal neuronal ensembles that were modulated by attention states or decision-making predicted firing rate dynamics of their neurons during those functional states at slower timescales. Overall, our findings demonstrate directional routing of spiking activity across nonhuman primate frontal and striatal areas, as well as the functional and network states that modulate the direction and magnitude of these interactions. Summary Fast spatio-temporal dynamics of brain activity subserves the routing of information across distant regions and is integral to flexible cognition, decision-making, and selective attention. This study demonstrates that routing dynamics emerge as 20 ms brief lead and lag relationships of spiking activities across distant brain areas. The direction and magnitude of the lead and lag relationships systematically switched during frequency-specific oscillatory bursts and when attention shifts to visual cues.
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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) | 0.001 | 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".