Comprehensive profiling of anaesthetised brain dynamics across phylogeny
Bibliographic record
Abstract
Intrinsic dynamics of neuronal circuits shape information processing. Combining neuroimaging with causal perturbation offers the opportunity to understand how local dynamics mediate the link between neurobiology and functional repertoire. We compile a unique dataset of multi-scale neural activity during wakefulness and anaesthetic-induced suppression of information processing encompassing human, macaque, marmoset, mouse, zebrafish and nematode. Applying massive feature extraction, we comprehensively characterise local neural dynamics across >6,000 time-series features. Using dynamics as a common space for cross-species comparison reveals a conserved dynamical profile of anaesthesia across species, characterised by shorter intrinsic timescales of neural activity and dampened interregional synchrony. This dynamical regime is experimentally reversed in vivo by deep-brain stimulation of the macaque centromedian thalamus, restoring behavioural responsiveness. Spatially, this conserved dynamical phenotype covaries with conserved transcriptional profiles of excitatory and inhibitory neurotransmission across human, macaque, marmoset and mouse cortex. Biophysical modelling provides a mechanistic link between the macroscale dynamical phenotype of anaesthesia, and microscale effects of key molecular targets on the timescales of synaptic excitation and inhibition. Altogether, comprehensive dynamical phenotyping reveals a shared neural endpoint of anaesthesia: across species and scales, anaesthetics induce spatio-temporal isolation of local neural activity.
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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".