Linking connectomics and dynamics in the human brain
Bibliographic record
Abstract
Abstract To understand human cognition, it is essential to study the brain on multiple levels, from microscopic to macroscopic scales. Computational connectomics is a new area of neuroscience where scientists seek to combine empirical observations within a computational theory of the brain. The whole-brain network modeling and simulation platform, The Virtual Brain (TVB), is a remarkable innovation in the field of computational connectomics. By combining the connectivity of individual persons with local biologically realistic populationmodels, TVB allows simulation and prediction of the local activity of neuronal populations and the global activity unfolding along the gray matter, both of which can be linked to empiricalmeasures of electrical, hemodynamic, and structural aspects of the brain. TVB is currently used to study the structural, functional, and computational alterations in the diseased brain with reported successes in stroke and epilepsy. Subjectspecific brain models provided by TVB will result in robust and efficient personalized diagnostics, prognostics, and treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".