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Record W4231079776 · doi:10.1515/s13295-016-0027-1

Linking connectomics and dynamics in the human brain

2016· article· en· W4231079776 on OpenAlexaff
Leon Stefanovski, Amna Ghani, Anthony R. McIntosh, Petra Ritter

Bibliographic record

Venuee-Neuroforum · 2016
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsConnectomicsNeuroscienceConnectomeComputer scienceHuman brainComputational modelPrognosticsCognitionBrain activity and meditationArtificial intelligencePsychologyFunctional connectivityElectroencephalographyData mining

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.031
GPT teacher head0.269
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2016
Admission routes1
Has abstractyes

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