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Record W2725668405

Brain Coordination Dynamics in Altered States of Consciousness in Children

2014· dissertation· en· W2725668405 on OpenAlexfundno aff
Vera Nenadovic

Bibliographic record

VenueTSpace (University of Toronto) · 2014
Typedissertation
Languageen
FieldMedicine
TopicTechnology and Human Factors in Education and Health
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsConsciousnessDynamics (music)Altered statePsychologyNeuroscienceCognitive sciencePedagogy
DOInot available

Abstract

fetched live from OpenAlex

The brain is a complex dynamic and self-organizing system. Normal brain function emerges from synchronized neuronal firing between local neurons which are integrated into large scale networks via white matter tracts. Normal brain function and consciousness arise from the continual integration and dissolution of neuronal networks, and this fluctuation in synchronization is termed variability. Brain electrical activity is recorded as local field potentials using electroencephalography (EEG). The phase synchrony and variability of EEG waveforms can be quantified. The healthy brain exhibits a relatively low degree of phase synchrony and a high degree of variability.
\nClinicians are interested in using a complex system approach to brain function to provide dynamic information on neuronal physiology and pathology not available by other evaluation methods. A common challenge in paediatric critical care is evaluation of the comatose child post brain injury. Coma and medical interventions confound the clinical examination making monitoring and prognostication of outcome difficult. Brain cells and white matter tracts are disrupted post injury altering the phase synchrony between neuronal networks. It is proposed in this thesis that the estimation of the variability in EEG phase synchrony can evaluate paediatric brain function.
\nThe EEG recordings of normal children and patients in coma post brain injury are used, in a series of studies, to test the main hypothesis that slow EEG wave brain states associated with brain injury have higher magnitudes of EEG phase synchrony and lower variability values than those of EEG waves associated with consciousness. Further, the effects of age, brain development brain and the effect of a conscious slow wave EEG state (hyperventilation) on phase synchrony and variability are evaluated.
\nResults of the studies showed that EEG phase synchrony is increased in all slow wave states and is highest in comatose children with poor neurological outcome. Younger children’s brains have higher phase synchrony than older children. The variability of the EEG phase synchrony differentiates between the awake (higher values) and unconscious states (lower values). Physiologic models underlying EEG phase synchrony are discussed. The EEG phase synchrony and variability measures provide new insight into paediatric brain function.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.008
GPT teacher head0.282
Teacher spread0.275 · 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.

Study designObservational
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

Citations0
Published2014
Admission routes1
Has abstractyes

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