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Record W7017462783

An Analysis Of The Relationship Between Neuronal And Haemodynamic Responses To Stress From Simultaneous Recordings Of Optical Topography And EEG Signals

2014· other· en· W7017462783 on OpenAlexaboutno aff

Bibliographic record

VenueUTPedia (Universiti Teknologi Petronas) · 2014
Typeother
Languageen
FieldEngineering
TopicHuman auditory perception and evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsElectroencephalographyHemodynamicsHaemodynamic responseMental arithmeticStress (linguistics)Mental stressCorrelationSession (web analytics)
DOInot available

Abstract

fetched live from OpenAlex

Physiological studies had been done extensively by researchers in evaluating human stress using Electroencephalogram (EEG). However, the usage of Optical Topography (OT) to evaluate the human stress is still a new field. EEG has been an established measuring device for stress through the electrical response arising from neuronal activities. On the other hand, the haemodynamic response due to stress has yet been studied. This project analyses the simultaneous recordings of the EEG and OT in response to mental stress. Data was recorded from 12 subjects that underwent tasks based on Montreal Imaging Stress Task in order to invoke mental stress. The EEG and OT datasets were analysed through the power spectrum and oxyhaemoglobin level respectively. The alpha power band has been found to be lower in the control session compared to the stress sessions. While for the OT, the oxyhaemoglobin level has been higher in the control session compared to the stress sessions. The results are then used for correlation with the data from the OT. From the correlation result obtained, it showed little significant relationship between the neuron and haemodynamic response due to stress.

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 score0.035
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
Bibliometrics0.0010.000
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 head0.021
GPT teacher head0.253
Teacher spread0.232 · 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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