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Brain Waves Reflect Cognition-Emotion State as a Diagnostic Tool for Intervention in Dysfunctional States: A Real-World Evidence

2022· article· en· W4293802571 on OpenAlex
Sílvia Mayoral-Rodrígez, Frederic Pérez-Alvarez, Carmen Timoneda Gallart

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Intellectual Disability - Diagnosis and Treatment · 2022
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsDysfunctional familyCognitionPsychologyIntervention (counseling)Clinical psychologyAudiologyDevelopmental psychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Objective: This study aims to characterize electrical signals to establish a diagnosis of cognitive-emotional dysfunction and guide a successful therapeutic intervention. Therefore, the present study aimed to observe these frequency bands in a sample of dysfunctional neurological behaviors to establish a neural marker of neural dysfunction that helps diagnose and monitor treatment. Methods: A descriptive retrospective (extracted from the database) observational study design based on real-world historical data from routine clinical practice. According to DSM-5, low academic achievement (n =70), disruptive behavior (externalizing behavior problems) (n=70), and somatic syndrome disorder (n=70) were the subjects. The mean age of the sample was 14.13 (SD = 1.46; range 12-18), 31.5% women. The measuring instrument was the NeXus-10, which is suitable for acquiring a wide range of physiological signals. Brain electrical activity was recorded by using the quantitative electroencephalograph (qEEG) in accordance with the 10-20 International Electrode Placement System. In particular, the specific form of miniQ (mini-qEEG) was used. Results: A pattern record present in all cases were identified. The record refers to (a) activity along the midline, namely, Fz-Cz-Pz, (b) activity from the center (Cz) to back, namely, Pz-O1 and O2, (c) activity from the center (Cz) forward (Fz), and (d) comparison between hemispheres. The characteristics of theta, alpha, and beta waves define the characteristic pattern of neurological dysfunction. The reversal of the dysfunctional pattern coincided with the remission of the clinical symptoms after treatment, which occurred in 87,6% of the subjects. We define remission as not meeting DSM-5 criteria. Conclusion: This study suggests that miniQ register could be considered a simple and objective tool for studying neurological dysfunction. This dysfunction is explained according to current neurological knowledge of interactive cognition-emotion processing. MiniQ may be a cheap and reliable method and a promising tool for the investigation in the field.

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.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.053
GPT teacher head0.355
Teacher spread0.302 · 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