MétaCan
Menu
Back to cohort
Record W2020596985 · doi:10.1080/10874208.2011.623093

sLORETA and fMRI Detection of Medial Prefrontal Default Network Anomalies in Adult ADHD

2011· article· en· W2020596985 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Neurotherapy · 2011
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyDefault mode networkPrefrontal cortexFunctional connectivityNeuroscienceCognitive psychologyCognition

Abstract

fetched live from OpenAlex

Attention deficit hyperactivity disorder (ADHD) is a developmental psychiatric disorder thought to affect approximately 5 to 10% of school-age children, of whom 30 to 65% continue to exhibit symptoms into adulthood. The prevalence of ADHD in adults is also an estimated 4%, second only to depression. Across studies there appear to be significant network dysfunctions involved in ADHD. Typically the foci of interest in ADHD included the insular cortices, frontal lobes, basal ganglia, and cerebellum. More recently, attention has been directed to the default network of the brain and its functional integrity in ADHD with focus on the precuneus and parietal lobes and interactions with medial prefrontal cortices. Functional magnetic resonance imaging (fMRI) measures neurovascular coupling as measured by the blood oxygenated level dependent signal (BOLD). Electroencephalogram (EEG) measures brain electrical information. Because fMRI is an indirect measure of neuronal activity and EEG is a direct measure, combining the results from these two imaging modalities under the same task conditions may provide a more complete story as to the what (EEG) and where (fMRI) activity exists. This article discusses the benefits of using standardized low resolution electromagnetic tomography (sLORETA) analysis of the EEG as compared to fMRI. The goal of the study, the data from which we use for our justification, was to discover the functional differences in ADHD and non-ADHD brains with different brain imaging modalities. We hoped to elucidate functional connectivity patterns by interpreting the data acquired with the EEG using sLORETA and the data acquired with the fMRI scans. We further hoped to find correlation with the sLORETA and fMRI interpretations so as to confirm that EEG is an adequate stand-alone methodology to evaluate ADHD. Participants included 6 ADHD and 7 non-ADHD subjects. They were initially interviewed by phone and administered the Connors Rating Scale and the Mini International Neuropsychiatric Interview to determine accuracy of symptom reporting and to rule out psychological comorbidities. Exclusion criteria consisted of previous head trauma, recent drug or alcohol abuse (14 days), or neurological syndromes. We recorded sequential 19-channel EEG and fMRI during the eyes-open and eyes-closed states and while performing the Stroop test. The QEEG results were evaluated with comparison to a normative database and with sLORETA analysis.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.352
Threshold uncertainty score0.342

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)0.0000.000

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 head0.046
GPT teacher head0.291
Teacher spread0.245 · 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