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Record W2794698425 · doi:10.1093/schbul/sby017.552

F21. ELECTROPHYSIOLOGICAL PARAMETERS OF SELECTIVE ATTENTION IN ADOLESCENTS WITH A FIRST EPISODE OF PSYCHOSIS: A COMPARISON WITH ADHD

2018· article· en· W2794698425 on OpenAlexaff
Iris Selten, Jacob Rydkjær, Anne Katrine Pagsberg, Birgitte Fagerlund, Birte Glenthøj, Jens Richardt Møllegaard Jepsen, Bob Oranje

Bibliographic record

VenueSchizophrenia Bulletin · 2018
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsChild, Adolescent and Family Mental Health
Fundersnot available
KeywordsPsychosisElectrophysiologyPsychologyAudiologySelective attentionPsychiatryNeuroscienceMedicineCognition

Abstract

fetched live from OpenAlex

Neuropsychological deficiencies in attentional processes and filtering of information are shown by both patients with schizophrenia and Attention Deficit Hyperactivity Disorder (ADHD). Given that behavioral symptoms differ, differential neurophysiological processes are likely to be underlying each disorder. Deficiencies in early auditory processing measured by event-related potentials (ERPs) such as the P300 amplitude and mismatch negativity are suggested to be biomarkers for schizophrenia. Here we study if these electrophysiological processes are impaired in, and specific for, young individuals with a first episode psychosis (FEP), by directly comparing them with typically developing peers and adolescents with ADHD. 27 FEP patients, 25 ADHD patients and 45 age and gender matched Healthy Controls (HC), all aged between 12 and 17 years old, were assessed for their N1, N2, P2, P3a, P3b, MMN and PN amplitudes in a selective attention paradigm (auditory oddball task). ADHD patients showed significantly smaller N2 and P3b amplitudes than HC, whereas FEP patients showed intermediate amplitudes. In addition, we found a second order interaction effect, indicating that the HC group had larger P2 amplitudes to attended deviant stimuli than to unattended deviant stimuli, whereas the response to non-attended deviant stimuli did not differ from that to non-attended standard stimuli. The ADHD group did not show this difference, in fact, they showed P2 amplitudes to unattended deviant stimuli that were larger than those to unattended standards. Interestingly, this effect was also found in the FEP group, although this only reached trend level (p = 0.08) of statistical significance. Post-hoc dividing the FEP group in patients with and without a diagnosis of schizophrenia, showed the same second order interaction effect in patients without schizophrenia as that in the ADHD subjects, while the interaction effect in patients with schizophrenia was identical to that of the HC. Furthermore, FEP patients without schizophrenia showed significantly smaller P3b amplitudes compared to FEP patients with schizophrenia and HC. Last, FEP patients with schizophrenia showed trend level significant smaller MMN amplitudes than HC (p = 0.09). No further significant group differences were found. FEP patients without schizophrenia showed impaired neurophysiological functioning compared to their counterparts with schizophrenia, who in turn showed similar performance as healthy controls. Given that use of medication did not differ between FEP patients with and without schizophrenia, our data suggest that other factors may play a role, such as comorbid symptoms. Since we found considerable overlap between FEP patients without schizophrenia and ADHD patients our current data do not support the theory that any of the investigated electrophysiological measures are useful as specific biomarkers for schizophrenia.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.022
GPT teacher head0.287
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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