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Record W3028156911 · doi:10.1093/schbul/sbaa030.323

M11. ALTERED TRANSCRANIAL MAGNETIC STIMULATION ELECTROENCEPHALOGRAPHIC MARKERS IN SCHIZOPHRENIA

2020· article· en· W3028156911 on OpenAlexaff
Daphne Voineskos, Reza Zomorrodi, Zafiris Daskalakis

Bibliographic record

VenueSchizophrenia Bulletin · 2020
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsN100Transcranial magnetic stimulationNeuroscienceElectroencephalographyInhibitory postsynaptic potentialPsychologyNeurophysiologyEvoked potentialSchizophrenia (object-oriented programming)Cerebral cortexStimulationAudiologyMedicineEvent-related potentialPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Cortical inhibition is a neurophysiological process in which cortical gamma-aminobutyric acid (GABA) inhibitory interneurons modulate the activity of pyramidal neurons in the cerebral cortex. Multiple lines of evidence, including neurophysiological and neuropathological, report that individuals with schizophrenia have deficits in cortical inhibition. Combining transcranial magnetic stimulation (TMS) with electroencephalography is a reliable approach to measure inhibitory processes in the cortex. The overall waveform produced by TMS-EEG may index cortical reactivity as a whole and previous investigations have linked the N45 component peak and the N100 component peak with GABA-A and GABA-B inhibitory neurotransmission, respectively. The aim of this study was to stimulate the DLPFC with TMS and examine resultant differences in the TMS-EEG waveform peaks between patients with schizophrenia and healthy subjects. We hypothesized that individuals with schizophrenia will have smaller TMS-evoked potentials, specifically the amplitudes of the N100 and N45 components, those previously related to GABA-ergic inhibition. Methods We applied TMS over the left DLPFC and recorded EEG activity in 48 healthy subjects (mean age: 33.8±5.3) and 46 patients with schizophrenia (mean age: 43.3±6.4). Monophasic TMS pulses were administered using a 7-cm figure-of-8 coil, and two Magstim 200 stimulators connected via a Bistim module. Single pulse TMS was administered over the left DLPFC with 100 total pulses, which were delivered every 5s. Resultant waveforms were extracted and analyzed through custom MATLAB scripts. The TMS-evoked potential waveform was examined through Global Mean Field Amplitude (GMFA) analysis of waveform peaks in each the two groups. Normality of the distribution of each variable was assessed and a Mann Whitney U test was then performed for each variable of interest to assess differences between groups. Results Individuals in the schizophrenia group demonstrated smaller measures of cortical inhibition in the DLPFC. Specifically, smaller amplitudes of the N45 (U=724.00, p=0.004) and N100 peaks (U=831.00, p=0.039), although the overall AUC of the waveform did not differ between groups (U=969.00, p=0.307). Further analysis is underway to examine medication and symptom cluster effects. Discussion These results demonstrate novel findings of deficits in both GABA-A and GABA-B associated measures of cortical inhibition as indexed by single pulse TMS-EEG. This reinforces previous evidence from different research modalities demonstrating overall GABAergic inhibitory deficits in schizophrenia, and specifically provides new support which confirms recent findings of aberrant GABA-Aergic inhibitory neurotransmission in 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)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.000

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 head0.228
Teacher spread0.206 · 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
Published2020
Admission routes1
Has abstractyes

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