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Record W2601514509 · doi:10.1093/schbul/sbx023.076

SA78. Cholinergic Activity as Measured by Short-Latency Afferent Inhibition From the Dorsolateral Prefrontal Cortex in Nonsmokers With Schizophrenia: A Combined TMS–EEG Technique

2017· article· en· W2601514509 on OpenAlexaffabout
Yoshihiro Noda, Mera S. Barr, Reza Zommorodi, Robin Cash, Tarek K. Rajji, Robert Chen, Zafiris Daskalakis, Daniel M. Blumberger

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsN100Transcranial magnetic stimulationDorsolateral prefrontal cortexPsychologyNeuroscienceSchizophrenia (object-oriented programming)ElectroencephalographyPrefrontal cortexAudiologyStimulationMedicineCognitionEvent-related potentialPsychiatry

Abstract

fetched live from OpenAlex

Background: Short-latency afferent inhibition (SAI) is the neurophysiological transcranial magnetic stimulation (TMS) paradigm that indexes central cholinergic activity from the motor cortex (M1). Recently, we established a method to index SAI from the dorsolateral prefrontal cortex (DLPFC), an area implicated in the pathophysiology of schizophrenia (SCZ). Here, we investigated SAI in both M1 and the DLPFC in SCZ patients compared to healthy controls (HC). We hypothesized that modulation of N100 on TMS-evoked potential (TEP) by SAI paradigm from the DLPFC would be attenuated in SCZ compared to HC. Further, the modulation of N100 would be correlated with cognitive performance. Methods: Age-matched 12 SCZ and 12 HC were examined with a combined TMS-electroencephalography (EEG). SAI from the left M1 (M1–SAI) and DLPFC (DLPFC–SAI) were indexed by conditioning a single suprathreshold TMS with right median nerve stimulation at interstimulus intervals of N20+2ms (M1–SAI) and N20+4ms (DLPFC–SAI), respectively. TEPs by M1– and DLPFC–SAI were analyzed using independent component analysis individually. Results: With M1–SAI paradigm, there was no significant change in TEP N100 (t11 = −2.30, P = .822) in the SCZ group or no significant difference in N100 modulation between the HC and SCZ groups (t22 = 1.917, P = 0.068). However, with DLPFC–SAI paradigm, we observed a significant N100 attenuation at the DLPFC (t11 = −4.926, P < .0001), and modulation of N100 was significantly different between the HC and SCZ groups (t22 = 5.456, P < .0001; SCZ < HC). Furthermore, the N100 modulation by DLPFC–SAI was significantly correlated with executive function as measured with the Trail Making Test (r = −0.740, P = .006, N = 12). Conclusion: The modulation of N100 by the DLPFC–SAI may reflect the prefrontal pathophysiology of SCZ and thus could be a potential biomarker for cholinergic and executive dysfunction in SCZ. Funding: This research was supported by the Temerty Centre for Therapeutic Brain Intervention through the CAMH Foundation, and Canada Foundation for Innovation.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.019
GPT teacher head0.244
Teacher spread0.224 · 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 designBench or experimental
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

Citations2
Published2017
Admission routes2
Has abstractyes

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