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Record W3215017765 · doi:10.1016/j.brs.2021.10.267

Variability in TMS-EEG response can partially be described by the phase of ongoing brain oscillation

2021· article· en· W3215017765 on OpenAlexaff
Mohsen Poorganji, Reza Zomorrodi, Colin Hawco, Itay Hadas, Aron Hill, Tarek K. Rajji, Robert Chen, Daphne Voineskos, Daniel M. Blumberger, Zafiris J. Daskalakis

Bibliographic record

VenueBrain stimulation · 2021
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversity Health NetworkUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsOscillation (cell signaling)ElectroencephalographyPhase (matter)NeurosciencePsychologyAudiologyMedicinePhysicsBiology

Abstract

fetched live from OpenAlex

frequency (~300 Hz) oscillations in GP and STN.This evoked activity resembled a sinusoid, growing in the shape of a sigmoid throughout the burst, and decaying exponentially after the last burst stimulation.This novel sigmoid-exponential-sinusoid (SES) model successfully fit the data with R-squared values of up to 0.9.Theories of the origin of this phenomenon involve local patterns of inhibition and excitation in STN, or interactions between STN and connected structures, such as the pallidum.Our detected high-frequency oscillations in STN and GP from pallidal stimulation, complementing those previously observed from STN stimulation, support the hypothesis that the phenomenon is generated by a loop involving both structures.No oscillatory response was detected when stimulating or recording in thalamus.This implies that the phenomenon is likely unique to BG, making it a promising biomarker.It has also been suggested as a possible feedback signal for closed-loop DBS, which our SES model parameters provide convenient quantitative measurements for.Finally, our findings in a dystonic patient imply that this phenomenon is not unique to Parkinson's disease, but likely generalizable to other movement disorders and perhaps even healthy subjects.

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)0.002
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.845
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.050
GPT teacher head0.315
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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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