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Record W4392706179 · doi:10.1002/mds.29747

Effects of <scp>GPi DBS</scp> on Sensorimotor Integration in Dystonia: A Pilot <scp>ON</scp>/<scp>OFF</scp> Study

2024· letter· en· W4392706179 on OpenAlexaffabout
Ana Paula Arantes, Nicole A. Zalasky, Ludymila Ribeiro Borges, Rachel E. Sondergaard, Davide Martino, Zelma H. T. Kiss

Bibliographic record

VenueMovement Disorders · 2024
Typeletter
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsHotchkiss Brain InstituteUniversity of Calgary
Fundersnot available
KeywordsMedicineNeurosciencePsychology

Abstract

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Deep brain stimulation (DBS) of the globus pallidus pars interna (GPi) is an effective therapy for severe dystonia; however, the mechanism by which DBS improves dystonia is still poorly understood.1-3 To determine the role of cholinergic modulation in dystonia and DBS, we measured short-latency afferent inhibition (SAI), a transcranial magnetic stimulation (TMS) protocol sensitive to cortical cholinergic function.4 We studied patients with dystonia in both DBS-ON and DBS-OFF conditions, expecting that DBS state would modify SAI. Although cholinergic modulation is known to influence long-term plasticity,5 SAI has never been studied in GPi-DBS. The SAI protocol consisted of 120 TMS pulses (at the lowest stimulator intensity producing a motor evoked potential (MEP) of approximately 1 mV in 5/10 trials) delivered to the dominant motor cortex, preceded by suprathreshold (meaning 2X perceptual threshold) electrical nerve stimulation (NS) applied to the contralateral median nerve using three interstimulus intervals (ISI, 21, 25, and 27 ms) (Fig. 1A). SAI is defined as the inhibition induced by the NS conditioned compared to unconditioned TMS trials (Fig. 1B) and is represented as a ratio. Testing was performed with DBS-ON or -OFF first and repeated after a 20-minute washout/rest between conditions. In 10 patients (3M/7F, 57.6 ± 12.9 years) with GPi-DBS, there were no significant differences in SAI comparing DBS-ON (mean SAI = 0.9052) and DBS-OFF (mean SAI = 0.7441) (paired t-test, t[9] = 2.63, P = 0.0803). At least one of the ISIs produced inhibition in all but one patient. Similarly, the sex- and age-matched control group (3M/7F; 57.6 ± 11.9 years) displayed no difference between SAI in the first versus second testing condition (t[9] = −0.048, P = 0.582). A two-way ANOVA comparing SAIs between conditions (ON/OFF) and groups (Patient/Control) showed no statistically significant interaction between effects and group (F[1] = 0.879, P = 0.355) (Fig. 1D). Neither group nor condition was statistically related to the mean amplitude of SAI (F(1) = 1.655, P = 0.207; F(1) = 3.016, P = 0.091). SAI was normal in dystonia subjects relative to age- and sex-matched controls, and GPi-DBS did not alter SAI. As in previous reports,4 SAI was quite variable (Fig. 1B); age, experimental environment, cognitive attention, sleep, and other factors can influence SAI. SAI has been reported to be both normal and abnormal in dystonia,6 and DBS in subthalamic nucleus is believed to normalize it.2 Because our protocol was limited by the short time available for testing, it is possible that the brief interruption in DBS in chronic DBS patients may have been insufficient, preventing a statistically significant change in SAI to be measured. Similarly, mixed medication use within a heterogeneous cohort may have been a factor. It is also possible that increased inhibition may have been observed using a higher peripheral nerve stimulation intensity. We previously showed that DBS in the rodent equivalent of GPi results in cholinergic modulation of neuronal activity with extracellular recordings in patients during surgery confirming similar findings.7 SAI, however, is thought to depend on cortical cholinergic activity that may be unrelated to local DBS effects in the basal ganglia. Compared to subthalamic (STN)-DBS, which works faster to treat dystonia,2 clinical benefits occur gradually with GPi-DBS for dystonia.3 This is consistent with our results because only one of our patients had worsening dystonia OFF GPi-DBS. The different time course of response to STN-DBS and GPi-DBS does suggest different mechanisms of action for the two treatments, and cholinergic activity may still play a role in the long-term brain plasticity associated with DBS improvement. Also, variability in plasticity measures has not only been acknowledged but has also been suggested to be informative in dystonia.8 SAI changes between DBS-ON and -OFF states approach significance in our small and heterogeneous patient cohort following brief DBS interruption; this warrants further mechanistic inquiry into GPi-DBS in dystonia aimed to delineate sources of variability in plasticity measures such as those that may modify cholinergic function. This study was funded by the Dystonia Medical Research Foundation and the Natural Sciences and Engineering Research Council (NSERC) of Canada. A.P.A. holds a BRAIN-CREATE Postdoctoral Fellowship, and R.E.S. held an NSERC studentship. We thank all study participants for agreeing to be part of our study. (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript Preparation: A. Writing of the first draft, B. Review and Critique. (4) Patient recruitment. A.P.A.: 1A, 1B, 1C, 2A, 2B, 2C, 3A, 3B N.A.Z.: 1A, 1B, 1C, 2A, 2B, 2C, 3B R.E.S.: 1A, 2C, 3B Z.H.T.K.: 1A, 1B, 1C, 2A, 2B, 2C, 3A, 3B, 4 L.R.B.: 1B, 1C, 2C D.M.: 1A, 3B, 4 The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.014
GPT teacher head0.258
Teacher spread0.244 · 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 designNon-randomized trial
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
Published2024
Admission routes2
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