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Record W4223515758 · doi:10.1016/j.brs.2022.04.004

Priming the pump? Evaluating the effect of multiple intermittent theta burst sessions on cortical excitability in a nonhuman primate model

2022· letter· en· W4223515758 on OpenAlexaboutno aff
Colleen A. Hanlon, Hilary R. Smith, Phillip M. Epperly, Miracle Collier, Lindsey K. Galbo, Paul W. Czoty

Bibliographic record

VenueBrain stimulation · 2022
Typeletter
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsnot available
FundersNational Institute on Alcohol Abuse and Alcoholism
KeywordsTranscranial magnetic stimulationBurstingNeuroscienceStimulationPsychologyCTBSBrain stimulationHippocampal formationMotor cortexPrimary motor cortex

Abstract

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Leveraging preclinical knowledge regarding the role of hippocampal theta burst stimulation in learning and memory, in 2005 Huang and colleagues were the first to apply an intermittent bursting form of transcranial magnetic stimulation (theta burst stimulation, iTBS) to the human cortex [[1]Huang Y.Z. Edwards M.J. Rounis E. Bhatia K.P. Rothwell J.C. Theta burst stimulation of the human motor cortex.Neuron. 2005; 45: 201-206https://doi.org/10.1016/j.neuron.2004.12.033Abstract Full Text Full Text PDF PubMed Scopus (2437) Google Scholar]. Intermittent TBS increased cortical excitability in a manner that was more temporally efficient than non-bursting stimulation protocols. This manuscript has now been cited more than 3100 times and TBS may now be the dominant stimulation protocol of interest in the TMS field. It is currently used as a research tool and as a clinical treatment protocol for depression. While the translational relevance and temporal efficiency of TBS are powerful, there are many unanswered questions regarding the inter-individual variability in response to TBS. There have been numerous studies demonstrating a high degree of within- and between-subject variance in changes in cortical excitability following a single session of iTBS [2Corp D.T. Bereznicki H.G. Clark G.M. Youssef G.J. Fried P.J. Jannati A. Davies C.B. Gomes-Osman J. Stamm J. Chung S.W. Bowe S.J. Large-scale analysis of interindividual variability in theta-burst stimulation data: results from the ‘Big TMS Data Collaboration.Brain Stimul. 2020 Sep 1; 13: 1476-1488https://doi.org/10.1016/j.brs.2020.07.018Abstract Full Text Full Text PDF PubMed Scopus (29) Google Scholar, 3McCalley D.M. Lench D.H. Doolittle J.D. Imperatore J.P. Hoffman M. Hanlon C.A. Determining the optimal pulse number for theta burst induced change in cortical excitability.Sci Rep. 2021; 11: 8726https://doi.org/10.1038/s41598-021-87916-2Crossref PubMed Scopus (13) Google Scholar, 4Suppa A. Huang Y.Z. Funke K. Ridding M.C. Cheeran B. Di Lazzaro V. Ziemann U. Rothwell J.C. Ten years of theta burst stimulation in humans: established knowledge, unknowns and prospects.Brain Stimul. 2016 May 1; 9: 323-335https://doi.org/10.1016/j.brs.2016.01.006Abstract Full Text Full Text PDF PubMed Scopus (241) Google Scholar]. While the brain stimulation field has begun to look deeper into biological factors that may explain response variability in humans, there is growing concern that, on a fundamental level, iTBS may not be a reliable tool to increase cortical excitability. This study was designed to address this gap in our knowledge through a nonhuman primate model. Nonhuman primates provide a complementary experimental system with neuroanatomical similarity to humans, yet amenable to more controlled experimental designs. Using a cohort of 6 animals, we recently demonstrated that it is possible to collect motor evoked potentials and recruitment curves with high test-retest reliability using standard figure-of-8 coils in sedated NHPs [[5]Hanlon C.A. Czoty P.W. Smith H.R. Epperly P.M. Galbo L.K. Cortical excitability in a nonhuman primate model of TMS.Brain Stimul. 2021; 14: 19-21https://doi.org/10.1016/j.brs.2020.10.008Abstract Full Text Full Text PDF PubMed Scopus (1) Google Scholar]. The primary hypothesis of this study was that a single session of iTBS (600 pulses), does in fact, increase motor cortical excitability. A secondary hypothesis was that multiple TBS sessions induce a metaplasticity state wherein one iTBS session influences the next iTBS session. To test this hypothesis we evaluate the effect of 3 sessions of iTBS (10-15-min between-session interval) on cortical excitability in a cohort of 12 sedated NHPs. Methods: The Wake Forest University Animal Care and Use Committee approved Procedures. Data were acquired from 12 male cynomolgous macaques (14.0 ± 1.2yrs; December 2020–January 2021). Coregistration and neuronavigation: A T1-weighted MRI scan from each animal was imported into the neuronavigation system (Brainsight 2.4, Rogue Research Inc., Canada), Scalp-to-cortex distance was measured (25.95 ± 11.35 mm; 9.2–43.4). EMG: Monkeys were sedated (5–10 mg/kg ketamine) followed by inhaled isoflurane (1.0–1.5% to effect). Once the animal was in place (supine, head and chest elevated approximately 45°), the forearm was shaved. Disposable surface electrodes (24mm Covidien) were placed over the right flexor digitorum. The EMG signal was recorded at 10240 Hz with a 5–3000Hz bandpass filter (EMG Pod, Rogue Research Inc., Canada). TMS setup: The scalp position associated with the largest MEP was marked as a target (D70 Air Film Coil, Magstim Super Rapid2, Welcony, UK). TMS experiment: Three sessions of iTBS (iTBS 1, 2 & 3) were delivered (600 pulses/session, 3 pulses/burst, 10.6-s inter train interval, 64% machine output (MO) (see supplement for parameter rationale). A 2 minute sampling period took place before and after each iTBS session (5 pulses @ 80, 90, 75, 85, 70, 95% MO delivered in that order). The peak-to-peak amplitude of the unrectified EMG signal was computed in the 50-ms response window beginning 10 ms after the TMS pulse. There was a 10 min break between each sampling interval (2 min) such that the average time between iTBS1-2 and iTBS 2–3 was 15.2 ± 0.3min. Analysis: A linear mixed model was constructed (repeated factors: time, trial, intensity; covariate: scalp-cortex distance; dependent measure: MEP; SPSS 26.0, IBM Statistics). Estimated marginal means were calculated for all fixed effects and subsequent pairwise comparisons were Bonferroni corrected. Results: There was an effect of time (Fig. 1; F(6,298) = 12.25, p < 0.001) and intensity (Supplemental data, F(5,390) = 240.65, p < 0.001) on MEP. MEP amplitude increased immediately after iTBS 1 (T1-T2; mean difference (MD) ± standard error (SEM) = 62.9 ± 15.75 μV, p = 0.002) and decayed during the 15-min interval. There was a significant increase in MEP immediately after iTBS 3 (T5-T6; 51.3 ± 10.6 μV, p < 0.001) which remained elevated (T5-T7; 81.7 ± 13.3 μV, p < 0.001). Overall there was a significant increase in MEP after this 3-session protocol that remained elevated after iTBS 3 (T1-T7; 98.5 ± 15.5 μV p < 0.001). Full output of the model and relevant comparisons are present in the supplementary data. Summary: This study demonstrates that, in a cohort of 12 NHPs, 600 pulses of intermittent TBS reliably increases motor evoked potential - providing an important translational bridge between electrophysiological studies in rodents and applied studies in humans. The NHPs in this study were all sedated (which limits the direct translational impact to humans). This is also an important strength, however, as it reveals that in a controlled brain state 600 pulses of iTBS reliably increases cortical excitability. This is consistent with an observation by Papazachariadis and colleagues (2014) that 600 pulses of iTBS can increase somatosensory evoked potentials as well as the power of theta and gamma oscillations in sedated NHPs [[10]Papazachariadis O. Dante V. Verschure P.F. Del Giudice P. Ferraina S. iTBS-induced LTP-like plasticity parallels oscillatory activity changes in the primary sensory and motor areas of macaque monkeys.PLoS One. 2014 Nov 10; 9e112504https://doi.org/10.1371/journal.pone.0112504Crossref PubMed Scopus (15) Google Scholar]. Additionally, our data suggest that iTBS may display metaplasticity properties, wherein the threshold, direction, and magnitude of change is influenced/primed by previous sessions [[6]Abraham W.C. Bear M.F. Metaplasticity: the plasticity of synaptic plasticity.Trends Neurosci. 1996; 19: 126-130https://doi.org/10.1016/S0166-2236(96)80018-XAbstract Full Text PDF PubMed Scopus (1185) Google Scholar]. This adds to a growing body of research demonstrating the impact of priming on TBS-induced cortical excitability change [7Goldsworthy M.R. Pitcher J.B. Ridding M.C. The application of spaced theta burst protocols induces long-lasting neuroplastic changes in the human motor cortex.Eur J Neurosci. 2012; 35: 125-134https://doi.org/10.1111/j.1460-9568.2011.07924.xCrossref PubMed Scopus (107) Google Scholar, 8Todd G. Flavel S.C. Ridding M.C. Priming theta-burst repetitive transcranial magnetic stimulation with low- and high-frequency stimulation.Exp Brain Res. 2009; 195: 307-315https://doi.org/10.1007/s00221-009-1791-8Crossref PubMed Scopus (61) Google Scholar, 9Tse N.Y. Goldsworthy M.R. Ridding M.C. Coxon J.P. Fitzgerald P.B. Fornito A. Rogasch N.C. The effect of stimulation interval on plasticity following repeated blocks of intermittent theta burst stimulation.Sci Rep. 2018 Jun 4; 8 (1-0)https://doi.org/10.1038/s41598-018-26791-wCrossref Scopus (37) Google Scholar]. The details of the timecourse, however, will need to be clarified in future experiments. We acknowledge barriers that limit generalizability of this NHP model to human literature. The most potent is likely the use of sedation in these animals. The controlled state of the animal, however, led to low variability in MEPs - supporting the suggestion that variability in “brain state” may be one of the most influential factors contributing to TBS variability in human subjects. As with all science, the results of this study are limited to the specific protocol tested in this study. We believe that data from these 12 NHPs adds a valuable and complementary contribution to our knowledge regarding the ability of iTBS to increase cortical excitability when animals are in a controlled brain state. Colleen A. Hanlon: Conceptualization, Methodology, Investigation, Formal analysis, Writing, Visualization, Resources, Project administration. Paul W. Czoty: Conceptualization, Methodology, Investigation, Formal analysis, Writing – reviewing & editing, Resources. Hilary Smith: Conceptualization, Methodology, Investigation, Writing. Phillip Epperly: Conceptualization, Methodology, Investigation, Animal Care. Lindsey Galbo: Conceptualization, Methodology, Investigation, Animal Care. Miracle Collier: Study execution, animal care, data analysis. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests Dr. Hanlon has previously served as a consultant to the Roswell Park Cancer Institute, Brainsway, Inc, and Welcony-Magstim. None of these entities were involved in the conceptualization, design, execution, or data analysis for this project. She has received research support from the National Institute of Health (NIH) . Dr. Czoty has received research support from the NIH . Other authors declare no potential conflict of interest. This research as supported by the National Institute on Alcohol and Alcoholism ( P50AA026117 , T32AA007565 ). We would like to thank Alexander Opitz Ph.D.& Ivan Alekseichuk Ph.D. at University of Minnesota for providing us with a head model of the NHP template brain that is compatible with SIMNIBS. The following is the Supplementary data to this article: Download .docx (.06 MB) Help with docx files Multimedia component 1

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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)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.112
GPT teacher head0.381
Teacher spread0.269 · 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 designSimulation or modeling
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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Citations5
Published2022
Admission routes1
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