Response to significant influence of static magnetic stimulation applied for 30 minutes over the human M1 on corticospinal excitability
Bibliographic record
Abstract
We are pleased that our recent attempt to replicate the methods and results from Dileone et al. [[1]Dileone M. Mordillo-Mateos L. Oliviero A. Foffani G. Long-lasting effects of transcranial static magnetic field stimulation on motor cortex excitability.Brain Stimulat. 2018 Aug; 11: 676-688Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar] has garnered attention from the authors of the original findings. Briefly, despite having a ∼99% probability of replicating the results from Dileone et al. [[1]Dileone M. Mordillo-Mateos L. Oliviero A. Foffani G. Long-lasting effects of transcranial static magnetic field stimulation on motor cortex excitability.Brain Stimulat. 2018 Aug; 11: 676-688Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar], our results revealed that transcranial static magnetic stimulation (tSMS) yielded neither significant (all uncorrected p values > 0.101) nor meaningful (effect size values below medium-sized benchmark values; all Cohen’s dz < 0.408) depression of corticospinal excitability (CSE) [[2]Hamel R. Fontaine É.D.L. Bernier P.-M. Lepage J.-F. Letter to the editor: No influence of static magnetic stimulation applied for 30 minutes over the human M1 on corticospinal excitability.Brain Stimul Basic Transl Clin Res Neuromodulation. 2020 May 1; 13: 594-596PubMed Scopus (2) Google Scholar], a finding also reported by another group using a smaller sample [[3]Kufner M. Brückner S. Kammer T. No modulatory effects by transcranial static magnetic field stimulation of human motor and somatosensory cortex.Brain Stimulat. 2017 Jun; 10: 703-710Abstract Full Text Full Text PDF PubMed Scopus (17) Google Scholar]. Upon re-analysis of our data set, the authors reached the conclusion that tSMS rather significantly depressed CSE, hence disputing our conclusion. However, we believe that several issues severely undermine the alternative conclusion reached by the authors. First, we believe that the outlined variability of motor-evoked potential (MEP) measurements stems from the intrinsic inherent variability of this complex electrophysiological read-out signal rather than to inadequate data acquisition procedures. As we initially reported, neuronavigation was used and 30 MEPs were measured per time point to respectively ensure the reliability of coil positioning and obtain representative averages of MEP amplitude (100% probability of falling within the average’s 95% confidence intervals [[4]Chang W.H. Fried P.J. Saxena S. Jannati A. Gomes-Osman J. Kim Y.-H. et al.Optimal number of pulses as outcome measures of neuronavigated transcranial magnetic stimulation.Clin Neurophysiol Off J Int Fed Clin Neurophysiol. 2016; 127: 2892-2897Crossref PubMed Scopus (59) Google Scholar]). Considered as two key means to improve the reliability of CSE assessment [[5]Guerra A. López-Alonso V. Cheeran B. Suppa A. Solutions for managing variability in non-invasive brain stimulation studies.Neurosci Lett. 2017 Dec 30; : 133332PubMed Google Scholar], we reasoned this would prevent post-hoc arbitrary data trimming, which can lead to circular analyses and double-dipping [[6]Kriegeskorte N. Simmons W.K. Bellgowan P.S.F. Baker C.I. Circular analysis in systems neuroscience: the dangers of double dipping.Nat Neurosci. 2009 May; 12: 535-540Crossref PubMed Scopus (1752) Google Scholar]. Namely, doing so can erroneously reduce data variability and inflate the effect size, thus giving the impression of increased statistical power [[7]Algermissen J. Mehler D.M.A. May the power be with you: are there highly powered studies in neuroscience, and how can we get more of them?.J Neurophysiol. 2018 01; 119: 2114-2117Crossref PubMed Scopus (18) Google Scholar]. In order to increase the reliability of conclusions in neuroscience, it is best advised to discourage such practice [[6]Kriegeskorte N. Simmons W.K. Bellgowan P.S.F. Baker C.I. Circular analysis in systems neuroscience: the dangers of double dipping.Nat Neurosci. 2009 May; 12: 535-540Crossref PubMed Scopus (1752) Google Scholar,[8]Makin T.R. Orban de Xivry J.-J. Ten common statistical mistakes to watch out for when writing or reviewing a manuscript.eLife. 2019 09; 8Crossref Scopus (49) Google Scholar]. Second, in their reply, the authors disregarded a standardized approach to analyze MEPs – an approach used in their original work [[1]Dileone M. Mordillo-Mateos L. Oliviero A. Foffani G. Long-lasting effects of transcranial static magnetic field stimulation on motor cortex excitability.Brain Stimulat. 2018 Aug; 11: 676-688Abstract Full Text Full Text PDF PubMed Scopus (28) Google Scholar] – and alternatively performed unwarranted analyses where parametric tests are conducted on log-transformed (or not) of median values or averages of median values. While the reasoning for such flexible and ill-justified analytical approaches can be debated, this practice increases the risk of reporting a false positive [[8]Makin T.R. Orban de Xivry J.-J. Ten common statistical mistakes to watch out for when writing or reviewing a manuscript.eLife. 2019 09; 8Crossref Scopus (49) Google Scholar]. Third, if we adhere to the statistical approach taken by Dileone and colleagues, we observe that the newfound results reached slightly above 50% of achieved statistical power. This level of power indicates that concluding that tSMS significantly depressed CSE has a high (∼50%) probability of being based on false positives [[8]Makin T.R. Orban de Xivry J.-J. Ten common statistical mistakes to watch out for when writing or reviewing a manuscript.eLife. 2019 09; 8Crossref Scopus (49) Google Scholar]. These analyses were performed by first calculating the t-values from the inverse distribution of the reported p-values and the 17° of freedom (n = 18), which allowed to calculate Cohen’s dz values and achieved power. Specifically, for the paired t-test conducted on the average of the median values of all 6 post-measurements (not normalized MEP data), the achieved power was 51.4% (t(17) = 2.439, p = 0.026, Cohen’s dz = 0.575). Similarly, for the one-sample t-test conducted on the median values of all 6 post-measurements (normalized MEP data), the achieved power was 51.2% (t(17) = 2.181, p = 0.0435, Cohen’s dz = 0.514). Given the current replication crisis in neuroscience [[7]Algermissen J. Mehler D.M.A. May the power be with you: are there highly powered studies in neuroscience, and how can we get more of them?.J Neurophysiol. 2018 01; 119: 2114-2117Crossref PubMed Scopus (18) Google Scholar,[9]Szucs D. Ioannidis J.P.A. Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature.PLoS Biol. 2017; 15e2000797Crossref PubMed Scopus (265) Google Scholar], efforts must be promptly devoted to incorporate such considerations when interpreting results in order to increase the validity and reliability of scientific conclusions. To conclude, we believe that our initial conclusion that tSMS did neither yield a significant nor meaningful depressing effect on CSE is adequately supported by our data. As small studies (n ≤ 10) are more likely to report inflated effect sizes [[7]Algermissen J. Mehler D.M.A. May the power be with you: are there highly powered studies in neuroscience, and how can we get more of them?.J Neurophysiol. 2018 01; 119: 2114-2117Crossref PubMed Scopus (18) Google Scholar,[9]Szucs D. Ioannidis J.P.A. Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature.PLoS Biol. 2017; 15e2000797Crossref PubMed Scopus (265) Google Scholar], and that post-hoc and flexible statistical analysis bears an important risk of unwarranted conclusion [[6]Kriegeskorte N. Simmons W.K. Bellgowan P.S.F. Baker C.I. Circular analysis in systems neuroscience: the dangers of double dipping.Nat Neurosci. 2009 May; 12: 535-540Crossref PubMed Scopus (1752) Google Scholar,[8]Makin T.R. Orban de Xivry J.-J. Ten common statistical mistakes to watch out for when writing or reviewing a manuscript.eLife. 2019 09; 8Crossref Scopus (49) Google Scholar], studies with larger sample size (n ≥ 34; if a Cohen’s dz of 0.5 is considered as the smallest effect size of interest [[10]Lakens D. Equivalence tests: a practical primer for t tests, correlations, and meta-analyses.Soc Psychol Personal Sci. 2017 May; 8: 355-362Crossref PubMed Scopus (602) Google Scholar]; power = 80%, paired t-tests) will be needed to ascertain that tSMS effectively depresses CSE, and this, to a magnitude relevant to the field. The authors have no conflict of interest to declare. This work was funded by the Natural Sciences and Engineering Research Council of Canada (Grant number: RGPIN-2017-05510 ) and Fonds de la recherche du Québec -Santé (Grant number: 33140 ). Letter to the editor: No influence of static magnetic stimulation applied for 30 minutes over the human M1 on corticospinal excitabilityBrain Stimulation: Basic, Translational, and Clinical Research in NeuromodulationVol. 13Issue 3PreviewWe have read with great interest the article recently published by Dileone et al. (2018) [1] reporting that a 30-min application of transcranial static magnetic stimulation (tSMS) over the human primary motor cortex (M1) can yield long-lasting (∼30 min) inhibition of corticospinal excitability (CSE), an effect that is reminiscent of long-term depression plasticity. These results are exciting as they open the door for potential therapeutic applications of tSMS, especially since the technique is portable, inexpensive, and requires little training for its utilization. Full-Text PDF Open AccessSignificant influence of static magnetic field stimulation applied for 30 minutes over the human M1 on corticospinal excitabilityBrain Stimulation: Basic, Translational, and Clinical Research in NeuromodulationVol. 13Issue 3PreviewWe read with great interest the letter recently published by Hamel et al. reporting “no influence of static magnetic field stimulation applied for 30 minutes over the human M1 on corticospinal excitability” [1], as measured by motor evoked potentials (MEPs) elicited by single-pulse transcranial magnetic stimulation (TMS). First of all, we would like to thank the authors for their attempt to replicate some of our findings on the long-lasting effects of transcranial static magnetic field stimulation (tSMS) [2,6]. Full-Text PDF Open Access
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".