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Abstract The analysis of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS) is crucial in research and clinical medical practice. MEPs are characterized by their latency and the treatment of a single patient may require the characterization of thousands of MEPs. Given the difficulty of developing reliable and accurate algorithms, currently the assessment of MEPs is performed with visual inspection and manual annotation by a medical expert; making it a time-consuming, inaccurate, and error-prone process. In this study, we developed DELMEP, a deep learning-based algorithm to automate the estimation of MEP latency. Our algorithm resulted in a mean absolute error of about 0.5 ms and an accuracy that was practically independent of the MEP amplitude. The low computational cost of the DELMEP algorithm allows employing it in on-the-fly characterization of MEPs for brain-state-dependent and closed-loop brain stimulation protocols. Moreover, its learning ability makes it a particularly promising option for artificial-intelligence-based personalized clinical applications.

Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS−EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS−EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS−EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS−EEG covered all aspects that should be considered in TMS−EEG experiments, providing methodological recommendations (when possible) for effective TMS−EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS−EEG methodology and thus may promote standardization of experimental and computational procedures across groups.

Background Spontaneous cortical oscillations have been shown to modulate cortical responses to transcranial magnetic stimulation (TMS). However, whether these oscillations influence cortical effective connectivity is largely unknown. We conducted a pilot study to set the basis for addressing how spontaneous oscillations affect cortical effective connectivity measured through TMS-evoked potentials (TEPs). Methods We applied TMS to the left primary motor cortex and right pre-supplementary motor area of three subjects while recording EEG. We classified trials off-line into positive- and negative-phase classes according to the mu and beta rhythms. We calculated differences in the global mean-field amplitude (GMFA) and compared the cortical spreading of the TMS-evoked activity between the two classes. Results Phase affected the GMFA in four out of 12 datasets (3 subjects × 2 stimulation sites × 2 frequency bands). Two of the observed significant intervals were before 50 ms, two between 50 and 100 ms, and one after 100 ms post-stimulus. Source estimates showed complex spatial differences between the classes in the cortical spreading of the TMS-evoked activity. Conclusions TMS-evoked effective connectivity seems to depend on the phase of local cortical oscillations at the stimulated site. This work paves the way to design future closed-loop stimulation paradigms.

Coregistration of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows non-invasive probing of brain circuits: TMS induces brain activation due to the generation of a properly oriented focused electric field (E-field) using a coil placed on a selected position over the scalp, while EEG captures the effects of the stimulation on brain electrical activity. Moreover, the combination of these techniques allows the investigation of several brain properties, including brain functional connectivity. The choice of E-field parameters, such as intensity, orientation, and position, is crucial for eliciting cortex-specific effects. Here, we evaluated whether and how the spatial pattern, i.e., topography and strength of functional connectivity, is modulated by the stimulus orientation. We systematically altered the E-field orientation when stimulating the left pre-supplementary motor area and showed an increase of functional connectivity in areas associated with the primary motor cortex and an E-field orientation-specific modulation of functional connectivity intensity.

Besides stimulus intensities and interstimulus intervals (ISI), the electric field (E-field) orientation is known to affect both short-interval intracortical inhibition (SICI) and facilitation (SICF) in paired-pulse transcranial magnetic stimulation (TMS). However, it has yet to be established how distinct orientations of the conditioning (CS) and test stimuli (TS) affect the SICI and SICF generation. With the use of a multi-channel TMS transducer that provides electronic control of the stimulus orientation and intensity, we aimed to investigate how changes in the CS and TS orientation affect the strength of SICI and SICF. We hypothesized that the CS orientation would play a major role for SICF than for SICI, whereas the CS intensity would be more critical for SICI than for SICF. In eight healthy subjects, we tested two ISIs (1.5 and 2.7 ms), two CS and TS orientations (anteromedial (AM) and posteromedial (PM)), and four CS intensities (50, 70, 90, and 110% of the resting motor threshold (RMT)). The TS intensity was fixed at 110% RMT. The intensities were adjusted to the corresponding RMT in the AM and PM orientations. SICI and SICF were observed in all tested CS and TS orientations. SICI depended on the CS intensity in a U-shaped manner in any combination of the CS and TS orientations. With 70% and 90% RMT CS intensities, stronger PM-oriented CS induced stronger inhibition than weaker AM-oriented CS. Similar SICF was observed for any CS orientation. Neither SICI nor SICF depended on the TS orientation. We demonstrated that SICI and SICF could be elicited by the CS perpendicular to the TS, which indicates that these stimuli affected either overlapping or strongly connected neuronal populations. We concluded that SICI is primarily sensitive to the CS intensity and that CS intensity adjustment resulted in similar SICF for different CS orientations.

Paired associative stimulation (PAS) combines transcranial magnetic stimulation (TMS) and peripheral nerve stimulation (PNS) to induce plastic changes in the corticospinal tract. PAS employing single 0.2-Hz TMS pulses synchronized with the first pulse of 50-100 Hz PNS trains potentiates motor-evoked potentials (MEPs) in a stable manner in healthy participants and enhances voluntary motor output in spinal cord injury (SCI) patients. We further investigated the impact of settings of this PAS variant on MEP potentiation in healthy subjects. In experiment 1, we compared 0.2-Hz vs 0.4-Hz PAS. In experiment 2, PNS frequencies of 100 Hz, 200 Hz, and 400 Hz were compared. In experiment 3, we added a second TMS pulse. When compared with 0.4-Hz PAS, 0.2-Hz PAS was significantly more effective after 30 minutes (p = 0.05) and 60 minutes (p = 0.014). MEP potentiation by PAS with 100-Hz and 200-Hz PNS did not differ. PAS with 400-Hz PNS was less effective than 100-Hz (p = 0.023) and 200-Hz (p = 0.013) PNS. Adding an extra TMS pulse rendered PAS strongly inhibitory. These negative findings demonstrate that the 0.2-Hz PAS with 100-Hz PNS previously used in clinical studies is optimal and the modifications employed here do not enhance its efficacy.

Neuromodulation technologies, such as transcranial magnetic stimulation (TMS), are promising tools for neurorehabilitation, aphasia therapy included, but not yet in common clinical use. Combined with behavioral techniques, in particular treatment-efficient Intensive Language-Action Therapy (ILAT, previously CIAT or CILT), TMS could substantially amplify the beneficial effect of such behavioral therapy alone (Thiel et al., 2013; Martin et al., 2014; Mendoza et al., 2016; Kapoor, 2017). In this randomized study of 17 subjects with post-stroke aphasia in the chronic stage, we studied the combined effect of ILAT and 1-Hz placebo-controlled navigated repetitive TMS (rTMS) to the right-hemispheric inferior frontal cortex—that is, to the anterior part of the non-dominant hemisphere's homolog Broca's area (pars triangularis). Patients were randomized to groups A and B. Patients in group A received a 2-week period of rTMS during naming training where they named pictures displayed on the screen once every 10 s, followed by 2 weeks of rTMS and naming combined with ILAT. Patients in group B received the same behavioral therapy but TMS was replaced by sham stimulation. The primary outcome measures for changes in language performance were the Western Aphasia Battery's aphasia quotient AQ; the secondary outcome measures were the Boston naming test (BNT) and the Action naming test (Action BNT, ANT). All subjects completed the study. At baseline, no statistically significant group differences were discovered for age, post-stroke time or diagnosis. ILAT was associated with significant improvement across groups, as documented by both primary and secondary outcome measures. No significant effect of rTMS could be documented. Our results agree with previous results proving ILAT's ability to improve language in patients with chronic aphasia. In contrast with earlier claims, however, a beneficial effect of rTMS in chronic post-stroke aphasia rehabilitation was not detected in this study.Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT03629665

BackgroundIn spinal paired associative stimulation (PAS), orthodromic and antidromic volleys elicited by transcranial magnetic stimulation (TMS) and peripheral nerve stimulation (PNS) coincide at corticomotoneuronal synapses at the spinal cord. The interstimulus interval (ISI) between TMS and PNS determines whether PAS leads to motor-evoked potential (MEP) potentiation or depression. PAS applied as a long-term treatment for neurological patients might alter conduction of neural fibers over time. Moreover, measurements of motoneuron conductance for determination of ISIs may be challenging in these patients.ResultsWe sought to design a PAS protocol to induce MEP potentiation at wide range of ISIs. We tested PAS consisting of high-intensity (100% SO) TMS and high-frequency (50 Hz) PNS in 5 subjects at 5 different ISIs. Our protocol induced potentiation of MEP amplitudes in all subjects at all tested intervals. TMS and PNS alone did not result in MEP potentiation. The variant of PAS protocol described here does not require exact adjustment of ISIs in order to achieve effective potentiation of MEPs. ConclusionsThis variant of PAS might be feasible as a long-term treatment in rehabilitation of neurological patients.

Objective. Stroke alters cortical excitability both in the lesioned and in the nonlesioned hemisphere. Stroke recovery has been studied using transcranial magnetic stimulation (TMS). Spontaneous brain oscillations and somatosensory evoked fields (SEFs) measured by magnetoencephalography (MEG) are modified in stroke patients during recovery. Methods. We recorded SEFs and spontaneous MEG activity and motor threshold (MT) short intracortical inhibition (SICI) and intracortical facilitation (ICF) with navigated TMS (nTMS) at one and three months after first-ever hemispheric ischemic strokes. Changes of MEG and nTMS parameters attributed to gamma-aminobutyrate and glutamate transmission were compared. Results. ICF correlated with the strength and extent of SEF source areas depicted by MEG at three months. The nTMS MT and event-related desynchronization (ERD) of beta-band MEG activity and SICI and the beta-band MEG event-related synchronization (ERS) were correlated, but less strongly. Conclusions. This first report using sequential nTMS and MEG in stroke recovery found intra- and interhemispheric correlations of nTMS and MEG estimates of cortical excitability. ICF and SEF parameters, MT and the ERD of the lesioned hemisphere, and SICI and ERS of the nonlesioned hemisphere were correlated. Covarying excitability in the lesioned and nonlesioned hemispheres emphasizes the importance of the hemispheric balance of the excitability of the sensorimotor system.

Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS−EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS−EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS−EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS−EEG covered all aspects that should be considered in TMS−EEG experiments, providing methodological recommendations (when possible) for effective TMS−EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS−EEG methodology and thus may promote standardization of experimental and computational procedures across groups. • TMS−EEG is a powerful technique for basic research and clinical applications. • The methodological combination of TMS−EEG is challenging. • The lack of standardization may affect reproducibility and limit the comparability of results produced across groups. • This article covers all aspects that should be considered in TMS−EEG experiments. • We provide methodological recommendations for effective TMS−EEG recordings and analysis. [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation (TMS) is widely used in brain research and treatment of various brain dysfunctions. However, the optimal way to target stimulation and administer TMS therapies, for example, where and in which electric field direction the stimuli should be given, is yet to be determined. To develop an automated closed-loop system for adjusting TMS parameters (in this work, the stimulus orientation) online based on TMS-evoked brain activity measured with electroencephalography (EEG). We developed an automated closed-loop TMS–EEG set-up. In this set-up, the stimulus parameters are electronically adjusted with multi-locus TMS. As a proof of concept, we developed an algorithm that automatically optimizes the stimulation orientation based on single-trial EEG responses. We applied the algorithm to determine the electric field orientation that maximizes the amplitude of the TMS–EEG responses. The validation of the algorithm was performed with six healthy volunteers, repeating the search twenty times for each subject. The validation demonstrated that the closed-loop control worked as desired despite the large variation in the single-trial EEG responses. We were often able to get close to the orientation that maximizes the EEG amplitude with only a few tens of pulses. Optimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity. • Closed-loop set-up for guiding TMS with brain activity feedback. • Automatic stimulus orientation optimization based on TMS-evoked EEG responses. • Adjusting TMS parameters electronically allows fast and effortless procedures. • TMS-evoked EEG responses depend on the stimulus orientation. [Display omitted] [ABSTRACT FROM AUTHOR]