The rt-TEP tool: real-time visualization of TMS-Evoked Potential to maximize cortical activation and minimize artifacts

Mapping cortical excitability in the human dorsolateral prefrontal cortex

BACKGROUND

Transcranial magnetic stimulation (TMS) to the dorsolateral prefrontal cortex (dlPFC) is an effective treatment for depression, but the neural effects after TMS remains unclear. TMS paired with electroencephalography (TMS-EEG) can causally probe these neural effects. Nonetheless, variability in single pulse TMS-evoked potentials (TEPs) across dlPFC subregions, and potential artifact induced by muscle activation, necessitate detailed mapping for accurate treatment monitoring.

OBJECTIVE

To characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and specifically that conditions with larger muscle artifact may exhibit lower observed EL-TEPs due to over-rejection during preprocessing. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach.

METHODS

In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses.

RESULTS

Stimulation location significantly influenced observed EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%.

SIGNIFICANCE

EL-TEPs can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols.

Transcranial magnetic stimulation of primary motor cortex elicits an immediate transcranial evoked potential

BACKGROUND

Transcranial evoked potentials (TEPs) measured via electroencephalography (EEG) are widely used to study the cortical responses to transcranial magnetic stimulation (TMS). Immediate transcranial evoked potentials (i-TEPs) have been obscured by pulse and muscular artifacts. Thus, the TEP peaks that are commonly reported have latencies that are too long to be caused by direct excitation of cortical neurons.

METHODS

In 25 healthy individuals, we recorded i-TEPs evoked by a single biphasic TMS pulse targeting the primary motor hand area (M1HAND) or parietal or midline control sites. Sampling EEG at 50 kHz enabled us to reduce the duration of the TMS pulse artifact to a few milliseconds, while minor adjustments of the TMS coil tilt or position enabled us to avoid cranial muscular twitches during the experiment.

RESULTS

We observed an early positive EEG deflection starting after approx. 2 ms followed by a series of superimposed peaks with an inter-peak interval of ∼1.1-1.4 ms in multiple electrodes surrounding the stimulated sensorimotor region. This multi-peak i-TEP response was only evoked by TMS of the M1HAND region and was modified by changes in stimulation intensity and current direction.

DISCUSSION

Single-pulse TMS of the M1HAND evokes an immediate local multi-peak response at the cortical site of stimulation. Our results suggest that the observed i-TEP patterns are genuine cortical responses evoked by TMS caused by synchronized excitation of pyramidal neurons in the targeted precentral cortex. This notion needs to be corroborated in future studies, including further investigations into the potential contribution of instrumental or physiological artifacts.

Real-time optimization to enhance noninvasive cortical excitability assessment in the human dorsolateral prefrontal cortex

Objective

We currently lack a robust noninvasive method to measure prefrontal excitability in humans. Concurrent TMS and EEG in the prefrontal cortex is usually confounded by artifacts. Here we asked if real-time optimization could reduce artifacts and enhance a TMS-EEG measure of left prefrontal excitability.

Methods

This closed-loop optimization procedure adjusts left dlPFC TMS coil location, angle, and intensity in real-time based on the EEG response to TMS. Our outcome measure was the left prefrontal early (20-60 ms) and local TMS-evoked potential (EL-TEP).

Results

In 18 healthy participants, this optimization of coil angle and brain target significantly reduced artifacts by 63% and, when combined with an increase in intensity, increased EL-TEP magnitude by 75% compared to a non-optimized approach.

Conclusions

Real-time optimization of TMS parameters during dlPFC stimulation can enhance the EL-TEP.

Significance

Enhancing our ability to measure prefrontal excitability is important for monitoring pathological states and treatment response.

Evoked oscillatory cortical activity during acute pain: Probing brain in pain by transcranial magnetic stimulation combined with electroencephalogram

Temporal dynamics of local cortical rhythms during acute pain remain largely unknown. The current study used a novel approach based on transcranial magnetic stimulation combined with electroencephalogram (TMS-EEG) to investigate evoked-oscillatory cortical activity during acute pain. Motor (M1) and dorsolateral prefrontal cortex (DLPFC) were probed by TMS, respectively, to record oscillatory power (event-related spectral perturbation and relative spectral power) and phase synchronization (inter-trial coherence) by 63 EEG channels during experimentally induced acute heat pain in 24 healthy participants. TMS-EEG was recorded before, during, and after noxious heat (acute pain condition) and non-noxious warm (Control condition), delivered in a randomized sequence. The main frequency bands (α, β1, and β2) of TMS-evoked potentials after M1 and DLPFC stimulation were recorded close to the TMS coil and remotely. Cold and heat pain thresholds were measured before TMS-EEG. Over M1, acute pain decreased α-band oscillatory power locally and α-band phase synchronization remotely in parietal-occipital clusters compared with non-noxious warm (all p < .05). The remote (parietal-occipital) decrease in α-band phase synchronization during acute pain correlated with the cold (p = .001) and heat pain thresholds (p = .023) and to local (M1) α-band oscillatory power decrease (p = .024). Over DLPFC, acute pain only decreased β1-band power locally compared with non-noxious warm (p = .015). Thus, evoked-oscillatory cortical activity to M1 stimulation is reduced by acute pain in central and parietal-occipital regions and correlated with pain sensitivity, in contrast to DLPFC, which had only local effects. This finding expands the significance of α and β band oscillations and may have relevance for pain therapies.

Thalamic feedback shapes brain responses evoked by cortical stimulation in mice and humans

Cortical stimulation with single pulses is a common technique in clinical practice and research. However, we still do not understand the extent to which it engages subcortical circuits which contribute to the associated evoked potentials (EPs). Here we find that cortical stimulation generates remarkably similar EPs in humans and mice, with a late component similarly modulated by the subject's behavioral state. We optogenetically dissect the underlying circuit in mice, demonstrating that the late component of these EPs is caused by a thalamic hyperpolarization and rebound. The magnitude of this late component correlates with the bursting frequency and synchronicity of thalamic neurons, modulated by the subject's behavioral state. A simulation of the thalamo-cortical circuit highlights that both intrinsic thalamic currents as well as cortical and thalamic GABAergic neurons contribute to this response profile. We conclude that the cortical stimulation engages cortico-thalamo-cortical circuits highly preserved across different species and stimulation modalities.

Reliability of the TMS-evoked potential in dorsolateral prefrontal cortex

We currently lack a reliable method to probe cortical excitability noninvasively from the human dorsolateral prefrontal cortex (dlPFC). We recently found that the strength of early and local dlPFC transcranial magnetic stimulation (TMS)-evoked potentials (EL-TEPs) varied widely across dlPFC subregions. Despite these differences in response amplitude, reliability at each target is unknown. Here we quantified within-session reliability of dlPFC EL-TEPs after TMS to six left dlPFC subregions in 15 healthy subjects. We evaluated reliability (concordance correlation coefficient [CCC]) across targets, time windows, quantification methods, regions of interest, sensor- vs. source-space, and number of trials. On average, the medial target was most reliable (CCC = 0.78) and the most anterior target was least reliable (CCC = 0.24). However, all targets except the most anterior were reliable (CCC > 0.7) using at least one combination of the analytical parameters tested. Longer (20 to 60 ms) and later (30 to 60 ms) windows increased reliability compared to earlier and shorter windows. Reliable EL-TEPs (CCC up to 0.86) were observed using only 25 TMS trials at a medial dlPFC target. Overall, medial dlPFC targeting, wider windows, and peak-to-peak quantification improved reliability. With careful selection of target and analytic parameters, highly reliable EL-TEPs can be extracted from the dlPFC after only a small number of trials.

Changes in Cortical Activation by Transcranial Magnetic Stimulation Due to Coil Rotation Are Not Attributable to Cranial Muscle Activation

Transcranial magnetic stimulation coupled with electroencephalography (TMS-EEG) allows for the study of brain dynamics in health and disease. Cranial muscle activation can decrease the interpretability of TMS-EEG signals by masking genuine EEG responses and increasing the reliance on preprocessing methods but can be at least partly prevented by coil rotation coupled with the online monitoring of signals; however, the extent to which changing coil rotation may affect TMS-EEG signals is not fully understood. Our objective was to compare TMS-EEG data obtained with an optimal coil rotation to induce motor evoked potentials (M1standard) while rotating the coil to minimize cranial muscle activation (M1emg). TMS-evoked potentials (TEPs), TMS-related spectral perturbation (TRSP), and intertrial phase clustering (ITPC) were calculated in both conditions using two different preprocessing pipelines based on independent component analysis (ICA) or signal-space projection with source-informed reconstruction (SSP-SIR). Comparisons were performed with cluster-based correction. The concordance correlation coefficient was computed to measure the similarity between M1standard and M1emg TMS-EEG signals. TEPs, TRSP, and ITPC were significantly larger in M1standard than in M1emg conditions; a lower CCC than expected was also found. These results were similar across the preprocessing pipelines. While rotating the coil may be advantageous to reduce cranial muscle activation, it may result in changes in TMS-EEG signals; therefore, this solution should be tailored to the specific experimental context.

Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state

The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.

Unconsciousness or unresponsiveness in akinetic mutism? Insights from a multimodal longitudinal exploration

The clinical assessment of patients with disorders of consciousness (DoC) relies on the observation of behavioural responses to standardised sensory stimulation. However, several medical comorbidities may directly impair the production of reproducible and appropriate responses, thus reducing the sensitivity of behaviour-based diagnoses. One such comorbidity is akinetic mutism (AM), a rare neurological syndrome characterised by the inability to initiate volitional motor responses, sometimes associated with clinical presentations that overlap with those of DoC. In this paper, we describe the case of a patient with large bilateral mesial frontal lesions, showing prolonged behavioural unresponsiveness and severe disorganisation of electroencephalographic (EEG) background, compatible with a vegetative state/unresponsive wakefulness syndrome (VS/UWS). By applying an unprecedented multimodal battery of advanced imaging and electrophysiology-based techniques (AIE) encompassing spontaneous EEG, evoked potentials, event-related potentials, transcranial magnetic stimulation combined with EEG and structural and functional MRI, we provide the following: (i) a demonstration of the preservation of consciousness despite unresponsiveness in the context of AM, (ii) a plausible neurophysiological explanation for behavioural unresponsiveness and its subsequent recovery during rehabilitation stay and (iii) novel insights into the relationships between DoC, AM and parkinsonism. The present case offers proof-of-principle evidence supporting the clinical utility of a multimodal hierarchical workflow that combines AIEs to detect covert signs of consciousness in unresponsive patients.

Evoked EEG Responses to TMS Targeting Regions Outside the Primary Motor Cortex and Their Test-Retest Reliability

Transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) potentials (TEPs) provide unique insights into cortical excitability and connectivity. However, confounding EEG signals from auditory and somatosensory co-stimulation complicate TEP interpretation. Our optimized sham procedure established with TMS of primary motor cortex (Gordon in JAMA 245:118708, 2021) differentiates direct cortical EEG responses to TMS from those caused by peripheral sensory inputs. Using this approach, this study aimed to investigate TEPs and their test-retest reliability when targeting regions outside the primary motor cortex, specifically the left angular gyrus, supplementary motor area, and medial prefrontal cortex. We conducted three identical TMS-EEG sessions one week apart involving 24 healthy participants. In each session, we targeted the three areas separately using a figure-of-eight TMS coil for active TMS, while a second coil away from the head produced auditory input for sham TMS. Masking noise and electric scalp stimulation were applied in both conditions to achieve matched EEG responses to peripheral sensory inputs. High test-retest reliability was observed in both conditions. However, reliability declined for the 'cleaned' TEPs, resulting from the subtraction of evoked EEG response to the sham TMS from those to the active, particularly for latencies > 100 ms following the TMS pulse. Significant EEG differences were found between active and sham TMS at latencies < 90 ms for all targeted areas, exhibiting distinct spatiotemporal characteristics specific to each target. In conclusion, our optimized sham procedure effectively reveals EEG responses to direct cortical activation by TMS in brain areas outside primary motor cortex. Moreover, we demonstrate the impact of peripheral sensory inputs on test-retest reliability of TMS-EEG responses.

Cleaning up the Brickyard: How Theory and Methodology Shape Experiments in Cognitive Neuroscience of Language

The capacity for language is a defining property of our species, yet despite decades of research, evidence on its neural basis is still mixed and a generalized consensus is difficult to achieve. We suggest that this is partly caused by researchers defining "language" in different ways, with focus on a wide range of phenomena, properties, and levels of investigation. Accordingly, there is very little agreement among cognitive neuroscientists of language on the operationalization of fundamental concepts to be investigated in neuroscientific experiments. Here, we review chains of derivation in the cognitive neuroscience of language, focusing on how the hypothesis under consideration is defined by a combination of theoretical and methodological assumptions. We first attempt to disentangle the complex relationship between linguistics, psychology, and neuroscience in the field. Next, we focus on how conclusions that can be drawn from any experiment are inherently constrained by auxiliary assumptions, both theoretical and methodological, on which the validity of conclusions drawn rests. These issues are discussed in the context of classical experimental manipulations as well as study designs that employ novel approaches such as naturalistic stimuli and computational modeling. We conclude by proposing that a highly interdisciplinary field such as the cognitive neuroscience of language requires researchers to form explicit statements concerning the theoretical definitions, methodological choices, and other constraining factors involved in their work.

Common Data Elements for Disorders of Consciousness: Recommendations from the Electrophysiology Working Group

BACKGROUND

Electroencephalography (EEG) has long been recognized as an important tool in the investigation of disorders of consciousness (DoC). From inspection of the raw EEG to the implementation of quantitative EEG, and more recently in the use of perturbed EEG, it is paramount to providing accurate diagnostic and prognostic information in the care of patients with DoC. However, a nomenclature for variables that establishes a convention for naming, defining, and structuring data for clinical research variables currently is lacking. As such, the Neurocritical Care Society's Curing Coma Campaign convened nine working groups composed of experts in the field to construct common data elements (CDEs) to provide recommendations for DoC, with the main goal of facilitating data collection and standardization of reporting. This article summarizes the recommendations of the electrophysiology DoC working group.

METHODS

After assessing previously published pertinent CDEs, we developed new CDEs and categorized them into "disease core," "basic," "supplemental," and "exploratory." Key EEG design elements, defined as concepts that pertained to a methodological parameter relevant to the acquisition, processing, or analysis of data, were also included but were not classified as CDEs.

RESULTS

After identifying existing pertinent CDEs and developing novel CDEs for electrophysiology in DoC, variables were organized into a framework based on the two primary categories of resting state EEG and perturbed EEG. Using this categorical framework, two case report forms were generated by the working group.

CONCLUSIONS

Adherence to the recommendations outlined by the electrophysiology working group in the resting state EEG and perturbed EEG case report forms will facilitate data collection and sharing in DoC research on an international level. In turn, this will allow for more informed and reliable comparison of results across studies, facilitating further advancement in the realm of DoC research.

Somatosensory input in the context of transcranial magnetic stimulation coupled with electroencephalography: An evidence-based overview

The transcranial evoked potential (TEP) is a powerful technique to investigate brain dynamics, but some methodological issues limit its interpretation. A possible contamination of the TEP by electroencephalographic (EEG) responses evoked by the somatosensory input generated by transcranial magnetic stimulation (TMS) has been postulated; nonetheless, a characterization of these responses is lacking. The aim of this work was to review current evidence about possible somatosensory evoked potentials (SEP) induced by sources of somatosensory input in the craniofacial region. Among these, only contraction of craniofacial muscle and stimulation of free cutaneous nerve endings may be able to induce EEG responses, but direct evidence is lacking due to experimental difficulties in isolating these inputs. Notably, EEG evoked activity in this context is represented by a N100/P200 complex, reflecting a saliency-related multimodal response, rather than specific activation of the primary somatosensory cortex. Strategies to minimize or remove these responses by EEG processing still yield uncertain results; therefore, data inspection is of paramount importance to judge a possible contamination of the TEP by multimodal potentials caused by somatosensory input.

Mapping cortical excitability in the human dorsolateral prefrontal cortex

Objective

To characterize early TEPs anatomically and temporally (20-50 ms) close to the TMS pulse (EL-TEPs), as well as associated muscle artifacts (<20 ms), across the dlPFC. We hypothesized that TMS location and angle influence EL-TEPs, and that EL-TEP amplitude is inversely related to muscle artifact. Additionally, we sought to determine an optimal group-level TMS target and angle, while investigating the potential benefits of a personalized approach.

Methods

In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses.

Results

Stimulation location significantly influenced EL-TEPs, with posterior and medial targets yielding larger EL-TEPs. Regions with high EL-TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger EL-TEP responses compared to other dlPFC targets. Optimal dlPFC target differed across subjects, suggesting that a personalized targeting approach might boost the EL-TEP by an additional 36%.

Significance

Early local TMS-evoked potentials (EL-TEPs) can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. The identification of an optimal group-level target and the potential for further refinement through personalized targeting hold significant implications for optimizing depression treatment protocols.

Highlights

Early local TMS-evoked potentials (EL-TEPs) varied significantly across the dlPFC as a function of TMS target.TMS targets with less muscle artifact had significantly larger EL-TEPs.Selection of a postero-medial target increased EL-TEPs by 102% compared to anterior targets.

A three-dimensional adaptive rational interpolation algorithm for removing TMS-EEG pulse artifacts

Objective.Transcranial magnetic stimulation in combination with electroencephalography (TMS-EEG) has been widely used to study the reactivity and connectivity of brain regions. In order to efficiently and fast solve the pulse artifacts problem caused by TMS electromagnetic pulses, a three-dimensional adaptive rational quadratic Hermite interpolation algorithm is proposed.Approach.Firstly, a three-dimensional signal matrix is obtained by a signal recombination algorithm, where the removed window is automatically obtained by a derivative threshold. Secondly, the adaptive rational quartic Hermite interpolation algorithm is used to interpolate the removed window. Finally, the performance of the algorithm is verified using simulated and public database data.Main results.The simulation results show that the proposed algorithm improves the SNR by 23.88%-47.60%, reduces the RMSE by 46.52%-81.11%, reduces the average MAE by 47.83%-58.33%, and reduces the time consumption of the proposed algorithm by 45.90% compared with the piecewise cubic Hermite interpolation algorithm.Significance.Therefore, TMS-EEG pulse artifacts can be removed effectively and quickly with the proposed algorithm.

Acute pain drives different effects on local and global cortical excitability in motor and prefrontal areas: insights into interregional and interpersonal differences in pain processing

Pain-related depression of corticomotor excitability has been explored using transcranial magnetic stimulation-elicited motor-evoked potentials. Transcranial magnetic stimulation-electroencephalography now enables non-motor area cortical excitability assessments, offering novel insights into cortical excitability changes during pain states. Here, pain-related cortical excitability changes were explored in the dorsolateral prefrontal cortex and primary motor cortex (M1). Cortical excitability was recorded in 24 healthy participants before (Baseline), during painful heat (Acute Pain), and non-noxious warm (Warm) stimulation at the right forearm in a randomized sequence, followed by a pain-free stimulation measurement. Local cortical excitability was assessed as the peak-to-peak amplitude of early transcranial magnetic stimulation evoked potential, whereas global-mean field power measured the global excitability. Relative to the Baseline, Acute Pain decreased the peak-to-peak amplitude in M1 and dorsolateral prefrontal cortex compared with Warm (both P < 0.05). A reduced global-mean field power was only found in M1 during Acute Pain compared with Warm (P = 0.003). Participants with the largest reduction in local cortical excitability under Acute Pain showed a negative correlation between dorsolateral prefrontal cortex and M1 local cortical excitability (P = 0.006). Acute experimental pain drove differential pain-related effects on local and global cortical excitability changes in motor and non-motor areas at a group level while also revealing different interindividual patterns of cortical excitability changes, which can be explored when designing personalized treatment plans.

State-dependent effectiveness of cathodal transcranial direct current stimulation on cortical excitability

The extensive use of transcranial direct current stimulation (tDCS) in experimental and clinical settings does not correspond to an in-depth understanding of its underlying neurophysiological mechanisms. In previous studies, we employed an integrated system of Transcranial Magnetic Stimulation and Electroencephalography (TMS-EEG) to track the effect of tDCS on cortical excitability. At rest, anodal tDCS (a-tDCS) over the right Posterior Parietal Cortex (rPPC) elicits a widespread increase in cortical excitability. In contrast, cathodal tDCS (c-tDCS) fails to modulate cortical excitability, being indistinguishable from sham stimulation. Here we investigated whether an endogenous task-induced activation during stimulation might change this pattern, improving c-tDCS effectiveness in modulating cortical excitability. In Experiment 1, we tested whether performance in a Visuospatial Working Memory Task (VWMT) and a modified Posner Cueing Task (mPCT), involving rPPC, could be modulated by c-tDCS. Thirty-eight participants were involved in a two-session experiment receiving either c-tDCS or sham during tasks execution. In Experiment 2, we recruited sixteen novel participants who performed the same paradigm but underwent TMS-EEG recordings pre- and 10 min post- sham stimulation and c-tDCS. Behavioral results showed that c-tDCS significantly modulated mPCT performance compared to sham. At a neurophysiological level, c-tDCS significantly reduced cortical excitability in a frontoparietal network likely involved in task execution. Taken together, our results provide evidence of the state dependence of c-tDCS in modulating cortical excitability effectively. The conceptual and applicative implications are discussed.

Reliability and Validity of Transcranial Magnetic Stimulation-Electroencephalography Biomarkers

Noninvasive brain stimulation and neuroimaging have revolutionized human neuroscience with a multitude of applications, including diagnostic subtyping, treatment optimization, and relapse prediction. It is therefore particularly relevant to identify robust and clinically valuable brain biomarkers linking symptoms to their underlying neural mechanisms. Brain biomarkers must be reproducible (i.e., have internal reliability) across similar experiments within a laboratory and be generalizable (i.e., have external reliability) across experimental setups, laboratories, brain regions, and disease states. However, reliability (internal and external) is not alone sufficient; biomarkers also must have validity. Validity describes closeness to a true measure of the underlying neural signal or disease state. We propose that these metrics, reliability and validity, should be evaluated and optimized before any biomarker is used to inform treatment decisions. Here, we discuss these metrics with respect to causal brain connectivity biomarkers from coupling transcranial magnetic stimulation (TMS) with electroencephalography (EEG). We discuss controversies around TMS-EEG stemming from the multiple large off-target components (noise) and relatively weak genuine brain responses (signal), as is unfortunately often the case in noninvasive human neuroscience. We review the current state of TMS-EEG recordings, which consist of a mix of reliable noise and unreliable signal. We describe methods for evaluating TMS-EEG biomarkers, including how to assess internal and external reliability across facilities, cognitive states, brain networks, and disorders and how to validate these biomarkers using invasive neural recordings or treatment response. We provide recommendations to increase reliability and validity, discuss lessons learned, and suggest future directions for the field.

Pathway and directional specificity of Hebbian plasticity in the cortical visual motion processing network

Cortico-cortical paired associative stimulation (ccPAS), which repeatedly pairs single-pulse transcranial magnetic stimulation (TMS) over two distant brain regions, is thought to modulate synaptic plasticity. We explored its spatial selectivity (pathway and direction specificity) and its nature (oscillatory signature and perceptual consequences) when applied along the ascending (Forward) and descending (Backward) motion discrimination pathway. We found unspecific connectivity increases in bottom-up inputs in the low gamma band, probably reflecting visual task exposure. A clear distinction in information transfer occurred in the re-entrant alpha signals, which were only modulated by Backward-ccPAS, and predictive of visual improvements in healthy participants. These results suggest a causal involvement of the re-entrant MT-to-V1 low-frequency inputs in motion discrimination and integration in healthy participants. Modulating re-entrant input activity could provide single-subject prediction scenarios for visual recovery. Visual recovery might indeed partly rely on these residual inputs projecting to spared V1 neurons.

Motor potentials evoked by transcranial magnetic stimulation: interpreting a simple measure of a complex system

Transcranial magnetic stimulation (TMS) is a non-invasive technique that is increasingly used to study the human brain. One of the principal outcome measures is the motor-evoked potential (MEP) elicited in a muscle following TMS over the primary motor cortex (M1), where it is used to estimate changes in corticospinal excitability. However, multiple elements play a role in MEP generation, so even apparently simple measures such as peak-to-peak amplitude have a complex interpretation. Here, we summarize what is currently known regarding the neural pathways and circuits that contribute to the MEP and discuss the factors that should be considered when interpreting MEP amplitude measured at rest in the context of motor processing and patients with neurological conditions. In the last part of this work, we also discuss how emerging technological approaches can be combined with TMS to improve our understanding of neural substrates that can influence MEPs. Overall, this review aims to highlight the capabilities and limitations of TMS that are important to recognize when attempting to disentangle sources that contribute to the physiological state-related changes in corticomotor excitability.

Clinical diagnostic utility of transcranial magnetic stimulation in neurological disorders. Updated report of an IFCN committee

The review provides a comprehensive update (previous report: Chen R, Cros D, Curra A, Di Lazzaro V, Lefaucheur JP, Magistris MR, et al. The clinical diagnostic utility of transcranial magnetic stimulation: report of an IFCN committee. Clin Neurophysiol 2008;119(3):504-32) on clinical diagnostic utility of transcranial magnetic stimulation (TMS) in neurological diseases. Most TMS measures rely on stimulation of motor cortex and recording of motor evoked potentials. Paired-pulse TMS techniques, incorporating conventional amplitude-based and threshold tracking, have established clinical utility in neurodegenerative, movement, episodic (epilepsy, migraines), chronic pain and functional diseases. Cortical hyperexcitability has emerged as a diagnostic aid in amyotrophic lateral sclerosis. Single-pulse TMS measures are of utility in stroke, and myelopathy even in the absence of radiological changes. Short-latency afferent inhibition, related to central cholinergic transmission, is reduced in Alzheimer's disease. The triple stimulation technique (TST) may enhance diagnostic utility of conventional TMS measures to detect upper motor neuron involvement. The recording of motor evoked potentials can be used to perform functional mapping of the motor cortex or in preoperative assessment of eloquent brain regions before surgical resection of brain tumors. TMS exhibits utility in assessing lumbosacral/cervical nerve root function, especially in demyelinating neuropathies, and may be of utility in localizing the site of facial nerve palsies. TMS measures also have high sensitivity in detecting subclinical corticospinal lesions in multiple sclerosis. Abnormalities in central motor conduction time or TST correlate with motor impairment and disability in MS. Cerebellar stimulation may detect lesions in the cerebellum or cerebello-dentato-thalamo-motor cortical pathways. Combining TMS with electroencephalography, provides a novel method to measure parameters altered in neurological disorders, including cortical excitability, effective connectivity, and response complexity.

Measuring Consciousness in the Intensive Care Unit

Early reemergence of consciousness predicts long-term functional recovery for patients with severe brain injury. However, tools to reliably detect consciousness in the intensive care unit are lacking. Transcranial magnetic stimulation electroencephalography has the potential to detect consciousness in the intensive care unit, predict recovery, and prevent premature withdrawal of life-sustaining therapy.

TMS-EEG and resting-state EEG applied to altered states of consciousness: oscillations, complexity, and phenomenology

Exploring the neurobiology of the profound changes in consciousness induced by classical psychedelic drugs may require novel neuroimaging methods. Serotonergic psychedelic drugs such as psilocybin produce states of increased sensory-emotional awareness and arousal, accompanied by increased spontaneous electroencephalographic (EEG) signal diversity. By directly stimulating cortical tissue, the altered dynamics and propagation of the evoked EEG activity can reveal drug-induced changes in the overall brain state. We combine Transcranial Magnetic Stimulation (TMS) and EEG to reveal that psilocybin produces a state of increased chaotic brain activity which is not a result of altered complexity in the underlying causal interactions between brain regions. We also map the regional effects of psilocybin on TMS-evoked activity and identify changes in frontal brain structures that may be associated with the phenomenology of psychedelic experiences.

Natural Oscillatory Frequency Slowing in the Premotor Cortex of Early-Course Schizophrenia Patients: A TMS-EEG Study

Despite the heavy burden of schizophrenia, research on biomarkers associated with its early course is still ongoing. Single-pulse Transcranial Magnetic Stimulation coupled with electroencephalography (TMS-EEG) has revealed that the main oscillatory frequency (or "natural frequency") is reduced in several frontal brain areas, including the premotor cortex, of chronic patients with schizophrenia. However, no study has explored the natural frequency at the beginning of illness. Here, we used TMS-EEG to probe the intrinsic oscillatory properties of the left premotor cortex in early-course schizophrenia patients (<2 years from onset) and age/gender-matched healthy comparison subjects (HCs). State-of-the-art real-time monitoring of EEG responses to TMS and noise-masking procedures were employed to ensure data quality. We found that the natural frequency of the premotor cortex was significantly reduced in early-course schizophrenia compared to HCs. No correlation was found between the natural frequency and age, clinical symptom severity, or dose of antipsychotic medications at the time of TMS-EEG. This finding extends to early-course schizophrenia previous evidence in chronic patients and supports the hypothesis of a deficit in frontal cortical synchronization as a core mechanism underlying this disorder. Future work should further explore the putative role of frontal natural frequencies as early pathophysiological biomarkers for schizophrenia.

TMS combined with EEG: Recommendations and open issues for data collection and analysis

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.

Fast computational E-field dosimetry for transcranial magnetic stimulation using adaptive cross approximation and auxiliary dipole method (ACA-ADM)

Transcranial Magnetic Stimulation (TMS) is a non-invasive brain stimulation technique that uses a coil to induce an electric field (E-field) in the brain and modulate its activity. Many applications of TMS call for the repeated execution of E-field solvers to determine the E-field induced in the brain for different coil placements. However, the usage of solvers for these applications remains impractical because each coil placement requires the solution of a large linear system of equations. We develop a fast E-field solver that enables the rapid evaluation of the E-field distribution for a brain region of interest (ROI) for a large number of coil placements, which is achieved in two stages. First, during the pre-processing stage, the mapping between coil placement and brain ROI E-field distribution is approximated from E-field results for a few coil placements. Specifically, we discretize the mapping into a matrix with each column having the ROI E-field samples for a fixed coil placement. This matrix is approximated from a few of its rows and columns using adaptive cross approximation (ACA). The accuracy, efficiency, and applicability of the new ACA approach are determined by comparing its E-field predictions with analytical and standard solvers in spherical and MRI-derived head models. During the second stage, the E-field distribution in the brain ROI from a specific coil placement is determined by the obtained rows and columns in milliseconds. For many applications, only the E-field distribution for a comparatively small ROI is required. For example, the solver can complete the pre-processing stage in approximately 4 hours and determine the ROI E-field in approximately 40 ms for a 100 mm diameter ROI with less than 2% error enabling its use for neuro-navigation and other applications. Highlight: We developed a fast solver for TMS computational E-field dosimetry, which can determine the ROI E-field in approximately 40 ms for a 100 mm diameter ROI with less than 2% error.

Assessing awareness in severe Alzheimer's disease

There is an urgent need to understand the nature of awareness in people with severe Alzheimer's disease (AD) to ensure effective person-centered care. Objective biomarkers of awareness validated in other clinical groups (e.g., anesthesia, minimally conscious states) offer an opportunity to investigate awareness in people with severe AD. In this article we demonstrate the feasibility of using Transcranial magnetic stimulation (TMS) combined with EEG, event related potentials (ERPs) and fMRI to assess awareness in severe AD. TMS-EEG was performed in six healthy older controls and three people with severe AD. The perturbational complexity index (PCIST) was calculated as a measure of capacity for conscious awareness. People with severe AD demonstrated a PCIST around or below the threshold for consciousness, suggesting reduced capacity for consciousness. ERPs were recorded during a visual perception paradigm. In response to viewing faces, two patients with severe AD provisionally demonstrated similar visual awareness negativity to healthy controls. Using a validated fMRI movie-viewing task, independent component analysis in two healthy controls and one patient with severe AD revealed activation in auditory, visual and fronto-parietal networks. Activation patterns in fronto-parietal networks did not significantly correlate between the patient and controls, suggesting potential differences in conscious awareness and engagement with the movie. Although methodological issues remain, these results demonstrate the feasibility of using objective measures of awareness in severe AD. We raise a number of challenges and research questions that should be addressed using these biomarkers of awareness in future studies to improve understanding and care for people with severe AD.

PerBrain: a multimodal approach to personalized tracking of evolving state-of-consciousness in brain-injured patients: protocol of an international, multicentric, observational study

BACKGROUND

Disorders of consciousness (DoC) are severe neurological conditions in which consciousness is impaired to various degrees. They are caused by injury or malfunction of neural systems regulating arousal and awareness. Over the last decades, major efforts in improving and individualizing diagnostic and prognostic accuracy for patients affected by DoC have been made, mainly focusing on introducing multimodal assessments to complement behavioral examination. The present EU-funded multicentric research project "PerBrain" is aimed at developing an individualized diagnostic hierarchical pathway guided by both behavior and multimodal neurodiagnostics for DoC patients.

METHODS

In this project, each enrolled patient undergoes repetitive behavioral, clinical, and neurodiagnostic assessments according to a patient-tailored multi-layer workflow. Multimodal diagnostic acquisitions using state-of-the-art techniques at different stages of the patients' clinical evolution are performed. The techniques applied comprise well-established behavioral scales, innovative neurophysiological techniques (such as quantitative electroencephalography and transcranial magnetic stimulation combined with electroencephalography), structural and resting-state functional magnetic resonance imaging, and measurements of physiological activity (i.e. nasal airflow respiration). In addition, the well-being and treatment decision attitudes of patients' informal caregivers (primarily family members) are investigated. Patient and caregiver assessments are performed at multiple time points within one year after acquired brain injury, starting at the acute disease phase.

DISCUSSION

Accurate classification and outcome prediction of DoC are of crucial importance for affected patients as well as their caregivers, as individual rehabilitation strategies and treatment decisions are critically dependent on the latter. The PerBrain project aims at optimizing individual DoC diagnosis and accuracy of outcome prediction by integrating data from the suggested multimodal examination methods into a personalized hierarchical diagnosis and prognosis procedure. Using the parallel tracking of both patients' neurological status and their caregivers' mental situation, well-being, and treatment decision attitudes from the acute to the chronic phase of the disease and across different countries, this project aims at significantly contributing to the current clinical routine of DoC patients and their family members.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT04798456 . Registered 15 March 2021 - Retrospectively registered.

The role of neuronavigation in TMS-EEG studies: current applications and future perspectives

Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) allows measuring non-invasively the electrical response of the human cerebral cortex to a direct perturbation. Complementing TMS-EEG with a structural neuronavigation tool (nTMS-EEG) is key for accurately selecting cortical areas, targeting them, and adjusting the stimulation parameters based on some relevant anatomical priors. This step, together with the employment of visualization tools designed to perform a quality check of TMS-evoked potentials (TEPs) in real-time during acquisition, is key for maximizing the impact of the TMS pulse on the cortex and in ensuring highly reproducible measurements within sessions and across subjects. Moreover, storing stimulation parameters in the neuronavigation system can help in reproducing the stimulation parameters within and across experimental sessions and sharing them across research centers. Finally, the systematic employment of neuronavigation in TMS-EEG studies is also key to standardize measurements in clinical populations in search for reliable diagnostic and prognostic TMS-EEG-based biomarkers for neurological and psychiatric disorders.

Physiological symmetry of transcranial magnetic stimulation-evoked EEG spectral features

Transcranial magnetic stimulation (TMS)-evoked EEG potentials (TEPs) have been used to study the excitability of different cortical areas (CAs) in humans. Characterising the interhemispheric symmetry of TMS-EEG may provide further understanding of structure-function association in physiological and pathological conditions. We hypothesise that, in keeping with the underlying cytoarchitectonics, TEPs in contralateral homologous CAs share similar, symmetric spectral features, whilst ipsilateral TEPs from different CAs diverge in their waveshape and frequency content. We performed single-pulse (<1 Hz) navigated monophasic TMS, combined with high-density EEG with active electrodes, in 10 healthy participants. We targeted two bilateral CAs: premotor and motor. We compared frequency power bands, computed Pearson correlation coefficient (R) and Correlated Component Analysis (CorrCA) to detect divergences, as well as common components across TEPs. The main frequency of TEPs was faster in premotor than in motor CAs (p < .05) across all participants. Frequencies were not different between contralateral homologous CAs, whilst, despite closer proximity, there was a significant difference between ipsilateral premotor and motor CAs (p > .5), with frequency decreasing from anterior to posterior CAs. Correlation was high between contralateral homologous CAs and low between ipsilateral CAs. When applying CorrCA, specific components were shared by contralateral homologous TEPs. We show physiological symmetry of TEP spectral features between contralateral homologous CAs, whilst ipsilateral premotor and motor TEPs differ despite lower geometrical distance. Our findings support the role of TEPs as biomarker of local cortical properties and provide a first reference dataset for TMS-EEG studies in asymmetric brain disorders.

Local brain-state dependency of effective connectivity: a pilot TMS-EEG study

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.

Exploring the spatial resolution of TMS-EEG coupling on the sensorimotor region

The use of TMS-EEG coupling as a neuroimaging tool for the functional exploration of the human brain recently gained strong interest. If this tool directly inherits the fine temporal resolution from EEG, its spatial counterpart remains unknown. In this study, we explored the spatial resolution of TMS-EEG coupling by evaluating the minimal distance between two stimulated cortical sites that would significantly evoke different response dynamics. TMS evoked responses were mapped on the sensorimotor region in twenty participants. The stimulation grid was composed of nine targets separated between 10 and 15 mm on average. The dynamical signatures of TMS evoked activity were extracted and compared between sites using both local and remote linear regression scores and spatial generalized mixed models. We found a significant effect of the distance between stimulated sites on their dynamical signatures, neighboring sites showing differentiable response dynamics. Besides, common dynamical signatures were also found between sites up to 25-30 mm from each other. This overlap in dynamical properties decreased with distance and was stronger between sites within the same Brodmann area. Our results suggest that the spatial resolution of TMS-EEG coupling might be at least as high as 10 mm. Furthermore, our results reveal an anisotropic spatial resolution that was higher across than within the same Brodmann areas, in accordance with the TMS induced E-field modeling. Common cytoarchitectonic leading to shared dynamical properties within the same Brodmann area could also explain this anisotropy. Overall, these findings suggest that TMS-EEG benefits from the spatial resolution of TMS, which makes it an accurate technique for meso-scale brain mapping.

Identifying novel biomarkers with TMS-EEG - Methodological possibilities and challenges

Biomarkers are essential for understanding the underlying pathologies in brain disorders and for developing effective treatments. Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an emerging neurophysiological tool that can be used for biomarker development. This method can identify biomarkers associated with the function and dynamics of the inhibitory and excitatory neurotransmitter systems and effective connectivity between brain areas. In this review, we outline the current state of the TMS-EEG biomarker field by summarizing the existing protocols and the possibilities and challenges associated with this methodology.

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning

Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an explainable consciousness indicator (ECI) using deep learning to disentangle the components of consciousness. We employ electroencephalographic (EEG) responses to transcranial magnetic stimulation under various conditions, including sleep (n = 6), general anesthesia (n = 16), and severe brain injury (n = 34). We also test our framework using resting-state EEG under general anesthesia (n = 15) and severe brain injury (n = 34). ECI simultaneously quantifies arousal and awareness under physiological, pharmacological, and pathological conditions. Particularly, ketamine-induced anesthesia and rapid eye movement sleep with low arousal and high awareness are clearly distinguished from other states. In addition, parietal regions appear most relevant for quantifying arousal and awareness. This indicator provides insights into the neural correlates of altered states of consciousness.

The authors propose an explainable consciousness indicator using deep learning to quantify arousal and awareness under sleep, anesthesia, and in patients with disorders of consciousness.

Designing and comparing cleaning pipelines for TMS-EEG data: a theoretical overview and practical example

Combining transcranial magnetic stimulation (TMS) with electroencephalography (EEG) is growing in popularity as a method for probing the reactivity and connectivity of neural circuits in basic and clinical research. However, using EEG to measure the neural responses to TMS is challenging due to the unique artifacts introduced by combining the two techniques. In this paper, we overview the artifacts present in TMS-EEG data and the offline cleaning methods used to suppress these unwanted signals. We then describe how open science practices, including the development of open-source toolboxes designed for TMS-EEG analysis (e.g., TESA - the TMS-EEG signal analyser), have improved the availability and reproducibility of TMS-EEG cleaning methods. We provide theoretical and practical considerations for designing TMS-EEG cleaning pipelines and then give an example of how to compare different pipelines using TESA. We show that changing even a single step in a pipeline designed to suppress decay artifacts results in TMS-evoked potentials (TEPs) with small differences in amplitude and spatial topography. The variability in TEPs resulting from the choice of cleaning pipeline has important implications for comparing TMS-EEG findings between research groups which use different online and offline approaches. Finally, we discuss the challenges of validating cleaning pipelines and recommend that researchers compare outcomes from TMS-EEG experiments using multiple pipelines to ensure findings are not related to the choice of cleaning methods. We conclude that the continued improvement, availability, and validation of cleaning pipelines is essential to ensure TMS-EEG reaches its full potential as a method for studying human neurophysiology.

Closed-loop optimization of transcranial magnetic stimulation with electroencephalography feedback

Background

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.

Objective

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).

Methods

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.

Results

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.

Conclusion

Optimizing stimulation with EEG feedback in a closed-loop manner is feasible and enables effective coupling to brain activity.

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Closed-loop set-up for guiding TMS with brain activity feedback.

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Automatic stimulus orientation optimization based on TMS-evoked EEG responses.

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Adjusting TMS parameters electronically allows fast and effortless procedures.

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TMS-evoked EEG responses depend on the stimulus orientation.