State-dependent TMS effects in the visual cortex after visual adaptation : A combined TMS-EEG study

Objective: The impact of transcranial magnetic stimulation (TMS) has been shown to depend on the initial brain state of the stimulated cortical region. This observation has led to the development of paradigms that aim to enhance the specificity of TMS effects by using visual/luminance adaptation to modulate brain state prior to the application of TMS. However, the neural basis of interactions between TMS and adaptation is unknown. Here, we examined these interactions by using electroencephalography (EEG) to measure the impact of TMS over the visual cortex after luminance adaptation. Methods: Single-pulses of neuronavigated TMS (nTMS) were applied at two different intensities over the left visual cortex after adaptation to either high or low luminance. We then analyzed the effects of adaptation on the global and local cortical excitability. Results: The analysis revealed a significant interaction between the TMS-evoked responses and the adaptation condition. In particular, when nTMS was applied with high intensity, the evoked responses were larger after adaptation to high than low luminance.Conclusion: This result provides the first neural evidence on the interaction between TMS with visual adaptation. Significance: TMS can activate neurons differentially as a function of their adaptation state.(c) 2021 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Characterization of cochlear implant artifacts in electrically evoked auditory steady-state responses

AbstractObjectiveElectrically evoked auditory steady-state responses (EASSRs) are neural potentials measured in the electroencephalogram (EEG) in response to periodic pulse trains presented, for example, through a cochlear implant (CI). EASSRs could potentially be used for objective CI fitting. However, EEG signals are contaminated with electrical CI artifacts. In this paper, we characterized the CI artifacts for monopolar mode stimulation and evaluated at which pulse rate, linear interpolation over the signal part contaminated with CI artifact is successful.MethodsCI artifacts were characterized by means of their amplitude growth functions and duration.ResultsCI artifact durations were between 0.7 and 1.7ms, at contralateral recording electrodes. At ipsilateral recording electrodes, CI artifact durations are range from 0.7 to larger than 2ms.ConclusionAt contralateral recording electrodes, the artifact was shorter than the interpulse interval across subjects for 500pps, which was not always the case for 900pps.SignificanceCI artifact-free EASSRs are crucial for reliable CI fitting and neuroscience research. The CI artifact has been characterized and linear interpolation allows to remove it at contralateral recording electrodes for stimulation at 500pps

Automatic and robust noise suppression in EEG and MEG : The SOUND algorithm

Electroencephalography (EEG) and magnetoencephalography (MEG) often suffer from noise-and artifact-contaminated channels and trials. Conventionally, EEG and MEG data are inspected visually and cleaned accordingly, e.g., by identifying and rejecting the so-called "bad" channels. This approach has several shortcomings: data inspection is laborious, the rejection criteria are subjective, and the process does not fully utilize all the information in the collected data. Here, we present noise-cleaning methods based on modeling the multi-sensor and multi-trial data. These approaches offer objective, automatic, and robust removal of noise and disturbances by taking into account the sensor-or trial-specific signal-to-noise ratios. We introduce a method called the source-estimate-utilizing noise-discarding algorithm (the SOUND algorithm). SOUND employs anatomical information of the head to cross-validate the data between the sensors. As a result, we are able to identify and suppress noise and artifacts in EEG and MEG. Furthermore, we discuss the theoretical background of SOUND and show that it is a special case of the well-known Wiener estimators. We explain how a completely data-driven Wiener estimator (DDWiener) can be used when no anatomical information is available. DDWiener is easily applicable to any linear multivariate problem; as a demonstrative example, we show how DDWiener can be utilized when estimating event-related EEG/MEG responses. We validated the performance of SOUND with simulations and by applying SOUND to multiple EEG and MEG datasets. SOUND considerably improved the data quality, exceeding the performance of the widely used channel-rejection and interpolation scheme. SOUND also helped in localizing the underlying neural activity by preventing noise from contaminating the source estimates. SOUND can be used to detect and reject noise in functional brain data, enabling improved identification of active brain areas.Peer reviewe

Транскраниальная магнитная стимуляция с электроэнцефалографией: методология, экспериментальные и клинические возможности

Combined use of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is a highly informative cutting edge technology which is relevant for fundamental, clinical and  translational research. Unique capabilities of TMS-EEG approach  allow to assess the functional state and connectivity of brain regions  thus opening new prospects for the evaluation of the TMS effects in  non-motor cortical areas. TMS-EEG responses have diagnostic and  prognostic potential for many neurological and mental illnesses.  Simultaneous co-registration of TMS with EEG remains a technically  sophisticated procedure and requires specialized equipment in  conjunction with application of complex data analysis techniques.  This review describes the details of TMS-EEG technique, principles of the experiment design, the shape and the reproducibility of TMS- evoked responses and applications of this promising approach both  in research and in clinics. Комбинированное использование транскраниальной магнитной стимуляции и электроэнцефалографии (ТМС-ЭЭГ) является современным высокоинформативным  экспериментальным подходом, который находит применение как в фундаментальных, так и  в клинических и трансляционных исследованиях. Уникальные возможности ТМС-ЭЭГ  позволяют оценивать функциональное состояние и связность областей мозга, а также  открывают новые перспективы оценки эффектов ТМС недвигательных областей коры.  Маркеры ТМС-ЭЭГ обладают диагностическим и прогностическим потенциалом в отношении  многих неврологических и психических болезней. Регистрация ЭЭГ одновременно с ТМС  остается технически сложной процедурой и требует наличия как специального  оборудования, так и примения сложных методов анализа данных. В настоящем обзоре  описаны технические особенности ТМС-ЭЭГ, принцип построения дизайна исследований, вид и  стабильность ТМС вызванного ответа на ЭЭГ, а также область применения метода ТМС-ЭЭГ

Comparative analysis of TMS-EEG signal using different approaches in healthy subjects

openThe integration of transcranial magnetic stimulation with electroencephalography (TMS-EEG) represents a useful non-invasive approach to assess cortical excitability, plasticity and intra-cortical connectivity in humans in physiological and pathological conditions. However, biological and environmental noise sources can contaminate the TMS-evoked potentials (TEPs). Therefore, signal preprocessing represents a fundamental step in the analysis of these potentials and is critical to remove artefactual components while preserving the physiological brain activity. The objective of the present study is to evaluate the effects of different signal processing pipelines, (namely Leodori et al., Rogasch et al., Mutanen et al.) applied on TEPs recorded in five healthy volunteers after TMS stimulation of the primary motor cortex (M1) of the dominant hemisphere. These pipelines were used and compared to remove artifacts and improve the quality of the recorded signals, laying the foundation for subsequent analyses. Various algorithms, such as Independent Component Analysis (ICA), SOUND, and SSP-SIR, were used in each pipeline. Furthermore, after signal preprocessing, current localization was performed to map the TMS-induced neural activation in the cortex. This methodology provided valuable information on the spatial distribution of activity and further validated the effectiveness of the signal cleaning pipelines. Comparing the effects of the different pipelines on the same dataset, we observed considerable variability in how the pipelines affect various signal characteristics. We observed significant differences in the effects on signal amplitude and in the identification and characterisation of peaks of interest, i.e., P30, N45, P60, N100, P180. The identification and characteristics of these peaks showed variability, especially with regard to the early peaks, which reflect the cortical excitability of the stimulated area and are the more affected by biological and stimulation-related artifacts. Despite these differences, the topographies and source localisation, which are the most informative and useful in reconstructing signal dynamics, were consistent and reliable between the different pipelines considered. The results suggest that the existing methodologies for analysing TEPs produce different effects on the data, but are all capable of reproducing the dynamics of the signal and its components. Future studies evaluating different signal preprocessing methods in larger populations are needed to determine an appropriate workflow that can be shared through the scientific community, in order to make the results obtained in different centres comparable

„Balancing Vibrations" – Die neurophysiologische Erregbarkeit des primären Motorkortex bei depressiven Jugendlichen im Verlauf einer Sporttherapie - eine Zwischenauswertung -

Die Kombination TMS-EEG stellt eine einzigartige Möglichkeit dar, die kortikale Exzitabilität direkt und zeitlich hochaufgelöst zu untersuchen. Eine Komponente des TMS- evozierten Potentials stellt die N100 dar, welche im Kontext vergangener Arbeiten als Korrelat kortikaler Inhibition etabliert gilt. Veränderungen der N100 wurden bereits mit diversen neuropsychiatrischen Pathologien in Verbindung gebracht und sollen nun erstmals in einem Patientenkollektiv depressiver Jugendlichen untersucht werden. Das Ziel ist es, einen Zusammenhang zwischen Depressivität und N100-Amplituden zu untersuchen und damit den möglichen Einsatz der N100 als Biomarker und Verlaufsparameter für Depression zu evaluieren

Methods for analysis of brain connectivity : An IFCN-sponsored review

The goal of this paper is to examine existing methods to study the "Human Brain Connectome" with a specific focus on the neurophysiological ones. In recent years, a new approach has been developed to evaluate the anatomical and functional organization of the human brain: the aim of this promising multimodality effort is to identify and classify neuronal networks with a number of neurobiologically meaningful and easily computable measures to create its connectome. By defining anatomical and functional connections of brain regions on the same map through an integrated approach, comprising both modern neurophysiological and neuroimaging (i.e. flow/metabolic) brain-mapping techniques, network analysis becomes a powerful tool for exploring structural-functional connectivity mechanisms and for revealing etiological relationships that link connectivity abnormalities to neuropsychiatric disorders. Following a recent IFCN-endorsed meeting, a panel of international experts was selected to produce this current state-of-art document, which covers the available knowledge on anatomical and functional connectivity, including the most commonly used structural and functional MRI, EEG, MEG and non-invasive brain stimulation techniques and measures of local and global brain connectivity. (C) 2019 Published by Elsevier B.V. on behalf of International Federation of Clinical Neurophysiology.Peer reviewe

Manipulating neuronal communication by using low-intensity repetitive transcranial magnetic stimulation combined with electroencephalogram

Repetitive transcranial magnetic stimulation (rTMS) modulates ongoing brain rhythms by activating neuronal structures and evolving different neuronal mechanisms. In the current work, the role of stimulation strength and frequency for brain rhythms was studied. We hypothesized that a weak oscillating electric field induced by low-intensity rTMS could induce entrainment effects in the brain. To test the hypothesis, we conducted three separate experiments, in which we stimulated healthy human participants with rTMS. We individualized stimulation parameters using computational modeling of induced electric fields in the targets and individual frequency estimated by electroencephalography (EEG). We demonstrated the immediately induced entrainment of occipito-parietal and sensorimotor mu-alpha rhythm by low-intensity rTMS that resulted in phase and amplitude changes measured by EEG. Additionally, we found long-lasting corticospinal excitability changes in the motor cortex measured by motor evoked potentials from the corresponding musle.2021-11-2

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

Assessing neuromodulatory effects of non-invasive brain stimulation to the prefrontal cortex

Transcranial direct current stimulation (tDCS) and theta-burst stimulation (TBS) are two non-invasive brain stimulation (NIBS) techniques that use electricity to modulate cortical activity, showing promise for the treatment of neuropsychiatric disorders like depression. However, presenting high heterogeneity in efficacy and modest effect sizes. NIBS neurophysiological effects have been usually assessed in the motor cortex, but measurements are often associated with high variability and low reliability. Because in depression, NIBS are often administered to the dorsolateral prefrontal cortex (DLPFC), it is urgent to explore cortical properties in non-motor regions. Electroencephalography (EEG) combined with TMS has permitted the investigation of brain function beyond the motor region. TMS-evoked potentials (TEPs) may provide insights into the effects and mechanisms of NIBS applied to the DLPFC. However, the sensitivity and reliability of TEPs to track excitability changes induced by NIBS on the DLPFC has not been fully elucidated. The overall aims of the thesis were to clarify these gaps and aid in the development of tDCS/TBS as clinical interventions and TMS-EEG as a tool to examine brain properties. This was addressed via an individual patient data meta-analysis (IPD-MA) examining tDCS efficacy in depression and two experimental studies in healthy evaluating TBS effects on the DLPFC using TMS-EEG and the test-retest reliability of TEPs. Study 1 was an IPD-MA evaluating tDCS antidepressant effects and predictors of response. Results showed that tDCS was moderately effective with no significant predictors identified. These findings underscored the limitations of symptom-based studies and the need to use a physiological approach (TMS-EEG) to estimate the modulatory effects of NIBS at the cortical level to improve understanding of its mechanisms and causes of the limited efficacy. Study 2 was a sham-controlled experiment in healthy participants to assess the effects of TBS on the DLPFC using TEPs. We showed that TBS could exert changes in the DLPFC responsivity, although with smaller effect sizes than prior studies. In study 3, we examined the test-retest reliability of TEPs and the modulatory effects of TBS on the DLPFC. Results showed that TEPs were reliable within-block, but only later components (N100 and P200) had good concordance between sessions, and that reliability of TBS effects in neural excitability was poor. These findings contribute to understanding NIBS effects in the DLPFC and developing TMS-EEG as a technique to assess cortical properties