Visual deviant stimuli produce mismatch responses in the amplitude dynamics of neuronal oscillations

Objectives: Auditory and visual deviant stimuli evoke mismatch negativity (MMN) responses, which can be recorded with electroencephalography (EEG) and magnetoencephalography (MEG). However, little is known about the role of neuronal oscillations in encoding of rare stimuli. We aimed at verifying the existence of a mechanism for the detection of deviant visual stimuli on the basis of oscillatory responses, so-called visual mismatch oscillatory response (vMOR). Methods: Peripheral visual stimuli in an oddball paradigm, standard vs. deviant (7: 1), were presented to twenty healthy subjects. The oscillatory responses to an infrequent change in the direction of moving peripheral stimuli were recorded with a 60-channel EEG system. In order to enhance the detection of oscillatory responses, we used the common spatial pattern (CSP) algorithm, designed for the optimal extraction of changes in the amplitude of oscillations. Results: Both standard and deviant visual stimuli produced Event-Related Desynchronization (ERD) and Synchronization (ERS) primarily in the occipito-parietal cortical areas. ERD and ERS had overlapping time-courses and peaked at about 500-730 ms. These oscillatory responses, however, were significantly stronger for the deviant than for the standard stimuli. A difference between the oscillatory responses to deviant and standard stimuli thus reflects the presence of vMOR. Conclusions: The present study shows that the detection of visual deviant stimuli can be reflected in both synchronization and desynchronization of neuronal oscillations. This broadens our knowledge about the brain mechanisms encoding deviant sensory stimuli. (C) 2016 Elsevier Inc. All rights reserved.Peer reviewe

TMS-EEG: From basic research to clinical applications

Proceeding volume: 1626Transcranial magnetic stimulation (TMS) combined with electroencephalography (EEG) is a powerful technique for non-invasively studying cortical excitability and connectivity. The combination of TMS and EEG has widely been used to perform basic research and recently has gained importance in different clinical applications. In this paper, we will describe the physical and biological principles of TMS-EEG and different applications in basic research and clinical applications. We will present methods based on independent component analysis (ICA) for studying the TMS-evoked EEG responses. These methods have the capability to remove and suppress large artifacts, making it feasible, for instance, to study language areas with TMS-EEG. We will discuss the different applications and limitations of TMS and TMS-EEG in clinical applications. Potential applications of TMS are presented, for instance in neurosurgical planning, depression and other neurological disorders. Advantages and disadvantages of TMS-EEG and its variants such as repetitive TMS (rTMS) are discussed in comparison to other brain stimulation and neuroimaging techniques. Finally, challenges that researchers face when using this technique will be summarized.Peer reviewe

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

Effects of navigated TMS on object and action naming

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T4TE: Team for TMS−EEG to improve reproducibility through an open collaborative initiative

Funding Information: M.B. and A.Z. were supported by the Italian Ministry of Health - "Ricerca Corrente". PJ and TPM acknowledge funding from the Academy of Finland (grant number: 322423 and 321631 ).Peer reviewe

Analysing concurrent transcranial magnetic stimulation and electroencephalographic data

The concurrent use of transcranial magnetic stimulation with electroencephalography (TMS–EEG) is growing in popularity as a method for assessing various cortical properties such as excitability, oscillations and connectivity. However, this combination of methods is technically challenging, resulting in artifacts both during recording and following typical EEG analysis methods, which can distort the underlying neural signal. In this article, we review the causes of artifacts in EEG recordings resulting from TMS, as well as artifacts introduced during analysis (e.g. as the result of filtering over high-frequency, large amplitude artifacts). We then discuss methods for removing artifacts, and ways of designing pipelines to minimise analysis-related artifacts. Finally, we introduce the TMS–EEG signal analyser (TESA), an open-source extension for EEGLAB, which includes functions that are specific for TMS–EEG analysis, such as removing and interpolating the TMS pulse artifact, removing and minimising TMS-evoked muscle activity, and analysing TMS-evoked potentials. The aims of TESA are to provide users with easy access to current TMS–EEG analysis methods and to encourage direct comparisons of these methods and pipelines. It is hoped that providing open-source functions will aid in both improving and standardising analysis across the field of TMS–EEG research.Peer reviewe