Repetitive transcranial magnetic stimulation (rTMS) of the left dorsolateral prefrontal cortex (DLPFC) is an effective treatment for major depressive disorder (MDD), but response rates are low and effect sizes small. Synchronizing TMS pulses with instantaneous brain oscillations can reduce variability and increase efficacy of TMS-induced plasticity. To study whether brain oscillation-synchronized rTMS is feasible, safe and has neuromodulatory effects when targeting the DLPFC of patients with MDD. Using real-time EEG-triggered TMS we conducted a pseudo-randomized controlled single-session crossover trial of brain oscillation-synchronized rTMS of left DLPFC in 17 adult patients with antidepressant-resistant MDD. Stimulation conditions in separate sessions were: (1) rTMS triggered at the negative EEG peak of instantaneous alpha oscillations (alpha-synchronized rTMS), (2) a variation of intermittent theta-burst stimulation (modified iTBS), and (3) a random alpha phase control condition. Triggering TMS at the negative peak of instantaneous alpha oscillations by real-time analysis of the electrode F5 EEG signal was successful in 15 subjects. Two subjects reported mild transient discomfort at the site of stimulation during stimulation; no serious adverse events were reported. Alpha-synchronized rTMS, but not modified iTBS or the random alpha phase control condition, reduced resting-state alpha activity in left DLPFC and increased TMS-induced beta oscillations over frontocentral channels. Alpha-synchronized rTMS of left DLPFC is feasible, safe and has specific single-session neuromodulatory effects in patients with antidepressant-resistant MDD. Future studies need to further elucidate the mechanisms, optimize the parameters and investigate the therapeutic potential and efficacy of brain oscillation-synchronized rTMS in MDD.

In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.

Non-invasive brain stimulation (NIBS) experiments involve many recurring procedures that are not sufficiently standardized in the community. Given the diversity in experimental design and experience of the investigators, automated but yet flexible data collection and analysis tools are needed to increase objectivity, reliability, and reproducibility of NIBS experiments. The Brain Electrophysiological recording and STimulation (BEST) Toolbox is a MATLAB-based, open-source software with graphical user interface that allows users to design, run, and share freely configurable multi-protocol, multi-session NIBS studies, including transcranial magnetic, electric, and ultrasound stimulation (TMS, tES, TUS). Interfacing with a variety of recording and stimulation devices, the BEST toolbox analyzes EMG and EEG data, and configures stimulation parameters on-the-fly to facilitate closed-loop protocols and real-time applications. Its functionality is continuously expanded and includes e.g., TMS motor hotspot search, threshold estimation, motor evoked potential (MEP) and TMS-evoked EEG potential (TEP) measurements, dose-response curves, paired-pulse and dual-coil TMS, rTMS interventions.

Alpha oscillations are thought to reflect alternating cortical states of excitation and inhibition. Studies of perceptual thresholds and evoked potentials have shown the scalp EEG negative phase of the oscillation to correspond to a short-lasting low-threshold and high-excitability state of underlying visual, somatosensory, and primary motor cortex. The negative peak of the oscillation is assumed to correspond to the state of highest excitability based on biophysical considerations and considerable effort has been made to improve the extraction of a predictive signal by individually optimizing EEG montages. Here, we investigate whether it is the negative peak of sensorimotor µ-rhythm that corresponds to the highest corticospinal excitability, and whether this is consistent between individuals. In 52 adult participants, a standard 5-channel surface Laplacian EEG montage was used to extract sensorimotor µ-rhythm during transcranial magnetic stimulation (TMS) of primary motor cortex. Post-hoc trials were sorted from 800 TMS-evoked motor potentials (MEPs) according to the pre-stimulus EEG (estimated instantaneous phase) and MEP amplitude (as an index of corticospinal excitability). Different preprocessing transformations designed to improve the accuracy by which µ-alpha phase predicts excitability were also tested. By fitting a sinusoid to the MEP amplitudes, sorted according to pre-stimulus EEG-phase, we found that excitability was highest during the early rising phase, at a significant delay with respect to the negative peak by on average 45° or 10 ms. The individual phase of highest excitability was consistent across study participants and unaffected by two different EEG-cleaning methods that utilize 64 channels to improve signal quality by compensating for individual noise level and channel covariance. Personalized transformations of the montage did not yield better prediction of excitability from µ-alpha phase. The relationship between instantaneous phase of a brain oscillation and fluctuating cortical excitability appears to be more complex than previously hypothesized. In TMS of motor cortex, a standard surface Laplacian 5-channel EEG montage is effective in extracting a predictive signal and the phase corresponding to the highest excitability appears to be consistent between individuals. This is an encouraging result with respect to the clinical potential of therapeutic personalized brain interventions in the motor system. However, it remains to be investigated, whether similar results can be obtained for other brain areas and brain oscillations targeted with EEG and TMS.

Prefrontal theta oscillations are involved in neuronal information transfer and retention. Phases along the theta cycle represent varied excitability states, whereby high-excitability states correspond to high-frequency neuronal activity and heightened capacity for plasticity induction, as demonstrated in animal studies. Human studies corroborate this model and suggest a core role of prefrontal theta activity in working memory (WM). We aimed at modulating prefrontal neuronal excitability and WM performance in healthy humans, using real-time EEG analysis for triggering repetitive transcranial magnetic stimulation (rTMS) theta-phase synchronized to the left dorsomedial prefrontal cortex. 16 subjects underwent 3 different rTMS interventions on separate days, with pulses triggered according to the individual's real-time EEG activity: 400 rTMS gamma-frequency (100 Hz) triplet bursts applied during either the negative peak of the prefrontal theta oscillation, the positive peak, or at random phase. Changes in cortical excitability were assessed with EEG responses following single-pulse TMS, and behavioral effects by using a WM task. Negative-peak rTMS increased single-pulse TMS-induced prefrontal theta power and theta-gamma phase-amplitude coupling, and decreased WM response time. In contrast, positive-peak rTMS decreased prefrontal theta power, while no changes were observed after random-phase rTMS. Findings point to the feasibility of EEG-TMS technology in a theta-gamma phase-amplitude coupling mode for effectively modifying WM networks in human prefrontal cortex, with potential for therapeutic applications.

Transcranial magnetic stimulation (TMS) is a non-invasive technique to stimulate the brain, while electroencephalography (EEG) is a non-invasive technique to record its electrical activity. Their combined use (TMS-EEG) has been established only relatively recently, after successful development of TMS-compatible EEG amplifiers. TMS-EEG offers the unparalleled opportunity to directly perturb the brain with TMS and simultaneously record its response with EEG. This allows inferences on causal input-output relationships, therefore going critically beyond purely observational techniques, such as resting-state EEG or functional MRI, in the study of brain dynamics. This consensus review updates the work of Tremblay and coworkers [Clin Neurophysiol 2019; 130: 802-844]. Since then, substantial advances have been made in understanding contamination of TMS-EEG signals by physiological and non-physiological artifacts, as well as in developing strategies to avoid or control them. In parallel, new insights have emerged regarding the physiological mechanisms underlying TMS-EEG responses and their diagnostic and prognostic utility in a broad range of psychiatric and neurological disorders. As such, TMS-EEG is rapidly shaping a dynamic new field in clinical neurophysiology and neuroscience. This review provides a critical and comprehensive synthesis of current knowledge, including practical guidance for implementing TMS-EEG in the clinical setting.