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Transcranial magnetic stimulation (TMS) modulates neuronal activity, but the efficacy of an open-loop approach is limited due to the brain state's dynamic nature. Real-time integration with electroencephalography (EEG) increases experimental reliability and offers personalized neuromodulation therapy by using immediate brain states as biomarkers. Here, we review brain state-controlled TMS-EEG studies since the first publication several years ago. A summary of experiments on the sensorimotor mu rhythm (8-13 Hz) shows increased cortical excitability due to TMS pulse at the trough and decreased excitability at the peak of the oscillation. Pre-TMS pulse mu power also affects excitability. Further, there is emerging evidence that the oscillation phase in theta and beta frequency bands modulates neural excitability. Here, we provide a guide for real-time TMS-EEG application and discuss experimental and technical considerations. We consider the effects of hardware choice, signal quality, spatial and temporal filtering, and neural characteristics of the targeted brain oscillation. Finally, we speculate on how closed-loop TMS-EEG potentially could improve the treatment of neurological and mental disorders such as depression, Alzheimer's, Parkinson's, schizophrenia, and stroke. &#xD., (© 2024 The Author(s). Published by IOP Publishing Ltd.)

Human working memory is a key cognitive process that engages multiple functional anatomical nodes across the brain. Despite a plethora of correlative neuroimaging evidence regarding the working memory architecture, our understanding of critical hubs causally controlling overall performance is incomplete. Causal interpretation requires cognitive testing following safe, temporal, and controllable neuromodulation of specific functional anatomical nodes. Such experiments became available in healthy humans with the advance of transcranial alternating current stimulation (tACS). Here, we synthesize findings of 28 placebo-controlled studies (in total, 1,057 participants) that applied frequency-specific noninvasive stimulation of neural oscillations and examined working memory performance in neurotypical adults. We use a computational meta-modeling method to simulate each intervention in realistic virtual brains and test reported behavioral outcomes against the stimulation-induced electric fields in different brain nodes. Our results show that stimulating anterior frontal and medial temporal theta oscillations and occipitoparietal gamma rhythms leads to significant dose-dependent improvement in working memory task performance. Conversely, prefrontal gamma modulation is detrimental to performance. Moreover, we found distinct spatial expression of theta subbands, where working memory changes followed orbitofrontal high-theta modulation and medial temporal low-theta modulation. Finally, all these results are driven by changes in working memory accuracy rather than processing time measures. These findings provide a fresh view of the working memory mechanisms, complementary to neuroimaging research, and propose hypothesis-driven targets for the clinical treatment of working memory deficits., Competing Interests: Competing interests statement:The authors declare no competing interest.

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods., (© 2024. The Author(s).)

Transcranial magnetic stimulation (TMS) is a noninvasive brain stimulation method that is rapidly growing in popularity for studying causal brain-behavior relationships. However, its dose-dependent centrally induced neural mechanisms and peripherally induced sensory costimulation effects remain debated. Understanding how TMS stimulation parameters affect brain responses is vital for the rational design of TMS protocols. Studying these mechanisms in humans is challenging because of the limited spatiotemporal resolution of available noninvasive neuroimaging methods. Here, we leverage invasive recordings of local field potentials in a male and a female nonhuman primate (rhesus macaque) to study TMS mesoscale responses. We demonstrate that early TMS-evoked potentials show a sigmoidal dose-response curve with stimulation intensity. We further show that stimulation responses are spatially specific. We use several control conditions to dissociate centrally induced neural responses from auditory and somatosensory coactivation. These results provide crucial evidence regarding TMS neural effects at the brain circuit level. Our findings are highly relevant for interpreting human TMS studies and biomarker developments for TMS target engagement in clinical applications. SIGNIFICANCE STATEMENT Transcranial magnetic stimulation (TMS) is a widely used noninvasive brain stimulation method to stimulate the human brain. To advance its utility for clinical applications, a clear understanding of its underlying physiological mechanisms is crucial. Here, we perform invasive electrophysiological recordings in the nonhuman primate brain during TMS, achieving a spatiotemporal precision not available in human EEG experiments. We find that evoked potentials are dose dependent and spatially specific, and can be separated from peripheral stimulation effects. This means that TMS-evoked responses can indicate a direct physiological stimulation response. Our work has important implications for the interpretation of human TMS-EEG recordings and biomarker development., (Copyright © 2023 the authors.)

Background: Transcranial alternating current stimulation (tACS) is a widely used noninvasive brain stimulation (NIBS) technique to affect neural activity. TACS experiments have been coupled with computational simulations to predict the electromagnetic fields within the brain. However, existing simulations are focused on the magnitude of the field. As the possibility of inducing the phase gradient in the brain using multiple tACS electrodes arises, a simulation framework is necessary to investigate and predict the phase gradient of electric fields during multi-channel tACS., Objective: Here, we develop such a framework for phasor simulation using phasor algebra and evaluate its accuracy using in vivo recordings in monkeys., Methods: We extract the phase and amplitude of electric fields from intracranial recordings in two monkeys during multi-channel tACS and compare them to those calculated by phasor analysis using finite element models., Results: Our findings demonstrate that simulated phases correspond well to measured phases (r = 0.9). Further, we systematically evaluated the impact of accurate electrode placement on modeling and data agreement. Finally, our framework can predict the amplitude distribution in measurements given calibrated tissues' conductivity., Conclusions: Our validated general framework for simulating multi-phase, multi-electrode tACS provides a streamlined tool for principled planning of multi-channel tACS experiments., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Transcranial alternating current stimulation (tACS) can modulate human neural activity and behavior. Accordingly, tACS has vast potential for cognitive research and brain disorder therapies. The stimulation generates oscillating electric fields in the brain that can bias neural spike timing, causing changes in local neural oscillatory power and cross-frequency and cross-area coherence. tACS affects cognitive performance by modulating underlying single or nested brain rhythms, local or distal synchronization, and metabolic activity. Clinically, stimulation tailored to abnormal neural oscillations shows promising results in alleviating psychiatric and neurological symptoms. We summarize the findings of tACS mechanisms, its use for cognitive applications, and novel developments for personalized stimulation., Competing Interests: Declaration of interests The authors declare no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Neural oscillations in the primary motor cortex (M1) shape corticospinal excitability. Power and phase of ongoing mu (8-13 Hz) and beta (14-30 Hz) activity may mediate motor cortical output. However, the functional dynamics of both mu and beta phase and power relationships and their interaction, are largely unknown., Objective: Here, we employ recently developed real-time targeting of the mu and beta rhythm, to apply phase-specific brain stimulation and probe motor corticospinal excitability non-invasively. For this, we used instantaneous read-out and analysis of ongoing oscillations, targeting four different phases (0°, 90°, 180°, and 270°) of mu and beta rhythms with suprathreshold single-pulse transcranial magnetic stimulation (TMS) to M1. Ensuing motor evoked potentials (MEPs) in the right first dorsal interossei muscle were recorded. Twenty healthy adults took part in this double-blind randomized crossover study., Results: Mixed model regression analyses showed significant phase-dependent modulation of corticospinal output by both mu and beta rhythm. Strikingly, these modulations exhibit a double dissociation. MEPs are larger at the mu trough and rising phase and smaller at the peak and falling phase. For the beta rhythm we found the opposite behavior. Also, mu power, but not beta power, was positively correlated with corticospinal output. Power and phase effects did not interact for either rhythm, suggesting independence between these aspects of oscillations., Conclusion: Our results provide insights into real-time motor cortical oscillation dynamics, which offers the opportunity to improve the effectiveness of TMS by specifically targeting different frequency bands., Competing Interests: Declaration of competing interest Authors declare no conflict of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Weak extracellular electric fields can influence spike timing in neural networks. Approaches to noninvasively impose these fields on the brain have high therapeutic potential in neurology and psychiatry. Transcranial alternating current stimulation (TACS) is hypothesized to affect spike timing and cause neural entrainment. However, the conditions under which these effects occur in vivo are unknown. Here, we recorded single-unit activity in the neocortex in awake nonhuman primates during TACS and found dose-dependent neural entrainment to the stimulation waveform. Cluster analysis of changes in interspike intervals identified two main types of neural responses to TACS-increased burstiness and phase entrainment. Our results uncover key mechanisms of TACS and show that the stimulation affects spike timing in the awake primate brain at intensities feasible in humans. Thus, novel TACS protocols tailored to ongoing brain activity may be a tool to normalize spike timing in maladaptive brain networks and neurological disease., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Objective: Real-time approaches for transcranial magnetic stimulation (TMS) based on a specific EEG phase are a promising avenue for more precise neuromodulation interventions. However, optimal approaches to reliably extract the EEG phase in a frequency band of interest to inform TMS are still to be identified. Here, we implement a new real-time phase detection method for closed-loop EEG-TMS for robust phase extraction. We compare this algorithm with state-of-the-art methods and evaluate its performance both in silico and experimentally., Approach: We propose a new robust algorithm (Educated Temporal Prediction) for delivering real-time EEG phase-specific stimulation based on short prerecorded EEG training data. This method estimates the interpeak period from a training period and applies a bias correction to predict future peaks. We compare the accuracy and computation speed of the ETP algorithm with two existing methods (Fourier based, Autoregressive Prediction) using prerecorded resting EEG data and real-time experiments., Main Results: We found that Educated Temporal Prediction performs with higher accuracy than Fourier-based or Autoregressive methods both in silico and in vivo while being computationally more efficient. Further, we document the dependency of the EEG signal-to-noise ratio (SNR) on algorithm accuracy across all algorithms., Significance: Our results give important insights for real-time EEG-TMS technical development as well as experimental design. Due to its robustness and computational efficiency, our method can find broad use in experimental research or clinical applications. Through open sharing of code for all three methods, we enable broad access of TMS-EEG real-time algorithms to the community.

Background: Long-term recognition memory depends both on initial encoding and on subsequent recognition processes., Objective: In this study we aimed at improving long-term memory by modulating posterior parietal brain activity during the encoding process. If this area is causally involved in memory encoding, its facilitation should lead to behavioral improvement. Based on the dual-process memory framework, we also expected that the neuromodulation would dissociate subsequent familiarity-based and recollection-based recognition., Methods: We investigated the role of the posterior parietal brain oscillations in facial memory formation in three separate experiments using electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and model-driven, multi-electrode transcranial alternating current stimulation (tACS)., Results: Using fMRI and EEG, we confirmed that the right posterior parietal cortex is an essential node that promotes the encoding of long-term memories. We found that single-trial low theta power in this region predicts subsequent long-term recognition. On this basis, we fine-tuned the spatial and frequency settings of tACS during memory encoding. Model-driven tACS over the right posterior brain area augmented subsequent long-term recognition memory and particularly the familiarity of the observed stimuli. The recollection process, and short-term task performance as control remained unchanged. Control stimulation over the left hemisphere had no behavioral effect., Conclusion: We conclude that the right posterior brain area is crucial in long-term memory encoding., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Among the brain regions involved in the aesthetic evaluation of paintings, the prefrontal cortex seems to play a pivotal role. In particular, consistent neuroimaging evidence indicates that activity in the dorsolateral prefrontal cortex (mainly in the left hemisphere) and in medial and orbital sectors of the prefrontal cortex is linked to viewing aesthetically pleasing images. In this study, we focused on the contribution of the medial prefrontal cortex (mPFC) in mediating aesthetic decisions about paintings. We found that enhancing excitability in this region via anodal tDCS led participants to judge paintings as more beautiful. Although significant, the effects were moderate, possibly due to the neutral affective value of the artworks we used, suggesting that activity in mPFC may be critically dependent on the affective impact of the paintings.