Brain State-Dependent Brain Stimulation

No add-on therapeutic benefit of at-home anodal tDCS of the primary motor cortex to mindfulness meditation in patients with fibromyalgia

OBJECTIVE

This study investigated the efficacy of combining at-home anodal transcranial direct current stimulation (tDCS) of the left primary motor cortex (M1) with mindfulness meditation (MM) in fibromyalgia patients trained in mindfulness.

METHODS

Thirty-seven patients were allocated to receive ten daily sessions of MM paired with either anodal or sham tDCS over the primary motor cortex. Primary outcomes were pain intensity and quality of life. Secondary outcomes were psychological impairment, sleep quality, mood, affective pain, mindfulness level, and transcranial magnetic stimulation (TMS) measures of cortical excitability. Outcomes were analyzed pre- and post-treatment, with a one-month follow-up.

RESULTS

We found post-tDCS improvement in all clinical outcomes, including mindfulness level, except for positive affect and stress, in both groups without significant difference between active and sham conditions. No significant group*time interaction was found for all clinical and TMS outcomes.

CONCLUSIONS

Our findings demonstrate no synergistic or add-on efffect of anodal tDCS of the left M1 compared to the proper effect of MM in patients with fibromyalgia.

SIGNIFICANCE

Our findings challenge the potential of combining anodal tDCS of the left M1 and MM in fibromyalgia.

The Nested States Model: A Phenomenologically-Grounded Model of the Mind

BACKGROUND

Subjective experience is central to the nature of mental illness, yet it has not played a central role in most empirical approaches to psychopathology. While phenomenological perspectives in psychiatry have seen a recent resurgence, there remains a need for more detailed models of psychopathological processes based on explicit phenomenological and enactive foundations.

SUMMARY

We present a framework derived from the Nested States Model (NSM) through which such phenomenologically-grounded models might be constructed. The NSM describes the dynamic structure of subjective experience as a system of nested states that reciprocally influence one another across hierarchical layers. Here, we show how the NSM provides a scheme for characterizing patterns of experience that comprise various psychopathological processes. We demonstrate the utility of this scheme both for clinical practice and for building our knowledge of psychopathological processes more broadly.

KEY MESSAGES

The NSM can advance three aims that we see as critical for the lasting integration of phenomenological approaches to psychopathology within psychiatry. First, we show that the NSM provides a means for constructing clinical formulations and treatment considerations that center squarely on an individual's subjective experiences. Second, the NSM supplies a framework for organizing findings from clinical-phenomenological research that can guide the construction of broader phenomenologically-grounded models of psychopathological processes. Lastly, the NSM aligns our perspective on subjective experience with emerging perspectives on brain dynamics, helping to bridge phenomenological work with ongoing neurophysiological research.

Facilitating Corticomotor Excitability of the Contralesional Hemisphere Using Non-Invasive Brain Stimulation to Improve Upper Limb Motor Recovery from Stroke-A Scoping Review

Upper limb weakness following stroke poses a significant global psychosocial and economic burden. Non-invasive brain stimulation (NIBS) is a potential adjunctive treatment in rehabilitation. However, traditional approaches to rebalance interhemispheric inhibition may not be effective for all patients. The supportive role of the contralesional hemisphere in recovery of upper limb motor function has been supported by animal and clinical studies, particularly for those with severe strokes. This review aims to provide an overview of the facilitation role of the contralesional hemisphere for post-stroke motor recovery. While more studies are required to predict responses and inform the choice of NIBS approach, contralesional facilitation may offer new hope for patients in whom traditional rehabilitation and NIBS approaches have failed.

Transcranial temporal interference stimulation (tTIS) influences event-related alpha activity during mental rotation

Non-invasive brain stimulation techniques offer therapeutic potential for neurological and psychiatric disorders. However, current methods are often limited in their stimulation depth. The novel transcranial temporal interference stimulation (tTIS) aims to overcome this limitation by non-invasively targeting deeper brain regions. In this study, we aimed to evaluate the efficacy of tTIS in modulating alpha activity during a mental rotation task. The effects of tTIS were compared with transcranial alternating current stimulation (tACS) and a sham control. Participants were randomly assigned to a tTIS, tACS, or sham group. They performed alternating blocks of resting and mental rotation tasks before, during, and after stimulation. During the stimulation blocks, participants received 20 min of stimulation adjusted to their individual alpha frequency (IAF). We assessed shifts in resting state alpha power, event-related desynchronization (ERD) of alpha activity during mental rotation, as well as resulting improvements in behavioral performance. Our results indicate tTIS and tACS to be effective in modulating cortical alpha activity during mental rotation, leading to an increase in ERD from pre- to poststimulation as well as compared to sham stimulation. However, this increase in ERD was not correlated with enhanced mental rotation performance, and resting state alpha power remained unchanged. Our findings underscore the complex nature of tTIS and tACS efficacy, indicating that stimulation effects are more observable during active cognitive tasks, while their impacts are less pronounced on resting neuronal systems.

The relationship between parameters and effects in transcranial ultrasonic stimulation

Transcranial ultrasonic stimulation (TUS) is rapidly gaining traction for non-invasive human neuromodulation, with a pressing need to establish protocols that maximise neuromodulatory efficacy. In this review, we aggregate and examine empirical evidence for the relationship between tunable TUS parameters and in vitro and in vivo outcomes. Based on this multiscale approach, TUS researchers can make better informed decisions about optimal parameter settings. Importantly, we also discuss the challenges involved in extrapolating results from prior empirical work to future interventions, including the translation of protocols between models and the complex interaction between TUS protocols and the brain. A synthesis of the empirical evidence suggests that larger effects will be observed at lower frequencies within the sub-MHz range, higher intensities and pressures than commonly administered thus far, and longer pulses and pulse train durations. Nevertheless, we emphasise the need for cautious interpretation of empirical data from different experimental paradigms when basing protocols on prior work as we advance towards refined TUS parameters for human neuromodulation.

Working memory enhancement using real-time phase-tuned transcranial alternating current stimulation

BACKGROUND

Prior work has shown that transcranial alternating current stimulation (tACS) of parietooccipital alpha oscillations (8-14 Hz) can modulate working memory (WM) performance as a function of the phase lag to endogenous oscillations. However, leveraging this effect using real-time phase-tuned tACS has not been feasible so far due to stimulation artifacts preventing continuous phase tracking.

OBJECTIVES AND HYPOTHESIS

We aimed to develop a system that tracks and adapts the phase lag between tACS and ongoing parietooccipital alpha oscillations in real-time. We hypothesized that such real-time phase-tuned tACS enhances working memory performance, depending on the phase lag.

METHODS

We developed real-time phase-tuned closed-loop amplitude-modulated tACS (CLAM-tACS) targeting parietooccipital alpha oscillations. CLAM-tACS was applied at six different phase lags relative to ongoing alpha oscillations while participants (N = 21) performed a working memory task. To exclude that behavioral effects of CLAM-tACS were mediated by other factors such as sensory co-stimulation, a second group of participants (N = 25) received equivalent stimulation of the forehead.

RESULTS

WM accuracy improved in a phase lag dependent manner (p = 0.0350) in the group receiving parietooccipital stimulation, with the strongest enhancement observed at 330° phase lag between tACS and ongoing alpha oscillations (p = 0.00273, d = 0.976). Moreover, across participants, modulation of frontoparietal alpha oscillations correlated both in amplitude (p = 0.0248) and phase (p = 0.0270) with the modulation of WM accuracy. No such effects were observed in the control group receiving frontal stimulation.

CONCLUSIONS

Our results demonstrate the feasibility and efficacy of real-time phase-tuned CLAM-tACS in modulating both brain activity and behavior, thereby paving the way for further investigation into brain-behavior relationships and the exploration of innovative therapeutic applications.

Transcranial Direct Current Stimulation to Ameliorate Post-Stroke Cognitive Impairment

Post-stroke cognitive impairment is a common and disabling condition with few effective therapeutic options. After stroke, neural reorganization and other neuroplastic processes occur in response to ischemic injury, which can result in clinical improvement through spontaneous recovery. Neuromodulation through transcranial direct current stimulation (tDCS) is a promising intervention to augment underlying neuroplasticity in order to improve cognitive function. This form of neuromodulation leverages mechanisms of neuroplasticity post-stroke to optimize neural reorganization and improve function. In this review, we summarize the current state of cognitive neurorehabilitation post-stroke, the practical features of tDCS, its uses in stroke-related cognitive impairment across cognitive domains, and special considerations for the use of tDCS in the post-stroke patient population.

Evaluating frontoparietal network topography for diagnostic markers of Alzheimer's disease

Numerous prospective biomarkers are being studied for their ability to diagnose various stages of Alzheimer's disease (AD). High-density electroencephalogram (EEG) methods show promise as an accurate, economical, non-invasive approach to measuring the electrical potentials of brains associated with AD. Event-related potentials (ERPs) may serve as clinically useful biomarkers of AD. Through analysis of secondary data, the present study examined the performance and distribution of N4/P6 ERPs across the frontoparietal network (FPN) using EEG topographic mapping. ERP measures and memory as a function of reaction time (RT) were compared between a group of (n = 63) mild untreated AD patients and a control group of (n = 73) healthy age-matched adults. Based on the literature presented, it was expected that healthy controls would outperform patients in peak amplitude and mean component latency across three parameters of memory when measured at optimal N4 (frontal) and P6 (parietal) locations. It was also predicted that the control group would exhibit neural cohesion through FPN integration during cross-modal tasks, thus demonstrating healthy cognitive functioning consistent with older healthy adults. By targeting select frontal and parietal EEG reference channels based on N4/P6 component time windows and positivity, our findings demonstrated statistically significant group variations between controls and patients in N4/P6 peak amplitudes and latencies during cross-modal testing. Our results also support that the N4 ERP might be stronger than its P6 counterpart as a possible candidate biomarker. We conclude through topographic mapping that FPN integration occurs in healthy controls but is absent in AD patients during cross-modal memory tasks.

Closed-Loop Transcranial Electrical Neurostimulation for Sustained Attention Enhancement: A Pilot Study towards Personalized Intervention Strategies

Sustained attention is pivotal for tasks like studying and working for which focus and low distractions are necessary for peak productivity. This study explores the effectiveness of adaptive transcranial direct current stimulation (tDCS) in either the frontal or parietal region to enhance sustained attention. The research involved ten healthy university students performing the Continuous Performance Task-AX (AX-CPT) while receiving either frontal or parietal tDCS. The study comprised three phases. First, we acquired the electroencephalography (EEG) signal to identify the most suitable metrics related to attention states. Among different spectral and complexity metrics computed on 3 s epochs of EEG, the Fuzzy Entropy and Multiscale Sample Entropy Index of frontal channels were selected. Secondly, we assessed how tDCS at a fixed 1.0 mA current affects attentional performance. Finally, a real-time experiment involving continuous metric monitoring allowed personalized dynamic optimization of the current amplitude and stimulation site (frontal or parietal). The findings reveal statistically significant improvements in mean accuracy (94.04 vs. 90.82%) and reaction times (262.93 vs. 302.03 ms) with the adaptive tDCS compared to a non-stimulation condition. Average reaction times were statistically shorter during adaptive stimulation compared to a fixed current amplitude condition (262.93 vs. 283.56 ms), while mean accuracy stayed similar (94.04 vs. 93.36%, improvement not statistically significant). Despite the limited number of subjects, this work points out the promising potential of adaptive tDCS as a tailored treatment for enhancing sustained attention.

Exploring Motor Network Connectivity in State-Dependent Transcranial Magnetic Stimulation: A Proof-of-Concept Study

State-dependent non-invasive brain stimulation (NIBS) informed by electroencephalography (EEG) has contributed to the understanding of NIBS inter-subject and inter-session variability. While these approaches focus on local EEG characteristics, it is acknowledged that the brain exhibits an intrinsic long-range dynamic organization in networks. This proof-of-concept study explores whether EEG connectivity of the primary motor cortex (M1) in the pre-stimulation period aligns with the Motor Network (MN) and how the MN state affects responses to the transcranial magnetic stimulation (TMS) of M1. One thousand suprathreshold TMS pulses were delivered to the left M1 in eight subjects at rest, with simultaneous EEG. Motor-evoked potentials (MEPs) were measured from the right hand. The source space functional connectivity of the left M1 to the whole brain was assessed using the imaginary part of the phase locking value at the frequency of the sensorimotor μ-rhythm in a 1 s window before the pulse. Group-level connectivity revealed functional links between the left M1, left supplementary motor area, and right M1. Also, pulses delivered at high MN connectivity states result in a greater MEP amplitude compared to low connectivity states. At the single-subject level, this relation is more highly expressed in subjects that feature an overall high cortico-spinal excitability. In conclusion, this study paves the way for MN connectivity-based NIBS.

Chronometric TMS-fMRI of personalized left dorsolateral prefrontal target reveals state-dependency of subgenual anterior cingulate cortex effects

Transcranial magnetic stimulation (TMS) applied to a left dorsolateral prefrontal cortex (DLPFC) area with a specific connectivity profile to the subgenual anterior cingulate cortex (sgACC) has emerged as a highly effective non-invasive treatment option for depression. However, antidepressant outcomes demonstrate significant variability among therapy plans and individuals. One overlooked contributing factor is the individual brain state at the time of treatment. In this study we used interleaved TMS-fMRI to investigate the influence of brain state on acute TMS effects, both locally and remotely. TMS was performed during rest and during different phases of cognitive task processing. Twenty healthy participants were included in this study. In the first session, imaging data for TMS targeting were acquired, allowing for identification of individualized targets in the left DLPFC based on highest anti-correlation with the sgACC. The second session involved chronometric interleaved TMS-fMRI measurements, with 10 Hz triplets of TMS administered during rest and at distinct timings during an N-back task. Consistent with prior findings, interleaved TMS-fMRI revealed significant BOLD activation changes in the targeted network. The precise timing of TMS relative to the cognitive states during the task demonstrated distinct BOLD response in clinically relevant brain regions, including the sgACC. Employing a standardized timing approach for TMS using a task revealed more consistent modulation of the sgACC at the group level compared to stimulation during rest. In conclusion, our findings strongly suggest that acute local and remote effects of TMS are influenced by brain state during stimulation. This study establishes a basis for considering brain state as a significant factor in designing treatment protocols, possibly improving TMS treatment outcomes.

Opportunities and obstacles in non-invasive brain stimulation

Non-invasive brain stimulation (NIBS) is a complex and multifaceted approach to modulating brain activity and holds the potential for broad accessibility. This work discusses the mechanisms of the four distinct approaches to modulating brain activity non-invasively: electrical currents, magnetic fields, light, and ultrasound. We examine the dual stochastic and deterministic nature of brain activity and its implications for NIBS, highlighting the challenges posed by inter-individual variability, nebulous dose-response relationships, potential biases and neuroanatomical heterogeneity. Looking forward, we propose five areas of opportunity for future research: closed-loop stimulation, consistent stimulation of the intended target region, reducing bias, multimodal approaches, and strategies to address low sample sizes.

Stress priming transcranial direct current stimulation (tDCS) enhances updating of emotional content in working memory

Transcranial direct current stimulation (tDCS) targeting the prefrontal cortex has emerged as a valuable tool in psychiatric research. Understanding the impact of affective states, such as stress at the time of stimulation, on the efficacy of prefrontal tDCS is crucial for advancing tDCS interventions. Stress-primed tDCS, wherein stress is used as a priming agent, has the potential to modulate neural plasticity and enhance cognitive functions, particularly in emotional working memory. However, prior research using stress-primed tDCS focused solely on non-emotional working memory performance, yielding mixed results. In this sham-controlled study, we addressed this gap by investigating the effects of stress-primed bifrontal tDCS (active versus sham) on both non-emotional and emotional working memory performance. The study was conducted in 146 healthy individuals who were randomly assigned to four experimental groups. The Trier Social Stress Test (TSST) or a control variant of the test was used to induce a stress versus control state. The results showed that stress priming significantly enhanced the effects of tDCS on the updating of emotional content in working memory, as evidenced by improved accuracy. Notably, no significant effects of stress priming were found for non-emotional working memory performance. These findings highlight the importance of an individual's prior affective state in shaping their response to tDCS, especially in the context of emotional working memory.

Non-invasive neuromodulation of the right temporoparietal junction using theta-burst stimulation in functional neurological disorder

Background

Disrupted sense of agency (SoA)-the sense of being the agent of one's own actions-has been demonstrated in patients with functional neurological disorder (FND), and a key area of the corresponding neuronal network is the right temporoparietal junction (rTPJ). Several functional MRI (fMRI) studies have found hypoactivation as well as hyperactivation of the rTPJ in FND. In a proof-of-concept study, we tested whether repetitive transcranial magnetic stimulation (rTMS) over the rTPJ could restore this aberrant activity.

Methods

In a randomised, crossover, single-blinded, sham-controlled study design, theta-burst stimulation (tb-rTMS) was applied over the rTPJ in 23 patients with FND and 19 healthy controls (HC), with each participant undergoing three stimulatory visits (inhibitory continuous TBS (cTBS), excitatory intermittent TBS (iTBS) and sham). During fMRI, participants played a visuomotor task artificially reducing their SoA (manipulated agency, MA), repeated after each neurostimulation. We compared brain activity and behavioural SoA as primary outcomes before and after tb-rTMS and investigated the feasibility of tb-rTMS over the rTPJ in FND as secondary outcome.

Results

At baseline, patients showed decreased accuracy in detecting reduced agency compared with controls (p<0.001), paralleled by lower brain activation in the rTPJ during MA (p=0.037, volume of interest). A region of interest analysis on the rTPJ showed no effect of the sham condition in FND or HC (p=0.917; p=0.375) but revealed a significant effect of stimulation protocol (cTBS/iTBS, p=0.037) in patients with FND, with the excitatory protocol increasing the blood-oxygen-level-dependent (BOLD) signal, whereas this effect was not found in HC. In neither group, a behavioural effect of tb-rTMS was observed.

Conclusion

Aberrant processing of agency in FND was confirmed at baseline, reflected in behavioural outcome and reduced activity in the rTPJ. Tb-rTMS over this key region elicited neuronal changes in patients, paving ways for future studies exploring TMS as neurobiologically informed intervention to restore SoA in FND. We critically discuss methodological intricacies and outline further steps in this research line.

MEP and TEP features variability: is it just the brain-state?

Objective.The literature investigating the effects of alpha oscillations on corticospinal excitability is divergent. We believe inconsistency in the findings may arise, among others, from the electroencephalography (EEG) processing for brain-state determination. Here, we provide further insights in the effects of the brain-state on cortical and corticospinal excitability and quantify the impact of different EEG processing.Approach.Corticospinal excitability was measured using motor evoked potential (MEP) peak-to-peak amplitudes elicited with transcranial magnetic stimulation (TMS); cortical responses were studied through TMS-evoked potentials' TEPs features. A TMS-EEG-electromyography (EMG) dataset of 18 young healthy subjects who received 180 single-pulse (SP) and 180 paired pulses (PP) to determine short-intracortical inhibition (SICI) was investigated. To study the effect of different EEG processing, we compared the brain-state estimation deriving from three published methods. The influence of presence of neural oscillations was also investigated. To evaluate the effect of the brain-state on MEP and TEP features variability, we defined the brain-state based on specific EEG phase and power combinations, only in trials where neural oscillations were present. The relationship between TEPs and MEPs was further evaluated.Main results.The presence of neural oscillations resulted in more consistent results regardless of the EEG processing approach. Nonetheless, the latter still critically affected the outcomes, making conclusive claims complex. With our approach, the MEP amplitude was positively modulated by the alpha power and phase, with stronger responses during the trough phase and high power. Power and phase also affected TEP features. Importantly, similar effects were observed in both TMS conditions.Significance.These findings support the view that the brain state of alpha oscillations is associated with the variability observed in cortical and corticospinal responses to TMS, with a tight correlation between the two. The results further highlight the importance of closed-loop stimulation approaches while underlining that care is needed in designing experiments and choosing the analytical approaches, which should be based on knowledge from offline studies to control for the heterogeneity originating from different EEG processing strategies.

Alpha modulation via transcranial alternating current stimulation in adults with attention-deficit hyperactivity disorder

Background

One potential therapy treating attention-deficit/hyperactivity disorder (ADHD) is to modulate dysfunctional brain activations using brain stimulation techniques. While the number of studies investigating the effect of transcranial direct current stimulation on ADHD symptoms continues to increase, transcranial alternating current stimulation (tACS) is poorly examined. Previous studies reported impaired alpha brain oscillation (8-12 Hz) that may be associated with increased attention deficits in ADHD. Our aim was to enhance alpha power in adult ADHD patients via tACS, using different methods to explore potential therapeutic effects.

Methods

Undergoing a crossover design, adults with ADHD received active and sham stimulation on distinct days. Before and after each intervention, mean alpha power, attention performance, subjective symptom ratings, as well as head and gaze movement were examined.

Results

Frequency analyses revealed a significant power increase in the alpha band after both interventions. Despite a trend toward an interaction effect, this alpha power increase was, however, not significantly higher after active stimulation compared to sham stimulation. For the other measures, some additional pre-post effects were found, which were not intervention-related.

Conclusion

Our study cannot provide clear evidence for a tACS-induced increase in alpha power in adult ADHD patients, and thus no stimulation related improvement of attention parameters. We provide further recommendations for the future investigation of tACS as a potential ADHD treatment.

The behavioral and neural effects of parietal theta burst stimulation on the grasp network are stronger during a grasping task than at rest

Repetitive transcranial magnetic stimulation (TMS) is widely used in neuroscience and clinical settings to modulate human cortical activity. The effects of TMS on neural activity depend on the excitability of specific neural populations at the time of stimulation. Accordingly, the brain state at the time of stimulation may influence the persistent effects of repetitive TMS on distal brain activity and associated behaviors. We applied intermittent theta burst stimulation (iTBS) to a region in the posterior parietal cortex (PPC) associated with grasp control to evaluate the interaction between stimulation and brain state. Across two experiments, we demonstrate the immediate responses of motor cortex activity and motor performance to state-dependent parietal stimulation. We randomly assigned 72 healthy adult participants to one of three TMS intervention groups, followed by electrophysiological measures with TMS and behavioral measures. Participants in the first group received iTBS to PPC while performing a grasping task concurrently. Participants in the second group received iTBS to PPC while in a task-free, resting state. A third group of participants received iTBS to a parietal region outside the cortical grasping network while performing a grasping task concurrently. We compared changes in motor cortical excitability and motor performance in the three stimulation groups within an hour of each intervention. We found that parietal stimulation during a behavioral manipulation that activates the cortical grasping network increased downstream motor cortical excitability and improved motor performance relative to stimulation during rest. We conclude that constraining the brain state with a behavioral task during brain stimulation has the potential to optimize plasticity induction in cortical circuit mechanisms that mediate movement processes.

Boosting affective control with bifrontal transcranial direct current stimulation (tDCS): a proof-of-concept study in healthy individuals

Affective control refers to the ability to regulate emotions and is considered a marker of mental health. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, holds promise to enhance affective control. In this between-subjects study in healthy individuals, we investigated the effects of bifrontal tDCS on core processes and higher-level markers of affective control. As such, we assessed direct tDCS effects on emotional interference during an affective control task and indirect effects on an instructed reappraisal task afterward. Results showed that the affective control task combined with active tDCS, compared to sham, resulted in enhanced cognitive emotion regulation. Specifically, participants in the active tDCS condition showed an increased propensity to use reappraisal and were more successful in doing so. Moreover, there was reduced vagally mediated heart rate variability indicative of attenuated emotion and self-regulation, in the sham, but not in the active condition. Surprisingly, there were no effects of tDCS on emotional interference during the affective control task, with Bayesian analyses showing extreme evidence against these effects. Nevertheless, there was a positive association between the emotional interference during the affective control task and participants' reappraisal success afterward for the active, but not the sham tDCS condition. The study offers valuable insights to guide future work on combined tDCS with affective control tasks or training on the ability to regulate emotions.

Prior elicitation for Gaussian spatial process: An application to TMS brain mapping

The power and commensurate prior distributions are informative prior distributions that incorporate historical data as prior knowledge in Bayesian analysis to improve inference about a phenomenon under study. Although these distributions have been developed for analyzing non-spatial data, little or no attention has been given to spatial geostatistical data. In this study, we extend these informative prior distributions to a Gaussian spatial process, which enables the elicitation of prior knowledge from historical geostatistical data for Bayesian analysis. Three informative prior distributions were developed for spatial modeling, and an efficient Markov Chain Monte Carlo algorithm was developed for performing Bayesian analysis. Simulation studies were used to assess the adequacy of the informative prior distributions. Hierarchical models combined with the developed informative prior distributions were applied to analyze transcranial magnetic stimulation (TMS) brain mapping data to gain insights into the spatial pattern of a patient's response to motor cortex stimulation. The study quantified the uncertainty in motor response and found that the primary motor cortex of the hand is responsible for most of the movement of the right first dorsal interosseous muscle. The findings provide a deeper understanding of the neural mechanisms underlying motor function and ultimately aid the improvement of treatment options for individuals with health issues.

Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments

One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.

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.

Noise improves the association between effects of local stimulation and structural degree of brain networks

Stimulation to local areas remarkably affects brain activity patterns, which can be exploited to investigate neural bases of cognitive function and modify pathological brain statuses. There has been growing interest in exploring the fundamental action mechanisms of local stimulation. Nevertheless, how noise amplitude, an essential element in neural dynamics, influences stimulation-induced brain states remains unknown. Here, we systematically examine the effects of local stimulation by using a large-scale biophysical model under different combinations of noise amplitudes and stimulation sites. We demonstrate that noise amplitude nonlinearly and heterogeneously tunes the stimulation effects from both regional and network perspectives. Furthermore, by incorporating the role of the anatomical network, we show that the peak frequencies of unstimulated areas at different stimulation sites averaged across noise amplitudes are highly positively related to structural connectivity. Crucially, the association between the overall changes in functional connectivity as well as the alterations in the constraints imposed by structural connectivity with the structural degree of stimulation sites is nonmonotonically influenced by the noise amplitude, with the association increasing in specific noise amplitude ranges. Moreover, the impacts of local stimulation of cognitive systems depend on the complex interplay between the noise amplitude and average structural degree. Overall, this work provides theoretical insights into how noise amplitude and network structure jointly modulate brain dynamics during stimulation and introduces possibilities for better predicting and controlling stimulation outcomes.

The impact of gamma transcranial alternating current stimulation (tACS) on cognitive and memory processes in patients with mild cognitive impairment or Alzheimer's disease: A literature review

BACKGROUND

Transcranial alternating current stimulation (tACS)-a noninvasive brain stimulation technique that modulates cortical oscillations through entrainment-has been demonstrated to alter oscillatory activity and enhance cognition in healthy adults. TACS is being explored as a tool to improve cognition and memory in patient populations with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

OBJECTIVE

To review the growing body of literature and current findings obtained from the application of tACS in patients with MCI or AD, highlighting the effects of gamma tACS on brain function, memory, and cognition. Evidence on the use of brain stimulation in animal models of AD is also discussed. Important parameters of stimulation are underscored for consideration in protocols that aim to apply tACS as a therapeutic tool in patients with MCI/AD.

FINDINGS

The application of gamma tACS has shown promising results in the improvement of cognitive and memory processes that are impacted in patients with MCI/AD. These data demonstrate the potential for tACS as an interventional stand-alone tool or alongside pharmacological and/or other behavioral interventions in MCI/AD.

CONCLUSIONS

While the use of tACS in MCI/AD has evidenced encouraging results, the effects of this stimulation technique on brain function and pathophysiology in MCI/AD remains to be fully determined. This review explores the literature and highlights the need for continued research on tACS as a tool to alter the course of the disease by reinstating oscillatory activity, improving cognitive and memory processing, delaying disease progression, and remediating cognitive abilities in patients with MCI/AD.

Learning at your brain's rhythm: individualized entrainment boosts learning for perceptual decisions

Training is known to improve our ability to make decisions when interacting in complex environments. However, individuals vary in their ability to learn new tasks and acquire new skills in different settings. Here, we test whether this variability in learning ability relates to individual brain oscillatory states. We use a visual flicker paradigm to entrain individuals at their own brain rhythm (i.e. peak alpha frequency) as measured by resting-state electroencephalography (EEG). We demonstrate that this individual frequency-matched brain entrainment results in faster learning in a visual identification task (i.e. detecting targets embedded in background clutter) compared to entrainment that does not match an individual's alpha frequency. Further, we show that learning is specific to the phase relationship between the entraining flicker and the visual target stimulus. EEG during entrainment showed that individualized alpha entrainment boosts alpha power, induces phase alignment in the pre-stimulus period, and results in shorter latency of early visual evoked potentials, suggesting that brain entrainment facilitates early visual processing to support improved perceptual decisions. These findings suggest that individualized brain entrainment may boost perceptual learning by altering gain control mechanisms in the visual cortex, indicating a key role for individual neural oscillatory states in learning and brain plasticity.

Can a single session of noninvasive brain stimulation applied over the prefrontal cortex prevent stress-induced cortisol release?

INTRODUCTION

A better understanding of how the hypothalamic-pituitary-adrenal (HPA) axis can be externally regulated is of major importance, especially because hyperreactivity to stress has been proposed as a key factor in the onset and maintenance of many psychiatric conditions. Over the past decades, numerous studies have investigated whether non-invasive brain stimulation (NIBS) can regulate HPA axis reactivity in acute stress situation. As the current results did not allow us to draw clear conclusions, we decided to conduct a systematic review of the literature investigating the effect of a single NIBS session on stress-induced cortisol release.

METHODS

We searched MEDLINE and Web Of Science for articles indexed through December 2021. Among the 246 articles identified, 15 fulfilled our inclusion criteria with a quality estimated between 52 and 93%.

RESULTS

Of the different NIBS used and targeted brain regions, stimulating the left dorsolateral prefrontal cortex, with either high frequency repetitive transcranial magnetic stimulation or anodal transcranial direct current stimulation, seems to be the most appropriate for reducing cortisol release in acute stress situations.

CONCLUSIONS

Despite the heterogeneity of the stimulation parameters, the characteristics of participants, the modalities of cortisol collection, the timing of the NIBS session in relation to the stressor exposure, and methodological considerations, stimulating the left dorsolateral prefrontal cortex can be efficient to modulate stress-induced cortisol release.

Transcranial ultrasound stimulation modulates the interhemispheric balance of excitability in human motor cortex

Background. Low-intensity transcranial ultrasound stimulation (TUS) could induce both immediate and long-lasting neuromodulatory effects in human brains. Interhemispheric imbalance at prefrontal or motor cortices generally associates with various cognitive decline in aging and mental disorders. However, whether TUS could modulate the interhemispheric balance of excitability in human brain remains unknown.Objective. This study aims to explore whether repetitive TUS (rTUS) intervention can modulate the interhemispheric balance of excitability between bilateral motor cortex (M1) in healthy subjects.Approach. Motor evoked potentials (MEPs) at bilateral M1 were measured at 15 min and 0 min before a 15 min active or sham rTUS intervention on left M1 and at 0 min, 15 min and 30 min after the intervention, and the Chinese version of brief neurocognitive test battery (C-BCT) was conducted before and after the intervention respectively. Cortical excitability was quantified by MEPs, and the long-lasting changes of MEP amplitude was used as an index of plasticity.Results. In the active rTUS group (n= 20), the ipsilateral MEP amplitude increased significantly compared with baselines and lasted for up to 30 min after intervention, while the contralateral MEP amplitude decreased lasting for 15 min, yielding increased laterality between bilateral MEPs. Furthermore, rTUS intervention induced changes in some C-BCT scores, and the changes of scores correlated with the changes of MEP amplitudes induced by rTUS intervention. The sham rTUS group (n= 20) showed no significant changes in MEPs and C-BCT scores. In addition, no participants reported any adverse effects during and after the rTUS intervention, and no obvious temperature increase appeared in skull or brain tissues in simulation.Significance. rTUS intervention modulated the plasticity of ipsilateral M1 and the interhemispheric balance of M1 excitability in human brain, and improved cognitive performance, suggesting a considerable potential of rTUS in clinical interventions.

Optimization of phase prediction for brain-state dependent stimulation: a grid-search approach

Objective.Sources of heterogeneity in non-invasive brain stimulation literature can be numerous, with underlying brain states and protocol differences at the top of the list. Yet, incoherent results from brain-state-dependent stimulation experiments suggest that there are further factors adding to the variance. Hypothesizing that different signal processing pipelines might be partly responsible for heterogeneity; we investigated their effects on brain-state forecasting approaches.Approach.A grid-search was used to determine the fastest and most-accurate combination of preprocessing parameters and phase-forecasting algorithms. The grid-search was applied on a synthetic dataset and validated on electroencephalographic (EEG) data from a healthy (n= 18) and stroke (n= 31) cohort.Main results.Differences in processing pipelines led to different results; the grid-search chosen pipelines significantly increased the accuracy of published forecasting methods. The accuracy achieved in healthy was comparably high in stroke patients.Significance.This systematic offline analysis highlights the importance of the specific EEG processing and forecasting pipelines used for online state-dependent setups where precision in phase prediction is critical. Moreover, successful results in the stroke cohort pave the way to test state-dependent interventional treatment approaches.

Transcranial electrical stimulation: How can a simple conductor orchestrate complex brain activity?

Transcranial electrical stimulation (tES) is one of the oldest and yet least understood forms of brain stimulation. The idea that a weak electrical stimulus, applied outside the head, can meaningfully affect neural activity is often regarded as mysterious. Here, we argue that the direct effects of tES are not so mysterious: Extensive data from a wide range of model systems shows it has appreciable effects on the activity of individual neurons. Instead, the real mysteries are how tES interacts with the brain's own activity and how these dynamics can be controlled to produce desirable therapeutic effects. These are challenging problems, akin to repairing a complex machine while it is running, but they are not unique to tES or even neuroscience. We suggest that models of coupled oscillators, a common tool for studying interactions in other fields, may provide valuable insights. By combining these tools with our growing, interdisciplinary knowledge of brain dynamics, we are now in a good position to make progress in this area and meet the high demand for effective neuromodulation in neuroscience and psychiatry.

Revisiting the Rotational Field TMS Method for Neurostimulation

Transcranial magnetic stimulation (TMS) is a non-invasive technique that has shown high efficacy in the treatment of major depressive disorder (MDD) and is increasingly utilized for various neuropsychiatric disorders. However, conventional TMS is limited to activating only a small fraction of neurons that have components parallel to the induced electric field. This likely contributes to the significant variability observed in clinical outcomes. A novel method termed rotational field TMS (rfTMS or TMS 360°) enables the activation of a greater number of neurons by reducing the sensitivity to orientation. Recruitment of a larger number of neurons offers the potential to enhance efficacy and reduce variability in the treatment of clinical indications for which neuronal recruitment and organization may play a significant role, such as MDD and stroke. The potential of the method remains to be validated in clinical trials. Here, we revisit and describe in detail the rfTMS method, its principles, mode of operation, effects on the brain, and potential benefits for clinical TMS.

A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning

Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness - detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework's decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.

The hidden brain-state dynamics of tACS aftereffects

Non-invasive techniques to electrically stimulate the brain such as transcranial direct and alternating current stimulation (tDCS/tACS) are increasingly used in human neuroscience and offer potential new avenues to treat brain disorders. Previous research has shown that stimulation effects may depend on brain-states. However, this work mostly focused on experimentally induced brain-states over the course of several minutes. Besides such global, long-term changes in brain-states, previous research suggests, that the brain is likely to spontaneously alternate between states in sub-second ranges, which is much closer to the time scale at which it is generally believed to operate. Here, we utilized Hidden Markov Models (HMM) to decompose magnetoencephalography data obtained before and after tACS into spontaneous, transient brain-states with distinct spatial, spectral and connectivity profiles. Only one out of four spontaneous brain-states, likely reflecting default mode network activity, showed evidence for an effect of tACS on the power of spontaneous α-oscillations. The identified state appears to disproportionally drive the overall (non-state resolved) tACS effect. No or only marginal effects were found in the remaining states. We found no evidence that tACS influenced the time spent in each state. Although stimulation was applied continuously, our results indicate that spontaneous brain-states and their underlying functional networks differ in their susceptibility to tACS. Global stimulation aftereffects may be disproportionally driven by distinct time periods during which the susceptible state is active. Our results may pave the ground for future work to understand which features make a specific brain-state susceptible to electrical stimulation.

Phase matters when there is power: Phasic modulation of corticospinal excitability occurs at high amplitude sensorimotor mu-oscillations

Prior studies have suggested that oscillatory activity in cortical networks can modulate stimulus-evoked responses through time-varying fluctuations in neural excitation-inhibition dynamics. Studies combining transcranial magnetic stimulation (TMS) with electromyography (EMG) and electroencephalography (EEG) can provide direct measurements to examine how instantaneous fluctuations in cortical oscillations contribute to variability in TMS-induced corticospinal responses. However, the results of these studies have been conflicting, as some reports showed consistent phase effects of sensorimotor mu-rhythms with increased excitability at the negative mu peaks, while others failed to replicate these findings or reported unspecific mu-phase effects across subjects. Given the lack of consistent results, we systematically examined the modulatory effects of instantaneous and pre-stimulus sensorimotor mu-rhythms on corticospinal responses with offline EEG-based motor evoked potential (MEP) classification analyses across five identical visits. Instantaneous sensorimotor mu-phase or pre-stimulus mu-power alone did not significantly modulate MEP responses. Instantaneous mu-power analyses showed weak effects with larger MEPs during high-power trials at the overall group level analyses, but this trend was not reproducible across visits. However, TMS delivered at the negative peak of high magnitude mu-oscillations generated the largest MEPs across all visits, with significant differences compared to other peak-phase combinations. High power effects on MEPs were only observed at the trough phase of ongoing mu oscillations originating from the stimulated region, indicating site and phase specificity, respectively. More importantly, such phase-dependent power effects on corticospinal excitability were reproducible across multiple visits. We provide further evidence that fluctuations in corticospinal excitability indexed by MEP amplitudes are partially driven by dynamic interactions between the magnitude and the phase of ongoing sensorimotor mu oscillations at the time of TMS, and suggest promising insights for (re)designing neuromodulatory TMS protocols targeted to specific cortical oscillatory states.

Real-time stimulation during sleep: prior findings, novel developments, and future perspectives

Real-time brain stimulation is a powerful technique that continues to gain importance in the field of sleep and cognition. In this special issue, we collected 14 articles about real-time stimulation during sleep, including one review, 12 research articles and one letter covering both human and rodent research from various fields. We hope this special issue sparks greater interest and inspires fellow sleep researchers and clinicians to develop new ideas in the exciting topic of real-time stimulation.

Automated real-time EEG sleep spindle detection for brain-state-dependent brain stimulation

Sleep spindles are a hallmark electroencephalographic feature of non-rapid eye movement sleep, and are believed to be instrumental for sleep-dependent memory reactivation and consolidation. However, direct proof of their causal relevance is hard to obtain, and our understanding of their immediate neurophysiological consequences is limited. To investigate their causal role, spindles need to be targeted in real-time with sensory or non-invasive brain-stimulation techniques. While fully automated offline detection algorithms are well established, spindle detection in real-time is highly challenging due to their spontaneous and transient nature. Here, we present the real-time spindle detector, a robust multi-channel electroencephalographic signal-processing algorithm that enables the automated triggering of stimulation during sleep spindles in a phase-specific manner. We validated the real-time spindle detection method by streaming pre-recorded sleep electroencephalographic datasets to a real-time computer system running a Simulink® Real-Time™ implementation of the algorithm. Sleep spindles were detected with high levels of Sensitivity (~83%), Precision (~78%) and a convincing F1-Score (~81%) in reference to state-of-the-art offline algorithms (which reached similar or lower levels when compared with each other), for both naps and full nights, and largely independent of sleep scoring information. Detected spindles were comparable in frequency, duration, amplitude and symmetry, and showed the typical time-frequency characteristics as well as a centroparietal topography. Spindles were detected close to their centre and reliably at the predefined target phase. The real-time spindle detection algorithm therefore empowers researchers to target spindles during human sleep, and apply the stimulation method and experimental paradigm of their choice.

Frontoparietal network activation is associated with motor recovery in ischemic stroke patients

Strokes cause lesions that damage brain tissue, disrupt normal brain activity patterns and can lead to impairments in motor function. Although modulation of cortical activity is central to stimulation-based rehabilitative therapies, aberrant and adaptive patterns of brain activity after stroke have not yet been fully characterized. Here, we apply a brain dynamics analysis approach to study longitudinal brain activity patterns in individuals with ischemic pontine stroke. We first found 4 commonly occurring brain states largely characterized by high amplitude activations in the visual, frontoparietal, default mode, and motor networks. Stroke subjects spent less time in the frontoparietal state compared to controls. For individuals with dominant-hand CST damage, more time spent in the frontoparietal state from 1 week to 3-6 months post-stroke was associated with better motor recovery over the same time period, an association which was independent of baseline impairment. Furthermore, the amount of time spent in brain states was linked empirically to functional connectivity. This work suggests that when the dominant-hand CST is compromised in stroke, resting state configurations may include increased activation of the frontoparietal network, which may facilitate compensatory neural pathways that support recovery of motor function when traditional motor circuits of the dominant-hemisphere are compromised.

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.

Detection of Transcranial Alternating Current Stimulation Aftereffects Is Improved by Considering the Individual Electric Field Strength and Self-Rated Sleepiness

Non-invasive electrical stimulation methods, such as transcranial alternating current stimulation (tACS), are increasingly used in human neuroscience research and offer potential new avenues to treat neurological and psychiatric disorders. However, their often variable effects have also raised concerns in the scientific and clinical communities. This study aims to investigate the influence of subject-specific factors on the alpha tACS-induced aftereffect on the alpha amplitude (measured with electroencephalography, EEG) as well as on the connectivity strength between nodes of the default mode network (DMN) [measured with functional magnetic resonance imaging (fMRI)]. As subject-specific factors we considered the individual electrical field (EFIELD) strength at target regions in the brain, the frequency mismatch between applied stimulation and individual alpha frequency (IAF) and as a covariate, subject’s changes in mental state, i.e., sleepiness. Eighteen subjects participated in a tACS and a sham session conducted on different days. Each session consisted of three runs (pre/stimulation/). tACS was applied during the second run at each subject’s individual alpha frequency (IAF), applying 1 mA peak-to-peak intensity for 7 min, using an occipital bihemispheric montage. In every run, subjects watched a video designed to increase in-scanner compliance. To investigate the aftereffect of tACS on EEG alpha amplitude and on DMN connectivity strength, EEG data were recorded simultaneously with fMRI data. Self-rated sleepiness was documented using a questionnaire. Conventional statistics (ANOVA) did not show a significant aftereffect of tACS on the alpha amplitude compared to sham stimulation. Including individual EFIELD strengths and self-rated sleepiness scores in a multiple linear regression model, significant tACS-induced aftereffects were observed. However, the subject-wise mismatch between tACS frequency and IAF had no contribution to our model. Neither standard nor extended statistical methods confirmed a tACS-induced aftereffect on DMN functional connectivity. Our results show that it is possible and necessary to disentangle alpha amplitude changes due to intrinsic mechanisms and to external manipulation using tACS on the alpha amplitude that might otherwise be overlooked. Our results suggest that EFIELD is really the most significant factor that explains the alpha amplitude modulation during a tACS session. This knowledge helps to understand the variability of the tACS-induced aftereffects.

Breaking the boundaries of interacting with the human brain using adaptive closed-loop stimulation

The human brain is arguably one of the most complex systems in nature. To understand how it operates, it is essential to understand the link between neural activity and behavior. Experimental investigation of that link requires tools to interact with neural activity during behavior. Human neuroscience, however, has been severely bottlenecked by the limitations of these tools. While invasive methods can support highly specific interaction with brain activity during behavior, their applicability in human neuroscience is limited. Despite extensive development in the last decades, noninvasive alternatives have lacked spatial specificity and yielded results that are commonly fraught with variability and replicability issues, along with relatively limited understanding of the neural mechanisms involved. Here we provide a comprehensive review of the state-of-the-art in interacting with human brain activity and highlight current limitations and recent efforts to overcome these limitations. Beyond crucial technical and scientific advancements in electromagnetic brain stimulation, new frontiers in interacting with human brain activity such as task-irrelevant sensory stimulation and focal ultrasound stimulation are introduced. Finally, we argue that, along with technological improvements and breakthroughs in noninvasive methods, a paradigm shift towards adaptive closed-loop stimulation will be a critical step for advancing human neuroscience.

Stimulation Parameters Used During Repetitive Transcranial Magnetic Stimulation for Motor Recovery and Corticospinal Excitability Modulation in SCI: A Scoping Review

There is a growing interest in non-invasive stimulation interventions as treatment strategies to improve functional outcomes and recovery after spinal cord injury (SCI). Repetitive transcranial magnetic stimulation (rTMS) is a neuromodulatory intervention which has the potential to reinforce the residual spinal and supraspinal pathways and induce plasticity. Recent reviews have highlighted the therapeutic potential and the beneficial effects of rTMS on motor function, spasticity, and corticospinal excitability modulation in SCI individuals. For this scoping review, we focus on the stimulation parameters used in 20 rTMS protocols. We extracted the rTMS parameters from 16 published rTMS studies involving SCI individuals and were able to infer preliminary associations between specific parameters and the effects observed. Future investigations will need to consider timing, intervention duration and dosage (in terms of number of sessions and number of pulses) that may depend on the stage, the level, and the severity of the injury. There is a need for more real vs. sham rTMS studies, reporting similar designs with sufficient information for replication, to achieve a significant level of evidence regarding the use of rTMS in SCI.

A little goes a long way: Neurobiological effects of low intensity rTMS and implications for mechanisms of rTMS

Repetitive transcranial magnetic stimulation (rTMS) is a widespread technique in neuroscience and medicine, however its mechanisms are not well known. In this review, we consider intensity as a key therapeutic parameter of rTMS, and review the studies that have examined the biological effects of rTMS using magnetic fields that are orders of magnitude lower that those currently used in the clinic. We discuss how extensive characterisation of "low intensity" rTMS has set the stage for translation of new rTMS parameters from a mechanistic evidence base, with potential for innovative and effective therapeutic applications. Low-intensity rTMS demonstrates neurobiological effects across healthy and disease models, which include depression, injury and regeneration, abnormal circuit organisation, tinnitus etc. Various short and long-term changes to metabolism, neurotransmitter release, functional connectivity, genetic changes, cell survival and behaviour have been investigated and we summarise these key changes and the possible mechanisms behind them. Mechanisms at genetic, molecular, cellular and system levels have been identified with evidence that low-intensity rTMS and potentially rTMS in general acts through several key pathways to induce changes in the brain with modulation of internal calcium signalling identified as a major mechanism. We discuss the role that preclinical models can play to inform current clinical research as well as uncover new pathways for investigation.

P300 Modulation via Transcranial Alternating Current Stimulation in Adult Attention-Deficit/Hyperactivity Disorder: A Crossover Study

OBJECTIVE

A repeated finding regarding event-related potentials (ERPs) is that patients with ADHD show a reduced P300 amplitude. This raises the question of whether the attention of ADHD patients can be increased by stabilizing the P300. Assuming that the P300 is generated by event-related oscillations (EROs) in the low frequency range (0-8 Hz), one approach to increase the P300 could be to stimulate the patient's P300 underlying ERO by means of transcranial alternating current stimulation (tACS). The aim of this follow-up study was to investigate this hypothesized mechanism of action in adult ADHD patients.

MATERIALS AND METHODS

Undergoing a crossover design, 20 adult ADHD patients (10 female) received an actual stimulation via tACS on one day and a sham stimulation on another day. Before and after each intervention, EEG characteristics (P300 amplitudes, low frequency power) and attention performances (d2 attention test, visual oddball task (VOT)) were recorded.

RESULTS

Electrophysiological analyses revealed no evidence for an enhanced P300 amplitude or low frequency power increase after actual stimulation compared to sham stimulation. Instead, a significant effect was found for a stronger N700 amplitude increase after actual stimulation compared to sham stimulation. Consistent with the P300 null results, none of the examined neuropsychological performance measures indicated a tACS-induced improvement in attentional ability.

CONCLUSION

Contrary to a previous study using tACS to modulate the P300 in adult ADHD patients, the current study yields no evidence that tACS can increase the P300 amplitude in adult ADHD patients and that such P300 enhancement can directly improve neuropsychological parameters of attention.

Spontaneous Fluctuations in Oscillatory Brain State Cause Differences in Transcranial Magnetic Stimulation Effects Within and Between Individuals

Transcranial magnetic stimulation (TMS) can cause measurable effects on neural activity and behavioral performance in healthy volunteers. In addition, TMS is increasingly used in clinical practice for treating various neuropsychiatric disorders. Unfortunately, TMS-induced effects show large intra- and inter-subject variability, hindering its reliability, and efficacy. One possible source of this variability may be the spontaneous fluctuations of neuronal oscillations. We present recent studies using multimodal TMS including TMS-EMG (electromyography), TMS-tACS (transcranial alternating current stimulation), and concurrent TMS-EEG-fMRI (electroencephalography, functional magnetic resonance imaging), to evaluate how individual oscillatory brain state affects TMS signal propagation within targeted networks. We demonstrate how the spontaneous oscillatory state at the time of TMS influences both immediate and longer-lasting TMS effects. These findings indicate that at least part of the variability in TMS efficacy may be attributable to the current practice of ignoring (spontaneous) oscillatory fluctuations during TMS. Ignoring this state-dependent spread of activity may cause great individual variability which so far is poorly understood and has proven impossible to control. We therefore also compare two technical solutions to directly account for oscillatory state during TMS, namely, to use (a) tACS to externally control these oscillatory states and then apply TMS at the optimal (controlled) brain state, or (b) oscillatory state-triggered TMS (closed-loop TMS). The described multimodal TMS approaches are paramount for establishing more robust TMS effects, and to allow enhanced control over the individual outcome of TMS interventions aimed at modulating information flow in the brain to achieve desirable changes in cognition, mood, and behavior.

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder

Background: Major depressive disorder (MDD) is a severe mental illness marked by a continuous sense of sadness and a loss of interest. The default mode network (DMN) is a group of brain areas that are more active during rest and deactivate when engaged in task-oriented activities. The DMN of MDD has been found to have aberrant static functional network connectivity (FNC) in recent studies. In this work, we extend previous findings by evaluating dynamic functional network connectivity (dFNC) within the DMN subnodes in MDD. Methods: We analyzed resting-state functional magnetic resonance imaging data of 262 patients with MDD and 277 healthy controls (HCs). We estimated dFNCs for seven subnodes of the DMN, including the anterior cingulate cortex (ACC), posterior cingulate cortex (PCC), and precuneus (PCu), using a sliding window approach, and then clustered the dFNCs into five brain states. Classification of MDD and HC subjects based on state-specific FC was performed using a logistic regression classifier. Transition probabilities between dFNC states were used to identify relationships between symptom severity and dFNC data in MDD patients. Results: By comparing state-specific FNC between HC and MDD, a disrupted connectivity pattern was observed within the DMN. In more detail, we found that the connectivity of ACC is stronger, and the connectivity between PCu and PCC is weaker in individuals with MDD than in those of HC subjects. In addition, MDD showed a higher probability of transitioning from a state with weaker ACC connectivity to a state with stronger ACC connectivity, and this abnormality is associated with symptom severity. This is the first research to look at the dFC of the DMN in MDD with a large sample size. It provides novel evidence of abnormal time-varying DMN configuration in MDD and offers links to symptom severity in MDD subjects. Impact Statement This study is the first attempt that explored the temporal change on default mode network (DMN) connectivity in a relatively large cohort of patients with major depressive disorder (MDD). We also introduced a new hypothesis that explains the inconsistency in DMN functional network connectivity (FNC) comparison between MDD and healthy control based on static FNC in the previous literature. Additionally, our findings suggest that within anterior cingulate cortex connectivity and the connectivity between the precuneus and posterior cingulate cortex are the potential biomarkers for the future intervention of MDD.

The Brain Electrophysiological recording & STimulation (BEST) toolbox

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.