Timing is everything: Event-related transcranial direct current stimulation improves motor adaptation.

BACKGROUND: There is a current discord between the foundational theories underpinning motor learning and how we currently apply transcranial direct current stimulation (TDCS): the former is dependent on tight coupling of events while the latter is conducted with very low temporal resolution. OBJECTIVE: Here we aimed to investigate the temporal specificity of stimulation by applying TDCS in short epochs, and coincidentally with movement, during a motor adaptation task. METHODS: Participants simultaneously adapted a reaching movement to two opposing velocity-dependent force-fields (clockwise and counter-clockwise), distinguished by a contextual leftward or rightward shift in the task display and cursor location respectively. Brief bouts (<3 s) of event-related TDCS (er-TDCS) were applied over M1 or the cerebellum during movements for only one of these learning contexts. RESULTS: We show that when short duration stimulation is applied to the cerebellum and yoked to movement, only those reaching movements performed simultaneously with stimulation are selectively enhanced, whilst similar and interleaved movements are left unaffected. We found no evidence of improved adaptation following M1 er-TDCS, as participants displayed equivalent levels of error during both stimulated and unstimulated movements. Similarly, participants in the sham stimulation group adapted comparably during left and right-shift trials. CONCLUSIONS: It is proposed that the coupling of cerebellar stimulation and movement influences timing-dependent (i.e. Hebbian-like) mechanisms of plasticity to facilitate enhanced learning in the stimulated context.

Residual errors in visuomotor adaptation persist despite extended motor preparation periods.

A consistent finding in sensorimotor adaptation is a persistent undershoot of full compensation, such that performance asymptotes with residual errors greater than seen at baseline. This behavior has been attributed to limiting factors within the implicit adaptation system, which reaches a suboptimal equilibrium between trial-by-trial learning and forgetting. However, recent research has suggested that allowing longer motor planning periods prior to movement eliminates these residual errors. The additional planning time allows required cognitive processes to be completed before movement onset, thus increasing accuracy. Here, we looked to extend these findings by investigating the relationship between increased motor preparation time and the size of imposed visuomotor rotation (30°, 45°, or 60°), with regard to the final asymptotic level of adaptation. We found that restricting preparation time to 0.35 s impaired adaptation for moderate and larger rotations, resulting in larger residual errors compared to groups with additional preparation time. However, we found that even extended preparation time failed to eliminate persistent errors, regardless of magnitude of cursor rotation. Thus, the asymptote of adaptation was significantly less than the degree of imposed rotation, for all experimental groups. In addition, there was a positive relationship between asymptotic error and implicit retention. These data suggest that a prolonged motor preparation period is insufficient to reliably achieve complete adaptation, and therefore, our results suggest that factors beyond that of planning time contribute to asymptotic adaptation levels.NEW & NOTEWORTHY Residual errors in sensorimotor adaptation are commonly attributed to an equilibrium between trial-by-trial learning and forgetting. Recent research suggested that allowing sufficient time for mental rotation eliminates these errors. In a number of experimental conditions, we show that although restricted motor preparation time does limit adaptation-consistent with mental rotation-extending preparation time fails to eliminate the residual errors in motor adaptation.

Sensory Attenuation in Sport and Rehabilitation: Perspective from Research in Parkinson's Disease.

People with Parkinson's disease (PD) experience motor symptoms that are affected by sensory information in the environment. Sensory attenuation describes the modulation of sensory input caused by motor intent. This appears to be altered in PD and may index important sensorimotor processes underpinning PD symptoms. We review recent findings investigating sensory attenuation and reconcile seemingly disparate results with an emphasis on task-relevance in the modulation of sensory input. Sensory attenuation paradigms, across different sensory modalities, capture how two identical stimuli can elicit markedly different perceptual experiences depending on our predictions of the event, but also the context in which the event occurs. In particular, it appears as though contextual information may be used to suppress or facilitate a response to a stimulus on the basis of task-relevance. We support this viewpoint by considering the role of the basal ganglia in task-relevant sensory filtering and the use of contextual signals in complex environments to shape action and perception. This perspective highlights the dual effect of basal ganglia dysfunction in PD, whereby a reduced capacity to filter task-relevant signals harms the ability to integrate contextual cues, just when such cues are required to effectively navigate and interact with our environment. Finally, we suggest how this framework might be used to establish principles for effective rehabilitation in the treatment of PD.

Direct and indirect effects of cathodal cerebellar TDCS on visuomotor adaptation of hand and arm movements.

Adaptation of movements involving the proximal and distal upper-limb can be differentially facilitated by anodal transcranial direct current stimulation (TDCS) over the cerebellum and primary motor cortex (M1). Here, we build on this evidence by demonstrating that cathodal TDCS impairs motor adaptation with a differentiation of the proximal and distal upper-limbs, relative to the site of stimulation. Healthy young adults received M1 or cerebellar cathodal TDCS while making fast 'shooting' movements towards targets under 60° rotated visual feedback conditions, using either whole-arm reaching or fine hand and finger movements. As predicted, we found that cathodal cerebellar TDCS resulted in impairment of adaptation of movements with the whole arm compared to M1 and sham groups, which proved significantly different during late adaptation. However, cathodal cerebellar TDCS also significantly enhanced adaptation of hand movements, which may reflect changes in the excitability of the pathway between the cerebellum and M1. We found no evidence for change of adaptation rates using arm or finger movements following cathodal TDCS directly over M1. These results are further evidence to support movement specific effects of TDCS, and highlight how the connectivity and functional organisation of the cerebellum and M1 must be considered when designing TDCS-based therapies.

Investigating the role of phase-synchrony during encoding of episodic memories using electrical stimulation.

The multi-sensory nature of episodic memories indicates that communication between a multitude of brain areas is required for their effective creation and recollection. Previous studies have suggested that the effectiveness of memory processes depends on theta synchronization (4 Hz) of sensory areas relevant to the memory. This study aimed to manipulate theta synchronization between different sensory areas in order to further test this hypothesis. We intend to entrain visual cortex with 4 Hz alternating current stimulation (tACS), while simultaneously entraining auditory cortex with 4 Hz amplitude-modulated sounds. By entraining these different sensory areas, which pertain to learned audio-visual memory associations, we expect to find that when theta is synchronized across the different sensory areas, the memory performance would be enhanced compared to when theta is not synchronized across the sensory areas. We found no evidence for such an effect in this study. It is unclear whether this is due to an inability of 4 Hz tACS to entrain the visual cortex reliably, or whether sensory entrainment is not the underlying mechanism required for episodic memory.

Pedunculopontine Nucleus Microstructure Predicts Postural and Gait Symptoms in Parkinson's Disease.

BACKGROUND: There is an urgent need to identify individuals at risk of postural instability and gait difficulties, and the resulting propensity for falls, in Parkinson's disease. OBJECTIVES: Given known relationships between posture and gait and degeneration of the cholinergic pedunculopontine nucleus, we investigated whether metrics of pedunculopontine nucleus microstructural integrity hold independent utility for predicting future postural instability and gait difficulties and whether they could be combined with other candidate biomarkers to improve prognostication of these symptoms. METHODS: We used stereotactic mapping of the pedunculopontine nucleus and diffusion tensor imaging to extract baseline pedunculopontine nucleus diffusivity metrics in 147 participants with Parkinson's disease and 65 controls enrolled in the Parkinson's Progression Markers Initiative. We also recorded known candidate markers of posture and gait changes: loss of caudate dopamine and CSF ß-amyloid 1-42 levels at baseline; as well as longitudinal progression motor symptoms over 72-months. RESULTS: Survival analyses revealed that reduced dopamine in the caudate and increased axial diffusivity in the pedunculopontine nucleus incurred independent risk of postural instability and gait difficulties. Binary logistic regression and receiver operating characteristics analysis in 117 participants with complete follow-up data at 60 months revealed that only pedunculopontine nucleus microstructure provided more accurate discriminative ability for predicting future postural instability and gait difficulties than clinical and demographic variables alone. CONCLUSION: Dopaminergic and cholinergic loss incur independent risk for future postural instability and gait difficulties, and pedunculopontine nucleus microstructure can be used to prognosticate these symptoms from early Parkinson's disease stages. © 2020 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Targeted tDCS selectively improves motor adaptation with the proximal and distal upper limb.

BACKGROUND: The cerebellum and primary motor cortex (M1) are crucial to coordinated and accurate movements of the upper limbs. There is also appreciable evidence that these two structures exert somewhat divergent influences upon proximal versus distal upper limb control. Here, we aimed to differentially regulate the contribution of the cerebellum and M1 to proximal and distal effectors during motor adaptation, with transcranial direct current stimulation (tDCS). For this, we employed tasks that promote similar motor demands, but isolate whole arm from hand/finger movements, in order to functionally segregate the hierarchy of upper limb control. METHODS: Both young and older adults took part in a visuomotor rotation task; where they adapted to a 60° visuomotor rotation using either a hand-held joystick (requiring finger/hand movements) or a 2D robotic manipulandum (requiring whole-arm reaching movements), while M1, cerebellar or sham tDCS was applied. RESULTS: We found that cerebellar stimulation improved adaptation performance when arm movements were required to complete the task, while in contrast stimulation of M1 enhanced adaptation during hand and finger movements only. This double-dissociation was replicated in an independent group of older adults, demonstrating that the behaviour remains intact in ageing. CONCLUSIONS: These results suggest that stimulation of distinct motor areas can selectively improve motor adaptation in the proximal and distal upper limb. This also highlights new ways in which tDCS might be best applied to achieve reliable rehabilitation of upper limb motor deficits.

The perils of learning to move while speaking: One-sided interference between speech and visuomotor adaptation.

Our understanding of the adaptive processes that shape sensorimotor behavior is largely derived from studying isolated movements. Studies of visuomotor adaptation, in which participants adapt cursor movements to rotations of the cursor's screen position, have led to prominent theories of motor control. In response to changes in visual feedback of movements, explicit (cognitive) and implicit (automatic) learning processes adapt movements to counter errors. However, movements rarely occur in isolation. The extent to which explicit and implicit processes drive sensorimotor adaptation when multiple movements occur simultaneously, as in the real world, remains unclear. Here we address this problem in the context of speech and hand movements. Participants spoke in-time with rapid, hand-driven cursor movements. Using real-time alterations of vowel sound feedback, and visual rotations of the cursor's screen position, we induced sensorimotor adaptation in one or both movements simultaneously. Across three experiments (n = 60, n = 48 and n = 76, respectively), we demonstrate that visuomotor adaptation is markedly impaired by simultaneous speech adaptation, and the impairment is specific to the explicit learning process in visuomotor adaptation. In contrast, visuomotor adaptation had no impact on speech adaptation. The results demonstrate that the explicit learning process in visuomotor adaptation is sensitive to movements in other motor domains. They suggest that some forms of speech adaptation may lack an explicit learning process altogether.

The pedunculopontine region and breathing in Parkinson's disease.

OBJECTIVE: Respiratory abnormalities such as upper airway obstruction are common in Parkinson's disease (PD) and are an important cause of mortality and morbidity. We tested the effect of pedunculopontine region (PPNr) stimulation on respiratory maneuvers in human participants with PD, and separately recorded PPNr neural activity reflected in the local field potential (LFP) during these maneuvers. METHODS: Nine patients with deep brain stimulation electrodes in PPNr, and seven in globus pallidus interna (GPi) were studied during trials of maximal inspiration followed by forced expiration with stimulation OFF and ON. Local field potentials (LFPs) were recorded in the unstimulated condition. RESULTS: PEFR increased from 6.41 ± 0.63 L/sec in the OFF stimulation state to 7.5 L ± 0.65 L/sec in the ON stimulation state (z = -2.666, df = 8, P = 0.024). Percentage improvement in PEFR was strongly correlated with proximity of the stimulated electrode contact to the mesencephalic locomotor region in the rostral PPN (r = 0.814, n = 9, P = 0.008). Mean PPNr LFP power increased within the alpha band (7-11 Hz) during forced respiratory maneuvers (1.63 ± 0.16 µV2/Hz) compared to resting breathing (0.77 ± 0.16 µV2/Hz; z = -2.197, df = 6, P = 0.028). No changes in alpha activity or spirometric indices were seen with GPi recording or stimulation. Percentage improvement in PEFR was strongly positively correlated with increase in alpha power (r = 0.653, n = 14 (7 PPNr patients recorded bilaterally), P = 0.0096). INTERPRETATION: PPNr stimulation in PD improves indices of upper airway function. Increased alpha-band activity is seen within the PPNr during forced respiratory maneuvers. Our findings suggest a link between the PPNr and respiratory performance in PD.

Memory deficits in Parkinson's disease are associated with reduced beta power modulation.

There is an increasing recognition of the significant non-motor symptoms that burden people with Parkinson's disease. As such, there is a pressing need to better understand and investigate the mechanisms underpinning these non-motor deficits. The electrical activity within the brains of people with Parkinson's disease is known to exhibit excessive power within the beta range (12-30 Hz), compared with healthy controls. The weight of evidence suggests that this abnormally high level of beta power is the cause of bradykinesia and rigidity in Parkinson's disease. However, less is known about how the abnormal beta rhythms seen in Parkinson's disease impact on non-motor symptoms. In healthy adults, beta power decreases are necessary for successful episodic memory formation, with greater power decreases during the encoding phase predicting which words will subsequently be remembered. Given the raised levels of beta activity in people with Parkinson's disease, we hypothesized that the necessary decrease in power during memory encoding would be diminished and that this would interfere with episodic memory formation. Accordingly, we conducted a cross-sectional, laboratory-based experimental study to investigate whether there was a direct relationship between decreased beta modulation and memory formation in Parkinson's disease. Electroencephalography recordings were made during an established memory-encoding paradigm to examine brain activity in a cohort of adults with Parkinson's disease (N = 28, 20 males) and age-matched controls (N = 31, 18 males). The participants with Parkinson's disease were aged 65 ± 6 years, with an average disease duration of 6 ± 4 years, and tested on their normal medications to avoid the confound of exacerbated motor symptoms. Parkinson's disease participants showed impaired memory strength (P = 0.023) and reduced beta power decreases (P = 0.014) relative to controls. Longer disease duration was correlated with a larger reduction in beta modulation during encoding, and a concomitant reduction in memory performance. The inability to sufficiently decrease beta activity during semantic processing makes it a likely candidate to be the central neural mechanism underlying this type of memory deficit in Parkinson's disease. These novel results extend the notion that pathological beta activity is causally implicated in the motor and (lesser appreciated) non-motor deficits inherent to Parkinson's disease. These findings provide important empirical evidence that should be considered in the development of intelligent next-generation therapies.

A functional micro-electrode mapping of ventral thalamus in essential tremor.

Deep brain stimulation enables the delivery of therapeutic interventions to otherwise inaccessible areas of the brain while, at the same time, offering the unique opportunity to record from these same regions in awake patients. The posterior ventrolateral thalamus has become a reliable deep brain stimulation target for medically-refractory patients suffering from essential tremor. However, the contribution of the thalamus in essential tremor, and even whether posterior ventrolateral thalamus is the optimal target, remains a matter of ongoing debate. There are several lines of evidence supporting clusters of activity within the posterior ventrolateral thalamus that are important for tremor emergence. In this study we sought to map the functional properties of these clusters through microelectrode recordings during deep brain stimulation surgery. Data were obtained from 10 severely affected patients with essential tremor (12 hemispheres) undergoing deep brain stimulation surgery. Our results demonstrate power and coherence maxima located in the inferior posterior ventrolateral thalamus and immediate ventral region. Moreover, we identified distinct yet overlapping clusters of predominantly efferent (driving) and afferent (feedback) activity, with a preference for more efferent contributors, consistent with a net role in the driving of tremor output. Finally, we demonstrate that resolvable thalamic spiking activity directly relates to background activity and that the strength of tremor may be dictated by phase relationships between efferent and afferent pockets in the posterior ventrolateral thalamus. Taken together, these results provide important evidence for the role of the inferior posterior ventrolateral thalamus and its border region in essential tremor pathophysiology. Such results progress our mechanistic understanding and promote the adoption of next-generation therapies such as high resolution segregated deep brain stimulation electrodes.

Recent Trends in the Use of Electrical Neuromodulation in Parkinson's Disease.

PURPOSE OF REVIEW: This review aims to survey recent trends in electrical forms of neuromodulation, with a specific application to Parkinson's disease (PD). Emerging trends are identified, highlighting synergies in state-of-the-art neuromodulation strategies, with directions for future improvements in stimulation efficacy suggested. RECENT FINDINGS: Deep brain stimulation remains the most common and effective form of electrical stimulation for the treatment of PD. Evidence suggests that transcranial direct current stimulation (tDCS) most likely impacts the motor symptoms of the disease, with the most prominent results relating to rehabilitation. However, utility is limited due to its weak effects and high variability, with medication state a key confound for efficacy level. Recent innovations in transcranial alternating current stimulation (tACS) offer new areas for investigation. SUMMARY: Our understanding of the mechanistic foundations of electrical current stimulation is advancing and as it does so, trends emerge which steer future clinical trials towards greater efficacy.

Directional local field potentials: A tool to optimize deep brain stimulation.

BACKGROUND: Although recently introduced directional DBS leads provide control of the stimulation field, programing is time-consuming. OBJECTIVES: Here, we validate local field potentials recorded from directional contacts as a predictor of the most efficient contacts for stimulation in patients with PD. METHODS: Intraoperative local field potentials were recorded from directional contacts in the STN of 12 patients and beta activity compared with the results of the clinical contact review performed after 4 to 7 months. RESULTS: Normalized beta activity was positively correlated with the contact's clinical efficacy. The two contacts with the highest beta activity included the most efficient stimulation contact in up to 92% and that with the widest therapeutic window in 74% of cases. CONCLUSION: Local field potentials predict the most efficient stimulation contacts and may provide a useful tool to expedite the selection of the optimal contact for directional DBS. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Adaptive spectral tracking for coherence estimation: the z-tracker.

OBJECTIVE: A major challenge in non-stationary signal analysis is reliable estimation of correlation. Neurophysiological recordings can be many minutes in duration with data that exhibits correlation which changes over different time scales. Local smoothing can be used to estimate time-dependency, however, an effective framework needs to adjust levels of smoothing in response to changes in correlation. APPROACH: Here we present a novel data-adaptive algorithm, the z-tracker, for estimating local correlation in segmented data. The algorithm constructs single segment coherence estimates using multi-taper windows. These are subject to adaptive Kalman filtering/smoothing in the z-domain to construct a local coherence estimate for each segment. The error residual for each segment determines the levels of process noise, allowing the filter to adapt rapidly to sudden changes in correlation while applying greater smoothing to data where the correlation is consistent across segments. The method is compared to wavelet coherence, calculated using orthogonal Morse wavelets. MAIN RESULTS: The performance of the z-tracker is quantified against Morse wavelet coherence using a mean square deviation (MSD) metric. The z-tracker has significantly lower MSD than the wavelet estimate for time-varying coherence over long time scales (∼10-20 s), whereas the wavelet has lower MSD for coherence varying over short time scales (∼1-2 s). The z-tracker also has a lower MSD for slowly varying coherence with occasional step changes. The method is applied to detect changes in coherence in paired LFP recordings from rat prefrontal cortex and amygdala in response to a pharmacological challenge. SIGNIFICANCE: The z-tracker provides an effective and efficient method to estimate time varying correlation in multivariate data, leading to better characterisation of neurophysiology signals where correlation is subject to slow modulation over time. A number of suggestions are included for future refinements.

Modulation of Long-Range Connectivity Patterns via Frequency-Specific Stimulation of Human Cortex.

There is increasing interest in how the phase of local oscillatory activity within a brain area determines the long-range functional connectivity of that area. For example, increasing convergent evidence from a range of methodologies suggests that beta (20 Hz) oscillations may play a vital role in the function of the motor system [1-5]. The "communication through coherence" hypothesis posits that the precise phase of coherent oscillations in network nodes is a determinant of successful communication between them [6, 7]. Here we set out to determine whether oscillatory activity in the beta band serves to support this theory within the cortical motor network in vivo. We combined non-invasive transcranial alternating-current stimulation (tACS) [8-12] with resting-state functional MRI (fMRI) [13] to follow both changes in local activity and long-range connectivity, determined by inter-areal blood-oxygen-level-dependent (BOLD) signal correlation, as a proxy for communication in the human cortex. Twelve healthy subjects participated in three fMRI scans with 20 Hz, 5 Hz, or sham tACS applied separately on each scan. Transcranial magnetic stimulation (TMS) at beta frequency has previously been shown to increase local activity in the beta band [14] and to modulate long-range connectivity within the default mode network [15]. We demonstrated that beta-frequency tACS significantly changed the connectivity pattern of the stimulated primary motor cortex (M1), without changing overall local activity or network connectivity. This finding is supported by a simple phase-precession model, which demonstrates the plausibility of the results and provides emergent predictions that are consistent with our empirical findings. These findings therefore inform our understanding of how local oscillatory activity may underpin network connectivity.

The differentiated networks related to essential tremor onset and its amplitude modulation after alcohol intake.

The dysregulation of endogenous rhythms within brain networks have been implicated in a broad range of motor and non-motor pathologies. Essential tremor (ET), classically the purview of a single aberrant pacemaker, has recently become associated with network-level dysfunction across multiple brain regions. Specifically, it has been suggested that motor cortex constitutes an important node in a tremor-generating network involving the cerebellum. Yet the mechanisms by which these regions relate to tremor remain a matter of considerable debate. We sought to discriminate the contributions of cerebral and cerebellar dysregulation by combining high-density electroencephalography with subject-specific structural MRI. For that, we contrasted ET with voluntary (mimicked) tremor before and after ingestion of alcohol to regulate the tremorgenic networks. Our results demonstrate distinct loci of cortical tremor coherence, most pronounced over the sensorimotor cortices in healthy controls, but more frontal motor areas in ET-patients consistent with a heightened involvement of the supplementary motor area. We further demonstrate that the reduction in tremor amplitude associated with alcohol intake is reflected in altered cerebellar - but not cerebral - coupling with movement. Taken together, these findings implicate tremor emergence as principally associated with increases in activity within frontal motor regions, whereas modulation of the amplitude of established tremor relates to changes in cerebellar activity. These findings progress a mechanistic understanding of ET and implicate network-level vulnerabilities in the rhythmic nature of communication throughout the brain.

Tremor stability index: a new tool for differential diagnosis in tremor syndromes.

See Vidailhet et al. (doi:10.1093/brain/awx140) for a scientific commentary on this article. Misdiagnosis among tremor syndromes is common, and can impact on both clinical care and research. To date no validated neurophysiological technique is available that has proven to have good classification performance, and the diagnostic gold standard is the clinical evaluation made by a movement disorders expert. We present a robust new neurophysiological measure, the tremor stability index, which can discriminate Parkinson's disease tremor and essential tremor with high diagnostic accuracy. The tremor stability index is derived from kinematic measurements of tremulous activity. It was assessed in a test cohort comprising 16 rest tremor recordings in tremor-dominant Parkinson's disease and 20 postural tremor recordings in essential tremor, and validated on a second, independent cohort comprising a further 55 tremulous Parkinson's disease and essential tremor recordings. Clinical diagnosis was used as gold standard. One hundred seconds of tremor recording were selected for analysis in each patient. The classification accuracy of the new index was assessed by binary logistic regression and by receiver operating characteristic analysis. The diagnostic performance was examined by calculating the sensitivity, specificity, accuracy, likelihood ratio positive, likelihood ratio negative, area under the receiver operating characteristic curve, and by cross-validation. Tremor stability index with a cut-off of 1.05 gave good classification performance for Parkinson's disease tremor and essential tremor, in both test and validation datasets. Tremor stability index maximum sensitivity, specificity and accuracy were 95%, 95% and 92%, respectively. Receiver operating characteristic analysis showed an area under the curve of 0.916 (95% confidence interval 0.797­1.000) for the test dataset and a value of 0.855 (95% confidence interval 0.754­0.957) for the validation dataset. Classification accuracy proved independent of recording device and posture. The tremor stability index can aid in the differential diagnosis of the two most common tremor types. It has a high diagnostic accuracy, can be derived from short, cheap, widely available and non-invasive tremor recordings, and is independent of operator or postural context in its interpretation.

Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: A position paper.

Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned to fluctuations in excitability states. Moreover, offline EEG/MEG recordings prior to interventions can inform researchers and clinicians how to stimulate: by frequency-tuning NTBS to the oscillation of interest, intrinsic brain oscillations can be up- or down-regulated. In this paper, we provide an overview of existing approaches and ideas of EEG/MEG-guided interventions, and their promises and caveats. We point out potential future lines of research to address challenges.