Phase Synchronicity of μ-Rhythm Determines Efficacy of Interhemispheric Communication Between Human Motor Cortices

Motor sequence learning elicits mu peak-specific corticospinal plasticity

Motor cortical (M1) transcranial magnetic stimulation (TMS) interventions increase corticospinal output and improve motor learning when delivered during sensorimotor mu rhythm trough but not peak phases, suggesting that the mechanisms supporting motor learning may be most active during mu trough phases. Based on these findings, we predicted that motor sequence learning-related corticospinal plasticity would be most evident when measured during mu trough phases. Healthy adults were assigned to either a sequence or no-sequence group. Participants in the sequence group practiced the implicit serial reaction time task (SRTT), which contained an embedded, repeating 12-item sequence. Participants in the no-sequence group practiced a version of the SRTT that contained no sequence. We measured mu phase-independent and mu phase-dependent MEP amplitudes using EEG-informed single-pulse TMS before, immediately after, and 30 minutes after the SRTT in both groups. All participants performed a retention test one hour after SRTT acquisition. In both groups, mu phase-independent MEP amplitudes increased following SRTT acquisition, but the pattern of mu phase-dependent MEP amplitude changes after SRTT acquisition differed between groups. Relative to the no-sequence group, the sequence group showed greater peak-specific MEP amplitude increases 30 minutes after SRTT acquisition. Further, the magnitude of these peak-specific MEP amplitude increases was negatively associated with the magnitude of sequence-specific learning. Contrary to our original hypothesis, results revealed that motor sequence-specific learning elicits peak-specific corticospinal plasticity. Findings provide first direct evidence for the presence of a mu phase-dependent motor learning mechanism in the human brain.

New and Noteworthy

Recent work suggests that motor learning's neural mechanisms may be most active during specific sensorimotor mu rhythm phases. If so, motor sequence learning-induced corticospinal plasticity should be more evident during some mu phases than others. Our results show that motor sequence-specific learning elicits corticospinal plasticity that is most prominent during mu peak phases. Further, this peak-specific plasticity correlates with learning. Findings establish the presence of a mu phase-dependent motor learning mechanism in the human brain.

Interactions of transcranial magnetic stimulation with brain oscillations: a narrative review

Brain responses to transcranial magnetic stimulation (TMS) can be recorded with electroencephalography (EEG) and comprise TMS-evoked potentials and TMS-induced oscillations. Repetitive TMS may entrain endogenous brain oscillations. In turn, ongoing brain oscillations prior to the TMS pulse can influence the effects of the TMS pulse. These intricate TMS-EEG and EEG-TMS interactions are increasingly attracting the interest of researchers and clinicians. This review surveys the literature of TMS and its interactions with brain oscillations as measured by EEG in health and disease.

Sensory Entrained TMS (seTMS) enhances motor cortex excitability

Transcranial magnetic stimulation (TMS) applied to the motor cortex has revolutionized the study of motor physiology in humans. Despite this, TMS-evoked electrophysiological responses show significant variability, due in part to inconsistencies between TMS pulse timing and ongoing brain oscillations. Variable responses to TMS limit mechanistic insights and clinical efficacy, necessitating the development of methods to precisely coordinate the timing of TMS pulses to the phase of relevant oscillatory activity. We introduce Sensory Entrained TMS (seTMS), a novel approach that uses musical rhythms to synchronize brain oscillations and time TMS pulses to enhance cortical excitability. Focusing on the sensorimotor alpha rhythm, a neural oscillation associated with motor cortical inhibition, we examine whether rhythm-evoked sensorimotor alpha phase alignment affects primary motor cortical (M1) excitability in healthy young adults (n=33). We first confirmed using electroencephalography (EEG) that passive listening to musical rhythms desynchronizes inhibitory sensorimotor brain rhythms (mu oscillations) around 200 ms before auditory rhythmic events (27 participants). We then targeted this optimal time window by delivering single TMS pulses over M1 200 ms before rhythmic auditory events while recording motor-evoked potentials (MEPs; 19 participants), which resulted in significantly larger MEPs compared to standard single pulse TMS and an auditory control condition. Neither EEG measures during passive listening nor seTMS-induced MEP enhancement showed dependence on musical experience or training. These findings demonstrate that seTMS effectively enhances corticomotor excitability and establishes a practical, cost-effective method for optimizing non-invasive brain stimulation outcomes.

Influence of Large-Scale Brain State Dynamics on the Evoked Response to Brain Stimulation

Understanding how spontaneous brain activity influences the response to neurostimulation is crucial for the development of neurotherapeutics and brain-computer interfaces. Localized brain activity is suggested to influence the response to neurostimulation, but whether fast-fluctuating (i.e., tens of milliseconds) large-scale brain dynamics also have any such influence is unknown. By stimulating the prefrontal cortex using combined transcranial magnetic stimulation (TMS) and electroencephalography, we examined how dynamic global brain state patterns, as defined by microstates, influence the magnitude of the evoked brain response. TMS applied during what resembled the canonical Microstate C was found to induce a greater evoked response for up to 80 ms compared with other microstates. This effect was found in a repeated experimental session, was absent during sham stimulation, and was replicated in an independent dataset. Ultimately, ongoing and fast-fluctuating global brain states, as probed by microstates, may be associated with intrinsic fluctuations in connectivity and excitation-inhibition balance and influence the neurostimulation outcome. We suggest that the fast-fluctuating global brain states be considered when developing any related paradigms.

Effects of the motor cortical theta-burst transcranial-focused ultrasound stimulation on the contralateral motor cortex

Theta-burst transcranial ultrasound stimulation (tbTUS) increases primary motor cortex (M1) excitability for at least 30 min. However, the remote effects of focal M1 tbTUS on the excitability of other cortical areas are unknown. Here, we examined the effects of left M1 tbTUS on right M1 excitability. An 80 s train of active or sham tbTUS was delivered to the left M1 in 20 healthy subjects. Before and after the tbTUS, we measured: (1) corticospinal excitability using motor-evoked potential (MEP) amplitudes from single-pulse transcranial magnetic stimulation (TMS) of left and right M1; (2) interhemispheric inhibition (IHI) from left to right M1 and from right to left M1 using a dual-site paired-pulse TMS paradigm; and (3) intracortical circuits of the right M1 with short-interval intracortical inhibition and intracortical facilitation (ICF) using paired-pulse TMS. Left M1 tbTUS decreased right M1 excitability as shown by decreased MEP amplitudes, increased right M1 ICF and decreased short-interval IHI from left to right hemisphere at interstimulus interval (ISI) of 10 ms but not long-interval IHI at interstimulus interval of 40 ms. The study showed that left M1 tbTUS can change the excitability of remote cortical areas with decreased right M1 excitability and interhemispheric inhibition. The remote effects of tbTUS should be considered when it is used in neuroscience research and as a potential neuromodulation treatment for brain disorders. KEY POINTS: Transcranial ultrasound stimulation (TUS) is a novel non-invasive brain stimulation technique for neuromodulation with the advantages of being able to achieve high spatial resolution and target deep brain structures. A repetitive TUS protocol, with an 80 s train of theta burst patterned TUS (tbTUS), has been shown to increase primary motor cortex (M1) excitability, as well as increase alpha and beta movement-related spectral power in distinct brain regions. In this study, we examined on the effects of the motor cortical tbTUS on the excitability of contralateral M1 measured with MEPs elicited by transcranial magnetic stimulation. We showed that left M1 tbTUS decreased right M1 excitability and left-to-right M1 interhemispheric inhibition, and increased intracortical facilitation of right M1. These results lead to better understand the effects of tbTUS and can help the development of tbTUS for the treatment of neurological and psychiatric disorders and in neuroscience research.

Two common issues in synchronized multimodal recordings with EEG: Jitter and latency

Multimodal recording using electroencephalogram (EEG) and other biological signals (e.g., muscle activities, eye movement, pupil diameters, or body kinematics data) is ubiquitous in human neuroscience research. However, the precise time alignment of multiple data from heterogeneous sources (i.e., devices) is often arduous due to variable recording parameters of commercially available research devices and complex experimental setups. In this review, we introduced the versatility of a Lab Streaming Layer (LSL)-based application that can overcome two common issues in measuring multimodal data: jitter and latency. We discussed the issues of jitter and latency in multimodal recordings and the benefits of time-synchronization when recording with multiple devices. In addition, a computer simulation was performed to highlight how the millisecond-order jitter readily affects the signal-to-noise ratio of the electrophysiological outcome. Together, we argue that the LSL-based system can be used for research requiring precise time-alignment of datasets. Studies that detect stimulus-induced transient neural responses or test hypotheses regarding temporal relationships of different functional aspects with multimodal data would benefit most from LSL-based systems.

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.

Closed-Loop Brain Stimulation

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

Targeting motor cortex high-excitability states defined by functional connectivity with real-time EEG-TMS

We tested previous post-hoc findings indicating a relationship between functional connectivity (FC) in the motor network and corticospinal excitability (CsE), in a real-time EEG-TMS experiment in healthy participants. We hypothesized that high FC between left and right motor cortex predicts high CsE. FC was quantified in real-time by single-trial phase-locking value (stPLV), and TMS single pulses were delivered based on the current FC. CsE was indexed by motor-evoked potential (MEP) amplitude in a hand muscle. Possible confounding factors (pre-stimulus μ-power and phase, interstimulus interval) were evaluated post hoc. MEPs were significantly larger during high FC compared to low FC. Post hoc analysis revealed that the FC condition showed a significant interaction with μ-power in the stimulated hemisphere. Further, inter-stimulus interval (ISI) interacted with high vs. low FC conditions. In summary, FC was confirmed to be predictive of CsE, but should not be considered in isolation from μ-power and ISI. Moreover, FC was complementary to μ-phase in predicting CsE. Motor network FC is another marker of real-time accessible CsE beyond previously established markers, in particular phase and power of the μ rhythm, and may help define a more robust composite biomarker of high/low excitability states of human motor cortex.

TMS of parietal and occipital cortex locked to spontaneous transient large-scale brain states enhances natural oscillations in EEG

BACKGROUND

Fluctuating neuronal network states influence brain responses to transcranial magnetic stimulation (TMS). Our previous studies revealed that transient spontaneous bihemispheric brain states in the EEG, driven by oscillatory power, information flow and regional domination, modify cortical EEG responses to TMS. However, the impact of ongoing fluctuations of large-scale brain network states on TMS-EEG responses has not been explored.

OBJECTIVES

To determine the effects of large-scale brain network states on TMS-EEG responses.

METHODS

Resting-state EEG and structural MRI from 24 healthy subjects were recorded to infer large-scale brain states. TMS-EEG was acquired with TMS at state-related targets, identified by the spatial distribution of state activation power from resting-state EEG. TMS-induced oscillations were measured by event-related spectral perturbations (ERSPs), and classified with respect to the brain states preceding the TMS pulses. State-locked ERSPs with TMS at specific state-related targets and during state activation were compared with state-unlocked ERSPs.

RESULTS

Intra-individual comparison of ERSPs by threshold free cluster enhancement (TFCE) revealed that posterior and visual state-locked TMS, respectively, increased beta and alpha responses to TMS of parietal and occipital cortex compared to state-unlocked TMS. Also, the peak frequencies of ERSPs were increased with state-locked TMS. In addition, inter-individual correlation analyses revealed that posterior and visual state-locked TMS-induced oscillation power (ERSP clusters identified by TFCE) positively correlated with state-dependent oscillation power preceding TMS.

CONCLUSIONS

Spontaneous transient large-scale brain network states modify TMS-induced natural oscillations in specific brain regions. This significantly extends our knowledge on the critical importance of instantaneous state on explaining the brain's varying responsiveness to external perturbation.

Repetitive sensorimotor mu-alpha phase-targeted afferent stimulation produces no phase-dependent plasticity related changes in somatosensory evoked potentials or sensory thresholds

Phase-dependent plasticity has been proposed as a neurobiological mechanism by which oscillatory phase-amplitude cross-frequency coupling mediates memory process in the brain. Mimicking this mechanism, real-time EEG oscillatory phase-triggered transcranial magnetic stimulation (TMS) has successfully induced LTP-like changes in corticospinal excitability in the human motor cortex. Here we asked whether EEG phase-triggered afferent stimulation alone, if repetitively applied to the peaks, troughs, or random phases of the sensorimotor mu-alpha rhythm, would be sufficient to modulate the strength of thalamocortical synapses as assessed by changes in somatosensory evoked potential (SEP) N20 and P25 amplitudes and sensory thresholds (ST). Specifically, we applied 100 Hz triplets of peripheral electrical stimulation (PES) to the thumb, middle, and little finger of the right hand in pseudorandomized trials, with the afferent input from each finger repetitively and consistently arriving either during the cortical mu-alpha trough or peak or at random phases. No significant changes in SEP amplitudes or ST were observed across the phase-dependent PES intervention. We discuss potential limitations of the study and argue that suboptimal stimulation parameter choices rather than a general lack of phase-dependent plasticity in thalamocortical synapses are responsible for this null finding. Future studies should further explore the possibility of phase-dependent sensory stimulation.

Corticospinal excitability is highest at the early rising phase of sensorimotor µ-rhythm

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

Beta rhythmicity in human motor cortex reflects neural population coupling that modulates subsequent finger coordination stability

Human behavior is not performed completely as desired, but is influenced by the inherent rhythmicity of the brain. Here we show that anti-phase bimanual coordination stability is regulated by the dynamics of pre-movement neural oscillations in bi-hemispheric primary motor cortices (M1) and supplementary motor area (SMA). In experiment 1, pre-movement bi-hemispheric M1 phase synchrony in beta-band (M1-M1 phase synchrony) was online estimated from 129-channel scalp electroencephalograms. Anti-phase bimanual tapping preceded by lower M1-M1 phase synchrony exhibited significantly longer duration than tapping preceded by higher M1-M1 phase synchrony. Further, the inter-individual variability of duration was explained by the interaction of pre-movement activities within the motor network; lower M1-M1 phase synchrony and spectral power at SMA were associated with longer duration. The necessity of cortical interaction for anti-phase maintenance was revealed by sham-controlled repetitive transcranial magnetic stimulation over SMA in another experiment. Our results demonstrate that pre-movement cortical oscillatory coupling within the motor network unknowingly influences bimanual coordination performance in humans after consolidation, suggesting the feasibility of augmenting human motor ability by covertly monitoring preparatory neural dynamics.

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.

Spatially bivariate EEG-neurofeedback can manipulate interhemispheric inhibition

Human behavior requires inter-regional crosstalk to employ the sensorimotor processes in the brain. Although external neuromodulation techniques have been used to manipulate interhemispheric sensorimotor activity, a central controversy concerns whether this activity can be volitionally controlled. Experimental tools lack the power to up- or down-regulate the state of the targeted hemisphere over a large dynamic range and, therefore, cannot evaluate the possible volitional control of the activity. We addressed this difficulty by using the recently developed method of spatially bivariate electroencephalography (EEG)-neurofeedback to systematically enable the participants to modulate their bilateral sensorimotor activities. Here, we report that participants learn to up- and down-regulate the ipsilateral excitability to the imagined hand while maintaining constant contralateral excitability; this modulates the magnitude of interhemispheric inhibition (IHI) assessed by the paired-pulse transcranial magnetic stimulation (TMS) paradigm. Further physiological analyses revealed that the manipulation capability of IHI magnitude reflected interhemispheric connectivity in EEG and TMS, which was accompanied by intrinsic bilateral cortical oscillatory activities. Our results show an interesting approach for neuromodulation, which might identify new treatment opportunities, e.g., in patients suffering from a stroke.

µ-rhythm phase from somatosensory but not motor cortex correlates with corticospinal excitability in EEG-triggered TMS

BACKGROUND

Sensorimotor µ-rhythm phase is correlated with corticospinal excitability. Transcranial magnetic stimulation (TMS) of motor cortex results in larger motor evoked potentials (MEPs) during the negative peak of the EEG oscillation as extracted with a surface Laplacian. However, the anatomical source of the relevant oscillation is not clear and demonstration of the relationship is sensitive to the choice of EEG montage.

OBJECTIVE/HYPOTHESIS

Here, we compared two EEG montages preferentially sensitive to oscillations originating from the crown of precentral gyrus (dorsal premotor cortex) vs. postcentral gyrus (secondary somatosensory cortex). We hypothesized that the EEG signal from precentral gyrus would correlate more strongly with MEP amplitude, given that the corticospinal neurons are located in the anterior wall of the sulcus and the corticospinal tract has input from premotor cortex.

NEW METHOD

Real-time EEG-triggered TMS of motor cortex was applied in 6 different conditions in randomly interleaved order, 3 phase conditions (positive peak, negative peak, random phase of the ongoing µ-oscillation), and each phase condition for 2 different EEG montages corresponding to oscillations preferentially originating in precentral gyrus (premotor cortex) vs. postcentral gyrus (somatosensory cortex), extracted using FCC3h vs. C3 centered EEG montages.

RESULTS

The negative vs. positive peak of sensorimotor µ-rhythm as extracted from the C3 montage (postcentral gyrus, somatosensory cortex) correlated with states of high vs. low corticospinal excitability (p < 0.001), replicating previous findings. However, no significant correlation was found for sensorimotor µ-rhythm as extracted from the neighboring FCC3 montage (precentral gyrus, premotor cortex). This implies that EEG-signals from the somatosensory cortex are better predictors of corticospinal excitability than EEG-signals from the motor areas.

CONCLUSIONS

The extraction of a brain oscillation whose phase corresponds to corticospinal excitability is highly sensitive to the selected EEG montage and the location of the EEG sensors on the scalp. Here, the cortical source of EEG oscillations predicting response amplitude does not correspond to the cortical target of the stimulation, indicating that even in this simple case, a specific neuronal pathway from somatosensory cortex to primary motor cortex is involved.

Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS

Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.

Phase-dependent local brain states determine the impact of image-guided transcranial magnetic stimulation on motor network electroencephalographic synchronization

Recent studies have synchronized transcranial magnetic stimulation (TMS) application with pre-defined brain oscillatory phases showing how brain response to perturbation depends on the brain state. However, none have investigated whether phase-dependent TMS can possibly modulate connectivity with homologous distant brain regions belonging to the same network. In the framework of network-targeted TMS, we investigated whether stimulation delivered at a specific phase of ongoing brain oscillations might favour stronger cortico-cortical (c-c) synchronization of distant network nodes connected to the stimulation target. Neuronavigated TMS pulses were delivered over the primary motor cortex (M1) during ongoing electroencephalography recording in 24 healthy individuals over two repeated sessions 1 month apart. Stimulation effects were analysed considering whether the TMS pulse was delivered at the time of a positive (peak) or negative (trough) phase of μ-frequency oscillation, which determines c-c synchrony within homologous areas of the sensorimotor network. Diffusion weighted imaging was used to study c-c connectivity within the sensorimotor network and identify contralateral regions connected with the stimulation spot. Depending on when during the μ-activity the TMS-pulse was applied (peak or trough), its impact on inter-hemispheric network synchrony varied significantly. Higher M1-M1 phase-lock synchronization after the TMS-pulse (0-200 ms) in the μ-frequency band was found for trough compared to peak stimulation trials in both study visits. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of the response to the external perturbation, with implications for interventions aimed at engaging more distributed functional brain networks. KEY POINTS: Synchronized transcranial magnetic stimulation (TMS) pulses with pre-defined brain oscillatory phases allow evaluation of the impact of brain states on TMS effects. TMS pulses over M1 at the negative peak of the μ-frequency band induce higher phase-lock synchronization with interconnected contralateral homologous regions. Cortico-cortical synchronization changes are linearly predicted by the fibre density and cross-section of the white matter tract that connects the two brain regions. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of within-network synchronization.

Bridging the gap: TMS-EEG from Lab to Clinic

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has reached technological maturity and has been an object of significant scientific interest for over two decades. Ιn parallel, accumulating evidence highlights the potential of TMS-EEG as a useful tool in the field of clinical neurosciences. Nevertheless, its clinical utility has not yet been established, partly because technical and methodological limitations have created a gap between an evolving scientific tool and standard clinical practice. Here we review some of the identified gaps that still prevent TMS-EEG moving from science laboratories to clinical practice. The principal and partly overlapping gaps include: 1) complex and laborious application, 2) difficulty in obtaining high-quality signals, 3) suboptimal accuracy and reliability, and 4) insufficient understanding of the neurobiological substrate of the responses. All these four aspects need to be satisfactorily addressed for the method to become clinically applicable and enter the diagnostic and therapeutic arena. In the current review, we identify steps that might be taken to address these issues and discuss promising recent studies providing tools to aid bridging the gaps.

Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation

BACKGROUND

Transcranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer.

OBJECTIVE

To develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region.

METHODS

We designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand.

RESULTS

The transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum.

CONCLUSION

The developed mTMS system enables electronically targeted brain stimulation within a cortical region.

α Phase-Amplitude Tradeoffs Predict Visual Perception

Spontaneous α oscillations (∼10 Hz) have been associated with various cognitive functions, including perception. Their phase and amplitude independently predict cortical excitability and subsequent perceptual performance. However, the causal role of α phase-amplitude tradeoffs on visual perception remains ill-defined. We aimed to fill this gap and tested two clear predictions from the pulsed inhibition theory according to which α oscillations are associated with periodic functional inhibition. (1) High-α amplitude induces cortical inhibition at specific phases, associated with low perceptual performance, while at opposite phases, inhibition decreases (potentially increasing excitation) and perceptual performance increases. (2) Low-α amplitude is less susceptible to these phasic (periodic) pulses of inhibition, leading to overall higher perceptual performance. Here, cortical excitability was assessed in humans using phosphene (illusory) perception induced by single pulses of transcranial magnetic stimulation (TMS) applied over visual cortex at perceptual threshold, and its postpulse evoked activity recorded with simultaneous electroencephalography (EEG). We observed that prepulse α phase modulates the probability to perceive a phosphene, predominantly for high-α amplitude, with a nonoptimal phase for phosphene perception between -π/2 and -π/4. The prepulse nonoptimal phase further leads to an increase in postpulse-evoked activity [event-related potential (ERP)], in phosphene-perceived trials specifically. Together, these results show that α oscillations create periodic inhibitory moments when α amplitude is high, leading to periodic decrease of perceptual performance. This study provides strong causal evidence in favor of the pulsed inhibition theory.

Bihemispheric sensorimotor oscillatory network states determine cortical responses to transcranial magnetic stimulation

BACKGROUND

Brain responses to external stimuli vary with fluctuating states of neuronal activity. Previous work has demonstrated effects of phase and power of the ongoing local sensorimotor μ-alpha-oscillation on responses to transcranial magnetic stimulation (TMS) of motor cortex (M1). However, M1 is part of a distributed network, and the effects of oscillatory activity in this network on TMS-evoked EEG responses (TEPs) have not been explored.

OBJECTIVES

To determine the effects of oscillatory activity in the bihemispheric sensorimotor network on TEPs.

METHODS

31 healthy subjects received single-pulse TMS of the left M1 hand area during EEG recording. Ongoing bihemispheric sensorimotor cortex oscillatory states were reconstructed from the EEG directly preceding TMS, and inferred by a data-driven method combining a multivariate autoregressive model and a Hidden Markov model. TEP amplitudes (P25, N45, P70, N100 and P180) were then compared between different bihemispheric sensorimotor cortex oscillatory states.

RESULTS

Four bihemispheric sensorimotor cortex oscillatory states were identified, with different interhemispheric expressions of theta and alpha oscillations. High alpha-power states in the stimulated sensorimotor cortex increased P25 amplitude. Alpha power in the alpha-alpha state (stimulated - non-stimulated hemisphere) correlated in both hemispheres with N45 amplitude. Theta power in the alpha-theta state correlated in the non-stimulated hemisphere with P70 amplitude.

CONCLUSIONS

Bihemispheric sensorimotor cortex oscillatory states contribute to TEPs, with a relevance shift from stimulated to non-stimulated M1 from P25 over N45 to P70. This significantly extends previous findings: not only ongoing local oscillations but distributed network oscillatory states determine cortical responsiveness to external stimuli.

Causal roles of prefrontal cortex during spontaneous perceptual switching are determined by brain state dynamics

The prefrontal cortex (PFC) is thought to orchestrate cognitive dynamics. However, in tests of bistable visual perception, no direct evidence supporting such presumable causal roles of the PFC has been reported except for a recent work. Here, using a novel brain-state-dependent neural stimulation system, we identified causal effects on percept dynamics in three PFC activities—right frontal eye fields, dorsolateral PFC (DLPFC), and inferior frontal cortex (IFC). The causality is behaviourally detectable only when we track brain state dynamics and modulate the PFC activity in brain-state-/state-history-dependent manners. The behavioural effects are underpinned by transient neural changes in the brain state dynamics, and such neural effects are quantitatively explainable by structural transformations of the hypothetical energy landscapes. Moreover, these findings indicate distinct functions of the three PFC areas: in particular, the DLPFC enhances the integration of two PFC-active brain states, whereas IFC promotes the functional segregation between them. This work resolves the controversy over the PFC roles in spontaneous perceptual switching and underlines brain state dynamics in fine investigations of brain-behaviour causality.

A cube that seems to shift its spatial arrangement as you keep looking; the elegant silhouette of a pirouetting dancer, which starts to spin in the opposite direction the more you stare at it; an illustration that shows two profiles – or is it a vase? These optical illusions are examples of bistable visual perception. Beyond their entertaining aspect, they provide a way for scientists to explore the dynamics of human consciousness, and the neural regions involved in this process.

Some studies show that bistable visual perception is associated with the activation of the prefrontal cortex, a brain area involved in complex cognitive processes. However, it is unclear whether this region is required for the illusions to emerge. Some research has showed that even if sections of the prefrontal cortex are temporally deactivated, participants can still experience the illusions.

Instead, Takamitsu Watanabe proposes that bistable visual perception is a process tied to dynamic brain states – that is, that distinct regions of the prefontal cortex are required for this fluctuating visual awareness, depending on the state of the whole brain. Such causal link cannot be observed if brain activity is not tracked closely.

To investigate this, the brain states of 65 participants were recorded as individuals were experiencing the optical illusions; the activity of their various brain regions could therefore be mapped, and then areas of the prefrontal cortex could precisely be inhibited at the right time using transcranial magnetic stimulation. This revealed that, indeed, prefrontal cortex regions were necessary for bistable visual perception, but not in a simple way. Instead, which ones were required and when depended on activity dynamics taking place in the whole brain. Overall, these results indicate that monitoring brain states is necessary to better understand – and ultimately, control – the neural pathways underlying perception and behaviour.

Alpha-band cortico-cortical phase synchronization is associated with effective connectivity in the motor network

OBJECTIVE

Communication-through-coherence proposes that the phase synchronization (PS) of neural oscillations between cortical areas supports neural communication. In this study, we exploited transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) to test this hypothesis at the macroscale level, i.e., whether PS between cortical areas supports interarea communication. TEPs are electroencephalographic (EEG) responses time-locked to TMS pulses reflecting interarea communication, as they are generated by the transmission of neural activity from the stimulated area to connected regions. If interarea PS is important for communication, it should be associated with the TEP amplitude in the connected areas.

METHODS

TMS was delivered over the left primary motor cortex (M1) of fourteen healthy volunteers, and 70-channel EEG was recorded. Early TEP components were source-localized to identify their generators, i.e., distant brain regions activated by M1 through effective connections. Next, linear regressions were used to test the relationship between the TEP amplitude and the pre-stimulus PS between the M1 and the connected regions in four frequency bands (range 4-45 Hz).

RESULTS

Pre-stimulus interarea PS in the alpha-band was positively associated with the amplitude of early TEP components, namely, the N15 (ipsilateral supplementary motor area), P25 (contralateral M1) and P60 (ipsilateral parietal cortex).

CONCLUSIONS

Alpha-band PS predicts the response amplitude of the distant brain regions effectively connected to M1.

SIGNIFICANCE

Our study supports the role of EEG-PS in interarea communication, as theorized by communication-through-coherence.

Phase-dependent offline enhancement of human motor memory

BACKGROUND

Skill learning engages offline activity in the primary motor cortex (M1). Sensorimotor cortical activity oscillates between excitatory trough and inhibitory peak phases of the mu (8-12 Hz) rhythm. We recently showed that these mu phases influence the magnitude and direction of neuroplasticity induction within M1. However, the contribution of M1 activity during mu peak and trough phases to human skill learning has not been investigated.

OBJECTIVE

To evaluate the effects of phase-dependent TMS during mu peak and trough phases on offline learning of a newly-acquired motor skill.

METHODS

On Day 1, three groups of healthy adults practiced an explicit motor sequence learning task with their non-dominant left hand. After practice, phase-dependent TMS was applied to the right M1 during either mu peak or mu trough phases. The third group received sham TMS during random mu phases. On Day 2, all subjects were re-tested on the same task to evaluate offline learning.

RESULTS

Subjects who received phase-dependent TMS during mu trough phases showed increased offline skill learning compared to those who received phase-dependent TMS during mu peak phases or sham TMS during random mu phases. Additionally, phase-dependent TMS during mu trough phases elicited stronger whole-brain broadband oscillatory power responses than phase-dependent TMS during mu peak phases.

CONCLUSIONS

We conclude that sensorimotor mu trough phases reflect brief windows of opportunity during which TMS can strengthen newly-acquired skill memories.

Scalp electroencephalograms over ipsilateral sensorimotor cortex reflect contraction patterns of unilateral finger muscles

A variety of neural substrates are implicated in the initiation, coordination, and stabilization of voluntary movements underpinned by adaptive contraction and relaxation of agonist and antagonist muscles. To achieve such flexible and purposeful control of the human body, brain systems exhibit extensive modulation during the transition from resting state to motor execution and to maintain proper joint impedance. However, the neural structures contributing to such sensorimotor control under unconstrained and naturalistic conditions are not fully characterized. To elucidate which brain regions are implicated in generating and coordinating voluntary movements, we employed a physiologically inspired, two-stage method to decode relaxation and three patterns of contraction in unilateral finger muscles (i.e., extension, flexion, and co-contraction) from high-density scalp electroencephalograms (EEG). The decoder consisted of two parts employed in series. The first discriminated between relaxation and contraction. If the EEG data were discriminated as contraction, the second stage then discriminated among the three contraction patterns. Despite the difficulty in dissociating detailed contraction patterns of muscles within a limb from scalp EEG signals, the decoder performance was higher than chance-level by 2-fold in the four-class classification. Moreover, weighted features in the trained decoders revealed EEG features differentially contributing to decoding performance. During the first stage, consistent with previous reports, weighted features were localized around sensorimotor cortex (SM1) contralateral to the activated fingers, while those during the second stage were localized around ipsilateral SM1. The loci of these weighted features suggested that the coordination of unilateral finger muscles induced different signaling patterns in ipsilateral SM1 contributing to motor control. Weighted EEG features enabled a deeper understanding of human sensorimotor processing as well as of a more naturalistic control of brain-computer interfaces.

Induction of LTD-like corticospinal plasticity by low-frequency rTMS depends on pre-stimulus phase of sensorimotor μ-rhythm

Background

Neural oscillations reflect rapidly changing brain excitability states. We have demonstrated previously with EEG-triggered transcranial magnetic stimulation (TMS) of human motor cortex that the positive vs. negative peak of the sensorimotor μ-oscillation reflect corticospinal low-vs. high-excitability states. In vitro experiments showed that induction of long-term depression (LTD) by low-frequency stimulation depends on the postsynaptic excitability state.

Objective/Hypothesis: We tested the hypothesis that induction of LTD-like corticospinal plasticity in humans by 1 Hz repetitive TMS (rTMS) is enhanced when rTMS is synchronized with the low-excitability state, but decreased or even shifted towards long-term (LTP)-like plasticity when synchronized with the high-excitability state.

Methods

We applied real-time EEG-triggered 1-Hz-rTMS (900 pulses) to the hand area of motor cortex in healthy subjects. In a randomized double-blind three-condition crossover design, pulses were synchronized to either the positive or negative peak of the sensorimotor μ-oscillation, or were applied at random phase (control). The amplitude of motor evoked potentials was recorded as an index of corticospinal excitability before and after 1-Hz-rTMS.

Results

1-Hz-rTMS at random phase resulted in a trend towards LTD-like corticospinal plasticity. RTMS in the positive peak condition (i.e., the low-excitability state) induced significant LTD-like plasticity. RTMS in the negative peak condition (i.e., the high-excitability state) showed a trend towards LTP-like plasticity, which was significantly different from the other two conditions.

Conclusion

The level of corticospinal depolarization reflected by phase of the μ-oscillation determines the degree of corticospinal plasticity induced by low-frequency rTMS, a finding that may guide future personalized therapeutic stimulation.

•

Positive vs. negative phase of μ-rhythm are states of low vs. high excitability.

•

1-Hz-rTMS coupled to positive but not negative phase results in LTD-like plasticity.

•

Phase of μ-rhythm determines effect size of 1-Hz-rTMS induced plasticity.

The shaky ground truth of real-time phase estimation

Instantaneous phase of brain oscillations in electroencephalography (EEG) is a measure of brain state that is relevant to neuronal processing and modulates evoked responses. However, determining phase at the time of a stimulus with standard signal processing methods is not possible due to the stimulus artifact masking the future part of the signal. Here, we quantify the degree to which signal-to-noise ratio and instantaneous amplitude of the signal affect the variance of phase estimation error and the precision with which "ground truth" phase is even defined, using both the variance of equivalent estimators and realistic simulated EEG data with known synthetic phase. Necessary experimental conditions are specified in which pre-stimulus phase estimation is meaningfully possible based on instantaneous amplitude and signal-to-noise ratio of the oscillation of interest. An open source toolbox is made available for causal (using pre-stimulus signal only) phase estimation along with a EEG dataset consisting of recordings from 140 participants and a best practices workflow for algorithm optimization and benchmarking. As an illustration, post-hoc sorting of open-loop transcranial magnetic stimulation (TMS) trials according to pre-stimulus sensorimotor μ-rhythm phase is performed to demonstrate modulation of corticospinal excitability, as indexed by the amplitude of motor evoked potentials.

Interhemispheric symmetry of µ-rhythm phase-dependency of corticospinal excitability

Oscillatory activity in the µ-frequency band (8–13 Hz) determines excitability in sensorimotor cortex. In humans, the primary motor cortex (M1) in the two hemispheres shows significant anatomical, connectional, and electrophysiological differences associated with motor dominance. It is currently unclear whether the µ-oscillation phase effects on corticospinal excitability demonstrated previously for the motor-dominant M1 are also different between motor-dominant and motor-non-dominant M1 or, alternatively, are similar to reflect a ubiquitous physiological trait of the motor system at rest. Here, we applied single-pulse transcranial magnetic stimulation to the hand representations of the motor-dominant and the motor-non-dominant M1 of 51 healthy right-handed volunteers when electroencephalography indicated a certain µ-oscillation phase (positive peak, negative peak, or random). We determined resting motor threshold (RMT) as a marker of corticospinal excitability in the three µ-phase conditions. RMT differed significantly depending on the pre-stimulus phase of the µ-oscillation in both M1, with highest RMT in the positive-peak condition, and lowest RMT in the negative-peak condition. µ-phase-dependency of RMT correlated directly between the two M1, and interhemispheric differences in µ-phase-dependency were absent. In conclusion, µ-phase-dependency of corticospinal excitability appears to be a ubiquitous physiological trait of the motor system at rest, without hemispheric dominance.

Concurrent human TMS-EEG-fMRI enables monitoring of oscillatory brain state-dependent gating of cortico-subcortical network activity

Despite growing interest, the causal mechanisms underlying human neural network dynamics remain elusive. Transcranial Magnetic Stimulation (TMS) allows to noninvasively probe neural excitability, while concurrent fMRI can log the induced activity propagation through connected network nodes. However, this approach ignores ongoing oscillatory fluctuations which strongly affect network excitability and concomitant behavior. Here, we show that concurrent TMS-EEG-fMRI enables precise and direct monitoring of causal dependencies between oscillatory states and signal propagation throughout cortico-subcortical networks. To demonstrate the utility of this multimodal triad, we assessed how pre-TMS EEG power fluctuations influenced motor network activations induced by subthreshold TMS to right dorsal premotor cortex. In participants with adequate motor network reactivity, strong pre-TMS alpha power reduced TMS-evoked hemodynamic activations throughout the bilateral cortico-subcortical motor system (including striatum and thalamus), suggesting shunted network connectivity. Concurrent TMS-EEG-fMRI opens an exciting noninvasive avenue of subject-tailored network research into dynamic cognitive circuits and their dysfunction.

Neurophysiological aftereffects of 10 Hz and 20 Hz transcranial alternating current stimulation over bilateral sensorimotor cortex

Alpha (8-12 Hz) and beta (13-30 Hz) oscillations are believed to be involved in motor control. Their modulation with transcranial alternating current stimulation (tACS) has been shown to alter motor behavior and cortical excitability. The aim of the present study was to determine whether tACS applied bilaterally over sensorimotor cortex at 10 Hz and 20 Hz modulates interhemispheric interactions and corticospinal excitability. Thirty healthy volunteers participated in a randomized, cross-over, sham-controlled, double-blind protocol. Sham and active tACS (10 Hz, 20 Hz, 1 mA) were applied for 20 min over bilateral sensorimotor areas. The physiological effects of tACS on corticospinal excitability and interhemispheric inhibition were assessed with transcranial magnetic stimulation. Physiological mirror movements were assessed to measure the overflow of motor activity to the contralateral M1 during voluntary muscle contraction. Bilateral 10 Hz tACS reduced corticospinal excitability. There was no significant effect of tACS on physiological mirror movements and interhemispheric inhibition. Ten Hz tACS was associated with response patterns consistent with corticospinal inhibition in 57% of participants. The present results indicate that application of tACS at the alpha frequency can induce aftereffects in sensorimotor cortex of healthy individuals.

Pulsed Facilitation of Corticospinal Excitability by the Sensorimotor μ-Alpha Rhythm

Alpha oscillations (8-14 Hz) are assumed to gate information flow in the brain by means of pulsed inhibition; that is, the phasic suppression of cortical excitability and information processing once per alpha cycle, resulting in stronger net suppression for larger alpha amplitudes due to the assumed amplitude asymmetry of the oscillation. While there is evidence for this hypothesis regarding occipital alpha oscillations, it is less clear for the central sensorimotor μ-alpha rhythm. Probing corticospinal excitability via transcranial magnetic stimulation (TMS) of the primary motor cortex and the measurement of motor evoked potentials (MEPs), we have previously demonstrated that corticospinal excitability is modulated by both amplitude and phase of the sensorimotor μ-alpha rhythm. However, the direction of this modulation, its proposed asymmetry, and its underlying mechanisms remained unclear. We therefore used real-time EEG-triggered single- and paired-pulse TMS in healthy humans of both sexes to assess corticospinal excitability and GABA-A-receptor mediated short-latency intracortical inhibition (SICI) at rest during spontaneous high amplitude μ-alpha waves at different phase angles (peaks, troughs, rising and falling flanks) and compared them to periods of low amplitude (desynchronized) μ-alpha. MEP amplitude was facilitated during troughs and rising flanks, but no phasic suppression was observed at any time, nor any modulation of SICI. These results are best compatible with sensorimotor μ-alpha reflecting asymmetric pulsed facilitation but not pulsed inhibition of motor cortical excitability. The asymmetric excitability with respect to rising and falling flanks of the μ-alpha cycle further reveals that voltage differences alone cannot explain the impact of phase.SIGNIFICANCE STATEMENT The pulsed inhibition hypothesis, which assumes that alpha oscillations actively inhibit neuronal processing in a phasic manner, is highly influential and has substantially shaped our understanding of these oscillations. However, some of its basic assumptions, in particular its asymmetry and inhibitory nature, have rarely been tested directly. Here, we explicitly investigated the asymmetry of modulation and its direction for the human sensorimotor μ-alpha rhythm. We found clear evidence of pulsed facilitation, but not inhibition, in the human motor cortex, challenging the generalizability of the pulsed inhibition hypothesis and advising caution when interpreting sensorimotor μ-alpha changes in the sensorimotor system. This study also demonstrates how specific assumptions about the neurophysiological underpinnings of cortical oscillations can be experimentally tested noninvasively in humans.

Posttraining Alpha Transcranial Alternating Current Stimulation Impairs Motor Consolidation in Elderly People

The retention of a new sequential motor skill relies on repeated practice and subsequent consolidation in the absence of active skill practice. While the early phase of skill acquisition remains relatively unaffected in older adults, posttraining consolidation appears to be selectively impaired by advancing age. Motor learning is associated with posttraining changes of oscillatory alpha and beta neuronal activities in the motor cortex. However, whether or not these oscillatory dynamics relate to posttraining consolidation and how they relate to the age-specific impairment of motor consolidation in older adults remains elusive. Transcranial alternating current stimulation (tACS) is a noninvasive brain stimulation technique capable of modulating such neuronal oscillations. Here, we examined whether tACS targeting M1 immediately following explicit motor sequence training is capable of modulating motor skill consolidation in older adults. In two sets of double-blind, sham-controlled experiments, tACS targeting left M1 was applied at either 10 Hz (alpha-tACS) or 20 Hz (beta-tACS) immediately after termination of a motor sequence training with the right (dominant) hand. Task performance was retested after an interval of 6 hours to assess consolidation of the training-acquired skill. EEG was recorded over left M1 to be able to detect local after-effects on oscillatory activity induced by tACS. Relative to the sham intervention, consolidation was selectively disrupted by posttraining alpha-tACS of M1, while posttraining beta-tACS of M1 had no effect on delayed retest performance compared to the sham intervention. No significant postinterventional changes of oscillatory activity in M1 were detected following alpha-tACS or beta-tACS. Our findings point to a frequency-specific interaction of tACS with posttraining motor memory processing and may suggest an inhibitory role of immediate posttraining alpha oscillations in M1 with respect to motor consolidation in healthy older adults.

Role of Interhemispheric Cortical Interactions in Poststroke Motor Function

Background/Objective. We investigated interhemispheric interactions in stroke survivors by measuring transcranial magnetic stimulation (TMS)-evoked cortical coherence. We tested the effect of TMS on interhemispheric coherence during rest and active muscle contraction and compared coherence in stroke and older adults. We evaluated the relationships between interhemispheric coherence, paretic motor function, and the ipsilateral cortical silent period (iSP). Methods. Participants with (n = 19) and without (n = 14) chronic stroke either rested or maintained a contraction of the ipsilateral hand muscle during simultaneous recordings of evoked responses to TMS of the ipsilesional/nondominant (i/ndM1) and contralesional/dominant (c/dM1) primary motor cortex with EEG and in the hand muscle with EMG. We calculated pre- and post-TMS interhemispheric beta coherence (15-30 Hz) between motor areas in both conditions and the iSP duration during the active condition. Results. During active i/ndM1 TMS, interhemispheric coherence increased immediately following TMS in controls but not in stroke. Coherence during active cM1 TMS was greater than iM1 TMS in the stroke group. Coherence during active iM1 TMS was less in stroke participants and was negatively associated with measures of paretic arm motor function. Paretic iSP was longer compared with controls and negatively associated with clinical measures of manual dexterity. There was no relationship between coherence and. iSP for either group. No within- or between-group differences in coherence were observed at rest. Conclusions. TMS-evoked cortical coherence during hand muscle activation can index interhemispheric interactions associated with poststroke motor function and potentially offer new insights into neural mechanisms influencing functional recovery.

Distinct online and offline effects of alpha and beta transcranial alternating current stimulation (tACS) on continuous bimanual performance and task-set switching

In the present study we examined the effect of bihemispheric in-phase synchronization of motor cortical rhythms on complex bimanual coordination. Twenty young healthy volunteers received 10 Hz or 20 Hz tACS in a double-blind crossover design while performing a bimanual task-set switching paradigm. We used a bilateral high-density montage centred over the hand knob representation within the primary motor cortices to apply tACS time-locked to the switching events. Online tACS in either frequency led to faster but more erroneous switching transitions compared to trials without active stimulation. When comparing stimulation frequencies, 10 Hz stimulation resulted in higher error rates and slower switching transitions than 20 Hz stimulation. Furthermore, the stimulation frequencies showed distinct carry-over effects in trials following stimulation trains. Non-stimulated switching transitions were generally faster but continuous performance became more erroneous over time in the 20 Hz condition. We suggest that the behavioural effects of bifocal in-phase tACS are explained by online synchronization of long-range interhemispheric sensorimotor oscillations, which impacts on interhemispheric information flow and the top-down control required for flexible control of complex bimanual actions. Different stimulation frequencies may lead to distinct offline effects, which potentially accumulate over time and therefore need to be taken into account when evaluating subsequent performance.