Transcranial Magnetic Stimulation-EEG Biomarkers of Poststroke Upper-Limb Motor Function

Virtual Reality Action Observation and Motor Imagery to Enhance Neuroplastic Capacity in the Human Motor Cortex: A Pilot Double-blind, Randomized Cross-over Trial

Neuroplasticity is important for learning, development and recovery from injury. Therapies that can upregulate neuroplasticity are therefore of interest across a range of fields. We developed a novel virtual reality action observation and motor imagery (VR-AOMI) intervention and evaluated whether it could enhance the efficacy of mechanisms of neuroplasticity in the human motor cortex of healthy adults. A secondary question was to explore predictors of the change in neuroplasticity following VR-AOMI. A pre-registered, pilot randomized controlled cross-over trial was performed. Twenty right-handed adults (13 females; mean age: 23.0 ± 4.53 years) completed two experimental conditions in separate sessions; VR-AOMI and control. We used intermittent theta burst stimulation (iTBS) to induce long term potentiation-like plasticity in the motor cortex and recorded motor evoked potentials at multiple timepoints as a measure of corticospinal excitability. The VR-AOMI task did not significantly increase the change in MEP amplitude following iTBS when compared to the control task (Group × Timepoint interaction p = 0.17). However, regression analysis identified the change in iTBS response following VR-AOMI was significantly predicted by the baseline iTBS response in the control task. Specifically, participants that did not exhibit the expected increase in MEP amplitude following iTBS in the control condition appear to have greater excitability following iTBS in the VR-AOMI condition (r = -0.72, p < 0.001). Engaging in VR-AOMI might enhance capacity for neuroplasticity in some people who typically do not respond to iTBS. VR-AOMI may prime the brain for enhanced neuroplasticity in this sub-group.

Somatosensory input in the context of transcranial magnetic stimulation coupled with electroencephalography: An evidence-based overview

The transcranial evoked potential (TEP) is a powerful technique to investigate brain dynamics, but some methodological issues limit its interpretation. A possible contamination of the TEP by electroencephalographic (EEG) responses evoked by the somatosensory input generated by transcranial magnetic stimulation (TMS) has been postulated; nonetheless, a characterization of these responses is lacking. The aim of this work was to review current evidence about possible somatosensory evoked potentials (SEP) induced by sources of somatosensory input in the craniofacial region. Among these, only contraction of craniofacial muscle and stimulation of free cutaneous nerve endings may be able to induce EEG responses, but direct evidence is lacking due to experimental difficulties in isolating these inputs. Notably, EEG evoked activity in this context is represented by a N100/P200 complex, reflecting a saliency-related multimodal response, rather than specific activation of the primary somatosensory cortex. Strategies to minimize or remove these responses by EEG processing still yield uncertain results; therefore, data inspection is of paramount importance to judge a possible contamination of the TEP by multimodal potentials caused by somatosensory input.

Novel personalized treatment strategy for patients with chronic stroke with severe upper-extremity impairment: The first patient of the AVANCER trial

BACKGROUND

Around 25% of patients who have had a stroke suffer from severe upper-limb impairment and lack effective rehabilitation strategies. The AVANCER proof-of-concept clinical trial (NCT04448483) tackles this issue through an intensive and personalized-dosage cumulative intervention that combines multiple non-invasive neurotechnologies.

METHODS

The therapy consists of two sequential interventions, lasting until the patient shows no further motor improvement, for a minimum of 11 sessions each. The first phase involves a brain-computer interface governing an exoskeleton and multi-channel functional electrical stimulation enabling full upper-limb movements. The second phase adds anodal transcranial direct current stimulation of the motor cortex of the lesioned hemisphere. Clinical, electrophysiological, and neuroimaging examinations are performed before, between, and after the two interventions (T0, T1, and T2). This case report presents the results from the first patient of the study.

FINDINGS

The primary outcome (i.e., 4-point improvement in the Fugl-Meyer assessment of the upper extremity) was met in the first patient, with an increase from 6 to 11 points between T0 and T2. This improvement was paralleled by changes in motor-network structure and function. Resting-state and transcranial magnetic stimulation-evoked electroencephalography revealed brain functional changes, and magnetic resonance imaging (MRI) measures detected structural and task-related functional changes.

CONCLUSIONS

These first results are promising, pointing to feasibility, safety, and potential efficacy of this personalized approach acting synergistically on the nervous and musculoskeletal systems. Integrating multi-modal data may provide valuable insights into underlying mechanisms driving the improvements and providing predictive information regarding treatment response and outcomes.

FUNDING

This work was funded by the Wyss-Center for Bio and Neuro Engineering (WCP-030), the Defitech Foundation, PHRT-#2017-205, ERA-NET-NEURON (Discover), and SNSF (320030L_197899, NiBS-iCog).

Inhibitory and excitatory responses in the dorso-medial prefrontal cortex during threat processing

Objective

To evaluate cortical excitability during instructed threat processing.

Methods

Single and paired transcranial magnetic stimulation (TMS) pulses were applied to the right dorsomedial prefrontal cortex (dmPFC) during high-density electroencephalography (EEG) recording in young healthy participants (n = 17) performing an instructed threat paradigm in which one of two conditioned stimuli (CS+ but not CS-) was paired with an electric shock (unconditioned stimulus [US]). We assessed TMS-induced EEG responses with spectral power (both at electrode and source level) and information flow (effective connectivity) using Time-resolved Partial Directed Coherence (TPDC). Support vector regression (SVR) was used to predict behavioral fear ratings for CS+ based on TMS impact on excitability.

Results

During intracortical facilitation (ICF), frontal lobe theta power was enhanced for CS+ compared to single pulse TMS for the time window 0-0.5 s after TMS pulse onset (t(16) = 3.9, p < 0.05). At source level, ICF led to an increase and short intracortical inhibition (SICI) to a decrease of theta power in the bilateral dmPFC, relative to single pulse TMS during 0-0.5 s. Compared to single pulse TMS, ICF increased information flows, whereas SICI reduced the information flows in theta band between dmPFC, amygdala, and hippocampus (all at p < 0.05). The magnitude of information flows between dmPFC to amygdala and dmPFC to hippocampus during ICF (0-0.5 s), predicted individual behavioral fear ratings (CS+; coefficient above 0.75).

Conclusion

Distinct excitatory and inhibitory mechanisms take place in the dmPFC. These findings may facilitate future research attempting to investigate inhibitory/facilitatory mechanisms alterations in psychiatric disorders and their behavioral correlates.

The role of neurophysiological tools in the evaluation of ischemic stroke evolution: a narrative review

Ischemic stroke is characterized by a complex cascade of events starting from vessel occlusion. The term "penumbra" denotes the area of severely hypo-perfused brain tissue surrounding the ischemic core that can be potentially recovered if blood flow is reestablished. From the neurophysiological perspective, there are local alterations-reflecting the loss of function of the core and the penumbra-and widespread changes in neural networks functioning, since structural and functional connectivity is disrupted. These dynamic changes are closely related to blood flow in the affected area. However, the pathological process of stroke does not end after the acute phase, but it determines a long-term cascade of events, including changes of cortical excitability, that are quite precocious and might precede clinical evolution. Neurophysiological tools-such as Transcranial Magnetic Stimulation (TMS) or Electroencephalography (EEG)-have enough time resolution to efficiently reflect the pathological changes occurring after stroke. Even if they do not have a role in acute stroke management, EEG and TMS might be helpful for monitoring ischemia evolution-also in the sub-acute and chronic stages. The present review aims to describe the changes occurring in the infarcted area after stroke from the neurophysiological perspective, starting from the acute to the chronic phase.

Electroencephalogram (EEG) With or Without Transcranial Magnetic Stimulation (TMS) as Biomarkers for Post-stroke Recovery: A Narrative Review

Stroke is one of the leading causes of death and disability. Despite the high prevalence of stroke, characterizing the acute neural recovery patterns that follow stroke and predicting long-term recovery remains challenging. Objective methods to quantify and characterize neural injury are still lacking. Since neuroimaging methods have a poor temporal resolution, EEG has been used as a method for characterizing post-stroke recovery mechanisms for various deficits including motor, language, and cognition as well as predicting treatment response to experimental therapies. In addition, transcranial magnetic stimulation (TMS), a form of non-invasive brain stimulation, has been used in conjunction with EEG (TMS-EEG) to evaluate neurophysiology for a variety of indications. TMS-EEG has significant potential for exploring brain connectivity using focal TMS-evoked potentials and oscillations, which may allow for the system-specific delineation of recovery patterns after stroke. In this review, we summarize the use of EEG alone or in combination with TMS in post-stroke motor, language, cognition, and functional/global recovery. Overall, stroke leads to a reduction in higher frequency activity (≥8 Hz) and intra-hemispheric connectivity in the lesioned hemisphere, which creates an activity imbalance between non-lesioned and lesioned hemispheres. Compensatory activity in the non-lesioned hemisphere leads mostly to unfavorable outcomes and further aggravated interhemispheric imbalance. Balanced interhemispheric activity with increased intrahemispheric coherence in the lesioned networks correlates with improved post-stroke recovery. TMS-EEG studies reveal the clinical importance of cortical reactivity and functional connectivity within the sensorimotor cortex for motor recovery after stroke. Although post-stroke motor studies support the prognostic value of TMS-EEG, more studies are needed to determine its utility as a biomarker for recovery across domains including language, cognition, and hemispatial neglect. As a complement to MRI-based technologies, EEG-based technologies are accessible and valuable non-invasive clinical tools in stroke neurology.

Mapping causal circuit dynamics in stroke using simultaneous electroencephalography and transcranial magnetic stimulation

BACKGROUND

Motor impairment after stroke is due not only to direct tissue loss but also to disrupted connectivity within the motor network. Mixed results from studies attempting to enhance motor recovery with Transcranial Magnetic Stimulation (TMS) highlight the need for a better understanding of both connectivity after stroke and the impact of TMS on this connectivity. This study used TMS-EEG to map the causal information flow in the motor network of healthy adult subjects and define how stroke alters these circuits.

METHODS

Fourteen stroke patients and 12 controls received TMS to two sites (bilateral primary motor cortices) during two motor tasks (paretic/dominant hand movement vs. rest) while EEG measured the cortical response to TMS pulses. TMS-EEG based connectivity measurements were derived for each hemisphere and the change in connectivity (ΔC) between the two motor tasks was calculated. We analyzed if ΔC for each hemisphere differed between the stroke and control groups or across TMS sites, and whether ΔC correlated with arm function in stroke patients.

RESULTS

Right hand movement increased connectivity in the left compared to the right hemisphere in controls, while hand movement did not significantly change connectivity in either hemisphere in stroke. Stroke patients with the largest increase in healthy hemisphere connectivity during paretic hand movement had the best arm function.

CONCLUSIONS

TMS-EEG measurements are sensitive to movement-induced changes in brain connectivity. These measurements may characterize clinically meaningful changes in circuit dynamics after stroke, thus providing specific targets for trials of TMS in post-stroke rehabilitation.

Brain Oscillations and Their Implications for Neurorehabilitation

Neural oscillation is rhythmic or repetitive neural activities, which can be observed at all levels of the central nervous system (CNS). The large-scale oscillations measured by electroencephalography have long been used in clinical practice and may have a potential for the usage in neurorehabilitation for people with various CNS disorders. The recent advancement of computational neuroscience has opened up new opportunities to explore clinical application of the results of neural oscillatory activity analysis to evaluation and diagnosis; monitoring the rehab progress; prognostication; and personalized rehabilitation planning in neurorehabilitation. In addition, neural oscillation is catching more attention to its role as a target of noninvasive neuromodulation in neurological disorders.

Fronto-parietal involvement in chronic stroke motor performance when corticospinal tract integrity is compromised

BACKGROUND

Preserved integrity of the corticospinal tract (CST) is a marker of good upper-limb behavior and recovery following stroke. However, there is less understanding of neural mechanisms that might help facilitate upper-limb motor recovery in stroke survivors with extensive CST damage.

OBJECTIVE

The purpose of this study was to investigate resting state functional connectivity in chronic stroke survivors with different levels of CST damage and to explore neural correlates of greater upper-limb motor performance in stroke survivors with compromised ipsilesional CST integrity.

METHODS

Thirty chronic stroke survivors (24 males, aged 64.7 ± 10.8 years) participated in this study. Three experimental sessions were conducted to: 1) obtain anatomical (T1, T2) structural (diffusion) and functional (resting state) MRI sequences, 2) determine CST integrity with transcranial magnetic stimulation (TMS) and conduct assessments of upper-limb behavior, and 3) reconfirm CST integrity status. Participants were divided into groups according to the extent of CST damage. Those in the extensive CST damage group did not show TMS evoked responses and had significantly lower ipsilesional fractional anisotropy.

RESULTS

Of the 30 chronic stroke survivors, 12 were categorized as having extensive CST damage. Stroke survivors with extensive CST damage had weaker functional connectivity in the ipsilesional sensorimotor network and greater functional connectivity in the ipsilesional fronto-parietal network compared to those with preserved CST integrity. For participants with extensive CST damage, improved motor performance was associated with greater functional connectivity of the ipsilesional fronto-parietal network and higher fractional anisotropy of the ipsilesional rostral superior longitudinal fasciculus.

CONCLUSIONS

Stroke survivors with extensive CST damage have greater resting state functional connectivity of an ipsilesional fronto-parietal network that appears to be a behaviorally relevant neural mechanism that improves upper-limb motor performance.

Evaluation of White Matter Integrity Utilizing the DELPHI (TMS-EEG) System

Objective

The aim of this study was to evaluate brain white matter (WM) fibers connectivity damage in stroke and traumatic brain injury (TBI) subjects by direct electrophysiological imaging (DELPHI) that analyzes transcranial magnetic stimulation (TMS)-evoked potentials (TEPs).

Methods

The study included 123 participants, out of which 53 subjects with WM-related pathologies (39 stroke, 14 TBI) and 70 healthy age-related controls. All subjects underwent DELPHI brain network evaluations of TMS-electroencephalogram (EEG)-evoked potentials and diffusion tensor imaging (DTI) scans for quantification of WM microstructure fractional anisotropy (FA).

Results

DELPHI output measures show a significant difference between the healthy and stroke/TBI groups. A multidimensional approach was able to classify healthy from unhealthy with a balanced accuracy of 0.81 ± 0.02 and area under the curve (AUC) of 0.88 ± 0.01. Moreover, a multivariant regression model of DELPHI output measures achieved prediction of WM microstructure changes measured by FA with the highest correlations observed for fibers proximal to the stimulation area, such as frontal corpus callosum (r = 0.7 ± 0.02), anterior internal capsule (r = 0.7 ± 0.02), and fronto-occipital fasciculus (r = 0.65 ± 0.03).

Conclusion

These results indicate that features of TMS-evoked response are correlated to WM microstructure changes observed in pathological conditions, such as stroke and TBI, and that a multidimensional approach combining these features in supervised learning methods serves as a strong indicator for abnormalities and changes in WM integrity.

Differences in Power Spectral Densities and Phase Quantities Due to Processing of EEG Signals

There has been a growing interest in computational electroencephalogram (EEG) signal processing in a diverse set of domains, such as cortical excitability analysis, event-related synchronization, or desynchronization analysis. In recent years, several inconsistencies were found across different EEG studies, which authors often attributed to methodological differences. However, the assessment of such discrepancies is deeply underexplored. It is currently unknown if methodological differences can fully explain emerging differences and the nature of these differences. This study aims to contrast widely used methodological approaches in EEG processing and compare their effects on the outcome variables. To this end, two publicly available datasets were collected, each having unique traits so as to validate the results in two different EEG territories. The first dataset included signals with event-related potentials (visual stimulation) from 45 subjects. The second dataset included resting state EEG signals from 16 subjects. Five EEG processing steps, involved in the computation of power and phase quantities of EEG frequency bands, were explored in this study: artifact removal choices (with and without artifact removal), EEG signal transformation choices (raw EEG channels, Hjorth transformed channels, and averaged channels across primary motor cortex), filtering algorithms (Butterworth filter and Blackman-Harris window), EEG time window choices (-750 ms to 0 ms and -250 ms to 0 ms), and power spectral density (PSD) estimation algorithms (Welch's method, Fast Fourier Transform, and Burg's method). Powers and phases estimated by carrying out variations of these five methods were analyzed statistically for all subjects. The results indicated that the choices in EEG transformation and time-window can strongly affect the PSD quantities in a variety of ways. Additionally, EEG transformation and filter choices can influence phase quantities significantly. These results raise the need for a consistent and standard EEG processing pipeline for computational EEG studies. Consistency of signal processing methods cannot only help produce comparable results and reproducible research, but also pave the way for federated machine learning methods, e.g., where model parameters rather than data are shared.

Recovery from stroke: current concepts and future perspectives

Stroke is a leading cause of acquired, permanent disability worldwide. Although the treatment of acute stroke has been improved considerably, the majority of patients to date are left disabled with a considerable impact on functional independence and quality of life. As the absolute number of stroke survivors is likely to further increase due to the demographic changes in our aging societies, new strategies are needed in order to improve neurorehabilitation. The most critical driver of functional recovery post-stroke is neural reorganization. For developing novel, neurobiologically informed strategies to promote recovery of function, an improved understanding of the mechanisms enabling plasticity and recovery is mandatory.

This review provides a comprehensive survey of recent developments in the field of stroke recovery using neuroimaging and non-invasive brain stimulation. We discuss current concepts of how the brain reorganizes its functional architecture to overcome stroke-induced deficits, and also present evidence for maladaptive effects interfering with recovery. We demonstrate that the combination of neuroimaging and neurostimulation techniques allows a better understanding of how brain plasticity can be modulated to promote the reorganization of neural networks. Finally, neurotechnology-based treatment strategies allowing patient-tailored interventions to achieve enhanced treatment responses are discussed. The review also highlights important limitations of current models, and finally closes with possible solutions and future directions.

Transcranial Direct Current Stimulation to Facilitate Lower Limb Recovery Following Stroke: Current Evidence and Future Directions

Stroke remains a global leading cause of disability. Novel treatment approaches are required to alleviate impairment and promote greater functional recovery. One potential candidate is transcranial direct current stimulation (tDCS), which is thought to non-invasively promote neuroplasticity within the human cortex by transiently altering the resting membrane potential of cortical neurons. To date, much work involving tDCS has focused on upper limb recovery following stroke. However, lower limb rehabilitation is important for regaining mobility, balance, and independence and could equally benefit from tDCS. The purpose of this review is to discuss tDCS as a technique to modulate brain activity and promote recovery of lower limb function following stroke. Preliminary evidence from both healthy adults and stroke survivors indicates that tDCS is a promising intervention to support recovery of lower limb function. Studies provide some indication of both behavioral and physiological changes in brain activity following tDCS. However, much work still remains to be performed to demonstrate the clinical potential of this neuromodulatory intervention. Future studies should consider treatment targets based on individual lesion characteristics, stage of recovery (acute vs. chronic), and residual white matter integrity while accounting for known determinants and biomarkers of tDCS response.