Assessment of Event-Related EEG Power After Single-Pulse TMS in Unresponsive Wakefulness Syndrome and Minimally Conscious State Patients

Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review

The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.

Graph Analysis of TMS-EEG Connectivity Reveals Hemispheric Differences following Occipital Stimulation

(1) Background: Transcranial magnetic stimulation combined with electroencephalography (TMS-EEG) provides a unique opportunity to investigate brain connectivity. However, possible hemispheric asymmetries in signal propagation dynamics following occipital TMS have not been investigated. (2) Methods: Eighteen healthy participants underwent occipital single-pulse TMS at two different EEG sites, corresponding to early visual areas. We used a state-of-the-art Bayesian estimation approach to accurately estimate TMS-evoked potentials (TEPs) from EEG data, which has not been previously used in this context. To capture the rapid dynamics of information flow patterns, we implemented a self-tuning optimized Kalman (STOK) filter in conjunction with the information partial directed coherence (iPDC) measure, enabling us to derive time-varying connectivity matrices. Subsequently, graph analysis was conducted to assess key network properties, providing insight into the overall network organization of the brain network. (3) Results: Our findings revealed distinct lateralized effects on effective brain connectivity and graph networks after TMS stimulation, with left stimulation facilitating enhanced communication between contralateral frontal regions and right stimulation promoting increased intra-hemispheric ipsilateral connectivity, as evidenced by statistical test (p < 0.001). (4) Conclusions: The identified hemispheric differences in terms of connectivity provide novel insights into brain networks involved in visual information processing, revealing the hemispheric specificity of neural responses to occipital stimulation.

Oscillatory EEG-TMS Reactivity in Parkinson Disease

PURPOSE

A dysfunction of beta oscillatory activity is the neurophysiological hallmark of Parkinson disease (PD). How cortical activity reacts to external perturbations may provide insight into pathophysiological mechanisms. This study aims at identifying modifications in EEG rhythms after transcranial magnetic stimulation (TMS) in PD. We hypothesize that single-pulse TMS can modulate brain intrinsic oscillatory properties (e.g., beta excess).

METHODS

EEG data were coregistered during single-pulse TMS (100 stimuli over the primary motor cortex [M1, hotspot for Abductor Pollicis Brevis], random intertrial interval from 8 to 13 seconds). We used a time-frequency analysis based on wavelet method to characterize modification of oscillatory rhythms (delta [1-4 Hz], theta [4-7 Hz], alpha [8-12 Hz], and beta [13-30 Hz] in 15 participants with PD compared with 10 healthy controls.

RESULTS

An increase in beta power over the sensorimotor areas was recorded at rest in the PD group ( P < 0.05). Brain oscillations in PD transiently reset after TMS: beta power over M1 becomes comparable to that recorded in aged-matched healthy subjects in the 2 seconds following TMS.

CONCLUSIONS

Transcranial magnetic stimulation over the dominant motor cortex transiently normalizes cortical oscillations. More user-friendly noninvasive brain stimulation needs to be trialed, based on this proof of concept, to provide practical, portable techniques to treat motor symptoms in PD.

Measure functional network and cortical excitability in post-anoxic patients with unresponsive wakefulness syndrome diagnosed by behavioral scales

Background

Brain assessment shows great values in prognosis, treatment, resource allocation, and decision-making for patients with disorders of consciousness (DOC). However, less research focused on cortical conditions of patients with unresponsive wakefulness syndrome (UWS).

Methods

We recorded resting-state EEG and TMS-EEG from post-anoxic patients with UWS, diagnosed by repeated Coma Recovery Scale-Revised (CRS-R). Measurements of functional connectivity and networks were performed by phase lock value (PLV) and network parameters of graph theory (average path length, clustering coefficient, and small-world). Global cortical reactivity values (GCRV) were used to assess cortical excitability.

Results

The coefficient of variation (CV) presented marked inter-individual variations of PLV (CV = 0.285), network parameters (CV > 0.2), and GCRV (CV = 0.929) within these patients. The patients' PLV and network parameters at theta and alpha bands significantly correlated with their GCRV values. Patients with higher PLV (r = 0.560, 0.406), as well as better preserved network (lower average path length (r = -0.522, -0.483), higher clustering coefficient (r = 0.522, 0.445), and small-world (r = 0.522, 0.445) at theta and alpha bands, presented higher GCRV. The functional connectivity, which is significantly correlated with frontal GCRV, is also mainly located in the frontal region. These correlations were not significant at other frequency bands: Delta, beta, and gamma bands.

Conclusion

These findings suggested that the CRS-R-diagnosed post-anoxic patients with UWS had very different cortical conditions. Functional networks and cortical excitability measured by TMS-EEG could complement behavioral assessment to assess these patients' cortical conditions.

Significance

It provides a deeper understanding of neurophysiological dysfunction in patients with UWS and hints to the clinics that neural-electrophysiological assessment for such patients may be necessary to acquire their brain conditions, which may benefit stratified management for them.

Spontaneous and TMS-related EEG changes as new biomarkers to measure anti-epileptic drug effects

Robust biomarkers for anti-epileptic drugs (AEDs) activity in the human brain are essential to increase the probability of successful drug development. The frequency analysis of electroencephalographic (EEG) activity, either spontaneous or evoked by transcranial magnetic stimulation (TMS-EEG) can provide cortical readouts for AEDs. However, a systematic evaluation of the effect of AEDs on spontaneous oscillations and TMS-related spectral perturbation (TRSP) has not yet been provided. We studied the effects of Lamotrigine, Levetiracetam, and of a novel potassium channel opener (XEN1101) in two groups of healthy volunteers. Levetiracetam suppressed TRSP theta, alpha and beta power, whereas Lamotrigine decreased delta and theta but increased the alpha power. Finally, XEN1101 decreased TRSP delta, theta, alpha and beta power. Resting-state EEG showed a decrease of theta band power after Lamotrigine intake. Levetiracetam increased theta, beta and gamma power, while XEN1101 produced an increase of delta, theta, beta and gamma power. Spontaneous and TMS-related cortical oscillations represent a powerful tool to characterize the effect of AEDs on in vivo brain activity. Spectral fingerprints of specific AEDs should be further investigated to provide robust and objective biomarkers of biological effect in human clinical trials.

A structured ICA-based process for removing auditory evoked potentials

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs), recorded using electroencephalography (EEG), reflect a combination of TMS-induced cortical activity and multi-sensory responses to TMS. The auditory evoked potential (AEP) is a high-amplitude sensory potential-evoked by the "click" sound produced by every TMS pulse-that can dominate the TEP and obscure observation of other neural components. The AEP is peripherally evoked and therefore should not be stimulation site specific. We address the problem of disentangling the peripherally evoked AEP of the TEP from components evoked by cortical stimulation and ask whether removal of AEP enables more accurate isolation of TEP. We hypothesized that isolation of the AEP using Independent Components Analysis (ICA) would reveal features that are stimulation site specific and unique individual features. In order to improve the effectiveness of ICA for removal of AEP from the TEP, and thus more clearly separate the transcranial-evoked and non-specific TMS-modulated potentials, we merged sham and active TMS datasets representing multiple stimulation conditions, removed the resulting AEP component, and evaluated performance across different sham protocols and clinical populations using reduction in Global and Local Mean Field Power (GMFP/LMFP) and cosine similarity analysis. We show that removing AEPs significantly reduced GMFP and LMFP in the post-stimulation TEP (14 to 400 ms), driven by time windows consistent with the N100 and P200 temporal characteristics of AEPs. Cosine similarity analysis supports that removing AEPs reduces TEP similarity between subjects and reduces TEP similarity between stimulation conditions. Similarity is reduced most in a mid-latency window consistent with the N100 time-course, but nevertheless remains high in this time window. Residual TEP in this window has a time-course and topography unique from AEPs, which follow-up exploratory analyses suggest could be a modulation in the alpha band that is not stimulation site specific but is unique to individual subject. We show, using two datasets and two implementations of sham, evidence in cortical topography, TEP time-course, GMFP/LMFP and cosine similarity analyses that this procedure is effective and conservative in removing the AEP from TEP, and may thus better isolate TMS-evoked activity. We show TEP remaining in early, mid and late latencies. The early response is site and subject specific. Later response may be consistent with TMS-modulated alpha activity that is not site specific but is unique to the individual. TEP remaining after removal of AEP is unique and can provide insight into TMS-evoked potentials and other modulated oscillatory dynamics.

EEG as a marker of brain plasticity in clinical applications

Neural networks are dynamic, and the brain has the capacity to reorganize itself. This capacity is named neuroplasticity and is fundamental for many processes ranging from learning and adaptation to new environments to the response to brain injuries. Measures of brain plasticity involve several techniques, including neuroimaging and neurophysiology. Electroencephalography, often used together with other techniques, is a common tool for prognostic and diagnostic purposes, and cortical reorganization is reflected by EEG measurements. Changes of power bands in different cortical areas occur with fatigue and in response to training stimuli leading to learning processes. Sleep has a fundamental role in brain plasticity, restoring EEG bands alterations and promoting consolidation of learning. Exercise and physical inactivity have been extensively studied as both strongly impact brain plasticity. Indeed, EEG studies showed the importance of the physical activity to promote learning and the effects of inactivity or microgravity on cortical reorganization to cope with absent or altered sensorimotor stimuli. Finally, this chapter will describe some of the EEG changes as markers of neural plasticity in neurologic conditions, focusing on cerebrovascular and neurodegenerative diseases. In conclusion, neuroplasticity is the fundamental mechanism necessary to ensure adaptation to new stimuli and situations, as part of the dynamicity of life.

Mapping the Unconscious Brain: Insights From Advanced Neuroimaging

SUMMARY

Recent advances in neuroimaging have been a preeminent factor in the scientific effort to unravel mechanisms of conscious awareness and the pathophysiology of disorders of consciousness. In the first part of this review, we selectively discuss operational models of consciousness, the biophysical signal that is measured using different imaging modalities, and knowledge on disorders of consciousness that has been gleaned with each neuroimaging modality. Techniques considered include diffusion-weighted imaging, diffusion tensor imaging, different types of nuclear medicine imaging, functional MRI, magnetoencephalography, and the combined transcranial magnetic stimulation-electroencephalography approach. In the second part of this article, we provide an overview of how advanced neuroimaging can be leveraged to support neurological prognostication, the use of machine learning to process high-dimensional imaging data, potential applications in clinical practice, and future directions.

Insights of neurophysiology on unconscious state using combined transcranial magnetic stimulation and electroencephalography: A systematic review

Unconscious state has been investigated in numerous studies so far, but pathophysiology of this state is not fully understood. Recently, combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been developed to allow for non-invasive assessment of neurophysiology in the cerebral cortex. We conducted a systematic literature search for TMS-EEG studies on human unconscious state using PubMed with cross-reference and manual searches. The initial search yielded 137 articles, and 19 of them were identified as relevant, including one article found by manual search. This review included 10 studies for unresponsive wakefulness syndrome (UWS), 9 for minimally conscious states (MCS), 5 for medication-induced unconscious states, and 6 for natural non-rapid eye movement states. These studies analyzed TMS-evoked potential to calculate perturbational complexity index (PCI) and OFF-periods. In particular, PCI was found to be a potentially useful marker to differentiate between UWS and MCS. This review demonstrated that TMS-EEG could represent a promising neuroscientific tool to investigate various unconscious states. Further TMS-EEG research may help elucidate the neural basis of unconscious state.

Clinical diagnosis guidelines and neurorestorative treatment for chronic disorders of consciousness (2021 China version)

Chronic disorders of consciousness (DOC) include the vegetative state and the minimally consciousness state. The DOC diagnosis mainly relies on the evaluation of clinical behavioral scales, electrophysiological testing, and neuroimaging examinations. No specifically effective neurorestorative methods for chronic DOC currently exist. Any valuable exploration therapies of being able to repair functions and/or structures in the consciousness loop (e.g., drugs, hyperbaric medicines, noninvasive neurostimulation, sensory and environmental stimulation, invasive neuromodulation therapy, and cell transplantation) may become effective neurorestorative strategies for chronic DOC. In the viewpoint of Neurorestoratology, this guideline proposes the diagnostic and neurorestorative therapeutic suggestions and future exploration direction for this disease following the review of the existing treatment exploration achievements for chronic DOC.

Managing disorders of consciousness: the role of electroencephalography

Disorders of consciousness (DOC) are an important but still underexplored entity in neurology. Novel electroencephalography (EEG) measures are currently being employed for improving diagnostic classification, estimating prognosis and supporting medicolegal decision-making in DOC patients. However, complex recording protocols, a confusing variety of EEG measures, and complicated analysis algorithms create roadblocks against broad application. We conducted a systematic review based on English-language studies in PubMed, Medline and Web of Science databases. The review structures the available knowledge based on EEG measures and analysis principles, and aims at promoting its translation into clinical management of DOC patients.

Cerebellar-Stimulation Evoked Prefrontal Electrical Synchrony Is Modulated by GABA

Cerebellar-prefrontal connectivity has been recognized as important for behaviors ranging from motor coordination to cognition. Many of these behaviors are known to involve excitatory or inhibitory modulations from the prefrontal cortex. We used cerebellar transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) to probe cerebellar-evoked electrical activity in prefrontal cortical areas and used magnetic resonance spectroscopy (MRS) measures of prefrontal GABA and glutamate levels to determine if they are correlated with those potentials. Cerebellar-evoked bilateral prefrontal synchrony in the theta to gamma frequency range showed patterns that reflect strong GABAergic inhibitory function (r = - 0.66, p = 0.002). Stimulation of prefrontal areas evoked bilateral prefrontal synchrony in the theta to low beta frequency range that reflected, conversely, glutamatergic excitatory function (r = 0.66, p = 0.002) and GABAergic inhibitory function (r = - 0.65, p = 0.002). Cerebellar-evoked prefrontal synchronization had opposite associations with cognition and motor coordination: it was positively associated with working memory performance (r = 0.57, p = 0.008) but negatively associated with coordinated motor function as measured by rapid finger tapping (r = - 0.59, p = 0.006). The results suggest a relationship between regional GABA levels and interregional effects on synchrony. Stronger cerebellar-evoked prefrontal synchrony was associated with better working memory but surprisingly worse motor coordination, which suggests competing effects for motor activity and cognition. The data supports the use of a TMS-EEG-MRS approach to study the neurochemical basis of large-scale oscillations modulated by the cerebellar-prefrontal connectivity.

Challenges and demand for modeling disorders of consciousness following traumatic brain injury

Following severe traumatic brain injury (TBI), many patients experience coma - an unresponsive state lacking wakefulness or awareness. Coma rarely lasts more than two weeks, and emergence involves passing through a state of wakefulness without awareness of self or environment. Patients that linger in these Disorders of Consciousness (DoC) undergo clinical assessments of awareness for diagnosis into Unresponsive Wakefulness Syndrome (no awareness, also called vegetative state) or Minimally Conscious State (periodic increases in awareness). These diagnoses are notoriously inaccurate, offering little prognostic value. Recovery of awareness is unpredictable, returning within weeks, years, or never. This leaves patients' families with difficult decisions and little information on which to base them. Clinical studies have made significant advancements, but remain encumbered by high variability, limited data output, and a lack of necessary controls. Herein we discuss the clear and present need to establish a preclinical model of TBI-induced DoC, the significant challenges involved, and how such a model can be applied to support DoC research.

Understanding individual variability in symptoms and recovery following mTBI: A role for TMS-EEG?

The pathophysiology associated with mild traumatic brain injury (mTBI) includes neurometabolic and cytoskeletal changes that have been shown to impair structural and functional connectivity. Evidence that persistent neuropsychological impairments post injury are linked to structural and functional connectivity changes is increasing. However, to date the relationship between connectivity changes, heterogeneity of persistent symptoms and recovery post mTBI has been poorly characterised. Recent innovations in neuroimaging provide new ways of exploring connectivity changes post mTBI. Namely, combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) offers several advantages over traditional approaches for studying connectivity changes post TBI. Its ability to perturb neural function in a controlled manner allows for measurement of causal interactions or effective connectivity between brain regions. We review the current literature assessing structural and functional connectivity following mTBI and outline the rationale for the use of TMS-EEG as an ideal tool for investigating the neural substrates of connectivity dysfunction and reorganisation post mTBI. The diagnostic, prognostic and potential therapeutic implications will also be explored.

Disorders of consciousness after severe brain injury: therapeutic options

PURPOSE OF REVIEW

Very few options exist for patients who survive severe traumatic brain injury but fail to fully recover and develop a disorder of consciousness (e.g. vegetative state, minimally conscious state).

RECENT FINDINGS

Among pharmacological approaches, Amantadine has shown the ability to accelerate functional recovery. Although with very low frequency, Zolpidem has shown the ability to improve the level of consciousness transiently and, possibly, also in a sustained fashion. Among neuromodulatory approaches, transcranial direct current stimulation has been shown to transiently improve behavioral responsiveness, but mostly in minimally conscious patients. New evidence for thalamic deep brain stimulation calls into question its cost/benefit trade-off.

SUMMARY

The growing understanding of the biology of disorders of consciousness has led to a renaissance in the development of therapeutic interventions for patients with disorders of consciousness. High-quality evidence is emerging for pharmacological (i.e. Amantadine) and neurostimulatory (i.e. transcranial direct current stimulation) interventions, although further studies are needed to delineate preconditions, optimal dosages, and timing of administration. Other exciting new approaches (e.g. low intensity focused ultrasound) still await systematic assessment. A crucial future direction should be the use of neuroimaging measures of functional and structural impairment as a means of tailoring patient-specific interventions.