Cross-frequency cortex-muscle interactions are abnormal in young people with dystonia.

Sensory processing and sensorimotor integration are abnormal in dystonia, including impaired modulation of beta-corticomuscular coherence. However, cortex-muscle interactions in either direction are rarely described, with reports limited predominantly to investigation of linear coupling, using corticomuscular coherence or Granger causality. Information-theoretic tools such as transfer entropy detect both linear and non-linear interactions between processes. This observational case-control study applies transfer entropy to determine intra- and cross-frequency cortex-muscle coupling in young people with dystonia/dystonic cerebral palsy. Fifteen children with dystonia/dystonic cerebral palsy and 13 controls, aged 12-18 years, performed a grasp task with their dominant hand. Mechanical perturbations were provided by an electromechanical tapper. Bipolar scalp EEG over contralateral sensorimotor cortex and surface EMG over first dorsal interosseous were recorded. Multi-scale wavelet transfer entropy was applied to decompose signals into functional frequency bands of oscillatory activity and to quantify intra- and cross-frequency coupling between brain and muscle. Statistical significance against the null hypothesis of zero transfer entropy was established, setting individual 95% confidence thresholds. The proportion of individuals in each group showing significant transfer entropy for each frequency combination/direction was compared using Fisher's exact test, correcting for multiple comparisons. Intra-frequency transfer entropy was detected in all participants bidirectionally in the beta (16-32 Hz) range and in most participants from EEG to EMG in the alpha (8-16 Hz) range. Cross-frequency transfer entropy across multiple frequency bands was largely similar between groups, but a specific coupling from low-frequency EMG to beta EEG was significantly reduced in dystonia [P = 0.0061 (corrected)]. The demonstration of bidirectional cortex-muscle communication in dystonia emphasizes the value of transfer entropy for exploring neural communications in neurological disorders. The novel finding of diminished coupling from low-frequency EMG to beta EEG in dystonia suggests impaired cortical feedback of proprioceptive information with a specific frequency signature that could be relevant to the origin of the excessive low-frequency drive to muscle.

Subband Independent Component Analysis for Coherence Enhancement.

OBJECTIVE: Cortico-muscular coherence (CMC) is becoming a common technique for detection and characterization of functional coupling between the motor cortex and muscle activity. It is typically evaluated between surface electromyogram (sEMG) and electroencephalogram (EEG) signals collected synchronously during controlled movement tasks. However, the presence of noise and activities unrelated to observed motor tasks in sEMG and EEG results in low CMC levels, which often makes functional coupling difficult to detect. METHODS: In this paper, we introduce Coherent Subband Independent Component Analysis (CoSICA) to enhance synchronous cortico-muscular components in mixtures captured by sEMG and EEG. The methodology relies on filter bank processing to decompose sEMG and EEG signals into frequency bands. Then, it applies independent component analysis along with a component selection algorithm for re-synthesis of sEMG and EEG designed to maximize CMC levels. RESULTS: We demonstrate the effectiveness of the proposed method in increasing CMC levels across different signal-to-noise ratios first using simulated data. Using neurophysiological data, we then illustrate that CoSICA processing achieves a pronounced enhancement of original CMC. CONCLUSION: Our findings suggest that the proposed technique provides an effective framework for improving coherence detection. SIGNIFICANCE: The proposed methodologies will eventually contribute to understanding of movement control and has high potential for translation into clinical practice.

Dystonia in Childhood: How Insights from Paediatric Research Enrich the Network Theory of Dystonia.

Dystonia is now widely accepted as a network disorder, with multiple brain regions and their interconnections playing a potential role in the pathophysiology. This model reconciles what could previously have been viewed as conflicting findings regarding the neuroanatomical and neurophysiological characteristics of the disorder, but there are still significant gaps in scientific understanding of the underlying pathophysiology. One of the greatest unmet challenges is to understand the network model of dystonia in the context of the developing brain. This article outlines how research in childhood dystonia supports and contributes to the network theory and highlights aspects where data from paediatric studies has revealed novel and unique physiological insights, with important implications for understanding dystonia across the lifespan.

Harnessing cognitive strategy use for functional problems and proposed underlying mechanisms in childhood-onset dystonia.

BACKGROUND: There is a significant gap in knowledge about rehabilitation techniques and strategies that can help children and young people with hyperkinetic movement disorders (HMD) including dystonia to successfully perform daily activities and improve overall participation. A promising approach to support skill acquisition is the Cognitive Orientation to daily Occupational Performance (CO-OP) intervention. CO-OP uses cognitive strategies to help patients generate their own solutions to overcome self-identified problems encountered in everyday living. PURPOSE: 1. To identify and categorize strategies used by children with HMD to support skill acquisition during CO-OP; 2. To review the possible underlying mechanisms that might contribute to the cognitive strategies, in order to facilitate further studies for developing focused rehabilitation approaches. METHODS: A secondary analysis was performed on video-recorded data from a previous study exploring the efficacy of CO-OP for childhood onset HMD, in which CO-OP therapy sessions were delivered by a single occupational therapist. For the purpose of this study, we reviewed a total of 40 randomly selected hours of video footage of CO-OP sessions delivered to six participants (age 6-19 years) over ten intervention sessions. An observational recording sheet was applied to identify systematically the participants' or therapist's verbalizations of cognitive strategies during the therapy. The strategies were classified into six categories in line with published literature. RESULTS: Strategies used by HMD participants included distraction, externally focussed attention, internally focussed attention, emotion self-regulation, motor imagery and mental self-guidance. We postulate different underlying working mechanisms for these strategies, which have implications for the therapeutic management of children and young people with HMD including dystonia. CONCLUSIONS: Cognitive strategy training can fundamentally change and improve motor performance. On-going work will address both the underlying neural mechanisms of therapeutic change and the mediators and moderators that influence how change unfolds.

Multiscale Wavelet Transfer Entropy With Application to Corticomuscular Coupling Analysis.

OBJECTIVE: Functional coupling between the motor cortex and muscle activity is commonly detected and quantified by cortico-muscular coherence (CMC) or Granger causality (GC) analysis, which are applicable only to linear couplings and are not sufficiently sensitive: some healthy subjects show no significant CMC and GC, and yet have good motor skills. The objective of this work is to develop measures of functional cortico-muscular coupling that have improved sensitivity and are capable of detecting both linear and non-linear interactions. METHODS: A multiscale wavelet transfer entropy (TE) methodology is proposed. The methodology relies on a dyadic stationary wavelet transform to decompose electroencephalogram (EEG) and electromyogram (EMG) signals into functional bands of neural oscillations. Then, it applies TE analysis based on a range of embedding delay vectors to detect and quantify intra- and cross-frequency band cortico-muscular coupling at different time scales. RESULTS: Our experiments with neurophysiological signals substantiate the potential of the developed methodologies for detecting and quantifying information flow between EEG and EMG signals for subjects with and without significant CMC or GC, including non-linear cross-frequency interactions, and interactions across different temporal scales. The obtained results are in agreement with the underlying sensorimotor neurophysiology. CONCLUSION: These findings suggest that the concept of multiscale wavelet TE provides a comprehensive framework for analyzing cortex-muscle interactions. SIGNIFICANCE: The proposed methodologies will enable developing novel insights into movement control and neurophysiological processes more generally.

Unravelling Causal Relationships Between Cortex and Muscle with Errors-in-variables Models.

Corticomuscular communications are commonly estimated by Granger causality (GC) or directed coherence, with the aim of assessing the linear causal relationship between electroencephalogram (EEG) and electromyogram (EMG) signals. However, conventional GC based on standard linear regression (LR) models may be substantially underestimated in the presence of noise in both EEG and EMG signals: some healthy subjects with good motor skills show no significant GC. In this study, errors-in-variables (EIV) models are investigated for the purpose of estimating underlying linear time-invariant systems in the context of GC. The performance of the proposed method is evaluated using both simulated data and neurophysiological recordings, and compared with conventional GC. It is demonstrated that the inferred EIV-based causality offers an advantage over typical LR-based GC when detecting communication between the cortex and periphery using noisy EMG and EEG signals.

Sensorimotor Integration in Childhood Dystonia and Dystonic Cerebral Palsy-A Developmental Perspective.

Dystonia is a disorder of sensorimotor integration, involving dysfunction within the basal ganglia, cortex, cerebellum, or their inter-connections as part of the sensorimotor network. Some forms of dystonia are also characterized by maladaptive or exaggerated plasticity. Development of the neuronal processes underlying sensorimotor integration is incompletely understood but involves activity-dependent modeling and refining of sensorimotor circuits through processes that are already taking place in utero and which continue through infancy, childhood, and into adolescence. Several genetic dystonias have clinical onset in early childhood, but there is evidence that sensorimotor circuit development may already be disrupted prenatally in these conditions. Dystonic cerebral palsy (DCP) is a form of acquired dystonia with perinatal onset during a period of rapid neurodevelopment and activity-dependent refinement of sensorimotor networks. However, physiological studies of children with dystonia are sparse. This discussion paper addresses the role of neuroplasticity in the development of sensorimotor integration with particular focus on the relevance of these mechanisms for understanding childhood dystonia, DCP, and implications for therapy selection, including neuromodulation and timing of intervention.

EEG measures of sensorimotor processing and their development are abnormal in children with isolated dystonia and dystonic cerebral palsy.

Dystonia is a disorder of sensorimotor integration associated with abnormal oscillatory activity within the basal ganglia-thalamo-cortical networks. Event-related changes in spectral EEG activity reflect cortical processing but are sparsely investigated in relation to sensorimotor processing in dystonia. This study investigates modulation of sensorimotor cortex EEG activity in response to a proprioceptive stimulus in children with dystonia and dystonic cerebral palsy (CP). Proprioceptive stimuli, comprising brief stretches of the wrist flexors, were delivered via a robotic wrist interface to 30 young people with dystonia (20 isolated genetic/idiopathic and 10 dystonic CP) and 22 controls (mean age 12.7 years). Scalp EEG was recorded using the 10-20 international system and the relative change in post-stimulus power with respect to baseline was calculated for the alpha (8-12 Hz) and beta (14-30 Hz) frequency bands. A clear developmental profile in event-related spectral changes was seen in controls. Controls showed a prominent early alpha/mu band event-related desynchronisation (ERD) followed by an event-related synchronisation (ERS) over the contralateral sensorimotor cortex following movement of either hand. The alpha ERD was significantly smaller in the dystonia groups for both dominant and non-dominant hand movement (ANCOVA across the 3 groups with age as covariate: dominant hand F(2,47) = 4.45 p = 0.017; non-dominant hand F(2,42) = 9.397 p < 0.001. Alpha ERS was significantly smaller in dystonia for the dominant hand (ANCOVA F(2,47) = 7.786 p = 0.001). There was no significant difference in ERD or ERS between genetic/idiopathic dystonia and dystonic CP. CONCLUSION: Modulation of alpha/mu activity by a proprioceptive stimulus is reduced in dystonia, demonstrating a developmental abnormality of sensorimotor processing which is common to isolated genetic/idiopathic and acquired dystonia/dystonic CP.

Abnormal microscale neuronal connectivity triggered by a proprioceptive stimulus in dystonia.

We investigated modulation of functional neuronal connectivity by a proprioceptive stimulus in sixteen young people with dystonia and eight controls. A robotic wrist interface delivered controlled passive wrist extension movements, the onset of which was synchronised with scalp EEG recordings. Data were segmented into epochs around the stimulus and up to 160 epochs per subject were averaged to produce a Stretch Evoked Potential (StretchEP). Event-related network dynamics were estimated using a methodology that features Wavelet Transform Coherency (WTC). Global Microscale Nodal Strength (GMNS) was introduced to estimate overall engagement of areas into short-lived networks related to the StretchEP, and Global Connectedness (GC) estimated the spatial extent of the StretchEP networks. Dynamic Connectivity Maps showed a striking difference between dystonia and controls, with particularly strong theta band event-related connectivity in dystonia. GC also showed a trend towards higher values in dystonia than controls. In summary, we demonstrate the feasibility of this method to investigate event-related neuronal connectivity in relation to a proprioceptive stimulus in a paediatric patient population. Young people with dystonia show an exaggerated network response to a proprioceptive stimulus, displaying both excessive theta-band synchronisation across the sensorimotor network and widespread engagement of cortical regions in the activated network.

Application of Machine Learning Using Decision Trees for Prognosis of Deep Brain Stimulation of Globus Pallidus Internus for Children With Dystonia.

BACKGROUND: While Deep Brain Stimulation (DBS) of the Globus pallidus internus is a well-established therapy for idiopathic/genetic dystonia, benefits for acquired dystonia are varied, ranging from modest improvement to deterioration. Predictive biomarkers to aid DBS prognosis for children are lacking, especially in acquired dystonias, such as dystonic Cerebral Palsy. We explored the potential role of machine learning techniques to identify parameters that could help predict DBS outcome. METHODS: We conducted a retrospective study of 244 children attending King's College Hospital between September 2007 and June 2018 for neurophysiological tests as part of their assessment for possible DBS at Evelina London Children's Hospital. For the 133 individuals who underwent DBS and had 1-year outcome data available, we assessed the potential predictive value of six patient parameters: sex, etiology (including cerebral palsy), baseline severity (Burke-Fahn-Marsden Dystonia Rating Scale-motor score), cranial MRI and two neurophysiological tests, Central Motor Conduction Time (CMCT) and Somatosensory Evoked Potential (SEP). We applied machine learning analysis to determine the best combination of these features to aid DBS prognosis. We developed a classification algorithm based on Decision Trees (DTs) with k-fold cross validation for independent testing. We analyzed all possible combinations of the six features and focused on acquired dystonias. RESULTS: Several trees resulted in better accuracy than the majority class classifier. However, the two features that consistently appeared in top 10 DTs were CMCT and baseline dystonia severity. A decision tree based on CMCT and baseline severity provided a range of sensitivity and specificity, depending on the threshold chosen for baseline dystonia severity. In situations where CMCT was not available, a DT using SEP alone provided better than the majority class classifier accuracy. CONCLUSION: The results suggest that neurophysiological parameters can help predict DBS outcomes, and DTs provide a data-driven, highly interpretable decision support tool that lends itself to being used in clinical practice to help predict potential benefit of DBS in dystonic children. Our results encourage the introduction of neurophysiological parameters in assessment pathways, and data collection to facilitate multi-center evaluation and validation of these potential predictive markers and of the illustrative decision support tools presented here.

Abnormal patterns of corticomuscular and intermuscular coherence in childhood dystonia.

OBJECTIVE: Sensorimotor processing is abnormal in Idiopathic/Genetic dystonias, but poorly studied in Acquired dystonias. Beta-Corticomuscular coherence (CMC) quantifies coupling between oscillatory electroencephalogram (EEG) and electromyogram (EMG) activity and is modulated by sensory stimuli. We test the hypothesis that sensory modulation of CMC and intermuscular coherence (IMC) is abnormal in Idiopathic/Genetic and Acquired dystonias. METHODS: Participants: 11 children with Acquired dystonia, 5 with Idiopathic/Genetic dystonia, 13 controls (12-18 years). CMC and IMC were recorded during a grasp task, with mechanical perturbations provided by an electromechanical tapper. Coherence patterns pre- and post-stimulus were compared across groups. RESULTS: Beta-CMC increased post-stimulus in Controls and Acquired dystonia (p = 0.001 and p = 0.010, respectively), but not in Idiopathic/Genetic dystonia (p = 0.799). The modulation differed between groups, being larger in both Controls and Acquired dystonia compared with Idiopathic/Genetic dystonia (p = 0.003 and p = 0.022). Beta-IMC increased significantly post-stimulus in Controls (p = 0.004), but not in dystonia. Prominent 4-12 Hz IMC was seen in all dystonia patients and correlated with severity (rho = 0.618). CONCLUSION: Idiopathic/Genetic and Acquired dystonia share an abnormal low-frequency IMC. In contrast, sensory modulation of beta-CMC differed between the two groups. SIGNIFICANCE: The findings suggest that sensorimotor processing is abnormal in Acquired as well as Idiopathic/Genetic dystonia, but that the nature of the abnormality differs.

Somatosensory Evoked Potentials and Central Motor Conduction Times in children with dystonia and their correlation with outcomes from Deep Brain Stimulation of the Globus pallidus internus.

OBJECTIVES: To report Somatosensory Evoked Potentials (SEPs) and Central Motor Conduction Times (CMCT) in children with dystonia and to test the hypothesis that these parameters predict outcome from Deep Brain Stimulation (DBS). METHODS: 180 children with dystonia underwent assessment for Globus pallidus internus (GPi) DBS, mean age 10 years (range 2.5-19). CMCT to each limb was calculated using Transcranial Magnetic Stimulation. Median and posterior tibial nerve SEPs were recorded over contralateral and midline centro-parietal scalp. Structural abnormalities were assessed with cranial MRI. One-year outcome from DBS was assessed as percentage improvement in Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS-m). RESULTS: Abnormal CMCTs and SEPs were found in 19% and 47% of children respectively and were observed more frequently in secondary than primary dystonia. Of children proceeding to DBS, better outcome was seen in those with normal (n = 78/89) versus abnormal CMCT (n = 11/89) (p = 0.002) and those with normal (n = 35/51) versus abnormal SEPs (n = 16/51) (p = 0.001). These relationships were independent of dystonia aetiology and cranial MRI findings. CONCLUSIONS: CMCTs and SEPs provide objective evidence of motor and sensory pathway dysfunction in children with dystonia and relate to DBS outcome. SIGNIFICANCE: CMCTs and SEPs can contribute to patient selection and counselling of families about potential benefit from neuromodulation for dystonia.

Cortico-muscular coherence enhancement via coherent Wavelet enhanced Independent Component Analysis.

Functional coupling between the motor cortex and muscle activity is usually detected and characterized using the spectral method of cortico-muscular coherence (CMC) between surface electromyogram (sEMG) and electroencephalogram (EEG) recorded synchronously under motor control task. However, CMC is often weak and not easily detectable in all individuals. One of the reasons for the low levels of CMC is the presence of noise and components unrelated to the considered tasks in recorded sEMG and EEG signals. In this paper we propose a method for enhancing relative levels of sEMG components coherent with synchronous EEG signals via a variant of Wavelet Independent Component Analysis combined with a novel component selection algorithm. The effectiveness of the proposed algorithm is demonstrated using data collected in neurophysiologcal experiments.

The neurophysiology of paediatric movement disorders.

PURPOSE OF REVIEW: To demonstrate how neurophysiological tools have advanced our understanding of the pathophysiology of paediatric movement disorders, and of neuroplasticity in the developing brain. RECENT FINDINGS: Delineation of corticospinal tract connectivity using transcranial magnetic stimulation (TMS) is being investigated as a potential biomarker for response to therapy. TMS measures of cortical excitability and neuroplasticity are also being used to investigate the effects of therapy, demonstrating neuroplastic changes that relate to functional improvements. Analyses of evoked potentials and event-related changes in the electroencephalogaphy spectral activity provide growing evidence for the important role of aberrant sensory processing in the pathophysiology of many different movement disorders. Neurophysiological findings demonstrate that children with clinically similar phenotypes may have differing underlying pathophysiology, which in turn may explain differential response to therapy. Neurophysiological parameters can act as biomarkers, providing a means to stratify individuals, and are well suited to provide biofeedback. They therefore have enormous potential to facilitate improvements to therapy. SUMMARY: Although currently a small field, the role of neurophysiology in paediatric movement disorders is poised to expand, both fuelled by and contributing to the rapidly growing fields of neuro-rehabilitation and neuromodulation and the move towards a more individualized therapeutic approach.

Corticomuscular Coherence With Time Lag With Application to Delay Estimation.

Functional coupling between the motor cortex and muscle activity is usually detected and characterized using the spectral method of corticomuscular coherence (CMC). This functional coupling occurs with a time delay, which, if not properly accounted for, may decrease the coherence and make the synchrony difficult to detect. In this paper, we introduce the concept of CMC with time lag (CMCTL), that is the coherence between segments of motor cortex electroencephalogram (EEG) and electromyography (EMG) signals displaced from a central observation point. This concept is motivated by the need to compensate for the unknown delay between coupled cortex and muscle processes. We demonstrate using simulated data that under certain conditions the time lag between EEG and EMG segments at points of local maxima of CMCTL corresponds to the average delay along the involved corticomuscular conduction pathways. Using neurophysiological data, we then show that CMCTL with appropriate time lag enhances the coherence between cortical and muscle signals, and that time lags which correspond to local maxima of CMCTL provide estimates of delays involved in corticomuscular coupling that are consistent with the underlying physiology.

Modulation of corticomuscular coherence by peripheral stimuli.

The purpose of this study was to investigate the effects of peripheral afferent stimuli on the synchrony between brain and muscle activity as estimated by corticomuscular coherence (CMC). Electroencephalogram (EEG) from sensorimotor cortex and electromyogram (EMG) from two intrinsic hand muscles were recorded during a key grip motor task, and the modulation of CMC caused by afferent electrical and mechanical stimulation was measured. The particular stimuli used were graded single-pulse electrical stimuli, above threshold for perception and activating cutaneous afferents, applied to the dominant or non-dominant index finger, and a pulsed mechanical displacement of the gripped object causing the subject to feel as if the object may be dropped. Following electrical stimulation of the dominant index finger, the level of ß-range (14-36 Hz) CMC was reduced in a stimulus intensity-dependent fashion for up to 400 ms post-stimulus, then returned with greater magnitude before falling to baseline levels over 2.5 s, outlasting the reflex and evoked changes in EMG and EEG. Subjects showing no baseline ß-range CMC nevertheless showed post-stimulus increases in ß-range CMC with the same time course as those with baseline ß-range CMC. The mechanical stimuli produced similar modulation of ß-range CMC. Electrical stimuli to the non-dominant index finger produced no significant increase in ß-range CMC. The results suggest that both cutaneous and proprioceptive afferents have access to circuits generating CMC, but that only a functionally relevant stimulus produces significant modulation of the background ß-range CMC, providing further evidence that ß-range CMC has an important role in sensorimotor integration.

Rectification of the EMG is an unnecessary and inappropriate step in the calculation of Corticomuscular coherence.

Corticomuscular coherence (CMC) estimation is a frequency domain method used to detect a linear coupling between rhythmic activity recorded from sensorimotor cortex (EEG or MEG) and the electromyogram (EMG) of active muscles. In motor neuroscience, rectification of the surface EMG is a common pre-processing step prior to calculating CMC, intended to maximize information about action potential timing, whilst suppressing information relating to motor unit action potential (MUAP) shape. Rectification is believed to produce a general shift in the EMG spectrum towards lower frequencies, including those around the mean motor unit discharge rate. However, there are no published data to support the claim that EMG rectification enhances the detection of CMC. Furthermore, performing coherence analysis after the non-linear procedure of rectification, which results in a significant distortion of the EMG spectrum, is considered fundamentally flawed in engineering and digital signal processing. We calculated CMC between sensorimotor cortex EEG and EMG of two hand muscles during a key grip task in 14 healthy subjects. CMC calculated using unrectified and rectified EMG was compared. The use of rectified EMG did not enhance the detection of CMC, nor was there any evidence that MUAP shape information had an adverse effect on the CMC estimation. EMG rectification had inconsistent effects on the power and coherence spectra and obscured the detection of CMC in some cases. We also provide a comprehensive theoretical analysis, which, along with our empirical data, demonstrates that rectification is neither necessary nor appropriate in the calculation of CMC.