EEG-based sensorimotor neurofeedback for motor neurorehabilitation in children and adults: A scoping review.

Objective: Therapeutic interventions for children and young people with dystonia and dystonic/dyskinetic cerebral palsy are limited. EEG-based neurofeedback is emerging as a neurorehabilitation tool. This scoping review maps research investigating EEG-based sensorimotor neurofeedback in adults and children with neurological motor impairments, including augmentative strategies.

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.

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.

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.

Metabolic patterns in brain 18F-fluorodeoxyglucose PET relate to aetiology in paediatric dystonia.

There is a lack of imaging markers revealing the functional characteristics of different brain regions in paediatric dystonia. In this observational study, we assessed the utility of [18F]2-fluoro-2-deoxy-D-glucose (FDG)-PET in understanding dystonia pathophysiology by revealing specific resting awake brain glucose metabolism patterns in different childhood dystonia subgroups. PET scans from 267 children with dystonia being evaluated for possible deep brain stimulation surgery between September 2007 and February 2018 at Evelina London Children's Hospital (ELCH), UK, were examined.

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.

Dictionary Learning Strategies for Cortico-Muscular Coherence Detection and Estimation.

The spectral method of cortico-muscular coherence (CMC) can reveal the communication patterns between the cerebral cortex and muscle periphery, thus providing guidelines for the development of new therapies for movement disorders and insights into fundamental motor neuroscience. The method is applied to electroencephalogram (EEG) and surface electromyogram (sEMG) recorded synchronously during a motor task. However, synchronous EEG and sEMG components are typically too weak compared to additive noise and background activities making significant coherence very difficult to detect.

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.

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.

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 and which continue through infancy, childhood, and into adolescence.

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).

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).

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.

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.

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).

Understanding the relationship between brain and upper limb function in children with unilateral motor impairments: A multimodal approach.

Unlabelled: Atypical brain development and early brain injury have profound and long lasting impact on the development, skill acquisition, and subsequent independence of a child. Heterogeneity is present at the brain level and at the motor level; particularly with respect to phenomena of bilateral activation and mirrored movements (MMs). In this multiple case study we consider the feasibility of using several modalities to explore the relationship between brain structure and/or activity and hand function: Electroencephalography (EEG), both structural and functional Magnetic Resonance Imaging (sMRI, fMRI), diffusion tensor imaging (DTI), transcranial magnetic stimulation (TMS), Electromyography (EMG) and hand function assessments.

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.

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.

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.

Central Motor Conduction Time and diffusion tensor imaging metrics in children with complex motor disorders.

Objectives: To explore potential correlations between Diffusion Tensor Imaging (DTI) metrics and Central Motor Conduction Time (CMCT) in a cohort of children with complex motor disorders.

Methods: For a group of 49 children undergoing assessment for potential Deep Brain Stimulation (DBS) surgery, CMCT was derived from the latency of MEPs invoked by transcranial magnetic stimulation of the contralateral motor cortex and from peripheral conduction times. Tract-Based Spatial Statistics (TBSS) was used to compare Diffusion Tensor Imaging (DTI) metrics between children with normal and abnormal CMCT.