Fatigue in children using motor imagery and P300 brain-computer interfaces.

BACKGROUND: Brain-computer interface (BCI) technology offers children with quadriplegic cerebral palsy unique opportunities for communication, environmental exploration, learning, and game play. Research in adults demonstrates a negative impact of fatigue on BCI enjoyment, while effects on BCI performance are variable. To date, there have been no pediatric studies of BCI fatigue. The purpose of this study was to assess the effects of two different BCI paradigms, motor imagery and visual P300, on the development of self-reported fatigue and an electroencephalography (EEG) biomarker of fatigue in typically developing children. METHODS: Thirty-seven typically-developing school-aged children were recruited to a prospective, crossover study. Participants attended three sessions: (A) motor imagery-BCI, (B) visual P300-BCI, and (C) video viewing (control). The motor imagery task involved an imagined left- or right-hand squeeze. The P300 task involved attending to one square on a 3 × 3 grid during a random single flash sequence. Each paradigm had respective calibration periods and a similar visual counting game. Primary outcomes were self-reported fatigue and the power of the EEG alpha band both collected during resting-state periods pre- and post-task. Self-reported fatigue was measured using a 10-point visual analog scale. EEG alpha band power was calculated as the integrated power spectral density from 8 to 12 Hz of the EEG spectrum. RESULTS: Thirty-two children completed the protocol (age range 7-16, 63% female). Self-reported fatigue and EEG alpha band power increased across all sessions (F(1,155) = 33.9, p < 0.001; F = 5.0(1,149), p = 0.027 respectively). No differences in fatigue development were observed between session types. There was no correlation between self-reported fatigue and EEG alpha band power change. BCI performance varied between participants and paradigms as expected but was not associated with self-reported fatigue or EEG alpha band power. CONCLUSION: Short periods (30-mintues) of BCI use can increase self-reported fatigue and EEG alpha band power to a similar degree in children performing motor imagery and P300 BCI paradigms. Performance was not associated with our measures of fatigue; the impact of fatigue on useability and enjoyment is unclear. Our results reflect the variability of fatigue and the BCI experience more broadly in children and warrant further investigation.

Structural brain network lateralization across childhood and adolescence.

Developmental lateralization of brain function is imperative for behavioral specialization, yet few studies have investigated differences between hemispheres in structural connectivity patterns, especially over the course of development. The present study compares the lateralization of structural connectivity patterns, or topology, across children, adolescents, and young adults. We applied a graph theory approach to quantify key topological metrics in each hemisphere including efficiency of information transfer between regions (global efficiency), clustering of connections between regions (clustering coefficient [CC]), presence of hub-nodes (betweenness centrality [BC]), and connectivity between nodes of high and low complexity (hierarchical complexity [HC]) and investigated changes in these metrics during development. Further, we investigated BC and CC in seven functionally defined networks. Our cross-sectional study consisted of 211 participants between the ages of 6 and 21 years with 93% being right-handed and 51% female. Global efficiency, HC, and CC demonstrated a leftward lateralization, compared to a rightward lateralization of BC. The sensorimotor, default mode, salience, and language networks showed a leftward asymmetry of CC. BC was only lateralized in the salience (right lateralized) and dorsal attention (left lateralized) networks. Only a small number of metrics were associated with age, suggesting that topological organization may stay relatively constant throughout school-age development, despite known underlying changes in white matter properties. Unlike many other imaging biomarkers of brain development, our study suggests topological lateralization is consistent across age, highlighting potential nonlinear mechanisms underlying developmental specialization.

Analysis of EEG networks and their correlation with cognitive impairment in preschool children with epilepsy.

OBJECTIVE: Cognitive impairment (CI) is common in children with epilepsy and can have devastating effects on their quality of life. Early identification of CI is a priority to improve outcomes, but the current gold standard of detection with psychometric assessment is resource intensive and not always available. This paper proposes exploiting network analysis techniques to characterize routine clinical electroencephalography (EEG) to help identify CI in children with early-onset epilepsy (CWEOE) (0-5 years old). METHODS: Functional networks from routinely acquired EEGs of 51 newly diagnosed CWEOE were analyzed. Combinations of connectivity metrics with subnetwork analysis identified significant correlations between network properties and cognition scores via rank correlation analysis (Kendall's τ). Predictive properties were investigated using a cross-validated classification model with healthy cognition, mild/moderate CI, and severe CI classes. RESULTS: Network analysis revealed phase-dependent connectivity having higher sensitivity to CI and significant functional network changes across EEG frequencies. Nearly 70.5% of CWEOE were aptly classified as having healthy cognition, mild/moderate CI, or severe CI using network features. These features predicted CI classes 55% better than chance and halved misclassification penalties. CONCLUSIONS: Cognitive impairment in CWEOE can be detected with sensitivity at 85% (in identifying mild/moderate or severe CI) and specificity of 84%, by network analysis. SIGNIFICANCE: This study outlines a data-driven methodology for identifying candidate biomarkers of CI in CWEOE from network features. Following additional replication, the proposed method and its use of routinely acquired EEG forms an attractive proposition for supporting clinical assessment of CI.

MRI uncovers disrupted hippocampal microstructure that underlies memory impairments after early-life adversity.

Memory and related cognitive functions are progressively impaired in a subgroup of individuals experiencing childhood adversity and stress. However, it is not possible to identify vulnerable individuals early, a crucial step for intervention. In this study, high-resolution magnetic resonance imaging (MRI) and intra-hippocampal diffusion tensor imaging (DTI) were employed to examine for structural signatures of cognitive adolescent vulnerabilities in a rodent model of early-life adversity. These methods were complemented by neuroanatomical and functional assessments of hippocampal network integrity during adolescence, adulthood and middle-age. The high-resolution MRI identified selective loss of dorsal hippocampal volume, and intra-hippocampal DTI uncovered disruption of dendritic structure, consistent with disrupted local connectivity, already during late adolescence in adversity-experiencing rats. Memory deteriorated over time, and stunting of hippocampal dendritic trees was apparent on neuroanatomical analyses. Thus, disrupted hippocampal neuronal structure and connectivity, associated with cognitive impairments, are detectable via non-invasive imaging modalities in rats experiencing early-life adversity. These high-resolution imaging approaches may constitute promising tools for prediction and assessment of at-risk individuals in the clinic. © 2016 Wiley Periodicals, Inc.

Seeking the Amygdala: Novel Use of Diffusion Tensor Imaging to Delineate the Basolateral Amygdala.

The amygdaloid complex, including the basolateral nucleus (BLA), contributes crucially to emotional and cognitive brain functions, and is a major target of research in both humans and rodents. However, delineating structural amygdala plasticity in both normal and disease-related contexts using neuroimaging has been hampered by the difficulty of unequivocally identifying the boundaries of the BLA. This challenge is a result of the poor contrast between BLA and the surrounding gray matter, including other amygdala nuclei. Here, we describe a novel diffusion tensor imaging (DTI) approach to enhance contrast, enabling the optimal identification of BLA in the rodent brain from magnetic resonance (MR) images. We employed this methodology together with a slice-shifting approach to accurately measure BLA volumes. We then validated the results by direct comparison to both histological and cellular-identity (parvalbumin)-based conventional techniques for defining BLA in the same brains used for MRI. We also confirmed BLA connectivity targets using DTI-based tractography. The novel approach enables the accurate and reliable delineation of BLA. Because this nucleus is involved in and changed by developmental, degenerative and adaptive processes, the instruments provided here should be highly useful to a broad range of neuroimaging studies. Finally, the principles used here are readily applicable to numerous brain regions and across species.

Establishing a Clinical Brain-Computer Interface Program for Children With Severe Neurological Disabilities.

BACKGROUND: Children with severe motor impairment but intact cognition are deprived of fundamental human rights. Quadriplegic cerebral palsy is the most common scenario where rehabilitation options remain limited. Brain-computer interfaces (BCI) represent a potential solution, but pediatric populations have been neglected. Direct engagement of children and families could provide meaningful opportunities while informing program development. We describe a patient-centered, clinical, non-invasive pediatric BCI program. METHODS: Eligible children were identified within a population-based, tertiary care children's hospital. Criteria included 1) age six to 18 years, 2) severe physical disability (non-ambulatory, minimal hand use), 3) severely limited speech, and 4) evidence of grade 1 cognitive capacity. After initial screening for BCI competency, participants attended regular sessions, attempting commercially available and customized systems to play computer games, control devices, and attempt communication. RESULTS: We report the first 10 participants (median 11 years, range 6-16, 60% male). Over 334 hours of participation, there were no serious adverse events. BCI training was well tolerated, with favorable feedback from children and parents. All but one participant demonstrated the ability to perform BCI tasks. The majority performed well, using motor imagery based tasks for games and entertainment. Difficulties were most significant using P300, visual evoked potential based paradigms where maintenance of attention was challenging. Children and families expressed interest in continuing and informing program development. CONCLUSIONS: Patient-centered clinical BCI programs are feasible for children with severe disabilities. Carefully selected participants can often learn quickly to perform meaningful tasks on readily available systems. Patient and family motivation and engagement appear high.

Structural connectivity of the sensorimotor network within the non-lesioned hemisphere of children with perinatal stroke.

Perinatal stroke occurs early in life and often leads to a permanent, disabling weakness to one side of the body. To test the hypothesis that non-lesioned hemisphere sensorimotor network structural connectivity in children with perinatal stroke is different from controls, we used diffusion imaging and graph theory to explore structural topology between these populations. Children underwent diffusion and anatomical 3T MRI. Whole-brain tractography was constrained using a brain atlas creating an adjacency matrix containing connectivity values. Graph theory metrics including betweenness centrality, clustering coefficient, and both neighbourhood and hierarchical complexity of sensorimotor nodes were compared to controls. Relationships between these connectivity metrics and validated sensorimotor assessments were explored. Eighty-five participants included 27 with venous stroke (mean age = 11.5 ± 3.7 years), 26 with arterial stroke (mean age = 12.7 ± 4.0 years), and 32 controls (mean age = 13.3 ± 3.6 years). Non-lesioned primary motor (M1), somatosensory (S1) and supplementary motor (SMA) areas demonstrated lower betweenness centrality and higher clustering coefficient in stroke groups. Clustering coefficient of M1, S1, and SMA were inversely associated with clinical motor function. Hemispheric betweenness centrality and clustering coefficient were higher in stroke groups compared to controls. Hierarchical and average neighbourhood complexity across the hemisphere were lower in stroke groups. Developmental plasticity alters the connectivity of key nodes within the sensorimotor network of the non-lesioned hemisphere following perinatal stroke and contributes to clinical disability.

On the feasibility of simple brain-computer interface systems for enabling children with severe physical disabilities to explore independent movement.

Introduction: Children with severe physical disabilities are denied their fundamental right to move, restricting their development, independence, and participation in life. Brain-computer interfaces (BCIs) could enable children with complex physical needs to access power mobility (PM) devices, which could help them move safely and independently. BCIs have been studied for PM control for adults but remain unexamined in children. In this study, we explored the feasibility of BCI-enabled PM control for children with severe physical disabilities, assessing BCI performance, standard PM skills and tolerability of BCI. Materials and methods: Patient-oriented pilot trial. Eight children with quadriplegic cerebral palsy attended two sessions where they used a simple, commercial-grade BCI system to activate a PM trainer device. Performance was assessed through controlled activation trials (holding the PM device still or activating it upon verbal and visual cueing), and basic PM skills (driving time, number of activations, stopping) were assessed through distance trials. Setup and calibration times, headset tolerability, workload, and patient/caregiver experience were also evaluated. Results: All participants completed the study with favorable tolerability and no serious adverse events or technological challenges. Average control accuracy was 78.3 ± 12.1%, participants were more reliably able to activate (95.7 ± 11.3%) the device than hold still (62.1 ± 23.7%). Positive trends were observed between performance and prior BCI experience and age. Participants were able to drive the PM device continuously an average of 1.5 meters for 3.0 s. They were able to stop at a target 53.1 ± 23.3% of the time, with significant variability. Participants tolerated the headset well, experienced mild-to-moderate workload and setup/calibration times were found to be practical. Participants were proud of their performance and both participants and families were eager to participate in future power mobility sessions. Discussion: BCI-enabled PM access appears feasible in disabled children based on evaluations of performance, tolerability, workload, and setup/calibration. Performance was comparable to existing pediatric BCI literature and surpasses established cut-off thresholds (70%) of "effective" BCI use. Participants exhibited PM skills that would categorize them as "emerging operational learners." Continued exploration of BCI-enabled PM for children with severe physical disabilities is justified.

Iterative Development of a Software to Facilitate Independent Home Use of BCI Technologies for Children with Quadriplegic Cerebral Palsy.

Brain-computer interfaces (BCIs) are emerging as a new solution for children with severe disabilities to interact with the world. However, BCI technologies have yet to reach end-users in their daily lives due to significant translational gaps. To address these gaps, we applied user-centered design principles to establish a home BCI program for children with quadriplegic cerebral palsy. This work describes the technical development of the software we designed to facilitate BCI use at home. Children and their families were involved at each design stage to evaluate and provide feedback. Since deployment, seven families have successfully used the system independently at home and continue to use BCI at home to further enable participation and independence for their children. Clinical relevance- The design and successful implementation of user-centered software for home use will both inform on the feasibility of BCI as a long-term access solution for children with neurological disabilities as well as decrease barriers of accessibility and availability of BCI technologies for end-users.

Unlocking Independence: Exploring Movement with Brain-Computer Interface for Children with Severe Physical Disabilities.

Children with severe physical disabilities are often unable to independently explore their environments, further contributing to complex developmental delays. Brain-computer interfaces (BCIs) could be a novel access method to power mobility for children who struggle to use existing alternate access technologies, allowing them to reap the developmental, social, and psychological benefits of independent mobility. In this pilot study we demonstrated that children with quadriplegic cerebral palsy can use a simple BCI system to explore movement with a power mobility device. Four children were able to use the BCI to drive forward at least 7m, although more practice is needed to achieve more efficient driving skills through sustained BCI activations.

Developmental neuroplasticity of the white matter connectome in children with perinatal stroke.

OBJECTIVE: To employ diffusion imaging connectome methods to explore network development in the contralesional hemisphere of children with perinatal stroke and its relationship to clinical function. We hypothesized alterations in global efficiency of the intact hemisphere would correlate with clinical disability. METHODS: Children with unilateral perinatal arterial (n = 26) or venous (n = 27) stroke and typically developing controls (n = 32) underwent 3T diffusion and T1 anatomical MRI and completed established motor assessments. A validated atlas coregistered to whole-brain tractography for each individual was used to estimate connectivity between 47 regions. Graph theory metrics (assortativity, hierarchical coefficient of regression, global and local efficiency, and small worldness) were calculated for the left hemisphere of controls and the intact contralesioned hemisphere of both stroke groups. Validated clinical motor assessments were then correlated with connectivity outcomes. RESULTS: Global efficiency was higher in arterial strokes compared to venous strokes (p < 0.001) and controls (p < 0.001) and was inversely associated with all motor assessments (all p < 0.012). Additional graph theory metrics including assortativity, hierarchical coefficient of regression, and local efficiency also demonstrated consistent differences in the intact hemisphere associated with clinical function. CONCLUSIONS: The structural connectome of the contralesional hemisphere is altered after perinatal stroke and correlates with clinical function. Connectomics represents a powerful tool to understand whole brain developmental plasticity in children with disease-specific cerebral palsy.

Advancing Brain-Computer Interface Applications for Severely Disabled Children Through a Multidisciplinary National Network: Summary of the Inaugural Pediatric BCI Canada Meeting.

Thousands of youth suffering from acquired brain injury or other early-life neurological disease live, mature, and learn with only limited communication and interaction with their world. Such cognitively capable children are ideal candidates for brain-computer interfaces (BCI). While BCI systems are rapidly evolving, a fundamental gap exists between technological innovators and the patients and families who stand to benefit. Forays into translating BCI systems to children in recent years have revealed that kids can learn to operate simple BCI with proficiency akin to adults. BCI could bring significant boons to the lives of many children with severe physical impairment, supporting their complex physical and social needs. However, children have been neglected in BCI research and a collaborative BCI research community is required to unite and push pediatric BCI development forward. To this end, the pediatric BCI Canada collaborative network (BCI-CAN) was formed, under a unified goal to cooperatively drive forward pediatric BCI innovation and impact. This article reflects on the topics and discussions raised in the foundational BCI-CAN meeting held in Toronto, ON, Canada in November 2019 and suggests the next steps required to see BCI impact the lives of children with severe neurological disease and their families.

Introducing the Joint EEG-Development Inference (JEDI) Model: A Multi-Way, Data Fusion Approach for Estimating Paediatric Developmental Scores via EEG.

Accounting for developmental changes in children is a key consideration for adapting neurorehabilitation technologies to paediatric populations. Using well-established clinical tests and questionnaires can be resource and time intensive. With many data-driven rehabilitation approaches relying on EEG data, a means to rapidly assess and infer developmental status of children directly from these recordings could be critical. This paper proposes a new model for estimating classic developmental diagnostic scores by exploiting data fusion in a joint tensor-matrix decomposition of the EEG and score data. We have designated this model the joint EEG-development inference (JEDI) model. The proposed model is illustrated using a common EEG task (button press) via publicly available paediatric data from pre-adolescent children. Using three distinct recording blocks for training, validation, and testing and a ten-fold cross-validation scheme, a robust experimental design was used to evaluate the JEDI model under various conditions. Results indicate that the JEDI model can estimate the developmental scores of children while maintaining a high degree of similarity at a population level. These results highlight the JEDI model as a potential evolving tool for rapidly assessing child's development. Clinically, the proposed model could provide useful developmental information in a convenient and low resource manner.

Evaluation of matrix factorisation approaches for muscle synergy extraction.

The muscle synergy concept provides a widely-accepted paradigm to break down the complexity of motor control. In order to identify the synergies, different matrix factorisation techniques have been used in a repertoire of fields such as prosthesis control and biomechanical and clinical studies. However, the relevance of these matrix factorisation techniques is still open for discussion since there is no ground truth for the underlying synergies. Here, we evaluate factorisation techniques and investigate the factors that affect the quality of estimated synergies. We compared commonly used matrix factorisation methods: Principal component analysis (PCA), Independent component analysis (ICA), Non-negative matrix factorization (NMF) and second-order blind identification (SOBI). Publicly available real data were used to assess the synergies extracted by each factorisation method in the classification of wrist movements. Synthetic datasets were utilised to explore the effect of muscle synergy sparsity, level of noise and number of channels on the extracted synergies. Results suggest that the sparse synergy model and a higher number of channels would result in better estimated synergies. Without dimensionality reduction, SOBI showed better results than other factorisation methods. This suggests that SOBI would be an alternative when a limited number of electrodes is available but its performance was still poor in that case. Otherwise, NMF had the best performance when the number of channels was higher than the number of synergies. Therefore, NMF would be the best method for muscle synergy extraction.

On the use of higher-order tensors to model muscle synergies.

The muscle synergy concept provides the best framework to understand motor control and it has been recently utilised in many applications such as prosthesis control. The current muscle synergy model relies on decomposing multi-channel surface Electromyography (EMG) signals into a synergy matrix (spatial mode) and its weighting function (temporal mode). This is done using several matrix factorisation techniques, with Non-negative matrix factorisation (NMF) being the most prominent method. Here, we introduce a 4th-order tensor muscle synergy model that extends the current state of the art by taking spectral information and repetitions (movements) into account. This adds more depth to the model and provides more synergistic information. In particular, we illustrate a proof-of-concept study where the Tucker3 tensor decomposition model was applied to a subset of wrist movements from the Ninapro database. The results showed the potential of Tucker3 tensor factorisation in finding patterns of muscle synergies with information about the movements and highlights the differences between the current and proposed model.

Multiscale dispersion entropy for the regional analysis of resting-state magnetoencephalogram complexity in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive and irreversible brain disorder of the nervous system affecting memory, thinking, and emotion. It is the most important cause of dementia and an influential social problem in all the world. The complexity of brain recordings has been successfully used to help to characterize AD. We have recently introduced multiscale dispersion entropy (MDE) as a very fast and powerful tool to quantify the complexity of signals. The aim of this study is to assess the ability of MDE, in comparison with multiscale permutation entropy (MPE) and multiscale entropy (MSE), to discriminate 36 AD patients from 26 elderly age-matched control subjects using resting-state magnetoencephalogram (MEG) recordings. The results showed that MDE, unlike MSE, does not lead to undefined values. Moreover, the differences between the MDE values for AD palatines versus controls were more significant than their corresponding MSE- and MPE-based values. In addition, the computation time for our recently developed MDE was considerably less than that for MSE and even MPE.

Traumatic brain injury results in acute rarefication of the vascular network.

The role of the cerebrovascular network and its acute response to TBI is poorly defined and emerging evidence suggests that cerebrovascular reactivity is altered. We explored how cortical vessels are physically altered following TBI using a newly developed technique, vessel painting. We tested our hypothesis that a focal moderate TBI results in global decrements to structural aspects of the vasculature. Rats (naïve, sham-operated, TBI) underwent a moderate controlled cortical impact. Animals underwent vessel painting perfusion to label the entire cortex at 1 day post TBI followed by whole brain axial and coronal images using a wide-field fluorescence microscope. Cortical vessel network characteristics were analyzed for classical angiographic features (junctions, lengths) wherein we observed significant global (both hemispheres) reductions in vessel junctions and vessel lengths of 33% and 22%, respectively. Biological complexity can be quantified using fractal geometric features where we observed that fractal measures were also reduced significantly by 33%, 16% and 13% for kurtosis, peak value frequency and skewness, respectively. Acutely after TBI there is a reduction in vascular network and vascular complexity that are exacerbated at the lesion site and provide structural evidence for the bilateral hemodynamic alterations that have been reported in patients after TBI.

Activation of the neurokinin 3 receptor promotes filopodia growth and sprouting in rat embryonic hypothalamic cells.

Members of the tachykinin family have trophic effects on developing neurons. The tachykinin neurokinin 3 receptor (NK3R) appears early in embryonic development; during the peak birthdates of hypothalamic neurons, but its involvement in neural development has not been examined. To address its possible role, immortalized embryonic hypothalamic neurons (CLU209) were treated with CellMask, a plasma membrane stain, or the membranes were imaged in CLU209 cells that were transfected with a pEGFP-NK3R expression vector. Nontransfected cells and transfected cells were then treated with senktide, a NK3R agonist, or Dulbecco's Modified Eagle's Medium (DMEM) and time-lapse confocal images were captured for the following 30 min. Compared to DMEM, senktide treatment led to filopodia initiation from the soma of both nontransfected and transfected CLU209 cells. These filopodia had diameters and lengths of approximately 200 nm and 3 µm, respectively. Pretreatment with an IP3 receptor blocker, 2-aminoethoxydiphenyl borate (2-APB), prevented the senktide-induced growth in filopodia; demonstrating that NK3R-induced outgrowth of filopodia likely involves the release of intracellular calcium. Exposure of transfected CLU209 cells to senktide for 24 h led to further growth of filopodia and processes that extended 10-20 µm. A mathematical model, composed of a linear and population model was developed to account for the dynamics of filopodia growth during a timescale of minutes. The results suggest that the ligand-induced activation of NK3R affects early developmental processes by initiating filopodia formation that are a prerequisite for neuritogenesis.

Rapid, Coordinate Inflammatory Responses after Experimental Febrile Status Epilepticus: Implications for Epileptogenesis.

Epilepsy is a common neurological disorder with many causes. For temporal lobe epilepsy, antecedent insults are typically found. These risk factors include trauma or history of long fever-associated seizures (febrile status epilepticus) in childhood. Whereas the mechanisms by which such insults promote temporal lobe epilepsy are unknown, an extensive body of work has implicated inflammation and inflammatory mediators in both human and animal models of the disorder. However, direct evidence for an epileptogenic role for inflammation is lacking. Here we capitalized on a model where only a subgroup of insult-experiencing rodents develops epilepsy. We reasoned that if inflammation was important for generating epilepsy, then early inflammation should be more prominent in individuals destined to become epileptic compared with those that will not become epileptic. In addition, the molecular and temporal profile of inflammatory mediators would provide insights into which inflammatory pathways might be involved in the disease process. We examined inflammatory profiles in hippocampus and amygdala of individual rats and correlated them with a concurrent noninvasive, amygdalar magnetic resonance imaging epilepsy-predictive marker. We found significant individual variability in the expression of several important inflammatory mediators, but not in others. Of interest, a higher expression of a subset of hippocampal and amygdalar inflammatory markers within the first few hours following an insult correlated with the epilepsy-predictive signal. These findings suggest that some components of the inflammatory gene network might contribute to the process by which insults promote the development of temporal lobe epilepsy.