Andrew Geronimo

Residual alterations of brain electrical activity in clinically asymptomatic concussed individuals: An EEG study

OBJECTIVE To examine the neural substrates underlying performance on Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) and HeadRehab Virtual Reality (VR) balance and spatial modules in a concussed and control group. METHODS Thirteen controls and seven concussed participants were fitted with a Geodesic 128-channel EEG cap and completed three assessments: EEG baseline, ImPACT testing, and VR balance and spatial modules. Concussed participants completed were tested within 8 (5 ± 1) days after injury. RESULTS EEG power was significantly (p < .05) decreased in the concussed group over all testing modalities. EEG coherence was significantly (p < .05) increased in the concussed group during EEG baseline and ImPACT. For VR testing, two conditions showed significant (p < .05) increases in EEG coherence between ROIs, while two different conditions showed significant (p < .05) decreases in coherence levels. CONCLUSIONS Concussed participants passed all clinical concussion testing tools, but showed pathophysiological dysfunction when evaluating EEG variables. SIGNIFICANCE Concussed participants are able to compensate and achieve normal functioning due to recruiting additional brain networks. This allows concussed participants to pass clinical tests while still displaying electrophysiological deficits and clinicians must consider this information when making return-to-play decisions.

Performance predictors of brain–computer interfaces in patients with amyotrophic lateral sclerosis

OBJECTIVE Patients with amyotrophic lateral sclerosis (ALS) may benefit from brain-computer interfaces (BCI), but the utility of such devices likely will have to account for the functional, cognitive, and behavioral heterogeneity of this neurodegenerative disorder. APPROACH In this study, a heterogeneous group of patients with ALS participated in a study on BCI based on the P300 event related potential and motor-imagery. RESULTS The presence of cognitive impairment in these patients significantly reduced the quality of the control signals required to use these communication systems, subsequently impairing performance, regardless of progression of physical symptoms. Loss in performance among the cognitively impaired was accompanied by a decrease in the signal-to-noise ratio of task-relevant EEG band power. There was also evidence that behavioral dysfunction negatively affects P300 speller performance. Finally, older participants achieved better performance on the P300 system than the motor-imagery system, indicating a preference of BCI paradigm with age. SIGNIFICANCE These findings highlight the importance of considering the heterogeneity of disease when designing BCI augmentative and alternative communication devices for clinical applications.

Acceptance of brain-computer interfaces in amyotrophic lateral sclerosis

Abstract Brain-computer interfaces (BCI) have the potential to permit patients with amyotrophic lateral sclerosis (ALS) to communicate even when locked in. Although as many as half of patients with ALS develop cognitive or behavioral dysfunction, the impact of these factors on acceptance of and ability to use a BCI has not been studied. We surveyed patients with ALS and their caregivers about BCIs used as assistive communication tools. The survey focused on the features of a BCI system, the desired end-use functions, and requirements. Functional, cognitive, and behavioral data were collected from patients and analyzed for their influence over decisions about BCI device use. Results showed that behavioral impairment was associated with decreased receptivity to the use of BCI technology. In addition, the operation of a BCI system during a pilot study altered patients’ opinions of the utility of the system, generally in line with their perceived performance at controlling the device. In conclusion, these two findings have implications for the engineering design and clinical care phases of assistive device deployment.

Incorporation of telehealth into a multidisciplinary ALS Clinic: feasibility and acceptability

Abstract Objective: The practice of telehealth in the care of patients with ALS has received little attention, but has the potential to change the multidisciplinary care model. This study was carried out to assess the feasibility and acceptability of telehealth for ALS care via real-time videoconferencing from the clinic to patients’ homes. Methods: Patients and caregivers engaged in live telehealth videoconferencing from their homes with members of a multidisciplinary ALS care team who were located in an ALS clinic, in place of their usual in-person visit to the clinic. Participating patients, their caregivers, and health care providers (HCPs) completed surveys assessing satisfaction with the visit, quality of care, and confidence with the interface. Mixed methods analysis was used for survey responses. Results: Surveys from 11 patients, 12 caregivers, and 15 HCPs were completed. All patients and caregivers, and most HCPs, agreed that the system allowed for good communication, description of concerns, and provision of care recommendations. The most common sentiment conveyed by each group was that telehealth removed the burdens of travel, resulting in lower stress and more comfortable interactions. Caregivers and HCPs expressed more concerns than patients about the ways in which telehealth fell short of in-person care. Conclusions: Telehealth was generally viewed favourably by ALS patients, caregivers, and multidisciplinary team members. Improvements in technology and in methods to provide satisfactory remote care without person-to-person contact should be explored.

A simple generative model applied to motor-imagery brain-computer interfacing

In this study, a generative model is developed in order to translate neural activity into predictable device commands for brain-computer interface (BCI) applications. Generative approaches to BCI translation differ from widely-used discriminative approaches because they develop a model of brain activity dependent on the mental state of the user. Preliminary results indicate that two of three subjects were able to control the system at a level (>;70% accurate) that makes it a viable option for practical use. The accuracy rate of the generative model is compared to the accuracy rate calculated offline using a linear discriminant approach. The advantages of such a system are discussed, and the ongoing opportunities for paradigm improvement are outlined.

Feasibility of EEG Measures in Conjunction With Light Exercise for Return-to-Play Evaluation After Sports-Related Concussion.

Current clinical assessment of sports-related concussion and the determination of “Return-to-Play” lacks assessment of the pathophysiological processes affecting the concussed brain. The objective of this study was to demonstrate the feasibility of electroencephalogram measures that detect neuronal damage and monitor the healing process, giving an improved approximation of pathophysiological recovery.

Visual evoked potentials for attentional gating in a brain-computer interface

For synchronous brain-computer interface (BCI) paradigms tasks that utilize visual cues to direct the user, the neural signals extracted by the computer are representative of voluntary modulation as well as evoked responses. For these paradigms, the evoked potential is often overlooked as a source of artifact. In this paper, we put forth the hypothesis that cue priming, as a mechanism for attentional gating, is predictive of motor imagery performance, and thus a viable option for self-paced (asynchronous) BCI applications. We approximate attention by the amplitude features of visually evoked potentials (VEP)s found using two methods: trial matching to an average VEP template, and component matching to a VEP template defined using independent component analysis (ICA). Templates were used to rank trials that display high vs. low levels of fixation. Our results show that subject fixation, measured by VEP response, fails as a predictor of successful motor-imagery task completion. The implications for the BCI community and the possibilities for alternative cueing methods are given in the conclusions.

A Murine Model to Study Epilepsy and SUDEP Induced by Malaria Infection.

One of the largest single sources of epilepsy in the world is produced as a neurological sequela in survivors of cerebral malaria. Nevertheless, the pathophysiological mechanisms of such epileptogenesis remain unknown and no adjunctive therapy during cerebral malaria has been shown to reduce the rate of subsequent epilepsy. There is no existing animal model of postmalarial epilepsy. In this technical report we demonstrate the first such animal models. These models were created from multiple mouse and parasite strain combinations, so that the epilepsy observed retained universality with respect to genetic background. We also discovered spontaneous sudden unexpected death in epilepsy (SUDEP) in two of our strain combinations. These models offer a platform to enable new preclinical research into mechanisms and prevention of epilepsy and SUDEP.

Expansion of C9ORF72 in amyotrophic lateral sclerosis correlates with brain-computer interface performance

Abnormal expansion of hexanucleotide GGGGCC (G4C2) in the C9ORF72 gene has been associated with multiple neurodegenerative disorders, with particularly high prevalence in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Repeat expansions of this type have been associated with altered pathology, symptom rate and severity, as well as psychological changes. In this study, we enrolled twenty-five patients with ALS and fifteen neurologically healthy controls in a P300 brain-computer interface (BCI) training procedure. Four of the patients were found to possess an expanded allele, which was associated with a reduction in the quality of evoked potentials that led to reduced performance on the BCI task. Our findings warrant further exploration of the relationship between brain function and G4C2 repeat length. Such a relationship suggests that personalized assessment of suitability of BCI as a communication device in patients with ALS may be feasible.

Single Trial Predictors for Gating Motor-Imagery Brain-Computer Interfaces Based on Sensorimotor Rhythm and Visual Evoked Potentials

For brain-computer interfaces (BCIs) that utilize visual cues to direct the user, the neural signals extracted by the computer are representative of ongoing processes, visual evoked responses, and voluntary modulation. We proposed to use three brain signatures for predicting success on a single trial of a BCI task. The first two features, the amplitude and phase of the pre-trial mu amplitude, were chosen as a correlate for cortical excitability. The remaining feature, related to the visually evoked response to the cue, served as a possible measure of fixation and attention to the task. Of these three features, mu rhythm amplitude over the central electrodes at the time of cue presentation and to a lesser extent the single trial visual evoked response were correlated with the success on the subsequent imagery task. Despite the potential for gating trials using these features, an offline gating simulation was limited in its ability to produce an increase in device throughput. This discrepancy highlights a distinction between the identification of predictive features, and the use of this knowledge in an online BCI. Using such a system, we cannot assume that the user will respond similarly when faced with a scenario where feedback is altered by trials that are gated on a regular basis. The results of this study suggest the possibility of using individualized, pre-task neural signatures for personalized, and asynchronous (self-paced) BCI applications, although these effects need to be quantified in a real-time adaptive scenario in a future study.