CogNeuroEng 2017 Abstracts

Full Papers
Paper Nr: 2

A Simple and Practical Sensorimotor EEG Device for Recording in Patients with Special Needs


Stefan Ehrlich, Ana Alves-Pinto, Renée Lampe and Gordon Cheng

Abstract: In studies involving patients with special needs, the use of electroencephalography (EEG) recordings is among the most delicate measurement modalities. The quietness needed and the long preparation time can be challenging especially in young ages. Furthermore, the invasive appearance of the instrumentation involved is not appealing and can raise distrust in patients. We developed a customized EEG device which adresses these issues by merging commercially available EEG hardware with an unobtrusive headphones design. The resulting device has very short preparation times, non-clinical appearance, and delivers adequate data quality with respect to recording of sensorimotor rhythms. Our device was employed in a study investigating sensorimotor-related brain activity in adolescents and adults with cerebral palsy (CP) conducted at a day-care center. Experimenters reported convenient data collection and overall acceptance of the system among patients. The changes in sensorimotor rhythms over time during a hand motor task meet the observations described in the literature, supporting the functionality of our EEG device for the assessment of sensorimotor-related measures of brain activity in patients with sensorimotor disorders of neuronal origin.

Short Papers
Paper Nr: 1

Neurofeedback as a Neurorehabilitation Tool for Memory Deficits - A Phase 0 Clinical Trial


Katia Andrade, Nesma Houmani, Bruno Dubois and Francois Vialatte

Abstract: OBJECTIVES Although underexplored, the idea of using brain-computer interfaces (BCI) for behavioral and cognitive rehabilitation is based on recent evidence suggesting that not only self-regulated brain signals, but also involuntary brain signals may provide useful information about the BCI user. These BCI systems, also called passive BCIs, acquire brain waves from an electroencephalographic (EEG) amplifier and then utilize the biomarkers derived from the brain signal and adapt to the user’s performance without the purpose of voluntary control of the system (Zander & Kothe, 2011).The aim is to apply neuro-physiological regulation to foster cortical reorganization and compensatory cerebral activation by targeting brain-wave correlates of functional deficits, thus promoting Central Nervous System (CNS) plasticity (Duffau, 2006). Critically, CNS plasticity has been observed in early-stages of dementia, thus constituting a great challenge for the development of “cognitive BCIs” focused on the rehabilitation of brain functions in neurological patients (Hill et al., 2011). The main goal of this project is to promote CNS plasticity, and therefore cognitive reserve, through neurofeedback training in subjects with Subjective Memory Complaints (SMC) related to attentional deficits. It is a Phase 0 clinical trial. METHODS Several EEG markers were developed in the literature for Alzheimer’s disease (AD) detection and their efficiency was largely proven in the state-of-the-art (Cibils, 2002; Babiloni et al., 2004; Ilh et al., 1996; Vialatte et al., 2011; Houmani et al., 2015). In this project, we will transpose these biomarkers to the framework of our BCI-system and apply them in subjects with Subjective Memory Complaints (SMC). Such markers can be reduced to small sets of EEG channels: we conducted simulations, and obtained stable classifications results using a set of four EEG channels. Experiments will involve 40 SMC subjects, recruited at the Institut de la Mémoire et de la Maladie d’Alzheimer, in the Salpêtrière’s hospital, in Paris. Subjects will be assigned randomly to either the neurofeedback or the sham task. The procedure will be double-blinded. Subjects will participate in 20 (neurofeedback or sham) sessions, twice per week over a period of maximally 10 weeks. At the end of each neurofeedback/sham session, the state of the patients will be assessed in order to evaluate for any adverse effect. In case such effects were to be observed, the protocol would be interrupted. Each session of 30 minutes will start and end with a recording of 1 minute of rest EEG with eyes opened. In addition, subjects will be administered a pre-trial and a post-trial standardized neuropsychological battery, lasting 1 hour. The individual results (n=40) will be analyzed with a reliable change index (RCI; Jacobson & Truax, 1991). Additional analyses between neurofeedback and sham groups will be performed. The training protocol will be personalized. This is critical, since each subject has his/her own EEG pattern. Moreover, the use of one standard protocol could be ineffective or even adverse. RESULTS We expect the development of a cognitive BCI that allows 1) an electrophysiological reorganization of subjects’ brain activity, directly correlated with 2) subjective and objective improvement of subject’s memory and attentional functions, as measured by a previously validated Memory Complaints Questionnaire and specific neuropsychological tests, all administered to each subject pre- and post-trial. DISCUSSION Subjective Memory Complaints (SMC) are reports of problems with, or changes in, memory, being often a source of distress among older adults (Yates et al., 2017). Indeed, although the subjective decline lies within the normal limits of cognitive ageing, it negatively influences everyday functioning. However, attentional resources have been found to be critical for subjects’ perception of everyday memory functioning, which seems related to the role of prefrontal attention systems for memory retrieval (Davidson et al., 2006). Furthermore, it has been demonstrated that depression or anxiety may also influence the expression of SMC (Balash et al., 2013). Therefore, the examination of memory efficiency in older subjects requires not only memory tasks, but additional measures of cognitive function (focusing on attention), as well as mood examination. Criticaly, recent evidence from both neuroimaging and behavioral outcomes research supports the ability of the brain to adapt, modify, and learn throughout, at a minimum, the early stages of dementia. For instance, evidence from functional neuroimaging has shown that AD patients can use additional neural resources in the prefrontal cortex to compensate for losses attributable to the degenerative process of the disease (Grady et al., 2003). Moreover, neurofeedback (NFB) training has been found to improve attention abilities in elderly people (Angelakis et al., 2007; Wang & Hsieh, 2013). Taken together, these findings suggest that NFB may have a place in the treatment of individuals with Subjective Memory Complaints, as well as in patients in very mild stages of Alzheimer’s disease. Importantly, Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that leads to progressive decline of cognitive functions, along with behavioral disturbances and insidious loss of autonomy in daily living activities (Dubois et al., 2014). Its incidence increases exponentially with age, and doubles every 5 years after the age of 65 (Kukull et al., 2002; Qiu et al., 2009; Corrada et al., 2010), being the most common cause of dementia in late adult life. Accordingly, and because of the unprecedented level of aging in developed countries, the health care costs associated with AD are exceptional high, imposing a tremendous burden on modern societies. Currently, two classes of drugs, cholinesterase inhibitors [ChE-I] and N-metil-D-aspartate [NMDA] receptor antagonist, are recommended for the symptomatic treatment of AD, each targeting a different neurochemical component thought to underlie the condition (Cummings, 2000). Unfortunately, none of the available treatments is able to stop or reverse the disease progression, and their cost-effectiveness has been questioned (Loveman et al., 2006). Thus, continuing efforts are required, with an urgent need for the development of novel therapeutic strategies, envisaging not only pharmacological but also non-pharmacological interventions. This project represents a first step on this path, even though considerable development and controlled clinical trials will be required before these BCI interventions earn a place in our standard of clinical care.

Paper Nr: 3

Informative Oscillatory EEG Components and their Persistence in Time and Frequency


Michael Tangermann and Andreas Meinel

Abstract: Oscillatory brain activity measured by the electroencephalogram, local field potentials or magnetoencephalogram can reflect cognitive processes. It can be used to run brain-computer interfaces or to analyze information processing, user learning and rehabilitation progress, e.g., after stroke. To extract oscillatory components, which are informative about a user’s task and which show an enhanced signal-to-noise compared to raw multivariate recordings, data-driven spatial filtering methods are widely applied. Some of these approaches can learn spatial filters from labeled data. They typically require the data analyst to at least define a frequency band of interest and time interval relative to the course of events in the experiment. These hyperparameters are exploited by the filtering method in order to extract informative oscillatory features. Their choice typically is domain-specific and may require adaptations to individuals. Post-hoc data analysis, however, should not be restricted to the initial hyperparameter ranges. Thus we present an approach, which allows to characterize a given oscillatory component with respect to the frequency bands and the temporal windows for which it contains task-relevant information. The approach allows to track task-informative persistence of components over multiple experimental sessions and may be helpful to monitor motor learning and rehabilitation over time.