Integrating TAM with EEG Frontal Asymmetry

Recent evolution in the Information Systems (IS) community has involved neuroscience tools and methods in order to develop new theories concerning Human-Computer Interaction (HCI) and further understand IS acceptance models. Thus, the field of NeuroIS has emerged. Moreover, NeuroIS researchers have proposed encephalograph (EEG) as valuable usability metric. Particularly, EEG frontal asymmetry has been related to approach/withdraw behaviour and positive/negative affect concerning users’ perceptions. Furthermore, Technology Acceptance Model (TAM) has been established as the most notable model regarding IS acceptance. This study is a first attempt to integrate EEG frontal asymmetry with TAM in order to associate brain activation with the two most important variables of TAM: Perceived Usefulness and Perceived Ease of Use. Specifically, thirty one undergraduate students were chosen to use a Computer-Based Assessment (while being connected to the EEG) in the context of an introductory informatics course. Results indicate a direct positive association of frontal asymmetry on the aforementioned variables. These findings suggest that frontal asymmetry could be useful for validating and developing Information Technology (IT) theories, as well as designing and explaining the acceptance and adoption of new IS systems or products

Add-on topiramate in the treatment of refractory partial-onset epilepsy: Clinical experience of outpatient epilepsy clinics from 11 general hospitals

SummaryAn open, prospective, observational study was performed to assess efficacy and adverse-event profile of topiramate as add-on therapy in epilepsy. Outpatient neurology clinics from 11 general hospitals in Greece participated in the study. In total, 211 patients with treatment resistant partial-onset seizures who met the inclusion criteria, were studied. After baseline evaluation, topiramate was given at a target dose of 200mg/day over a 1-month titration period. In the subsequent maintenance period, the topiramate dose could be varied according to the clinical results. Patients were followed for in total 6 months, with monthly visits and regular physical, neurological and laboratory examinations. Seizure frequencies decreased to 35–40% of baseline values following 3 months of treatment and remained relatively constant thereafter. The average monthly seizure frequency over the 6-month study period was 4.61, compared to 9.21 at baseline. The number of responders (patients with at least 50% reduction in seizure frequency) followed a similar pattern, i.e., increase during the first 3 months levelling off at a final 80–85% response rate. Of those completing the study, 30% had been seizure-free for at least 3 months and 12% for 5 months. Topiramate was well tolerated, no deviations in laboratory values were found. Adverse events appeared to occur less frequently, and antiepileptic effects were more pronounced in this prospective open-label study than in earlier reports from randomised controlled trials. The nature of the patient population and the application of individualised dose optimisation are proposed as contributing factors to explain the favourable results of this study

Improved detection of amnestic MCI by means of discriminative vector quantization of single-trial cognitive ERP responses

Cognitive event-related potentials (ERPs) are widely employed in the study of dementive disorders. The morphology of averaged response is known to be under the influence of neurodegenerative processes and exploited for diagnostic purposes. This work is built over the idea that there is additional information in the dynamics of single-trial responses. We introduce a novel way to detect mild cognitive impairment (MCI) from the recordings of auditory ERP responses. Using single trial responses from a cohort of 25 amnestic MCI patients and a group of age-matched controls, we suggest a descriptor capable of encapsulating single-trial (ST) response dynamics for the benefit of early diagnosis. A customized vector quantization (VQ) scheme is first employed to summarize the overall set of ST-responses by means of a small-sized codebook of brain waves that is semantically organized. Each ST-response is then treated as a trajectory that can be encoded as a sequence of code vectors. A subject's set of responses is consequently represented as a histogram of activated code vectors. Discriminating MCI patients from healthy controls is based on the deduced response profiles and carried out by means of a standard machine learning procedure. The novel response representation was found to improve significantly MCI detection with respect to the standard alternative representation obtained via ensemble averaging (13% in terms of sensitivity and 6% in terms of specificity). Hence, the role of cognitive ERPs as biomarker for MCI can be enhanced by adopting the delicate description of our VQ scheme

Audiovisual stimulation to influence alpha brain oscillations: An EEG study of gender differences

We focused on gender differences regarding audiovisual stimulation on the alpha activity, as measured by the EEG. The bipolar “double banana” montage was used, placing nineteen scalp electrodes according to the 10–20 system. Subjects were 30 healthy, right handed, individuals, 15 males (mean age: 23.47 ± 3.39) and 15 females (mean age: 22.8 ± 3.74). The protocol consisted of 12 audiovisual stimuli: an 8 Hz binaural beat (right 450 Hz–left 442 Hz) combined with an 8 Hz flickering light at 4 different colours (RGBY), a 10 Hz binaural beat (right 450 Hz–left 440 Hz) combined with a 10 Hz flickering light at 4 different colours (RGBY), and 4 placebo stimuli (100 Hz flickering RGBY light combined with 100 Hz at both ears). The duration of the experiment for each subject was 653 s. Results were analyzed using the ERD/ERS method for lower (8–10 Hz) and upper (10–12 Hz) alpha band. Statistical analysis highlight significant gender differences concerning the stimuli’ effect at P4-O2 channel at specific time intervals: 1. Lower alpha: Green 8 Hz (0–300 ms) and Placebo red (500–900 ms) resulted in synchronization for females and desynchronization for males. Green 10 Hz synchronized (0–200 ms) for males and desynchronized for females. 2. Upper alpha: Placebo blue resulted in synchronization (200–600 ms) for females and desynchronization for males. Green 10 Hz synchronized (600–800 ms) for males while it desynchronized for females

The impact of audio-visual stimulation on alpha brain oscillations: An EEG study

Many studies investigated the brain responses as a reaction in auditory or visual stimuli separately. However a few studies have been published so far investigating the interactions of the two aforementioned stimuli. The current study comes to examine the impact of the audio-visual stimulation with binaural beats and flickering light in four different colors on low and upper alpha oscillations. For this purpose electroencephalogram (EEG) was adopted and Event Related Desynchronization/Event Related Synchronization (ERD/ERS) has been used as an index in order to investigate the alpha brain responses. Statistically significant results suggest that the combination of audio-visual stimuli with binaural beats and flickering light color at 8 and 10 Hz respectively can evoke significant Following Frequency Response (FFR) of the low and upper alpha oscillations

Influence of sleep disturbance on quality of life of patients with epilepsy

SummaryThe frequency of sleep disturbances in patients with epilepsy and their impact on quality of life (QoL) have been documented in a few reports, and the results are conflicting. We identified 124 consecutive epilepsy out-patients who visited the epilepsy out-patient clinics at the University Hospital of Alexandroupolis, the AHEPA Hospital in Thessaloniki and the Aeginitio Hospital in Athens. We measured excessive daytime sleepiness (EDS) with the Epworth Sleepiness Scale (ESS), obstructive sleep apnea (OSA) with the Sleep Apnea scale of the Sleep Disorders Questionnaire (SA-SDQ), and insomnia with the Athens Insomnia Scale (AIS). We evaluated quality of life by the Quality of Life in Epilepsy Inventory (QOLIE-31). EDS was found in 16.9% (21/124) of epileptic patients, OSA in 28.2% (35/124), and insomnia in 24.6% (30/122). In multivariate analysis, we found that insomnia was an independent negative factor for Total score (p<0.001), Overall QoL (p=0.002), Emotional well-being (p<0.001), Energy/fatigue (p<0.001), Cognitive functioning (p=0.04) and Social functioning (p=0.03), and OSA only for Cognitive functioning (p=0.01). According to our findings, EDS, OSA, and insomnia are frequent in epileptic patients. Epileptic patients with sleep disturbance, mainly insomnia, have significant QoL impairment