A. Denissen

A novel self-guided approach to alpha activity training

Fifty healthy participants took part in a double-blind placebo-controlled study in which they were either given auditory alpha activity (8-12Hz) training (N=18), random beta training (N=12), or no training at all (N=20). A novel wireless electrode system was used for training without instructions, involving water-based electrodes mounted in an audio headset. Training was applied approximately at central electrodes. Post-training measurement using a conventional full-cap EEG system revealed a 10% increase in alpha activity at posterior sites compared to pre-training levels, when using the conventional index of alpha activity and a non-linear regression fit intended to model individual alpha frequency. This statistically significant increase was present only in the group that received the alpha training, and remained evident at a 3 month follow-up session, especially under eyes open conditions where an additional 10% increase was found. In an exit interview, approximately twice as many participants in the alpha training group (53%) mentioned that the training was relaxing, compared to those in either the beta (20%) or no training (21%) control groups. Behavioural measures of stress and relaxation were indicative of effects of alpha activity training but failed to reach statistical significance. These results are discussed in terms of a lack of statistical power. Overall, results suggest that self-guided alpha activity training using this novel system is feasible and represents a step forward in the ease of instrumental conditioning of brain rhythms.

The time-course of alpha neurofeedback training effects in healthy participants

The time-course of alpha neurofeedback training (NFT) was investigated in 18 healthy participants who received 15 sessions of training (eyes open), each consisting of three training periods (data are from Van Boxtel et al., 2012). Here we report on the within- and between-session training effects using multilevel analyses. Over sessions, total alpha power (8-12 Hz) increased up to the tenth session, after which low alpha power (8-10 Hz) remained at the same level, while high alpha power (10-12 Hz) decreased. Within each training session, total alpha power increased from the first to the second period, and then decreased again. This decrease, however, was caused by a decrease in high alpha power only; low alpha power remained up to the end of training. These effects are discussed in terms of attention and motivation, and suggest different trainability for low and high alpha power.

Feasibility of eyes open alpha power training for mental enhancement in elite gymnasts

Abstract This study focuses on a novel, easy to use and instruction-less method for mental training in athletes. Previous findings suggest that particular mental capacities are needed for achieving peak performance; including attentional control, focus, relaxation and positive affect. Electroencephalography (EEG) alpha brain activity has been associated with neural inhibition during processes of selective attention, for improving efficiency in information processing. Here we hypothesised that eyes open alpha power training by music teaches athletes to (1) learn to self-regulate their brain activity, and (2) learn to increase their baseline alpha power, herewith improving mental capacities such as focusing the allocation of attention. The study was double-blind and placebo-controlled. Twelve elite gymnasts were either given eyes open alpha power training or random beta power training (controls). Results indicate small improvements in sleep quality, mental and physical shape. In our first attempt at getting a grip on mental capacities in athletes, we think this novel training method can be promising. Because gymnastics is one of the most mentally demanding sports, we value even small benefits for the athlete and consider them indicative for future research.

Heart Rate Variability, Sleep, and the Early Detection of Post-traumatic Stress Disorder

Measures of heart rate variability (HRV) are sensitive indices of autonomic nervous system functioning, capable of distinguishing activity of its two constituent branches, the sympathetic and parasympathetic nervous systems. As such, these measures are possibly useful as early markers of post-traumatic stress disorder (PTSD). We review the anatomical and physiological background of the cardiovascular system and provide guidelines for measuring the electrocardiogram and for deriving HRV measures. In addition, normative values for various HRV measures are provided, both in the time domain and in the frequency domain. We then review literature linking these HRV measures to PTSD, to sleep, and to the combination of PTSD and sleep. From this review, it appears that during awake resting states, PTSD patients are characterized by low parasympathetic tone, relative to healthy controls, resulting in elevated mean heart rates and reduced cardiac reactivity. By contrast, during sleep PTSD patients appear to be characterized by increased sympathetic activation, mainly observed during REM sleep, again with elevated mean heart rate and reduced reactivity as a consequence. We advocate the use of HRV measures in studies aimed at identifying individuals at risk for developing PTSD symptoms.

Advanced EEG Processing for the Detection of Drowsiness in Drivers

Drowsiness is a serious problem for drivers which causes many accidents every day. It is estimated that drowsiness is the cause of four deaths and 100 injuries per day in the United States. In this paper two methods have been developed to detect drowsiness based on features of ocular artifacts in EEG signals. The ocular artifacts are derived from the EEG signals by using Canonical Correlation Analysis (BSS-CCA). Wavelet transforms are used to automatically select components containing eye blinks. Sixteen features are then calculated from the eye blink and used for drowsiness detection. The first method is based on linear regression, the second on fuzzy detection. For the first method, the drowsiness level is correctly detected in 72% of the epochs. The second method uses fuzzy detection and detects the drowsiness correctly in 65% of the epochs. The best results are obtained when using one single eye blink feature.