History and evolution of computerized electroencephalography

Forgotten rhythms? Revisiting the first evidence for rhythms in cognition

Practically every neuroscientist knows that human brain rhythms were first recorded in the 1920s by Hans Berger, who coined the term 'alpha waves' for the regular activity of around 10 cycles per second that was clearly visible in many of his recordings. Almost 100 years later, alpha rhythms are still the subject of active investigation and continue to intrigue researchers. What we have perhaps forgotten though, is the clever experimentation that was carried out during the first decades of electroencephalogram (EEG) research, often using sophisticated, custom-made analysis and stimulation devices. Here, I review selected findings from the early EEG literature regarding the character, origin, and meaning of human brain rhythms, beginning with Berger's publications and then focusing on the use of regular visual stimulation as a tool to understand intrinsic brain rhythms. It is clear that many of these findings are still relevant to open questions about the role of rhythmic brain activity. In addition, they also contain some general lessons for contemporary neuroscientists, meaning that there is great value in looking back at these forgotten publications.

The Learning Curve in neurofeedback of Peter Van Deusen: A review article

The Learning Curve (TLC) in neurofeedback concept emerged after Peter Van Deusen compiled the results of articles on the expected electrical activity of the brain. This concept was subsequently tested on patients at four clinics in Atlanta between 1994 and 2001. The aim of this paper was to report the historical aspects of TLC. Articles published on the electronic databases MEDLINE/PubMed and Web of Science were reviewed. During patient evaluation, TLC investigates categories called disconnected, hot temporal lobes, reversal of alpha and beta waves, blocking, locking, and filtering or processing. This enables neuroscientists to use their training designs and, by means of behavioral psychology, to work on neuroregulation, as self-regulation for patients. TLC shows the relationships between electrical, mental and behavioral activity in patients. It also identifies details of patterns that can assist physicians in their choice of treatment.

Representing and decomposing neural potential signals

This paper reviews methodologies for analyzing neural potentials via frequency, time-frequency, or wavelet representations, and adaptive models that estimate the signal's spatial or temporal structure. The fundamental assumptions of each method are discussed. In particular, the Fourier transform is contrasted with overcomplete representations, which are able to precisely delineate the timing and/or frequency of neural events. Finally, a novel approach that combines overcomplete representations with adaptive signal models is presented. This approach describes a continuous signal as a linear combination of reoccurring waveforms, referred to as phasic events, which are often associated with neural processing. The new methodology automatically learns the reoccurring waveforms and quantifies the neural potentials by the set of amplitudes and timings.

Efficacy of yoga for mental performance in university students

BACKGROUND

With growing scientific evidence, yoga is emerging as an important health behavior-lifestyle modifying module to achieve holistic health at physical, mental, emotional, social and spiritual levels. Brain wave coherence (BWC) recordings from the surface of the skull are associated with different cognitive processes and plays both critical and useful roles in yoga with wide range of functional significance. The psycho-physiological changes that characterize the efficacy of yoga for better mental performance in university students have not been studied adequately.

OBJECTIVE

The study was designed to assess the mental performance through BWC analysis in university students undergoing Integrated Yoga Module (IYM).

MATERIALS AND METHODS

The IYM subjects (n=30) with 25.77±4.85 years of mean age participated in this single group pre-post study. The BWC data was collected before (pre) and after (post) the 21 days IYM using Brain Master (Model: 2E Part # 390-001), Michigan, USA.

STATISTICAL ANALYSIS

Means, standard deviations, Kolmogorov-Smirnov test and Wilcoxon signed rank test were used for analyzing data with the help of SPSS-16.

RESULTS

A complete statistical and spectral analysis showed 43.24% increase (P<0.001) in Delta, 9.13% increase (P=0.289) in Theta, 57.85% increase (P<0.001) in Alpha, 17.65% decrease (P=0.136) in Beta and 9.19% increase (P=0.586) in Gamma BWC between pre and post intervention measurements.

CONCLUSION

BWC study showed significant increase in both Delta and Alpha wave coherence suggesting that IYM can result in improvement of coherent and integrated brain functioning among students, thus paving the way for their better mental performance. Although this preliminary research is promising, more well-designed studies are needed before a strong recommendation can be made.

Time for Taste-A Review of the Early Cerebral Processing of Gustatory Perception

The first successfully recorded event-related potential (ERP) for taste, one of our basic senses, was published nearly half a century ago. Despite this large time span, surprisingly little is known about the early neural processing of taste perception. Here, we are providing a comprehensive and critical overview of over four decades of research, with a focus on the temporal dimension of cerebral taste processing in healthy humans. For this purpose, we review studies using techniques that permit a high temporal resolution, namely, electroencephalography and magnetoencephalography, ERP, and event-related magnetic fields (ERF). Our current knowledge of taste ERP is interpreted in the context of our understanding of other, nonchemical senses. Gaps in the existing literature are identified and discussed. Finally, we suggest directions for future investigations using gustatory ERP/ERF.

Hidden focal EEG seizures during prolonged suppressions and high-amplitude bursts in early infantile epileptic encephalopathy

OBJECTIVE

We report on a 27-month-old female with atypical early infantile epileptic encephalopathy (EIEE), who developed tonic spasms, partial seizures and myoclonic jerks along with episodic bradycardia at 5 days.

METHODS

We recorded digital electroencephalography (EEG) using either an 11-channel neonatal montage or 19 channel scalp electrodes, at 200 Hz sampling rate, and a single reference for a minimum of 30 min.

RESULTS

At 18 days EEG showed suppression-burst (SB) patterns during wakefulness and sleep. Tonic spasms concomitant with bursts recorded as brief, low-amplitude fast waves. EEG at 8 months showed increased amplitude of bursts to 1 mV and extension of suppression periods to 65 s. By increasing recording sensitivity, we detected focal epileptiform discharges of slow rhythmic sharp and slow waves building to 30 microV during suppression periods. Status epilepticus occurred at 16 months. EEG at 27 months returned to the previous SB pattern with rare partial seizures.

CONCLUSIONS

This report is the first to demonstrate clinically silent focal EEG seizures during prolonged suppression periods in atypical EIEE by off-line digital EEG.

SIGNIFICANCE

Digital EEG sensitivity can reveal covert electrical activity during suppression periods in epileptic neonates and infants.