Exploring EEG alpha oscillations has generated considerable interest, in particular with regards to the role they play in cognitive, psychomotor, psycho-emotional and physiological aspects of human life. However, there is no clearly agreed upon definition of what constitutes 'alpha activity' or which of the many indices should be used to characterize it.To address these issues this review attempts to delineate EEG alpha-activity, its physical, molecular and morphological nature, and examine the following indices: (1) the individual alpha peak frequency; (2) activation magnitude, as measured by alpha amplitude suppression across the individual alpha bandwidth in response to eyes opening, and (3) alpha "auto-rhythmicity" indices: which include intra-spindle amplitude variability, spindle length and steepness.Throughout, the article offers a number of suggestions regarding the mechanism(s) of alpha activity related to inter and intra-individual variability. In addition, it provides some insights into the various psychophysiological indices of alpha activity and highlights their role in optimal functioning and behavior.Key words: individual alpha peak frequency, individual alpha bandwidth, alpha amplitude suppression, spindle-form segments length, intra-spindle amplitude variability Highlights 1. Alpha indices are amplitude, peak frequency, band width and spindle structure 2. Alpha peak frequency could be an endophenotypic marker 3. Alpha band width and amplitude suppression reflect activation 4. The spindle-form, segment length and amplitude reflect a neuronal ensemble property 5. Alpha activity is manifested depending on the individual alpha peak frequency 2

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Introduction: Considerable interest has been, and still is, generated by the potential performance enhancing benefits of alpha neurofeedback training (NFT) for healthy participants. A plausible rationale for such training, with an aim to improve mood and/or enhance cognition, can be made based upon what is already known of the links between alpha EEG activity and behavior. However, designing an optimal NFT paradigm remains difficult because a number of methodological factors that may influence the outcome of such training remain largely unexplored. Method: This article focuses on these methodological factors in an attempt to highlight some of the unanswered questions and stimulate future research. Results: Specifically, this article examines the NFT training schedule; the variety, basis, and setting of reward thresholds; the nature and modality of the feedback signal provided; unidirectional as compared to bidirectional NFT; the establishment of a target frequency range for alpha; whether NFT should be conducted with eyes open or closed; and the identification of a clear index of learning. Conclusions: Throughout, the article provides a number of suggestions and possible directions for future research

The aim of the present work was to study correlational interactions between individual measures of alpha-activity in the baseline electroencephalogram (maximum peak frequency, range width, depth of alpha activity desynchronization reactions, structural characteristics of alpha spindles) and measures of non-verbal intellect ("Fluency," "Originality," "Flexibility") in the Torrance test in 98 healthy male subjects. These studies provided the first demonstration that individuals with high alpha-rhythm maximum peak frequency values and prolonged alpha spindles were generally characterized by more "fluent" non-verbal intellect. In turn, high levels of originality and intellectual plasticity showed a significant association with a wider range of alpha activity and variability of alpha spindle amplitude. The highest levels of originality in solving non-verbal tasks were seen in subjects with the lowest values for individual alpha-activity peak frequencies. These measures of the alpha rhythm can be regarded as individual markers of the productivity, plasticity, and originality of non-verbal intellect.

The influences of individual musical practice and the same practice supplemented with biofeedback using electrophysiological markers for optimum music-performing activity were studied in 39 music students. Traditional technical practice produced increases in integral EMG power and decreases in alpha activity in most of the students with initially low maximum alpha activity peak frequencies. Similar practice but combined with individual sessions of alpha-EEG/EMG biofeedback were accompanied by increases in the frequency, bandwidth, and activation responses of EEG alpha rhythms in all subjects, along with decreases in EEG integral power. The efficacy of training with biofeedback and the ability to experience psychomotor learning depended on the initial individual characteristics of EEG alpha activity.