EEG spectrum gravity as a preliminary arousal indicator and neurofeedback parameter

Pop-Jordanov, Jordan and Pop-Jordanova, Nada and Koceski, Saso (2011) EEG spectrum gravity as a preliminary arousal indicator and neurofeedback parameter. Neuroscience Letters, 500. e33. ISSN 03043940

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1016/j.neulet.2011.05.162

Abstract

The main aim of this paper is to analyze the EEG spectrum gravity (brain rate) as a preliminary indicator of mental arousal level and as a multiband neurofeedback parameter, considering the neurophysical mechanisms. The main characteristic of the integral EEG spectrum is its mean frequency, weighted over the whole spectrum (brain rate), defined as in (Pop-Jordanova & Pop-Jordanov, 2005). Conducted clinical experiments show that: (1) Brain-rate can be considered as an integral brain state attribute, correlated to its electric, mental and metabolic activity; (2) In preliminary assessment, brain-rate may serve as an indicator of general mental arousal level, similar to heart-rate (Kaniusas, Varoneckas, Alonderis & Podlipskyte, 2007), blood pressure and temperature as standard indicators of general bodily activation; (3) By comparing eyes-closed and eyes-open brain-rate values the diagnoses of inner arousal can simply be achieved; (4) As a measure of arousal level, brain-rate can be applied to discriminate between subgroups of “mixed” disorders (e.g. ADHD, OCD) (Pop-Jordanova, 2009); (5) Brain-rate can be used as a multiband biofeedback parameter in mediating the underarousal or overarousal states, complementary to few-band parameters and the skin conduction; (6) Brain-rate training is especially suitable to reveal the patterns of sensitivity/rigidity of EEG spectrum and its frequency bands, related to permeability of corresponding neuronal circuits; based on this information, individually adapted neurofeedback protocols can be elaborated.

Item Type: Article
Subjects: Natural sciences > Computer and information sciences
Engineering and Technology > Medical engineering
Divisions: Faculty of Computer Science
Depositing User: Saso Koceski
Date Deposited: 12 Dec 2012 12:58
Last Modified: 27 Dec 2012 08:46
URI: http://eprints.ugd.edu.mk/id/eprint/3446

Actions (login required)

View Item View Item