Correlations between the psychological peculiarities of an individual and the efficacy of a single neurofeedback session (by the EEG characteristics)

Abstract

Modifications of different EEG rhythms induced by a single neurofeedback session (by the EEG characteristics) directed toward an increase in the ratio of the spectral powers (SPs) of the α vs θ oscillations were compared with the psychological characteristics of the tested subjects (the group included 30 persons). A generally accepted neurofeedback technique was used; the intensity of acoustic white noise served as the feedback signal. EEG potentials were recorded from the C3 and C4 leads. Psychological testing was carried out using Eysenck's (EPQ), Rusalov's (OST), and Сattell's (16 PF) questionnaires. The directions of changes in the SPs of EEG frequency components were found to significantly correlate with some individuality-related peculiarities of the tested subjects. The SP of the δ rhythm correlated with the EPQ scale "neuroticism," OST scale "social plasticity," and 16 PF factors H ("parmia"), I ("premsia"), and Q 3 ("self-control of behavior"). The SP of the θ component demonstrated correlations with the OST scales "ergisity," "plasticity," and "social temp" and with 16 PF factors M ("autia"), Q 4 ("frustration"), and Q1 ("exvia"). The SP of the α rhythm correlated with 16 PF factors Q 3 ("self-control of behavior"), G ("strength of superEgo"), O ("hypothymia"), L ("protension"), and N ("shrewdness"). The SP of the β rhythm correlated with the OST scale "emotionality," while that of the γ rhythm showed correlations with the 16 PF indices L ("protension") and M ("autia"). Changes in the ratio of the α vs θ SPs correlated with the EPQ scale "neuroticism." Thus, our data confirm the statement that a high individual variability of the results of a single (first in the series) neurofeedback session is to a great extent related to peculiarities of the individual psychological pattern of the subject.

Alpha Neurofeedback Training for Performance Enhancement: Reviewing the Methodology

“…In contrast a variable reward threshold may change over time, starting at 8 mV and gradually increasing to 12 mV. Unfortunately, it is not always made clear why a particular reward threshold has been chosen and in some cases such information is not reported (e.g., Angelakis et al, 2007;Beatty, 1971;Hardt & Gale, 1993;Johnson & Meyer, 1974;Konareva, 2006;Wacker, 1996). Nevertheless, when such information is reported there is little consistency in its use.…”

“…However, identifying the specific frequency range of the alpha component of the EEG seems less certain. For example, previous attempts to enhance alpha using NFT have identified alpha as operating between 7-15 Hz (Brown, 1970), 7.5-13 Hz (Prewett & Adams, 1976), 8-12 Hz (e.g., Albert et al, 1974Cho et al, 2008;Fell et al, 2002), 8.5-12.5 Hz (Bauer, 1976), 8-13 Hz (e.g., Angelakis et al, 2007Hardt & Kamiya, 1978;Nowlis & Kamiya, 1970), 8.5-13.5 Hz (Valle & Levine, 1975), 8-14 Hz (Konareva, 2005, 2006, and 10 Hz AE 1 Hz (Drennen & O'Reilly, 1986). Such inconsistencies in identifying the frequency range of the training component not only make comparisons between studies problematic but also fail to take into account individual differences.…”

Effect of Neurofeedback Training Along with Swimming Exercise on the Electroencephalographic Changes and Visual Image-Induced Craving in Methamphetamine-Dependent Patients

“…At present, the neurobiological mechanisms to reduce EEG absolute power for 4 frequency bands and METH craving following the effectiveness of swimming exercise combined with NFB training are still unknown. It may be due to an ability to self-regulate dopaminergic neurons of the substantia nigra/ventral tegmental (Sulzer et al, 2013), the endogenous release of key neuromodulators (Ros et al, 2021), the regulation of serotonin (Konareva, 2006), and β-endorphin (Akbari, Dolatshahee, & Rezaee, 2016)…”

Recovering Hidden Responder Groups in Individuals Receiving Neurofeedback for Tinnitus

“…Further presumed causes of the heterogeneity are comorbidities, which may start with anxiety ( McCormack et al, 2015 ) or insomnia ( Lasisi and Gureje, 2011 ; Wallhäusser-Franke et al, 2013 ), continue to hyperacusis ( Goebel and Floezinger, 2008 ), and escalate to depression ( McKenna et al, 1991 ; Zöger et al, 2006 ; Zirke et al, 2013 ; Trevis et al, 2018 ). Other epiphenomena, including tinnitus-related distress ( Hesser and Andersson, 2014 ; Brüggemann et al, 2016 ), personality traits ( Konareva, 2006 ; Simões et al, 2019 ), and tinnitus-specific brain oscillation accompanied with structural and functional alterations in auditory and non-auditory brain areas ( Schlee et al, 2009 ; Adjamian et al, 2014 ) have been considered to contribute to or moderate the various manifestations of the phantom percept. Finally, all possible combinations of the mentioned phenomena complement the heterogeneous appearance ( Henry et al, 2005 ; Vanneste et al, 2010 ; Joos et al, 2012 ; Vanneste and De Ridder, 2012 ; Meyer et al, 2014 ).…”