Slow cortical potential neurofeedback in attention deficit hyperactivity disorder: Is there neurophysiological evidence for specific effects?
ABSTRACT This study compared changes in quantitative EEG (QEEG) and CNV (contingent negative variation) of children suffering from ADHD treated by SCP (slow cortical potential) neurofeedback (NF) with the effects of group therapy (GT) to separate specific from non-specific neurophysiological effects of NF. Twenty-six children (age: 11.1 +/- 1.15 years) diagnosed as having ADHD were assigned to NF (N = 14) or GT (N = 12) training groups. QEEG measures at rest, CNV and behavioral ratings were acquired before and after the trainings and statistically analyzed. For children with ADHD-combined type in the NF group, treatment effects indicated a tendency toward improvement of selected QEEG markers. We could not find the expected improvement of CNV, but CNV reduction was less pronounced in good NF performers. QEEG changes were associated with some behavioral scales. Analyses of subgroups suggested specific influences of SCP training on brain functions. To conclude, SCP neurofeedback improves only selected attentional brain functions as measurable with QEEG at rest or CNV mapping. Effects of neurofeedback including the advantage of NF over GT seem mediated by both specific and non-specific factors.
- SourceAvailable from: Wenya Nan
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- "Prior research classified the subjects into learners or non-learners according to their learning ability. Some studies reported the cases of non-learners even after repeated training sessions (Kotchoubey et al., 1999; Hanslmayr et al., 2005; Kropotov et al., 2005; Doehnert et al., 2008; deBeus and Kaiser, 2011; Escolano et al., 2011; Weber et al., 2011; Zoefel et al., 2011; Enriquez-Geppert et al., 2013b; Kouijzer et al., 2013). In Weber et al. (2011), about 50% of subjects were non-learners in sensorimotor rhythm (SMR; 12–15 Hz) neurofeedback. "
ABSTRACT: Individuals differ in their ability to learn how to regulate the brain activity by neurofeedback. This study aimed to investigate whether the resting alpha activity can predict the learning ability in alpha neurofeedback. A total of 25 subjects performed 20 sessions of individualized alpha neurofeedback and the learning ability was assessed by three indices respectively: the training parameter changes between two periods, within a short period and across the whole training time. It was found that the resting alpha amplitude measured before training had significant positive correlations with all learning indices and could be used as a predictor for the learning ability prediction. This finding would help the researchers in not only predicting the training efficacy in individuals but also gaining further insight into the mechanisms of alpha neurofeedback.Frontiers in Human Neuroscience 07/2014; 8:500. DOI:10.3389/fnhum.2014.00500 · 2.90 Impact Factor
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- "' capabilities to success - fully conclude neurofeedback training . Data across studies suggest that about a third of the participants ultimately can be classified as so - called non - responders : subjects who do not learn to significantly modulate their brain activity over the course of the training in accor - dance with instructions ( e . g . , Doehnert et al . , 2008 ; Drechsler et al . , 2007 ; Fuchs et al . , 2003 ; Kotchoubey et al . , 1999 ) . Correspondingly , non - responding participants also tend not to show changes in behav - ioral outcome measures ( e . g . , Hanslmayr et al . , 2005 ; Lubar et al . , 1995 ) . Yet , one also has to acknowledge that there is no real consensus on how to actu"
ABSTRACT: Neurofeedback training procedures designed to alter a person's brain activity have been in use for nearly four decades now and represent one of the earliest applications of brain computer interfaces (BCI). The majority of studies using neurofeedback technology relies on recordings of the electroencephalogram (EEG) and applies neurofeedback in clinical contexts, exploring its potential as treatment for psychopathological syndromes. This clinical focus significantly affects the technology behind neurofeedback BCIs. For example, in contrast to other BCI applications, neurofeedback BCIs usually rely on EEG-derived features with only a minimum of additional processing steps being employed. Here, we highlight the peculiarities of EEG-based neurofeedback BCIs and consider their relevance for software implementations. Having reviewed already existing packages for the implementation of BCIs, we introduce our own solution which specifically considers the relevance of multi-subject handling for experimental and clinical trials, for example by implementing ready-to-use solutions for pseudo-/sham-neurofeedback.International journal of psychophysiology: official journal of the International Organization of Psychophysiology 09/2013; DOI:10.1016/j.ijpsycho.2013.08.011 · 2.65 Impact Factor
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- "The cued-CPT (flanker version; (Doehnert et al., 2008; McLoughlin et al., 2010, 2011; Valko et al., 2010) consists of a black letter array formed of a centre letter flanked on each side by distractor letters, presented in "
ABSTRACT: Attention deficit hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder with a complex aetiology. The identification of candidate intermediate phenotypes that are both heritable and genetically linked to ADHD may facilitate the detection of susceptibility genes and elucidate aetiological pathways. Very low-frequency (VLF; <0.5 Hz) electroencephalographic (EEG) activity represents a promising indicator of risk for ADHD, but it currently remains unclear as to whether it is heritable or genetically linked to the disorder. Direct-current (DC)-EEG was recorded during a cognitive activation condition in 30 monozygotic and dizygotic adolescent twin pairs concordant or discordant for high ADHD symptom scores, and 37 monozygotic and dizygotic matched-control twin pairs with low ADHD symptom scores. Structural equation modelling was used to quantify the genetic and environmental contributions to the phenotypic covariance between ADHD and VLF activity. Attention deficit hyperactivity disorder was significantly associated with reduced VLF power during cognitive activation, which suggests reduced synchronization of widespread neuronal activity. Very low-frequency power demonstrated modest heritability (0.31), and the genetic correlation (-0.80) indicated a substantial degree of overlap in genetic influences on ADHD and VLF activity. Altered VLF activity is a potential candidate intermediate phenotype of ADHD, which warrants further investigation of underlying neurobiological and genetic mechanisms.Journal of Child Psychology and Psychiatry 11/2011; 53(6):706-15. DOI:10.1111/j.1469-7610.2011.02501.x · 5.67 Impact Factor