2015
DOI: 10.3389/fnhum.2015.00677
|View full text |Cite
|
Sign up to set email alerts
|

Resting and Initial Beta Amplitudes Predict Learning Ability in Beta/Theta Ratio Neurofeedback Training in Healthy Young Adults

Abstract: Neurofeedback (NF) training has been proved beneficial in cognitive and behavioral performance improvement in healthy individuals. Unfortunately, the NF learning ability shows large individual difference and in a number of NF studies there are even some non-learners who cannot successfully self-regulate their brain activity by NF. This study aimed to find out the neurophysiological predictor of the learning ability in up-regulating beta-1 (15–18 Hz)/theta (4–7 Hz) ratio (BTR) training in healthy young adults. … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
24
1

Year Published

2016
2016
2023
2023

Publication Types

Select...
8
1

Relationship

2
7

Authors

Journals

citations
Cited by 28 publications
(26 citation statements)
references
References 64 publications
1
24
1
Order By: Relevance
“…This result corresponds to previous findings suggested that a significant percent of the population (10-50%) are unable to influence their brain activity (Alkoby et al, 2017;Allison and Neuper, 2010;Jeunet et al, 2016). In previous studies, NF treatment efficiency was successfully predicted using behavioral factors such as control belief (Witte et al, 2013), motivation, mood (Nijboer et al, 2010(Nijboer et al, , 2008, memory (Daum et al, 1993;Roberts et al, 1989;Wangler et al, 2011) or by EEG markers such as resting-state alpha (Wan et al, 2014) or beta (Nan et al, 2015) (for detailed review see Alkoby et al, 2017). However, in our sample prediction was unsuccessful using behavioral, neural or clinical factors.…”
Section: Clinical Perspective Of Amyg-efp-nfmentioning
confidence: 64%
“…This result corresponds to previous findings suggested that a significant percent of the population (10-50%) are unable to influence their brain activity (Alkoby et al, 2017;Allison and Neuper, 2010;Jeunet et al, 2016). In previous studies, NF treatment efficiency was successfully predicted using behavioral factors such as control belief (Witte et al, 2013), motivation, mood (Nijboer et al, 2010(Nijboer et al, , 2008, memory (Daum et al, 1993;Roberts et al, 1989;Wangler et al, 2011) or by EEG markers such as resting-state alpha (Wan et al, 2014) or beta (Nan et al, 2015) (for detailed review see Alkoby et al, 2017). However, in our sample prediction was unsuccessful using behavioral, neural or clinical factors.…”
Section: Clinical Perspective Of Amyg-efp-nfmentioning
confidence: 64%
“…The identification of “non-responders” has been reported in published EEG-NFB experiments and clinical applications. It is possible that susceptibility to EEG-NFB training differs greatly between individuals, which alone demands further investigation (Weber et al, 2011 ; Wan et al, 2014 ; Nan et al, 2015 ). However, at present, it is not appropriate to restrict the experimental group to the participants with clear effects and exclude non-responders from the analyses.…”
Section: Methodsmentioning
confidence: 99%
“…An example of the latter is low training susceptibility of a subgroup of participants frequently referred to as non-responders. In order to identify potential non-responders and exclude them at the initial stages of screening for NFB training a new line of research has emerged focused on individual factors that might predict training success (Weber et al, 2011 ; Nan et al, 2015 ). Here we concentrate on the neurofeedback methodology, in which important factors influencing training success may be: feedback modality, training intensity, choice of EEG band(s) used for the feedback signal, and the number and positions of electrodes from which feedback signal is recorded.…”
Section: Methodsmentioning
confidence: 99%
“…Many factors may influence the success of neurofeedback procedures such as age of the trainees, their personal traits and beliefs about neurofeedback training, training susceptibility of participants, trainer behavior, feedback modality (visual, auditory, combined), training intensity, choice of EEG used for the feedback signal, and the number and positions of electrodes (36)(37)(38). However, we could not consider all of these factors in our study design and analysis.…”
Section: Discussionmentioning
confidence: 92%