Validation of eyes-closed resting alpha amplitude predicting neurofeedback learning of upregulation alpha activity

AbstractNeurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8–12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS’s alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.

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Reduced Variability of Auditory Alpha Activity in Chronic Tinnitus

Neural Plasticity ◽

10.1155/2014/436146 ◽

2014 ◽

Vol 2014 ◽

pp. 1-9 ◽

Cited By ~ 29

Author(s):

Winfried Schlee ◽

Martin Schecklmann ◽

Astrid Lehner ◽

Peter M. Kreuzer ◽

Veronika Vielsmeier ◽

...

Keyword(s):

Auditory Cortex ◽

Frequency Band ◽

Resting State ◽

Spectral Power ◽

Alpha Activity ◽

Chronic Tinnitus ◽

Alpha Frequency ◽

Alpha Frequency Band ◽

History Of ◽

The Moment

Subjective tinnitus is characterized by the conscious perception of a phantom sound which is usually more prominent under silence. Resting state recordings without any auditory stimulation demonstrated a decrease of cortical alpha activity in temporal areas of subjects with an ongoing tinnitus perception. This is often interpreted as an indicator for enhanced excitability of the auditory cortex in tinnitus. In this study we want to further investigate this effect by analysing the moment-to-moment variability of the alpha activity in temporal areas. Magnetoencephalographic resting state recordings of 21 tinnitus subjects and 21 healthy controls were analysed with respect to the mean and the variability of spectral power in the alpha frequency band over temporal areas. A significant decrease of auditory alpha activity was detected for the low alpha frequency band (8–10 Hz) but not for the upper alpha band (10–12 Hz). Furthermore, we found a significant decrease of alpha variability for the tinnitus group. This result was significant for the lower alpha frequency range and not significant for the upper alpha frequencies. Tinnitus subjects with a longer history of tinnitus showed less variability of their auditory alpha activity which might be an indicator for reduced adaptability of the auditory cortex in chronic tinnitus.

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Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training

NeuroImage ◽

10.1016/j.neuroimage.2021.118733 ◽

2021 ◽

pp. 118733

Author(s):

Takashi Nakano ◽

Masahiro Takamura ◽

Haruki Nishimura ◽

Maro Machizawa ◽

Naho Ichikawa ◽

...

Keyword(s):

Resting State ◽

Brain Activity ◽

Neurofeedback Training

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Beta Neurofeedback Training Improves Attentional Control in the Elderly

Psychological Reports ◽

10.1177/0033294119900348 ◽

2020 ◽

pp. 003329411990034 ◽

Cited By ~ 1

Author(s):

Jacek Bielas ◽

Łukasz Michalczyk

Keyword(s):

Executive Functioning ◽

Attentional Control ◽

Brain Activity ◽

Activity Patterns ◽

Reaction Times ◽

The Elderly ◽

Self Control ◽

Control Group ◽

Neurofeedback Training ◽

Age Related

One of the well-documented behavioral changes that occur with advancing age is a decline in executive functioning, for example, attentional control. Age-related executive deficits are said to be associated with a deterioration of the frontal lobes. Neurofeedback is a training method which aims at acquiring self-control over certain brain activity patterns. It is considered as an effective approach to help improve attentional and self-management capabilities. However, studies evaluating the efficacy of neurofeedback training to boost executive functioning in an elderly population are still relatively rare and controversial. The aim of our study was to contribute to the assessment of the efficacy of neurofeedback as a method for enhancing executive functioning in the elderly. We provided a group of seniors with beta up-training (12–22 Hz), consisting of 20 sessions (30 minutes each), on the Cz site and tested its possible beneficiary influence on attentional control assessed by means of the Stroop and Simon tasks. The analysis of the subjects’ mean reaction times during consecutive tasks in the test and the retest, after implementation of neurofeedback training, showed a significant improvement. In contrast, the difference in reaction times between the test and the retest in the control group who had not been submitted to neurofeedback training was not significant.

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The combination of acute exercise and eye closure has a synergistic effect on alpha activity

Scientific Reports ◽

10.1038/s41598-021-99783-y ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Takaaki Komiyama ◽

Ryoma Goya ◽

Chisa Aoyama ◽

Yusuke Yokota ◽

Yasushi Naruse ◽

...

Keyword(s):

Synergistic Effect ◽

Acute Exercise ◽

Alpha Activity ◽

Moderate Intensity ◽

Target Heart Rate ◽

Moderate Intensity Exercise ◽

Alpha Frequency ◽

Eyes Closed ◽

Eyes Open ◽

Eye Closure

AbstractAcute aerobic exercise increases the brain cortical activity in alpha frequency. Eye closure also increases alpha activity. However, whether the two have an additive or a synergistic effect on alpha activity has never been explored. This study observed electroencephalography (EEG) from fifteen participants seated on the cycle ergometer before, during, and after a cycling exercise with the eyes open and with them closed. Exercise intensity was set to a target heart rate (120–130 bpm), corresponding to light-to-moderate intensity exercise. Each epoch was 6 min and the last 4 min (eyes closed in the first 2 min and eyes open in the second 2 min) were analyzed. The EEG power spectrum densities were calculated for alpha frequency band activity (8–13 Hz). At rest, alpha activity was significantly greater with the eyes closed than open. Exercise significantly increased alpha activity in both eye conditions. More importantly, in the occipital site, the alpha-increasing effect of their combination was significantly greater than the sum of the effect of each, showing a synergistic effect. We concluded that acute light-to-moderate intensity exercise with the eyes closed has a synergistic effect on alpha activity.

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Dynamics of brain function in chronic pain patients assessed by microstate analysis of resting-state electroencephalography

10.1101/2020.09.29.318246 ◽

2020 ◽

Author(s):

Elisabeth S. May ◽

Cristina Gil Ávila ◽

Son Ta Dinh ◽

Henrik Heitmann ◽

Vanessa D. Hohn ◽

...

Keyword(s):

Chronic Pain ◽

Resting State ◽

Brain Function ◽

Temporal Dynamics ◽

Brain Activity ◽

Relevant Information ◽

Eyes Closed ◽

Eyes Open ◽

Eeg Recordings ◽

Microstate Analysis

AbstractChronic pain is a highly prevalent and severely disabling disease, which is associated with substantial changes of brain function. Such changes have mostly been observed when analyzing static measures of brain activity during the resting-state. However, brain activity varies over time and it is increasingly recognized that the temporal dynamics of brain activity provide behaviorally relevant information in different neuropsychiatric disorders. Here, we therefore investigated whether the temporal dynamics of brain function are altered in chronic pain. To this end, we applied microstate analysis to eyes-open and eyes-closed resting-state electroencephalography (EEG) data of 101 patients suffering from chronic pain and 88 age- and gender-matched healthy controls. Microstate analysis describes EEG activity as a sequence of a limited number of topographies termed microstates, which remain stable for tens of milliseconds. Our results revealed that sequences of 5 microstates, labelled with the letters A to E, described resting-state brain activity in both groups and conditions. Bayesian analysis of the temporal characteristics of microstates revealed that microstate D has a less predominant role in patients than in healthy participants. This difference was consistently found in eyes-open and eyes-closed EEG recordings. No evidence for differences in other microstates was found. As microstate D has been previously related to attentional networks and functions, abnormalities of microstate D might relate to dysfunctional attentional processes in chronic pain. These findings add to the understanding of the pathophysiology of chronic pain and might eventually contribute to the development of an EEG-based biomarker of chronic pain.

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Classification of Resting-State Status Based on Sample Entropy and Power Spectrum of Electroencephalography (EEG)

Applied Bionics and Biomechanics ◽

10.1155/2020/8853238 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Ahmed M. A. Mohamed ◽

Osman N. Uçan ◽

Oğuz Bayat ◽

Adil Deniz Duru

Keyword(s):

Resting State ◽

Sample Entropy ◽

Support Vector ◽

K Nearest Neighbors ◽

Linear Discriminant ◽

Frequency Bands ◽

Eyes Closed ◽

Eeg Data ◽

Eyes Open ◽

The Brain

An electroencephalogram (EEG) is a significant source of diagnosing brain issues. It is also a mediator between the external world and the brain, especially in the case of any mental illness; however, it has been widely used to monitor the dynamics of the brain in healthy subjects. This paper discusses the resting state of the brain with eyes open (EO) and eyes closed (EC) by using sixteen channels by the use of conventional frequency bands and entropy of the EEG signal. The Fast Fourier Transform (FFT) and sample entropy (SE) of each sensor are computed as methods of feature extraction. Six classifiers, including logistic regression (LR), K-Nearest Neighbors (KNN), linear discriminant (LD), decision tree (DT), support vector machine (SVM), and Gaussian Naive Bayes (GNB) are used to discriminate the resting states of the brain based on the extracted features. EEG data were epoched with one-second-length windows, and they were used to compute the features to classify EO and EC conditions. Results showed that the LR and SVM classifiers had the highest average classification accuracy (97%). Accuracies of LD, KNN, and DT were 95%, 93%, and 92%, respectively. GNB gained the least accuracy (86%) when conventional frequency bands were used. On the other hand, when SE was used, the average accuracies of SVM, LD, LR, GNB, KNN, and DT algorithms were 92% 90%, 89%, 89%, 86%, and 86%, respectively.

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Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks

Scientific Reports ◽

10.1038/s41598-021-02079-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Marina Krylova ◽

Stavros Skouras ◽

Adeel Razi ◽

Andrew A. Nicholson ◽

Alexander Karner ◽

...

Keyword(s):

Emotion Regulation ◽

Resting State ◽

Large Scale ◽

Brain Activity ◽

Self Regulation ◽

Learning Networks ◽

Neurofeedback Training ◽

Learning Mechanisms ◽

Social Emotion ◽

Target Network

AbstractNeurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.

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Psychological, Neurophysiological, and Mental Factors Associated With Gamma-Enhancing Neurofeedback Success

Basic and Clinical Neuroscience Journal ◽

10.32598/bcn.11.5.1878.1 ◽

2020 ◽

Vol 11 (5) ◽

pp. 701-714

Author(s):

Zeynab Khodakarami ◽

◽

Mohammad Firoozabadi ◽

Keyword(s):

Fluid Intelligence ◽

Brain Activity ◽

Cognitive Task ◽

Gain Control ◽

Learning Performance ◽

Gamma Activity ◽

Alpha Power ◽

Neurofeedback Training ◽

Eyes Closed ◽

Gamma Power

Introduction: Regarding the neurofeedback training process, previous studies indicate that 10%-50% of subjects cannot gain control over their brain activity even after repeated training sessions. This study is conducted to overcome this problem by investigating inter-individual differences in neurofeedback learning to propose some predictors for the trainability of subjects. Methods: Eight healthy female students took part in 8 (electroencephalography) EEG neurofeedback training sessions for enhancing EEG gamma power at the Oz channel. We studied participants’ preexisting fluid intelligence and EEG frequency sub-bands’ power during 2-min eyes-closed rest and a cognitive task as psychological and neurophysiological factors, concerning neurofeedback learning performance. We also assessed the self-reports of participants about mental strategies used by them during neurofeedback to identify the most effective successful strategies. Results: The results revealed that a significant percentage of individuals (25% in this study) cannot learn how to control their brain gamma activity using neurofeedback. Our findings suggest that fluid intelligence, gamma power during a cognitive task, and alpha power at rest can predict gamma-enhancing neurofeedback performance of individuals. Based on our study, neurofeedback learning is a form of implicit learning. We also found that learning without a user’s mental efforts to find out successful mental strategies, in other words, unconscious learning, lead to more success in gamma-enhancing neurofeedback. Conclusion: Our results may improve gamma neurofeedback efficacy for further clinical usage and studies by giving insight about both non-trainable individuals and effective mental strategies.

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The relevant resting-state brain activity of ecological microexpression recognition test (EMERT)

PLoS ONE ◽

10.1371/journal.pone.0241681 ◽

2020 ◽

Vol 15 (12) ◽

pp. e0241681

Author(s):

Ming Yin ◽

Jianxin Zhang ◽

Deming Shu ◽

Dianzhi Liu

Keyword(s):

Recognition Test ◽

Temporal Lobe ◽

Resting State ◽

Parietal Lobe ◽

Brain Activity ◽

Occipital Lobe ◽

Frontal Lobes ◽

Brain Areas ◽

Eyes Closed ◽

Eyes Open

Zhang, et al. (2017) established the ecological microexpression recognition test (EMERT), but it only used white models’ expressions as microexpressions and backgrounds, and there was no research detecting its relevant brain activity. The current study used white, black and yellow models’ expressions as microexpressions and backgrounds to improve the materials ecological validity of EMERT, and it used eyes-closed and eyes-open resting-state fMRI to detect relevant brain activity of EMERT for the first time. The results showed: (1) Two new recapitulative indexes of EMERT were adopted, such as microexpression M and microexpression SD. The participants could effectively identify almost all the microexpressions, and each microexpression type had a significantly background effect. The EMERT had good retest reliability and calibration validity. (2) ALFFs (Amplitude of Low-Frequency Fluctuations) in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression M. The relevant brain areas of microexpression M were some frontal lobes, insula, cingulate cortex, hippocampus, parietal lobe, caudate nucleus, thalamus, amygdala, occipital lobe, fusiform, temporal lobe, cerebellum and vermis. (3) ALFFs in both eyes-closed and eyes-open resting-states and ALFFs-difference could predict microexpression SD, and the ALFFs-difference was more predictive. The relevant brain areas of microexpression SD were some frontal lobes, insula, cingulate cortex, cuneus, amygdala, fusiform, occipital lobe, parietal lobe, precuneus, caudate lobe, putamen lobe, thalamus, temporal lobe, cerebellum and vermis. (4) There were many similarities and some differences in the relevant brain areas between microexpression M and SD. All these brain areas can be trained to enhance ecological microexpression recognition ability.

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Exploratory Analysis of Power Spectrum and Functional Connectivity During Resting State in Young Binge Drinkers: A MEG Study

International Journal of Neural Systems ◽

10.1142/s0129065715500082 ◽

2015 ◽

Vol 25 (03) ◽

pp. 1550008 ◽

Cited By ~ 17

Author(s):

A. Correas ◽

S. Rodriguez Holguín ◽

P. Cuesta ◽

E. López-Caneda ◽

L. M. García-Moreno ◽

...

Keyword(s):

Functional Connectivity ◽

Resting State ◽

Functional Organization ◽

Brain Activity ◽

Power Spectra ◽

First Year ◽

Eyes Closed ◽

Initial Sign ◽

First Year University ◽

The Brain

Binge Drinking (BD) is a pattern of intermittent intensive alcohol intake which has spread among young adults over the last decades. Adolescence constitutes a critical neuromaturation period in which the brain is particularly sensitive to the effects of alcohol. However, little is known about how BD affects the brain activity. This study aimed to characterize the brain's functional organization in BD and non-BD young population by means of analyzing functional connectivity (FC) and relative power spectra (PS) profiles measured with magnetoencephalography (MEG) during eyes-closed resting state. Our sample composed 73 first-year university students (35 BDs and 38 controls). Results showed that the BD subjects displayed a decreased alpha FC in frontal-parietal regions, and conversely, an enhanced FC in the delta, theta and beta bands in fronto-temporal networks. Besides the FC differences, the BD group showed a decreased PS within alpha range and an increased PS within theta range in the brain's occipital region. These differences in FC and PS measurements provide new evidence of the neurophysiological alterations related to the alcohol neurotoxicity and could represent an initial sign of an anomalous neural activity caused by a BD pattern of alcohol consumption during youth.

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