Spectral and brain mapping analysis of EEG based on Pwelch in schizophrenic patients

Akbar, Y; Khotimah, Siti Nurul; Haryanto, Freddy

doi:10.1088/1742-6596/694/1/012070

Cited by 16 publications

(7 citation statements)

References 7 publications

(7 reference statements)

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“…The retention period for each trial was extracted to calculate PSD P sd(f) via the Welch’s method ( Akbar et al, 2016 ). The PSD of a time series was defined as the distribution of power as a function of frequency.…”

Section: Methodsmentioning

confidence: 99%

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

Tian

Zhang

et al. 2017

Front. Hum. Neurosci.

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Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces.

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Section: Methodsmentioning

confidence: 99%

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

Tian

Zhang

et al. 2017

Front. Hum. Neurosci.

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“…A significant increase in the activity of delta waves and theta waves in the frontal lobe of people with schizophrenia has been reported. In contrast, the alpha waves indicated a decrease in the occipital lobe in all schizophrenic patients [68]. High alpha or low beta is associated with "active" intelligence.…”

Section: Discussionmentioning

confidence: 78%

Brain Waves Reflect Cognition-Emotion State as a Diagnostic Tool for Intervention in Dysfunctional States: A Real-World Evidence

Mayoral-Rodrígez

Pérez-Alvarez

Timoneda-Gallart

2022

J. Intellect. Disabl. Diagn. Treat.

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Objective: This study aims to characterize electrical signals to establish a diagnosis of cognitive-emotional dysfunction and guide a successful therapeutic intervention. Therefore, the present study aimed to observe these frequency bands in a sample of dysfunctional neurological behaviors to establish a neural marker of neural dysfunction that helps diagnose and monitor treatment. Methods: A descriptive retrospective (extracted from the database) observational study design based on real-world historical data from routine clinical practice. According to DSM-5, low academic achievement (n =70), disruptive behavior (externalizing behavior problems) (n=70), and somatic syndrome disorder (n=70) were the subjects. The mean age of the sample was 14.13 (SD = 1.46; range 12-18), 31.5% women. The measuring instrument was the NeXus-10, which is suitable for acquiring a wide range of physiological signals. Brain electrical activity was recorded by using the quantitative electroencephalograph (qEEG) in accordance with the 10-20 International Electrode Placement System. In particular, the specific form of miniQ (mini-qEEG) was used. Results: A pattern record present in all cases were identified. The record refers to (a) activity along the midline, namely, Fz-Cz-Pz, (b) activity from the center (Cz) to back, namely, Pz-O1 and O2, (c) activity from the center (Cz) forward (Fz), and (d) comparison between hemispheres. The characteristics of theta, alpha, and beta waves define the characteristic pattern of neurological dysfunction. The reversal of the dysfunctional pattern coincided with the remission of the clinical symptoms after treatment, which occurred in 87,6% of the subjects. We define remission as not meeting DSM-5 criteria. Conclusion: This study suggests that miniQ register could be considered a simple and objective tool for studying neurological dysfunction. This dysfunction is explained according to current neurological knowledge of interactive cognition-emotion processing. MiniQ may be a cheap and reliable method and a promising tool for the investigation in the field.

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“…Delta (1~4 Hz), theta (4~8 Hz), alpha (8~13 Hz), and beta (13~30 Hz) rhythm were extracted by Fourier transformation 39 . The power spectrum of each rhythm signal was then calculated using the pwelch algorithm 40 . The average power spectrum of all data epochs for each subject was used as the final power spectrum for the subject.…”

Section: Methodsmentioning

confidence: 99%

The Influence of Listening to Music on Adults with Left-behind Experience Revealed by EEG-based Connectivity

Tian

et al. 2020

Sci Rep

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The human brain has a close relationship with music. Music-induced structural and functional brain changes have been demonstrated in the healthy adult. In the present study, adults with left-behind experience (ALB) were divided into two groups. The experimental group (ALB-E) took part in the music therapy experiment with three stages, including before listening to music (pre-stage), initially listening to music (mid-stage) and after listening to music (post-stage). The control group (ALB-C) did not participate in music therapy. Scalp resting-state EEGs of ALB were recorded during the three stages. We found no significant frequency change in the ALB-C group. In the ALB-E group, only the theta power spectrum was significantly different at all stages. The topographical distributions of the theta power spectrum represented change in trends from the frontal regions to the occipital regions. The result of Granger causal analysis (GCA), based on theta frequency, showed a stronger information flow from the middle frontal gyrus to the middle temporal gyrus (MFG → MTG) in the left hemisphere at the pre-stage compared to the post-stage. Additionally, the experimental group showed a weaker information flow from inferior gyrus to superior temporal gyrus (IFG → STG) in the right hemisphere at post-test stage compared to the ALB-C group. Our results demonstrate that listening to music can play a positive role on improving negative feelings for individuals with left behind experience. Adults with Left-behind experience (ALB) generally refers to an individual that underwent an extended period of time in childhood without residing with parents and was instead brought up by grandparents or relatives. This is caused by unbalanced economic development within a geographical region and has become an emerging social phenomenon. This phenomenon is common in rural China, Philippines, Indonesia, and other countries 1. After the period of lacking parents' care and communication, ALB usually present strong psychological insecurity and mistrust for other people. In social occasions, ALB are not willing to take the initiative to establish good interpersonal relationships with others. From an early age, they will have a mentality of inferiority and cowardice which affects subsequent development. This can make ALB more likely to opt to escape and deal with problems in a negative way. In addition, ALB often show emotional indifference in their psychology. Long-term communication with parents is relatively sparse and there is little sense of family warmth, which will affect their overall personality and emotional attitude. This can result in a lack of social interest and methods for ALB, and social anxiety frequently occurs during their interactions with others. Previous studies have reported that people who have left-behind experience may present with depression, anxiety, loneliness, and lower satisfaction for life compared to those who have no left-behind experience 2. Researchers conducted a survey of 4857 involving children and adults with lef...

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Spectral and brain mapping analysis of EEG based on Pwelch in schizophrenic patients

Cited by 16 publications

References 7 publications

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

Brain Waves Reflect Cognition-Emotion State as a Diagnostic Tool for Intervention in Dysfunctional States: A Real-World Evidence

The Influence of Listening to Music on Adults with Left-behind Experience Revealed by EEG-based Connectivity

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