Comparison of brain effective connectivity in different states of attention and consciousness based on EEG signals

Rahimi, Masoomeh; Moradi, Mohammad Hassan; Ghassemi, Farnaz

doi:10.1016/j.bspc.2019.02.002

Cited by 9 publications

(3 citation statements)

References 36 publications

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“…The authors also explained how the power in alpha and beta bands has decreased with the difficulty of both actual and unreal movements. Rahimi et al [ 245 ] investigated the various states of consciousness and attention. The authors explained the significant differences between different states of consciousness and awareness.…”

Section: Bci Recent Advancementsmentioning

confidence: 99%

Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities

Yadav

Maini

2023

Multimed Tools Appl

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Brain-Computer Interfaces (BCI) is an exciting and emerging research area for researchers and scientists. It is a suitable combination of software and hardware to operate any device mentally. This review emphasizes the significant stages in the BCI domain, current problems, and state-of-the-art findings. This article also covers how current results can contribute to new knowledge about BCI, an overview of BCI from its early developments to recent advancements, BCI applications, challenges, and future directions. The authors pointed to unresolved issues and expressed how BCI is valuable for analyzing the human brain. Humans' dependence on machines has led humankind into a new future where BCI can play an essential role in improving this modern world.

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Section: Bci Recent Advancementsmentioning

confidence: 99%

Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities

Yadav

Maini

2023

Multimed Tools Appl

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“…In some articles, only the separation between the group of healthy people and those with attention disorder or ADHD by using brain signals and attention tests has been discussed [ 4 , 5 ]. In some other articles, the estimation of one of the five types of attention during a specific activity by brain signals has been discussed [ 6 , 7 ].…”

Section: Introductionmentioning

confidence: 99%

“…So far, various methodological approaches have been developed in order to measure different types of attention in combination with neuroimaging techniques. e mentioned methods include electroencephalography focusing on the measurement of event-related potentials (ERPs) for various purposes in the field of sports or various cognitive disorders, such as the study of sustained attention in combat sports athletes, attention-oriented processes in children with attention deficit hyperactivity disorder (ADHD) using measurement of event-related potentials during sustained attention as well as memory tasks are used as biomarkers to diagnose mild cognitive impairment [4][5][6][7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention

Jami

Khalilzadeh

Ghoshuni

et al. 2022

Computational Intelligence and Neuroscience

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Assessment of attention is of great importance as one of human cognitive abilities. Although neuropsychological tests have been developed and used to evaluate the ability to pay attention, their validity and reliability have been reduced due to some limitations such as the presence of intervention factors, including human factors, limited range of languages, and cultural influences. Therefore, direct outputs of the brain system, represented by event-related potentials (ERPs), and the analysis of its function in cognitive activities have become very important as a complementary tool to assess various types of attention. This research tries to assess 4 types of attention including sustained, alternative, selective, and divided, using an integrated visual-auditory test and brain signals simultaneously. Thus, the electroencephalogram (EEG) data were recorded using 19 channels, and the integrated visual and auditory (IVA-AE) test was simultaneously performed on twenty-eight healthy volunteers including 22 male and 6 female subjects with the average age of 27 ± 5.3 years. Then ERPs related to auditory and visual stimuli with synchronous averaging technique were extracted. A topographic brain mapping (topo-map) was plotted for each frame of stimulation. Next, an optical flow method was implemented on different topo-maps to obtain motion vectors from one map to another. After obtaining the overall brain graph of an individual, some features were extracted and used as measures of local and global connectivity. The extracted features were consequently evaluated along with the parameters of the IVA test by support vector machine regression (SVM-R). The volume of attention was then quantified by combining the IVA parameters. Ultimately, estimation accuracy of each type of attention including focused attention (86.1%), sustained attention (83.4%), selective attention (80.9%), and divided attention (79.9%) was obtained. According to the present study, there is a significant relationship between response control and attention indicators of the IVA test as well as ERP brain signals.

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A Novel Approach for Non-linear Deep Fuzzy Rule-Based Model and Its Applications in Biomedical Analyses

Davoodi

Moradi

2023

Intelligent Systems Reference Library

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Comparison of brain effective connectivity in different states of attention and consciousness based on EEG signals

Cited by 9 publications

References 36 publications

Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities

Electroencephalogram based brain-computer interface: Applications, challenges, and opportunities

A Novel Method Based on ERP and Brain Graph for the Simultaneous Assessment of Various Types of Attention

A Novel Approach for Non-linear Deep Fuzzy Rule-Based Model and Its Applications in Biomedical Analyses

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