Wearable electroencephalography (EEG) has the potential to improve everyday life through brain-computer interfaces (BCI) for applications such as sleep improvement, adaptive hearing aids, or thought-based digital device control. To make these innovations more practical for everyday use, researchers are looking to miniaturized, concealed EEG systems that can still collect neural activity precisely. For example, researchers are using flexible EEG electrode arrays that can be attached around the ear (cEEGrids) to study neural activations in everyday life situations. However, the use of such concealed EEG approaches is limited by measurement challenges such as reduced signal amplitudes and high recording system costs. In this article, we compare the performance of a lower-cost open-source amplification system, the OpenBCI Cyton+Daisy boards, with a benchmark amplifier, the MBrainTrain Smarting Mobi. Our results show that the OpenBCI system is a viable alternative for concealed EEG research, with highly similar noise performance, but slightly lower timing precision. This system can be a great option for researchers with a smaller budget and can, therefore, contribute significantly to advancing concealed EEG research.
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http://dx.doi.org/10.3390/s23094559 | DOI Listing |
J Neurosci
January 2025
School of Psychology and Neuroscience, University of Glasgow, Glasgow G12 8QB, United Kingdom
Brain oscillations in the alpha-band (8-14 Hz) have been linked to specific processes in attention and perception. In particular, decreases in posterior alpha-amplitude are thought to reflect activation of perceptually relevant brain areas for target engagement, while alpha-amplitude increases have been associated with inhibition for distractor suppression. Traditionally, these alpha-changes have been viewed as two facets of the same process.
View Article and Find Full Text PDFIBRO Neurosci Rep
December 2024
Faculty of Medicine and Health Technology, Tampere University, Tampere 33720, Finland.
Psychiatric disorders present diagnostic challenges due to individuals concealing their genuine emotions, and traditional methods relying on neurophysiological signals have limitations. Our study proposes an improved EEG-based diagnostic model employing Deep Learning (DL) techniques to address this. By experimenting with DL models on EEG data, we aimed to enhance psychiatric disorder diagnosis, offering promising implications for medical advancements.
View Article and Find Full Text PDFBehav Sci (Basel)
July 2024
Department of Psychology, Hangzhou Normal University, Hangzhou 311121, China.
Recent theory suggests that both the orienting response and arousal inhibition play roles in the effect of the concealed information test (CIT). However, the neural signatures associated with these two processes remain unclear. To address this issue, participants were motivated to either conceal or reveal crime-related stimulus during CIT while EEG was recorded.
View Article and Find Full Text PDFPsychophysiology
December 2024
Zhejiang Philosophy and Social Science Laboratory for Research in Early Development and Childcare, Hangzhou Normal University, Hangzhou, China.
This study examined the neural signatures associated with conflict-monitoring, recognition and feedback processing in a feedback Concealed Information Test (fCIT), and also examined whether all the ERPs can be used to detect concealed autobiographical information. Participants were randomly assigned to one of two groups (guilty or innocent) and then tested in the fCIT while undergoing electroencephalograms (EEGs). The results showed that the probe (participants' name) elicited a more negative N200, and a more positive recognition P300 than irrelevants among guilty participants.
View Article and Find Full Text PDFJ Neural Eng
August 2024
Beijing Institute of Basic Medical Sciences, Beijing 100850, People's Republic of China.
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