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Niu Y, Chen X, Chen Y, Yao Z, Chen X, Liu Z, Meng X, Liu Y, Zhao Z, Fan H. A gender recognition method based on EEG microstates. Comput Biol Med 2024; 173:108366. [PMID: 38554661 DOI: 10.1016/j.compbiomed.2024.108366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Revised: 03/19/2024] [Accepted: 03/21/2024] [Indexed: 04/02/2024]
Abstract
BACKGROUND Gender carries important information related to male and female characteristics, and a large number of studies have attempted to use physiological measurement methods for gender classification. Although previous studies have shown that there exist statistical differences in some Electroencephalographic (EEG) microstate parameters between males and females, it is still unknown that whether these microstate parameters can be used as potential biomarkers for gender classification based on machine learning. METHODS We used two independent resting-state EEG datasets: the first dataset included 74 females and matched 74 males, and the second one included 42 males and matched 42 females. EEG microstate analysis based on modified k-means clustering method was applied, and temporal parameter and nonlinear characteristics (sample entropy and Lempel-Ziv complexity) of EEG microstate sequences were extracted to compare between males and females. More importantly, these microstate temporal parameters and complexity were tried to train six machine learning methods for gender classification. RESULTS We obtained five common microstates for each dataset and each group. Compared with the male group, the female group has significantly higher temporal parameters of microstate B, C, E and lower temporal parameters of microstate A and D, and higher complexity of microstate sequence. When using combination of microstate temporal parameters and complexity or only microstate temporal parameters as classification features in an independent test set (the second dataset), we achieved 95.2% classification accuracy. CONCLUSION Our research findings indicate that the dynamics of microstate have considerable Gender-specific alteration. EEG microstates can be used as neurophysiological biomarkers for gender classification.
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Affiliation(s)
- Yanxiang Niu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Xin Chen
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Yuansen Chen
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Zixuan Yao
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Xuemei Chen
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Ziquan Liu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Xiangyan Meng
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China
| | - Yanqing Liu
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China.
| | - Zongya Zhao
- School of Medical Engineering, Xinxiang Medical University, Xinxiang, China.
| | - Haojun Fan
- Institute of Disaster and Emergency Medicine, Tianjin University, Tianjin, China; Wenzhou Safety (Emergency) Institute, Tianjin University, 325000, Wenzhou, China.
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Looser VN, Gerber M, Ludyga S. Physical activity and verbal memory performance: Mediating effects of resting-state brain activity. PROGRESS IN BRAIN RESEARCH 2024; 286:33-66. [PMID: 38876578 DOI: 10.1016/bs.pbr.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2024]
Abstract
Verbal short-term and long-term memory are crucial neuropsychological functions involved in core cognitive abilities. They constitute vital components of subjective well-being and academic achievement. To date, there is limited research on the association between regular physical activity and memory abilities during young adulthood. The Individual Alpha Peak Frequency (IAPF) contributes to various cognitive abilities and also appears to be sensitive to physical activity. Consequently, the IAPF has the potential to underlie the association between physical activity and verbal memory. We examined the direct relation of physical activity and verbal memory, and the potential indirect relation via IAPF in young adults. Regular physical activity was assessed via accelerometry on seven consecutive days in 115 participants (N=115, 48% female) aged 18-35 years (M=24.1, SD=3.8). In addition, verbal memory performance was assessed using an immediate and delayed free-recall task. Brain activity during rest was recorded with EEG, and IAPF was extracted for mediation analyses. Path analysis revealed pronounced sex differences in the association between physical activity, IAPF, and verbal memory performance. Exclusively in female participants, higher vigorous physical activity levels were associated with better recall performance. In contrast, no association of physical activity and memory was found in male participants. However, being more physically active was related to a higher IAPF exclusively in male participants. Physical activity shows differential associations between IAPF and verbal memory in male and female participants. However, the lack of a mediating role of IAPF suggests that this neurophysiological marker cannot explain these specific associations in young adults.
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Affiliation(s)
- Vera Nina Looser
- Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland.
| | - Markus Gerber
- Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland
| | - Sebastian Ludyga
- Department of Sport, Exercise and Health, University of Basel, Basel, Switzerland
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Finn CE, Han GT, Naples AJ, Wolf JM, McPartland JC. Development of peak alpha frequency reflects a distinct trajectory of neural maturation in autistic children. Autism Res 2023; 16:2077-2089. [PMID: 37638733 DOI: 10.1002/aur.3017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2023] [Accepted: 08/05/2023] [Indexed: 08/29/2023]
Abstract
Electroencephalographic peak alpha frequency (PAF) is a marker of neural maturation that increases with age throughout childhood. Distinct maturation of PAF is observed in children with autism spectrum disorder such that PAF does not increase with age and is instead positively associated with cognitive ability. The current study clarifies and extends previous findings by characterizing the effects of age and cognitive ability on PAF between diagnostic groups in a sample of children and adolescents with and without autism spectrum disorder. Resting EEG data and behavioral measures were collected from 45 autistic children and 34 neurotypical controls aged 8 to 18 years. Utilizing generalized additive models to account for nonlinear relations, we examined differences in the joint effect of age and nonverbal IQ by diagnosis as well as bivariate relations between age, nonverbal IQ, and PAF across diagnostic groups. Age was positively associated with PAF among neurotypical children but not among autistic children. In contrast, nonverbal IQ but not age was positively associated with PAF among autistic children. Models accounting for nonlinear relations revealed different developmental trajectories as a function of age and cognitive ability based on diagnostic status. Results align with prior evidence indicating that typical age-related increases in PAF are absent in autistic children and that PAF instead increases with cognitive ability in these children. Findings suggest the potential of PAF to index distinct trajectories of neural maturation in autistic children.
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Affiliation(s)
- Caroline E Finn
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Gloria T Han
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
- Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Adam J Naples
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - Julie M Wolf
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
| | - James C McPartland
- Child Study Center, Yale School of Medicine, New Haven, Connecticut, USA
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Li BZ, Nan W, Pun SH, Vai MI, Rosa A, Wan F. Modulating Individual Alpha Frequency through Short-Term Neurofeedback for Cognitive Enhancement in Healthy Young Adults. Brain Sci 2023; 13:926. [PMID: 37371404 DOI: 10.3390/brainsci13060926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 05/31/2023] [Accepted: 06/01/2023] [Indexed: 06/29/2023] Open
Abstract
Human alpha oscillation (7-13 Hz) has been extensively studied over the years for its connection with cognition. The individual alpha frequency (IAF), defined as the frequency that provides the highest power in the alpha band, shows a positive correlation with cognitive processes. The modulation of alpha activities has been accomplished through various approaches aimed at improving cognitive performance. However, very few studies focused on the direct modulation of IAF by shifting the peak frequency, and the understanding of IAF modulation remains highly limited. In this study, IAFs of healthy young adults were up-regulated through short-term neurofeedback training using haptic feedback. The results suggest that IAFs have good trainability and are up-regulated, also that IAFs are correlated with the enhanced cognitive performance in mental rotation and n-back tests compared to sham-neurofeedback control. This study demonstrates the feasibility of self-regulating IAF for cognition enhancement and provides potential therapeutic benefits for cognitive-impaired patients.
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Grants
- 2020YFB1313502 The National Key Research and Development Program of China under Grant
- 2021ZD0201300 The National Key Research and Development Program of China under Grant
- SGDX20201103094002009 The Shenzhen-Hong Kong-Macau S&TProgram (Category C) of SZSTI
- MYRG2022-00111-IME The University of Macau
- MYRG2020-00098-FST The University of Macau
- MYRG2022-00197-FST The University of Macau
- 0144/2019/A3 The Science and Technology Development Fund, Macau SAR
- 0022/2020/AFJ The Science and Technology Development Fund, Macau SAR
- SKL-AMSV (FDCTfunded),SKL-AMSV-ADDITIONAL FUND, SKL-AMSV(UM)-2023-2025 The Science and Technology Development Fund, Macau SAR
- 0045/2019/AFJ The Science and Technology Development Fund, Macau SAR
- CP-017-2022 The Lingyange Semi-conductor Inc. Zhuhai City, Guandong, China
- CP-031-2022 The Lingyange Semi-conductor Inc. Zhuhai City, Guandong, China
- CP-003-2023 The Blue Ocean Smart System (Nanjing) Limited
- 2023A1515010844 The Guangdong Basic and Applied Basic Research Foundation
- 81901830 The National Natural Science Foundation of China
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Affiliation(s)
- Ben-Zheng Li
- State Key Laboratory of Analog and Mixed Signal Very-Large-Scale Integration (VLSI), University of Macau, Macau 999078, China
- Department of Electrical and Computer Engineering, Faculty of Science and Engineering, University of Macau, Macau 999078, China
- Department of Physiology and Biophysics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Department of Electrical Engineering, University of Colorado Denver, Denver, CO 80204, USA
| | - Wenya Nan
- Department of Psychology, Shanghai Normal University, Shanghai 200234, China
| | - Sio Hang Pun
- State Key Laboratory of Analog and Mixed Signal Very-Large-Scale Integration (VLSI), University of Macau, Macau 999078, China
| | - Mang I Vai
- State Key Laboratory of Analog and Mixed Signal Very-Large-Scale Integration (VLSI), University of Macau, Macau 999078, China
- Department of Electrical and Computer Engineering, Faculty of Science and Engineering, University of Macau, Macau 999078, China
| | - Agostinho Rosa
- LaSEEB-System and Robotics Institute, LarSys, 1049-001 Lisbon, Portugal
| | - Feng Wan
- Department of Electrical and Computer Engineering, Faculty of Science and Engineering, University of Macau, Macau 999078, China
- Centre for Cognitive and Brain Sciences, Institute of Collaborative Innovation, University of Macau, Macau 999078, China
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The Influence of Mental Imagery Expertise of Pen and Paper Players versus Computer Gamers upon Performance and Electrocortical Correlates in a Difficult Mental Rotation Task. Symmetry (Basel) 2021. [DOI: 10.3390/sym13122337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
We investigated the influence of mental imagery expertise in 15 pen and paper role-players as an expert group compared to the gender-matched control group of computer role-players in the difficult Vandenberg and Kuse mental rotation task. In this task, the participants have to decide which two of four rotated figures match the target figure. The dependent measures were performance speed and accuracy. In our exploratory investigation, we further examined midline frontal theta band activation, parietal alpha band activation, and parietal alpha band asymmetry in EEG as indicator for the chosen rotation strategy. Additionally, we explored the gender influence on performance and EEG activation, although a very small female sample section was given. The expected gender difference concerning performance accuracy was negated by expertise in pen and paper role-playing women, while the gender-specific difference in performance speed was preserved. Moreover, gender differences concerning electro-cortical measures revealed differences in rotation strategy, with women using top-down strategies compared to men, who were using top-down strategies and active inhibition of associative cortical areas. These strategy uses were further moderated by expertise, with higher expertise leading to more pronounced activation patters, especially during successful performance. However, due to the very limited sample size, the findings of this explorative study have to be interpreted cautiously.
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Courtney SM, Hinault T. When the time is right: Temporal dynamics of brain activity in healthy aging and dementia. Prog Neurobiol 2021; 203:102076. [PMID: 34015374 DOI: 10.1016/j.pneurobio.2021.102076] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 05/08/2021] [Accepted: 05/14/2021] [Indexed: 10/21/2022]
Abstract
Brain activity and communications are complex phenomena that dynamically unfold over time. However, in contrast with the large number of studies reporting neuroanatomical differences in activation relative to young adults, changes of temporal dynamics of neural activity during normal and pathological aging have been grossly understudied and are still poorly known. Here, we synthesize the current state of knowledge from MEG and EEG studies that aimed at specifying the effects of healthy and pathological aging on local and network dynamics, and discuss the clinical and theoretical implications of these findings. We argue that considering the temporal dynamics of brain activations and networks could provide a better understanding of changes associated with healthy aging, and the progression of neurodegenerative disease. Recent research has also begun to shed light on the association of these dynamics with other imaging modalities and with individual differences in cognitive performance. These insights hold great potential for driving new theoretical frameworks and development of biomarkers to aid in identifying and treating age-related cognitive changes.
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Affiliation(s)
- S M Courtney
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA; F.M. Kirby Research Center, Kennedy Krieger Institute, MD 21205, USA; Department of Neuroscience, Johns Hopkins University, MD 21205, USA
| | - T Hinault
- Department of Psychological and Brain Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA; U1077 INSERM-EPHE-UNICAEN, Caen, France.
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