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You Y, Liu J, Wang D, Fu Y, Liu R, Ma X. Cognitive Performance in Short Sleep Young Adults with Different Physical Activity Levels: A Cross-Sectional fNIRS Study. Brain Sci 2023; 13:brainsci13020171. [PMID: 36831714 PMCID: PMC9954673 DOI: 10.3390/brainsci13020171] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 01/14/2023] [Accepted: 01/16/2023] [Indexed: 01/20/2023] Open
Abstract
Short sleep is a common issue nowadays. The purpose of this study was to investigate prefrontal cortical hemodynamics by evaluating changes in concentrations of oxygenated hemoglobin (HbO) in cognitive tests among short-sleep young adults and to explore the relationship between sleep duration, physical activity level, and cognitive function in this specific population. A total of 46 participants (25 males and 21 females) were included in our study, and among them, the average sleep duration was 358 min/day. Stroop performance in the short sleep population was linked to higher levels cortical activation in distinct parts of the left middle frontal gyrus. This study found that moderate-to-vigorous physical activity (MVPA) was significantly associated with lower accuracy of incongruent Stroop test. The dose-response relationship between sleep duration and Stroop performance under different levels of light-intensity physical activity (LPA) and MVPA was further explored, and increasing sleep time for different PA level was associated with better Stroop performance. In summary, this present study provided neurobehavioral evidence between cortical hemodynamics and cognitive function in the short sleep population. Furthermore, our findings indicated that, in younger adults with short sleep, more MVPA was associated with worse cognitive performance. Short sleep young adults should increase sleep time, rather than more MVPA, to achieve better cognitive function.
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Affiliation(s)
- Yanwei You
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China
- School of Social Sciences, Tsinghua University, Beijing 100084, China
| | - Jianxiu Liu
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China
- Vanke School of Public Health, Tsinghua University, Beijing 100084, China
| | - Dizhi Wang
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China
- School of Social Sciences, Tsinghua University, Beijing 100084, China
| | - Yingyao Fu
- Beijing Jianhua Experimental Etown School, Beijing 100176, China
| | - Ruidong Liu
- Sports Coaching College, Beijing Sport University, Beijing 100091, China
- Correspondence: (R.L.); (X.M.)
| | - Xindong Ma
- Division of Sports Science & Physical Education, Tsinghua University, Beijing 100084, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing 100084, China
- Correspondence: (R.L.); (X.M.)
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Zhu L, Haghani S, Najafizadeh L. On fractality of functional near-infrared spectroscopy signals: analysis and applications. NEUROPHOTONICS 2020; 7:025001. [PMID: 32377544 PMCID: PMC7189210 DOI: 10.1117/1.nph.7.2.025001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 04/13/2020] [Indexed: 06/11/2023]
Abstract
Significance: The human brain is a highly complex system with nonlinear, dynamic behavior. A majority of brain imaging studies employing functional near-infrared spectroscopy (fNIRS), however, have considered only the spatial domain and have ignored the temporal properties of fNIRS recordings. Methods capable of revealing nonlinearities in fNIRS recordings can provide new insights about how the brain functions. Aim: The temporal characteristics of fNIRS signals are explored by comprehensively investigating their fractal properties. Approach: Fractality of fNIRS signals is analyzed using scaled windowed variance (SWV), as well as using visibility graph (VG), a method which converts a given time series into a graph. Additionally, the fractality of fNIRS signals obtained under resting-state and task-based conditions is compared, and the application of fractality in differentiating brain states is demonstrated for the first time via various classification approaches. Results: Results from SWV analysis show the existence of high fractality in fNIRS recordings. It is shown that differences in the temporal characteristics of fNIRS signals related to task-based and resting-state conditions can be revealed via the VGs constructed for each case. Conclusions: fNIRS recordings, regardless of the experimental conditions, exhibit high fractality. Furthermore, VG-based metrics can be employed to differentiate rest and task-execution brain states.
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Affiliation(s)
- Li Zhu
- Rutgers University, Integrated Systems and NeuroImaging Laboratory, Department of Electrical and Computer Engineering, Piscataway, New Jersey, United States
| | - Sasan Haghani
- University of The District of Columbia, Department of Electrical and Computer Engineering, Washington DC, United States
| | - Laleh Najafizadeh
- Rutgers University, Integrated Systems and NeuroImaging Laboratory, Department of Electrical and Computer Engineering, Piscataway, New Jersey, United States
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Sun X, Long H, Zhao C, Duan Q, Zhu H, Chen C, Sun W, Ju F, Sun X, Zhao Y, Xue B, Tian F, Mou X, Yuan H. Analgesia-enhancing effects of repetitive transcranial magnetic stimulation on neuropathic pain after spinal cord injury:An fNIRS study. Restor Neurol Neurosci 2019; 37:497-507. [PMID: 31381538 DOI: 10.3233/rnn-190934] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Xiaolong Sun
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Hua Long
- Department of Orthopaedics, Tangdu Hospital, The Fourth Military Medical University, Xi’an, China
| | - Chenguang Zhao
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Qiang Duan
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
- Department of Rehabilitation Medicine, The People’s Hospital of China Three Gorges University, Yichang, China
| | - Huilin Zhu
- Children Developmental & Behavioral Center, Third Affiliated Hospital of Sun Yet-Sen University, Guangzhou, China
| | - Chunyan Chen
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Wei Sun
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Fen Ju
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Xinyan Sun
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Yilin Zhao
- Department of Medical Affair, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Baijie Xue
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Fei Tian
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Xiang Mou
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
| | - Hua Yuan
- Department of Rehabilitation Medicine, Xijing Hospital, The Fourth Military Medical University, Xi’an, China
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