Jinfeng Wen

Jinfeng Wen


Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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6 June 2022 in Computers in Biology and Medicine
Verified
Journal Article
Closed access
YZYangting Zhang
Yangting Zhang
KWKejie Wang
Kejie Wang
YWYu Wei
Yu Wei
XGXinwen Guo
Xinwen Guo
JWJinfeng Wen
Jinfeng Wen
YLYuxi Luo
Yuxi Luo

17 July 2020 in IEEE Transactions on Biomedical Engineering
Verified
Journal Article
Closed access
JYJuan Yang
Juan Yang
YPYu Pan
Yu Pan
WTWang Tingting
Wang Tingting
XZXiangmin Zhang
Xiangmin Zhang
JWJinfeng Wen
Jinfeng Wen
YLYuxi Luo
Yuxi Luo
Objective: We investigated the nature of interactions between the central nervous system (CNS) and the cardiorespiratory system during sleep. Methods: Overnight polysomnography recordings were obtained from 33 healthy individuals. The relative spectral powers of five frequency bands, three ECG morphological features and respiratory rate were obtained from six EEG channels, ECG, and oronasal airflow, respectively. The synchronous feature series were interpolated to 1 Hz to retain the high time-resolution required to detect rapid physiological variations. CNS-cardiorespiratory interaction networks were built for each EEG channel and a directionality analysis was conducted using multivariate transfer entropy. Finally, the difference in interaction between Deep, Light, and REM sleep (DS, LS, and REM) was studied. Results: Bidirectional interactions existed in central-cardiorespiratory networks, and the dominant direction was from the cardiorespiratory system to the brain during all sleep stages. Sleep stages had evident influence on these interactions, with the strength of information transfer from heart rate and respiration rate to the brain gradually increasing with the sequence of REM, LS, and DS. Furthermore, the occipital lobe appeared to receive the most input from the cardiorespiratory system during LS. Finally, different ECG morphological features were found to be involved with various central-cardiac and cardiac-respiratory interactions. Conclusion: These findings reveal detailed information regarding CNS-cardiorespiratory interactions during sleep and provide new insights into understanding of sleep control mechanisms. Significance: Our approach may facilitate the investigation of the pathological cardiorespiratory complications of sleep disorders.

27 May 2022 in Frontiers in Physiology
Verified
Journal Article
Open access
YSYingjie Song
Yingjie Song
KWKejie Wang
Kejie Wang
YWYu Wei
Yu Wei
YZYongpeng Zhu
Yongpeng Zhu
JWJinfeng Wen
Jinfeng Wen
YLYuxi Luo
Yuxi Luo
Depression, a common mental illness that seriously affects the psychological health of patients, is also thought to be associated with abnormal brain functional connectivity. This study aimed to explore the differences in the sleep-state functional network topology in depressed patients. A total of 25 healthy participants and 26 depressed patients underwent overnight 16-channel electroencephalography (EEG) examination. The cortical networks were constructed by using functional connectivity metrics of participants based on the weighted phase lag index (WPLI) between the EEG signals. The results indicated that depressed patients exhibited higher global efficiency and node strength than healthy participants. Furthermore, the depressed group indicated right-lateralization in the δ band. The top 30% of connectivity in both groups were shown in undirected connectivity graphs, revealing the distinct link patterns between the depressed and control groups. Links between the hemispheres were noted in the patient group, while the links in the control group were only observed within each hemisphere, and there were many long-range links inside the hemisphere. The altered sleep-state functional network topology in depressed patients may provide clues for a better understanding of the depression pathology. Overall, functional network topology may become a powerful tool for the diagnosis of depression.

12 October 2021 in Journal of Neuroscience Research
Verified
Journal Article
Closed access
PDF file
JLJiakai Lian
Jiakai Lian
YSYingjie Song
Yingjie Song
YZYangting Zhang
Yangting Zhang
XGXinwen Guo
Xinwen Guo
JWJinfeng Wen
Jinfeng Wen
YLYuxi Luo
Yuxi Luo

4 June 2020 in Frontiers in Psychiatry
Verified
Journal Article
Open access
PDF file
ZLZi-Lin Li
Zi-Lin Li
GHGao-Jie Huang
Gao-Jie Huang
ZLZe-Tian Li
Ze-Tian Li
SLShu-Bin Li
Shu-Bin Li
YWYi-Le Wang
Yi-Le Wang
LZLaiquan Zou
Laiquan Zou
Anhedonia, the loss or decline of the ability to enjoy pleasure, is an important clinical characteristic of schizophrenia. Schizotypal traits refer to the appearance of subclinical symptoms of schizophrenia across normal people. Still, few studies have investigated chemosensory anhedonia in schizophrenia patients and schizotypy individuals. Seventy-one schizophrenia patients (SCZ), 162 schizotypy individuals (SCT) as selected by the Schizotypal Personality Questionnaire (SPQ), and 182 healthy controls (HC) participated in our study. We used the Positive and Negative Syndrome Scale (PANSS) to measure the clinical symptoms of schizophrenia patients. All participants completed the Chemosensory Pleasure Scale (CPS), which was used to assess participants’ smell and taste hedonic capacities. We found that the three groups differed in chemosensory anhedonia. The SCZ group presented more severe chemosensory anhedonia than the SCT group, and the SCT group presented more severe chemosensory anhedonia than the HC group. We also found that chemosensory hedonic capacity was negatively correlated with negative schizotypal traits in the SCT group. Our results suggested that chemosensory anhedonia is an important characteristic of schizophrenia spectrum disorders.