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Ren H, Li Z, Li J, Zhou J, He Y, Li C, Wang Q, Chen X, Tang J. Correlation Between Cortical Thickness Abnormalities of the Olfactory Sulcus and Olfactory Identification Disorder and Persistent Auditory Verbal Hallucinations in Chinese Patients With Chronic Schizophrenia. Schizophr Bull 2024; 50:1232-1242. [PMID: 38577952 PMCID: PMC11349016 DOI: 10.1093/schbul/sbae040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
BACKGROUND AND HYPOTHESIS Persistent auditory verbal hallucinations (pAVHs) and olfactory identification impairment are common in schizophrenia (SCZ), but the neuroimaging mechanisms underlying both pAVHs and olfactory identification impairment are unclear. This study aimed to investigate whether pAVHs and olfactory identification impairment in SCZ patients are associated with changes in cortical thickness. STUDY DESIGN In this study, cortical thickness was investigated in 78 SCZ patients with pAVHs (pAVH group), 58 SCZ patients without AVHs (non-AVH group), and 83 healthy controls (HC group) using 3T magnetic resonance imaging. The severity of pAVHs was assessed by the Auditory Hallucination Rating Scale. Olfactory identification deficits were assessed using the Odor Stick Identification Test for Japanese (OSIT-J). In addition, the relationship between the severity of pAVHs and olfactory identification disorder and cortical thickness abnormalities was determined. STUDY RESULTS Significant reductions in cortical thickness were observed in the right medial orbital sulcus (olfactory sulcus) and right orbital sulcus (H-shaped sulcus) in the pAVH group compared to both the non-AVH and HC groups (P < .003, Bonferroni correction). Furthermore, the severity of pAVHs was found to be negatively correlated with the reduction in cortical thickness in the olfactory sulcus and H-shaped sulcus. Additionally, a decrease in cortical thickness in the olfactory sulcus showed a positive correlation with the OSIT-J scores (P < .05, false discovery rate correction). CONCLUSIONS Cortical thickness abnormalities in the olfactory sulcus may be a common neuroimaging mechanism for pAVHs and olfactory identification deficits in SCZ patients.
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Affiliation(s)
- Honghong Ren
- Department of Clinical Psychology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Clinical Psychology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Zongchang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinguang Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jun Zhou
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Ying He
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Chunwang Li
- Department of Radiology, Hunan Children’s Hospital, Changsha, China
| | - Qianjin Wang
- Department of Clinical Psychology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
- Department of Clinical Psychology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, China
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Xiaogang Chen
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jinsong Tang
- Department of Psychiatry, Sir Run-Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China
- Hunan Provincial Brain Hospital (The second people's Hospital of Hunan Province), Changsha, China
- Zigong Mental Health Center, Zigong, China
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Wang LN, Lin S, Tian L, Wu H, Jin WQ, Wang W, Pan WG, Yang CL, Ren YP, Ma X, Tang YL. Subregional thalamic functional connectivity abnormalities and cognitive impairments in first-episode schizophrenia. Asian J Psychiatr 2024; 96:104042. [PMID: 38615577 DOI: 10.1016/j.ajp.2024.104042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 03/15/2024] [Accepted: 03/31/2024] [Indexed: 04/16/2024]
Abstract
BACKGROUND Previous studies have documented thalamic functional connectivity (FC) abnormalities in schizophrenia, typically examining the thalamus as a whole. The specific link between subregional thalamic FC and cognitive deficits in first-episode schizophrenia (FES) remains unexplored. METHODS Using data from resting-state functional magnetic resonance imaging, we compared whole-brain FC with thalamic subregions between patients and HCs, and analyzed FC changes in drug-naïve patients separately. We then examined correlations between FC abnormalities with both cognitive impairment and clinical symptoms. RESULTS A total of 33 FES patients (20 drug-naïve) and 32 age- and sex-matched healthy controls (HCs) were included. Compared to HCs, FES patients exhibited increased FC between specific thalamic subregions and cortical regions, particularly bilateral middle temporal lobe and cuneus gyrus, left medial superior frontal gyrus, and right inferior/superior occipital gyrus. Decreased FC was observed between certain thalamic subregions and the left inferior frontal triangle. These findings were largely consistent in drug-naïve patients. Notably, deficits in social cognition and visual learning in FES patients correlated with increased FC between certain thalamic subregions and cortical regions involving the right superior occipital gyrus and cuneus gyrus. The severity of negative symptoms was associated with increased FC between a thalamic subregion and the left middle temporal gyrus. CONCLUSION Our findings suggest FC abnormalities between thalamic subregions and cortical areas in FES patients. Increased FC correlated with cognitive deficits and negative symptoms, highlighting the importance of thalamo-cortical connectivity in the pathophysiology of schizophrenia.
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Affiliation(s)
- Li-Na Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Shuo Lin
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Lu Tian
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Han Wu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wen-Qing Jin
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wen Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wei-Gang Pan
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Chun-Lin Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Yan-Ping Ren
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Xin Ma
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
| | - Yi-Lang Tang
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA 30329, USA; Mental Health Service Line, Atlanta VA Medical Center, Decatur, GA 30033, USA
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Huang Y, Li Y, Yuan Y, Zhang X, Yan W, Li T, Niu Y, Xu M, Yan T, Li X, Li D, Xiang J, Wang B, Yan T. Beta-informativeness-diffusion multilayer graph embedding for brain network analysis. Front Neurosci 2024; 18:1303741. [PMID: 38525375 PMCID: PMC10957763 DOI: 10.3389/fnins.2024.1303741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 02/07/2024] [Indexed: 03/26/2024] Open
Abstract
Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.
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Affiliation(s)
- Yin Huang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Ying Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Yuting Yuan
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Xingyu Zhang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Wenjie Yan
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Ting Li
- School of Life Science, Beijing Institute of Technology, Beijing, China
| | - Yan Niu
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Mengzhou Xu
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Ting Yan
- Translational Medicine Research Center, Shanxi Medical University, Taiyuan, China
| | - Xiaowen Li
- Computer Information Engineering Institute, Shanxi Technology and Business College, Taiyuan, China
| | - Dandan Li
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Jie Xiang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Bin Wang
- College of Computer Science and Technology (College of Data Science), Taiyuan University of Technology, Taiyuan, China
| | - Tianyi Yan
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
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Xiang J, Sun Y, Wu X, Guo Y, Xue J, Niu Y, Cui X. Abnormal Spatial and Temporal Overlap of Time-Varying Brain Functional Networks in Patients with Schizophrenia. Brain Sci 2023; 14:40. [PMID: 38248255 PMCID: PMC10813230 DOI: 10.3390/brainsci14010040] [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: 12/11/2023] [Revised: 12/25/2023] [Accepted: 12/27/2023] [Indexed: 01/23/2024] Open
Abstract
Schizophrenia (SZ) is a complex psychiatric disorder with unclear etiology and pathological features. Neuroscientists are increasingly proposing that schizophrenia is an abnormality in the dynamic organization of brain networks. Previous studies have found that the dynamic brain networks of people with SZ are abnormal in both space and time. However, little is known about the interactions and overlaps between hubs of the brain underlying spatiotemporal dynamics. In this study, we aimed to investigate different patterns of spatial and temporal overlap of hubs between SZ patients and healthy individuals. Specifically, we obtained resting-state functional magnetic resonance imaging data from the public dataset for 43 SZ patients and 49 healthy individuals. We derived a representation of time-varying functional connectivity using the Jackknife Correlation (JC) method. We employed the Betweenness Centrality (BC) method to identify the hubs of the brain's functional connectivity network. We then applied measures of temporal overlap, spatial overlap, and hierarchical clustering to investigate differences in the organization of brain hubs between SZ patients and healthy controls. Our findings suggest significant differences between SZ patients and healthy controls at the whole-brain and subnetwork levels. Furthermore, spatial overlap and hierarchical clustering analysis showed that quasi-periodic patterns were disrupted in SZ patients. Analyses of temporal overlap revealed abnormal pairwise engagement preferences in the hubs of SZ patients. These results provide new insights into the dynamic characteristics of the network organization of the SZ brain.
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Affiliation(s)
- Jie Xiang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yumeng Sun
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Xubin Wu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yuxiang Guo
- School of Software, Taiyuan University of Technology, Taiyuan 030024, China;
| | - Jiayue Xue
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Yan Niu
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
| | - Xiaohong Cui
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China; (J.X.); (Y.S.); (X.W.); (J.X.); (Y.N.)
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Fukuda S, Ohi K, Fujikane D, Takai K, Kuramitsu A, Fujita K, Muto Y, Sugiyama S, Shioiri T. Olfactory identification ability among schizophrenia patients, their first-degree relatives and healthy subjects. Aust N Z J Psychiatry 2023; 57:1367-1374. [PMID: 36967530 DOI: 10.1177/00048674231164568] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
OBJECTIVE Olfactory impairments, including identification, have been reported in patients with schizophrenia, while few studies have examined the olfactory function of unaffected first-degree relatives of patients with schizophrenia, and the sample sizes of first-degree relatives were relatively small. Here, we investigated olfactory identification ability among patients with schizophrenia, first-degree relatives and healthy controls (HCs) using relatively large sample sizes at a single institute. METHODS To assess olfactory identification ability, the open essence odorant identification test was administered to 172 schizophrenia patients, 75 first-degree relatives and 158 healthy controls. Differences in olfactory identification and correlations between olfactory ability and clinical variables were examined among these participants. RESULTS We found a significant difference in olfactory identification ability among the diagnostic groups (p = 7.65 × 10-16). Schizophrenia patients displayed lower olfactory identification ability than first-degree relatives (Cohen's d = -0.57, p = 3.13 × 10-6) and healthy controls (d = -1.00, p = 2.19 × 10-16). Furthermore, first-degree relatives had lower olfactory identification ability than healthy controls (d = -0.29, p = 0.039). Olfactory identification ability moderately and negatively correlated with the duration of illness (r = -0.41, p = 1.88 × 10-8) and negative symptoms (r = -0.28, p = 1.99 × 10-4) in schizophrenia patients, although the correlation with the duration of illness was affected by aging (r = -0.24). CONCLUSIONS Our results demonstrated that schizophrenia patients have impaired olfactory identification ability compared with first-degree relatives and healthy controls, and the impaired olfactory identification ability of first-degree relatives was intermediate between those in schizophrenia patients and healthy controls. Olfactory identification ability was relatively independent of clinical variables. Therefore, olfactory identification ability might be an intermediate phenotype for schizophrenia.
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Affiliation(s)
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
- Department of General Internal Medicine, Kanazawa Medical University, Ishikawa, Japan
| | - Daisuke Fujikane
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Kentaro Takai
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Ayumi Kuramitsu
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Koji Fujita
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Yukimasa Muto
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Shunsuke Sugiyama
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Toshiki Shioiri
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
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Kubota S, Masaoka Y, Sugiyama H, Yoshida M, Yoshikawa A, Koiwa N, Honma M, Kinno R, Watanabe K, Iizuka N, Ida M, Ono K, Izumizaki M. Hippocampus and Parahippocampus Volume Reduction Associated With Impaired Olfactory Abilities in Subjects Without Evidence of Cognitive Decline. Front Hum Neurosci 2020; 14:556519. [PMID: 33192392 PMCID: PMC7556227 DOI: 10.3389/fnhum.2020.556519] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 09/07/2020] [Indexed: 01/02/2023] Open
Abstract
The aim of this study was to investigate the relationship between olfactory recognition and morphological changes in olfactory brain regions including the amygdala, hippocampus, rectus, parahippocampus, orbitofrontal cortex, and medial frontal cortex in 27 elderly subjects and 27 younger healthy controls. The specific aim of the study was to determine which brain areas are associated with the initial decline of olfaction in elderly subjects, which occurs before the onset of dementia. All subjects underwent magnetic resonance imaging to measure anatomical brain volume and cortical thickness, and subjects were assessed using tests of olfactory acuity and cognitive function measured with the Montreal Cognitive Assessment. Overall brain volume reductions were observed in elderly subjects compared with young healthy controls, but only reduction in the volume of the left hippocampus was associated with decreased olfactory ability. The parahippocampus of elderly subjects was not different from that of controls; the extent of the reduction of parahippocampus volume varied among individuals, and reduction in this region was associated with olfactory decline. Similarly, parahippocampus thinning was associated with decreased olfactory function. The path analysis showed direct and indirect effects of hippocampus and parahippocampus volume on olfactory ability and that volume reductions in these areas were not associated with cognitive function. Parahippocampus volume reduction and thinning exhibited individual variation; this may be the first appearance of pathological changes and may lead to dysfunction in the connection of olfactory memory to the neocortex. Parahippocampus change may reflect the first sign of olfactory impairment prior to pathological changes in the hippocampus, amygdala and orbitofrontal cortex.
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Affiliation(s)
- Satomi Kubota
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan.,Division of Neurology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan
| | - Yuri Masaoka
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan
| | | | - Masaki Yoshida
- Department of Ophthalmology, Jikei Medical University, Tokyo, Japan
| | - Akira Yoshikawa
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan
| | - Nobuyoshi Koiwa
- Department of Health and Science, University of Human Arts and Sciences, Saitama, Japan
| | - Motoyasu Honma
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan
| | - Ryuta Kinno
- Division of Neurology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan
| | - Keiko Watanabe
- Division of Neurology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan
| | - Natsuko Iizuka
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan.,Division of Neurology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan
| | - Masahiro Ida
- National Hospital Organization Mito Medical Center, Ibaraki, Japan
| | - Kenjiro Ono
- Division of Neurology, Department of Medicine, Showa University School of Medicine, Tokyo, Japan
| | - Masahiko Izumizaki
- Department of Physiology, Showa University School of Medicine, Tokyo, Japan
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