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Yang J, Xiao R, Liu Y, He C, Han L, Xu X, Chen M, Zhong J. Spatiotemporal consistency analysis of cerebral small vessel disease: an rs-fMRI study. Front Neurosci 2024; 18:1385960. [PMID: 38841094 PMCID: PMC11150806 DOI: 10.3389/fnins.2024.1385960] [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: 02/14/2024] [Accepted: 05/08/2024] [Indexed: 06/07/2024] Open
Abstract
Introduction Cerebral small vessel disease (SVD) affects older adults, but traditional approaches have limited the understanding of the neural mechanisms of SVD. This study aimed to explore the effects of SVD on brain regions and its association with cognitive decline using the four-dimensional (spatiotemporal) consistency of local neural activity (FOCA) method. Methods Magnetic resonance imaging data from 42 patients with SVD and 38 healthy controls (HCs) were analyzed using the FOCA values. A two-sample t test was performed to compare the differences in FOCA values in the brain between the HCs and SVD groups. Pearson correlation analysis was conducted to analyze the association of various brain regions with SVD scores. Results The results revealed that the FOCA values in the right frontal_inf_oper, right temporal_pole_sup, and default mode network decreased, whereas those in the temporal_inf, hippocampus, basal ganglia, and cerebellum increased, in patients with SVD. Most of these varying brain regions were negatively correlated with SVD scores. Discussion This study suggested that the FOCA approach might have the potential to provide useful insights into the understanding of the neurophysiologic mechanisms of patients with SVD.
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Affiliation(s)
- Jie Yang
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
| | - Rui Xiao
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
| | - Yujian Liu
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
- Sichuan Vocational College of Health and Rehabilitation, Zigong, China
| | - Chaoliang He
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
| | - Limei Han
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
- North Sichuan Medical College, Nanchong, China
| | - Xiaoya Xu
- Department of Neurology, Zigong First People’s Hospital, Zigong, China
| | - Meining Chen
- MR Research and Collaboration, Siemens Healthineers, Shanghai, China
| | - Jianquan Zhong
- Department of Radiology, Zigong First People’s Hospital, Zigong, China
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Li T, Niu S, Qiu X, Zhai Z, Yang L, Chen L, Zhang XM. Altered Cerebral Blood Flow is Linked to Disease Duration in Patients with Generalized tonic‒clonic Seizures. Neuropsychiatr Dis Treat 2022; 18:2649-2659. [PMID: 36387946 PMCID: PMC9662018 DOI: 10.2147/ndt.s386509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Accepted: 10/29/2022] [Indexed: 11/11/2022] Open
Abstract
PURPOSE To investigate cerebral blood flow (CBF) characteristics in individuals with generalized tonic‒clonic seizures (GTCS) during the interictal phase using voxel-based analysis of 3D pseudocontinuous arterial spin labeling (PCASL). PATIENTS AND METHODS Patients with GTCS (GTCS group) (during the interictal period) and healthy volunteers (control group) underwent head MR imaging with a 3.0T MR scanner with a 3D PCASL sequence. CBF was compared between the two groups. Spearman correlations of CBF in regions of interest (ROIs) in GTCS patients with the duration of disease and age of onset were analyzed and corrected using the false discovery rate (FDR). RESULTS Twenty patients with GTCS (GTCS group) and twenty healthy volunteers (control group) were recruited for this study. On 3D PCASL, (1) GTCS patients had lower CBF in the brainstem, right cerebellum, right inferior temporal gyrus, parahippocampal gyrus, superior frontal gyrus, middle frontal gyrus, triangular part of inferior frontal gyrus, left temporal pole of superior temporal gyrus and thalamus and had higher CBF in the bilateral superior parietal gyri, precuneus, precentral gyri, postcentral gyri, and left dorsolateral superior frontal gyrus than controls. (2) The CBF of the right temporal pole of the middle temporal gyrus was negatively correlated with the duration of disease (PFDRcorrected<0.05), with a correlation coefficient r of -0.7333 and a PFDRcorrected value of 0.04. CONCLUSION Voxel-based analysis of 3D PCASL imaging can be used to sensitively detect brain perfusion differences in GTCS patients. The decrease in CBF in the right temporal pole of the middle temporal gyrus may be associated with disease onset. These findings may offer new perspectives on the pathogenesis of GTCS and the underlying pathophysiological changes associated with perfusion.
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Affiliation(s)
- Ting Li
- The First Affiliated Hospital, Jinan University, Guangzhou, People's Republic of China.,Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Shaowei Niu
- Department of Infection, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Xiang Qiu
- Department of Radiology, Integrated TCM & Western Medicine Hospital Affiliated to Chengdu University of TCM, Chengdu First People's Hospital, Chengdu, People's Republic of China
| | - Zhaohua Zhai
- Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Lin Yang
- Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Li Chen
- Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
| | - Xiao Ming Zhang
- The First Affiliated Hospital, Jinan University, Guangzhou, People's Republic of China.,Medical Imaging Key Laboratory of Sichuan Province, and Department of Radiology, Affiliated Hospital of North Sichuan Medical College, Nanchong, People's Republic of China
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Zhou X, Zhang Z, Yu L, Fan B, Wang M, Jiang B, Su Y, Li P, Zheng J. Disturbance of functional and effective connectivity of the salience network involved in attention deficits in right temporal lobe epilepsy. Epilepsy Behav 2021; 124:108308. [PMID: 34536737 DOI: 10.1016/j.yebeh.2021.108308] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/04/2021] [Accepted: 08/23/2021] [Indexed: 12/23/2022]
Abstract
The salience network (SN) acts as a switch that generates transient control signals to regulate the executive control network (ECN) and the default mode network (DMN) and has been implicated in cognitive processes. Temporal lobe epilepsy (TLE) is usually accompanied by different types of cognitive deficits, but whether it is associated with dysfunctional connectivity of the SN remains unknown. To address this, thirty-six patients with right TLE (rTLE) and thirty-six healthy controls (HCs) were recruited for the present study. All of the participants were subjected to attention network test (ANT) and resting-state functional resonance imaging (rs-fMRI) scanning. The patient group showed deficits in attention performance. Moreover, the functional connectivity (FC) and effective connectivity (EC) were analyzed based on key SN hubs (the anterior cingulate cortex (ACC) and the bilateral anterior insula (AI)). When compared with those in the HC group, the ACC showed increased FC with the left middle frontal gyrus and the left precentral gyrus, and the right AI showed decreased FC with the right precuneus and the right superior occipital gyrus in the patient group. The EC analysis revealed an increased inflow of information from the left middle temporal gyrus to the ACC and the right AI and an increased outflow of information from the bilateral AI to the left middle frontal gyrus. Furthermore, in the correlation analysis, the abnormal EC from the right AI to the left middle temporal gyrus was positively correlated with the executive control effect. These findings demonstrated aberrant modulation of the SN in rTLE, which was particularly characterized by dysfunctional connectivity between the SN and key brain regions in the DMN and ECN. Elucidation of this effect may further contribute to the comprehensive understanding of the neural mechanisms of the SN in regard to attention deficits in patients with TLE.
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Affiliation(s)
- Xia Zhou
- Department of Neurology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
| | - Zhao Zhang
- Department of Neurology, the Fifth Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Lu Yu
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Binglin Fan
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China
| | - Minli Wang
- Department of Neurology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
| | - Binjian Jiang
- Department of Neurology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
| | - Yuying Su
- Department of Neurology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
| | - Peihu Li
- Department of Neurology, the People's Hospital of Guangxi Zhuang Autonomous Region, Nanning 530021, China
| | - Jinou Zheng
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning 530021, China.
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Guo Y, Wang J, Jiao Q, Cao W, Cui D, Gao W, Qiu J, Su L, Lu G. Altered spatiotemporal consistency of corticolimbic circuitry in euthymic pediatric bipolar disorder. Brain Imaging Behav 2021; 15:1290-1299. [PMID: 32712799 DOI: 10.1007/s11682-020-00327-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Bipolar disorder (BD) is a life-threatening illness which clinically defined by an alternating pattern of depressive and manic episodes with a separated period of euthymia. It remains unknown about the consistency of temporal-spatial spontaneous brain activity in euthymic patients, especially in pediatric BD (PBD) patients.Resting-state fMRI signals of sixteen euthymic PBD patients and 16 healthy controls were processed and FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) and functional connectivity were calculated in the present study. Voxel-wised correlation between clinical and cognitive indices and FOCA in PBD was calculated.Compared with healthy subjects, euthymic PBD patients showed worse performance in tests of Stroop Color-Word Test, Digit Span Test and Trail Making Test. Euthymic PBD patients demonstrated increased FOCA in left inferior frontal gyrus, left anterior cingulate cortex and left superior frontal gyrus and decreased FOCA in right orbital frontal gyrus, bilateral precuneus, right superior occipital gyrus and bilateral superior parietal gyrus. Decreased functional connectivities were found between right orbital frontal gyrus and left amygdala, between left superior frontal gyrus and left putamen, and between left superior frontal gyrus and left insula. And increased functional connectivity was found between right superior occipital gyrus and right hippocampus. FOCA of parahippocampal gyrus was negatively correlated with the SCWT-B score in PBD patients.Abnormal spatiotemporal consistency of brain regions of corticolimbic circuitry is possible to contribute to an imbalance between emotional processing and cognitive control in euthymic PBD. The measurement of FOCA measure may provide important clues of understanding PBD.
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Affiliation(s)
- Yongxin Guo
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong Province, 271016, China
| | - Jinfeng Wang
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong Province, 271016, China
| | - Qing Jiao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong Province, 271016, China.
| | - Weifang Cao
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong Province, 271016, China
| | - Dong Cui
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong Province, 271016, China
| | - Weijia Gao
- Department of Child Psychology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang , 310003, China
| | - Jianfeng Qiu
- Department of Radiology, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, Shandong Province, 271016, China
| | - Linyan Su
- Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, 410011, Changsha, China.
| | - Guangming Lu
- Department of Medical Imaging, Jinling Hospital, Clinical School of Medical College, Nanjing University, 210002, Nanjing, China
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Zhang T, Zhang Y, Ren J, Yang C, Zhou H, Li L, Lei D, Gong Q, Zhou D, Yang T. Aberrant basal ganglia-thalamo-cortical network topology in juvenile absence epilepsy: A resting-state EEG-fMRI study. Seizure 2020; 84:78-83. [PMID: 33307464 DOI: 10.1016/j.seizure.2020.11.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Revised: 11/22/2020] [Accepted: 11/28/2020] [Indexed: 02/05/2023] Open
Abstract
PURPOSE The underlying pathophysiology of juvenile absence epilepsy (JAE) is unclear. Since cortical and subcortical brain regions are thought to be altered in genetic generalized epilepsy, the present study examined the resting-state functional network topology of the same regions in JAE. METHODS Electroencephalography and functional magnetic resonance imaging (EEG-fMRI) were performed on 18 JAE patients and 28 healthy controls (HCs). The topology of functional networks was analyzed using the graph-theoretic method. Both global and nodal network parameters were calculated, and parameters differing significantly between the two groups were correlated with clinical variables. RESULTS Both JAE patients and HCs had small-world functional network topological architectures. However, JAE patients showed higher values for the global parameters of clustering coefficient (Cp) and normalized characteristic path length (Lambda). At the nodal level, patients exhibited greater centrality at widespread cortices, including the left superior parietal gyrus, right superior temporal gyrus, right orbital part of middle frontal gyrus and bilateral supplementary motor area. Conversely, patients showed decreased nodal centrality predominantly in the limbic network, left thalamus and right caudate nucleus. Degree centrality in the right hippocampus and betweenness centrality in the right caudate nucleus positively correlated with epilepsy duration. CONCLUSION The global functional network of JAE shows small-world properties, but tends to be regular with higher segregation and lower integration. Regions in the basal ganglia-thalamo-cortical network have aberrant nodal centrality. The hippocampus and caudate nucleus may reorganize as epilepsy progresses. Our findings indicate the pathogenesis and compensatory mechanisms to seizure attacks and cognitive deficits of JAE.
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Affiliation(s)
- Tianyu Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yingying Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiechuan Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Cheng Yang
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Huanyu Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Lei Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Tianhua Yang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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Jiang S, Pei H, Huang Y, Chen Y, Liu L, Li J, He H, Yao D, Luo C. Dynamic Temporospatial Patterns of Functional Connectivity and Alterations in Idiopathic Generalized Epilepsy. Int J Neural Syst 2020; 30:2050065. [PMID: 33161788 DOI: 10.1142/s0129065720500653] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The dynamic profile of brain function has received much attention in recent years and is also a focus in the study of epilepsy. The present study aims to integrate the dynamics of temporal and spatial characteristics to provide comprehensive and novel understanding of epileptic dynamics. Resting state fMRI data were collected from eighty-three patients with idiopathic generalized epilepsy (IGE) and 87 healthy controls (HC). Specifically, we explored the temporal and spatial variation of functional connectivity density (tvFCD and svFCD) in the whole brain. Using a sliding-window approach, for a given region, the standard variation of the FCD series was calculated as the tvFCD and the variation of voxel-wise spatial distribution was calculated as the svFCD. We found primary, high-level, and sub-cortical networks demonstrated distinct tvFCD and svFCD patterns in HC. In general, the high-level networks showed the highest variation, the subcortical and primary networks showed moderate variation, and the limbic system showed the lowest variation. Relative to HC, the patients with IGE showed weaken temporal and enhanced spatial variation in the default mode network and weaken temporospatial variation in the subcortical network. Besides, enhanced temporospatial variation in sensorimotor and high-level networks was also observed in patients. The hyper-synchronization of specific brain networks was inferred to be associated with the phenomenon responsible for the intrinsic propensity of generation and propagation of epileptic activities. The disrupted dynamic characteristics of sensorimotor and high-level networks might potentially contribute to the driven motion and cognition phenotypes in patients. In all, presently provided evidence from the temporospatial variation of functional interaction shed light on the dynamics underlying neuropathological profiles of epilepsy.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Yang Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Linli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Hui He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu P. R. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, P. R. China
- High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, P. R. China
- Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu P. R. China
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Spatiotemporal consistency analysis of attention-deficit/hyperactivity disorder children. Neurosci Lett 2020; 734:135099. [DOI: 10.1016/j.neulet.2020.135099] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 05/21/2020] [Accepted: 05/25/2020] [Indexed: 11/22/2022]
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Dong L, Luo C, Liu X, Jiang S, Li F, Feng H, Li J, Gong D, Yao D. Neuroscience Information Toolbox: An Open Source Toolbox for EEG-fMRI Multimodal Fusion Analysis. Front Neuroinform 2018; 12:56. [PMID: 30197593 PMCID: PMC6117508 DOI: 10.3389/fninf.2018.00056] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Accepted: 08/10/2018] [Indexed: 11/30/2022] Open
Abstract
Recently, scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) multimodal fusion has been pursued in an effort to study human brain function and dysfunction to obtain more comprehensive information on brain activity in which the spatial and temporal resolutions are both satisfactory. However, a more flexible and easy-to-use toolbox for EEG–fMRI multimodal fusion is still lacking. In this study, we therefore developed a freely available and open-source MATLAB graphical user interface toolbox, known as the Neuroscience Information Toolbox (NIT), for EEG–fMRI multimodal fusion analysis. The NIT consists of three modules: (1) the fMRI module, which has batch fMRI preprocessing, nuisance signal removal, bandpass filtering, and calculation of resting-state measures; (2) the EEG module, which includes artifact removal, extracting EEG features (event onset, power, and amplitude), and marking interesting events; and (3) the fusion module, in which fMRI-informed EEG analysis and EEG-informed fMRI analysis are included. The NIT was designed to provide a convenient and easy-to-use toolbox for researchers, especially for novice users. The NIT can be downloaded for free at http://www.neuro.uestc.edu.cn/NIT.html, and detailed information, including the introduction of NIT, user’s manual and example data sets, can also be observed on this website. We hope that the NIT is a promising toolbox for exploring brain information in various EEG and fMRI studies.
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Affiliation(s)
- Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Xiaobo Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Hongshuo Feng
- School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Diankun Gong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.,School of Life Science and Technology, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, China
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