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      Functional and structural networks decoupling in generalized tonic–clonic seizures and its reorganization by drugs

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          Abstract

          Objective

          To investigate potential functional and structural large‐scale network disturbances in untreated patients with generalized tonic–clonic seizures (GTCS) and the effects of antiseizure drugs.

          Methods

          In this study, 41 patients with GTCS, comprising 21 untreated patients and 20 patients who received antiseizure medications (ASMs), and 29 healthy controls were recruited to construct large‐scale brain networks based on resting‐state functional magnetic resonance imaging and diffusion tensor imaging. Structural and functional connectivity and network‐level weighted correlation probability (NWCP) were further investigated to identify network features that corresponded to response to ASMs.

          Results

          Untreated patients showed more extensive enhancement of functional and structural connections than controls. Specifically, we observed abnormally enhanced connections between the default mode network (DMN) and the frontal–parietal network. In addition, treated patients showed similar functional connection strength to that of the control group. However, all patients exhibited similar structural network alterations. Moreover, the NWCP value was lower for connections within the DMN and between the DMN and other networks in the untreated patients; receiving ASMs could reverse this pattern.

          Significance

          Our study identified alterations in structural and functional connectivity in patients with GTCS. The influence of ASMs may be more noticeable within the functional network; moreover, abnormalities in both the functional and structural coupling state may be improved by ASM treatment. Therefore, the coupling state of structural and functional connectivity may be used as an indicator of the efficacy of ASMs.

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          Most cited references60

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          Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain.

          N. Tzourio-Mazoyer, B Landeau, D Papathanassiou … (2003)
          An anatomical parcellation of the spatially normalized single-subject high-resolution T1 volume provided by the Montreal Neurological Institute (MNI) (D. L. Collins et al., 1998, Trans. Med. Imag. 17, 463-468) was performed. The MNI single-subject main sulci were first delineated and further used as landmarks for the 3D definition of 45 anatomical volumes of interest (AVOI) in each hemisphere. This procedure was performed using a dedicated software which allowed a 3D following of the sulci course on the edited brain. Regions of interest were then drawn manually with the same software every 2 mm on the axial slices of the high-resolution MNI single subject. The 90 AVOI were reconstructed and assigned a label. Using this parcellation method, three procedures to perform the automated anatomical labeling of functional studies are proposed: (1) labeling of an extremum defined by a set of coordinates, (2) percentage of voxels belonging to each of the AVOI intersected by a sphere centered by a set of coordinates, and (3) percentage of voxels belonging to each of the AVOI intersected by an activated cluster. An interface with the Statistical Parametric Mapping package (SPM, J. Ashburner and K. J. Friston, 1999, Hum. Brain Mapp. 7, 254-266) is provided as a freeware to researchers of the neuroimaging community. We believe that this tool is an improvement for the macroscopical labeling of activated area compared to labeling assessed using the Talairach atlas brain in which deformations are well known. However, this tool does not alleviate the need for more sophisticated labeling strategies based on anatomical or cytoarchitectonic probabilistic maps.
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            Circos: an information aesthetic for comparative genomics.

            Martin Krzywinski, Jacqueline Schein, Inanç Birol … (2009)
            We created a visualization tool called Circos to facilitate the identification and analysis of similarities and differences arising from comparisons of genomes. Our tool is effective in displaying variation in genome structure and, generally, any other kind of positional relationships between genomic intervals. Such data are routinely produced by sequence alignments, hybridization arrays, genome mapping, and genotyping studies. Circos uses a circular ideogram layout to facilitate the display of relationships between pairs of positions by the use of ribbons, which encode the position, size, and orientation of related genomic elements. Circos is capable of displaying data as scatter, line, and histogram plots, heat maps, tiles, connectors, and text. Bitmap or vector images can be created from GFF-style data inputs and hierarchical configuration files, which can be easily generated by automated tools, making Circos suitable for rapid deployment in data analysis and reporting pipelines.
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              The organization of the human cerebral cortex estimated by intrinsic functional connectivity.

              B. Yeo, Fenna M. Krienen, Jorge Sepulcre … (2011)
              Information processing in the cerebral cortex involves interactions among distributed areas. Anatomical connectivity suggests that certain areas form local hierarchical relations such as within the visual system. Other connectivity patterns, particularly among association areas, suggest the presence of large-scale circuits without clear hierarchical relations. In this study the organization of networks in the human cerebrum was explored using resting-state functional connectivity MRI. Data from 1,000 subjects were registered using surface-based alignment. A clustering approach was employed to identify and replicate networks of functionally coupled regions across the cerebral cortex. The results revealed local networks confined to sensory and motor cortices as well as distributed networks of association regions. Within the sensory and motor cortices, functional connectivity followed topographic representations across adjacent areas. In association cortex, the connectivity patterns often showed abrupt transitions between network boundaries. Focused analyses were performed to better understand properties of network connectivity. A canonical sensory-motor pathway involving primary visual area, putative middle temporal area complex (MT+), lateral intraparietal area, and frontal eye field was analyzed to explore how interactions might arise within and between networks. Results showed that adjacent regions of the MT+ complex demonstrate differential connectivity consistent with a hierarchical pathway that spans networks. The functional connectivity of parietal and prefrontal association cortices was next explored. Distinct connectivity profiles of neighboring regions suggest they participate in distributed networks that, while showing evidence for interactions, are embedded within largely parallel, interdigitated circuits. We conclude by discussing the organization of these large-scale cerebral networks in relation to monkey anatomy and their potential evolutionary expansion in humans to support cognition.
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                Author and article information

                Contributors
                Cheng Luo:
                ORCID: https://orcid.org/0000-0003-0524-5886
                chengluo@uestc.edu.cn
                Liang Yu:
                ORCID: https://orcid.org/0000-0002-2020-1446
                18981838653@163.com
                Journal
                Journal ID (nlm-ta): Epilepsia Open
                Journal ID (iso-abbrev): Epilepsia Open
                Journal ID (doi): 10.1002/(ISSN)2470-9239
                Journal ID (publisher-id): EPI4
                Title: Epilepsia Open
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 2470-9239
                Publication date (Electronic): 27 July 2023
                Publication date Collection: September 2023
                Volume: 8
                Issue: 3 ( doiID: 10.1002/epi4.v8.3 )
                Pages: 1038-1048
                Affiliations
                [ 1 ] The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for Neuroinformation School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China
                [ 2 ] Research Unit of NeuroInformation (2019RU035) Chinese Academy of Medical Sciences Chengdu China
                [ 3 ] Neurology Department Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, The Affiliated Hospital of University of Electronic Science and Technology of China Chengdu China
                [ 4 ] Department of Neurology The First Affiliated Hospital of Hainan Medical University Haikou China
                [ 5 ] High‐Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China
                Author notes
                [*] [* ] Correspondence

                Cheng Luo and Liang Yu, University of Electronic Science and Technology of China, Second North Jianshe Road, Chengdu 610054, China.

                Email: chengluo@ 123456uestc.edu.cn and 18981838653@ 123456163.com

                Author information
                https://orcid.org/0000-0001-5202-5216
                https://orcid.org/0000-0002-7430-9639
                https://orcid.org/0000-0003-0524-5886
                https://orcid.org/0000-0002-2020-1446
                Article
                Publisher ID: EPI412781 Other ID: EPI4-0082-2022.R2
                DOI: 10.1002/epi4.12781
                PMC ID: 10472403
                PubMed ID: 37394869
                SO-VID: 3f531e88-72dd-4f8c-8a1d-2a5f0c768929
                Copyright © © 2023 The Authors. Epilepsia Open published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                Date received : 13 July 2022
                Date accepted : 27 June 2023
                Page count
                Figures: 3, Tables: 1, Pages: 11, Words: 6332
                Funding
                Funded by: Chengdu Science and Technology Bureau , doi 10.13039/501100010822;
                Award ID: 2021‐YF09‐00107‐SN
                Funded by: National Key R&D Program of China
                Award ID: 2018YFA0701400
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 62003058
                Award ID: 62201133
                Award ID: 81960249
                Award ID: 82101620
                Funded by: Project of Science and Technology Department of Hainan Province
                Award ID: ZDYF2021SHFZ095
                Funded by: Project of Science and Technology Department of Sichuan Province
                Award ID: 2021YJ0165
                Award ID: 2022NSFSC0530
                Award ID: 2022NSFSC1320
                Funded by: the CAMS Innovation Fund for Medical Sciences
                Award ID: 2019‐I2M‐5‐039
                Categories
                Subject: Original Article
                Subject: Original Articles
                Custom metadata
                source-schema-version-number 2.0
                cover-date September 2023
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.3.3 mode:remove_FC converted:01.09.2023

                Keywords: antiseizure medications,connectivity,coupling degree,epilepsy,mri
                Data availability:
                Keywords: antiseizure medications, connectivity, coupling degree, epilepsy, mri

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