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de Araújo E Silva M, Fiorin FDS, Santiago RMDM, Rodrigues AC. Brain connectivity analysis in preictal phases of seizure induced by pentylenetetrazol in rats. Brain Res 2024; 1842:149118. [PMID: 38986828 DOI: 10.1016/j.brainres.2024.149118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 06/28/2024] [Accepted: 07/06/2024] [Indexed: 07/12/2024]
Abstract
Abnormal patterns of brain connectivity characterize epilepsy. However, little is known about these patterns during the stages preceding a seizure induced by pentylenetetrazol (PTZ). To investigate brain connectivity in male Wistar rats during the preictal phase of PTZ-induced seizures (60 mg/kg), we recorded local field potentials in the primary motor (M1) cortex, the ventral anterior (VA) nucleus of the thalamus, the hippocampal CA1 area, and the dentate gyrus (DG) during the baseline period and after PTZ administration. While there were no changes in power density between the baseline and preictal periods, we observed an increase in directional functional connectivity in theta from the hippocampal formation to M1 and VA, as well as in middle gamma from DG to CA1 and from CA1 to M1, and also in slow gamma from M1 to CA1. These findings are supported by increased phase coherence between DG-M1 in theta and CA1-M1 in middle gamma, as well as enhanced phase-amplitude coupling of delta-middle gamma in M1 and delta-fast gamma in CA1. Interestingly, we also noted a slight decrease in phase synchrony between CA1 and VA in slow gamma. Together, these results demonstrate increased functional connectivity between brain regions during the PTZ-induced preictal period, with this increase being particularly driven by the hippocampal formation.
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Affiliation(s)
- Mariane de Araújo E Silva
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil
| | - Fernando da Silva Fiorin
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil.
| | - Rodrigo Marques de Melo Santiago
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil
| | - Abner Cardoso Rodrigues
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil
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2
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Guo F, Li Y, Jian Z, Cui Y, Gong W, Li A, Jing W, Xu P, Chen K, Guo D, Yao D, Xia Y. Dose-related adaptive reconstruction of DMN in isoflurane administration: a study in the rat. BMC Anesthesiol 2023; 23:224. [PMID: 37380958 PMCID: PMC10303294 DOI: 10.1186/s12871-023-02153-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Accepted: 05/26/2023] [Indexed: 06/30/2023] Open
Abstract
BACKGROUND The anesthetic states are accompanied by functional alterations. However, the dose-related adaptive alterations in the higher-order network under anesthesia, e. g. default mode network (DMN), are poorly revealed. METHODS We implanted electrodes in brain regions of the rat DMN to acquire local field potentials to investigate the perturbations produced by anesthesia. Relative power spectral density, static functional connectivity (FC), fuzzy entropy of dynamic FC, and topological features were computed from the data. RESULTS The results showed that adaptive reconstruction was induced by isoflurane, exhibiting reduced static and stable long-range FC, and altered topological features. These reconstruction patterns were in a dose-related fashion. CONCLUSION These results might impart insights into the neural network mechanisms underlying anesthesia and suggest the potential of monitoring the depth of anesthesia based on the parameters of DMN.
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Affiliation(s)
- Fengru Guo
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Yuqin Li
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Zhaoxin Jian
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Yan Cui
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Wenhui Gong
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Airui Li
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Wei Jing
- Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 4030030 China
| | - Peng Xu
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Ke Chen
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Daqing Guo
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Dezhong Yao
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
| | - Yang Xia
- Department of Neurosurgery, MOE Key Lab for Neuroinformation, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, 611731 China
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Zhang Q, Jing W, Wu S, Zhu M, Jiang J, Liu X, Yu D, Cheng L, Feng B, Wen J, Xiong F, Lu Y, Du H. Development of a synchronous recording and photo-stimulating electrode in multiple brain neurons. Front Neurosci 2023; 17:1195095. [PMID: 37383109 PMCID: PMC10293621 DOI: 10.3389/fnins.2023.1195095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/25/2023] [Indexed: 06/30/2023] Open
Abstract
The investigation of brain networks and neural circuits involves the crucial aspects of observing and modulating neurophysiological activity. Recently, opto-electrodes have emerged as an efficient tool for electrophysiological recording and optogenetic stimulation, which has greatly facilitated the analysis of neural coding. However, implantation and electrode weight control have posed significant challenges in achieving long-term and multi-regional brain recording and stimulation. To address this issue, we have developed a mold and custom-printed circuit board-based opto-electrode. We report successful opto-electrode placement and high-quality electrophysiological recordings from the default mode network (DMN) of the mouse brain. This novel opto-electrode facilitates synchronous recording and stimulation in multiple brain regions and holds promise for advancing future research on neural circuits and networks.
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Affiliation(s)
- Qingping Zhang
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Wei Jing
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Shiping Wu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Mengzheng Zhu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Jingrui Jiang
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Xiang Liu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Dian Yu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Long Cheng
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Bin Feng
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Neurobiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jianbin Wen
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Feng Xiong
- Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, National Center for Magnetic Resonance in Wuhan, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
| | - Youming Lu
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Department of Pathophysiology, School of Basic Medicine, Huazhong University of Science and Technology, Wuhan, China
| | - Huiyun Du
- Department of Physiology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
- Wuhan Center for Brain Science, Huazhong University of Science and Technology, Wuhan, China
- Hubei Key Laboratory of Drug Target Research and Pharmacodynamic Evaluation, Wuhan, China
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4
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Bencurova P, Laakso H, Salo RA, Paasonen E, Manninen E, Paasonen J, Michaeli S, Mangia S, Bares M, Brazdil M, Kubova H, Gröhn O. Infantile status epilepticus disrupts myelin development. Neurobiol Dis 2021; 162:105566. [PMID: 34838665 PMCID: PMC8845085 DOI: 10.1016/j.nbd.2021.105566] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/12/2021] [Accepted: 11/23/2021] [Indexed: 11/25/2022] Open
Abstract
Temporal lobe epilepsy (TLE) is the most prevalent type of epilepsy in adults; it often starts in infancy or early childhood. Although TLE is primarily considered to be a grey matter pathology, a growing body of evidence links this disease with white matter abnormalities. In this study, we explore the impact of TLE onset and progression in the immature brain on white matter integrity and development utilising the rat model of Li-pilocarpine-induced TLE at the 12th postnatal day (P). Diffusion tensor imaging (DTI) and Black-Gold II histology uncovered disruptions in major white matter tracks (corpus callosum, internal and external capsules, and deep cerebral white matter) spreading through the whole brain at P28. These abnormalities were mostly not present any longer at three months after TLE induction, with only limited abnormalities detectable in the external capsule and deep cerebral white matter. Relaxation Along a Fictitious Field in the rotating frame of rank 4 indicated that white matter changes observed at both timepoints, P28 and P72, are consistent with decreased myelin content. The animals affected by TLE-induced white matter abnormalities exhibited increased functional connectivity between the thalamus and medial prefrontal and somatosensory cortex in adulthood. Furthermore, histological analyses of additional animal groups at P15 and P18 showed only mild changes in white matter integrity, suggesting a gradual age-dependent impact of TLE progression. Taken together, TLE progression in the immature brain distorts white matter development with a peak around postnatal day 28, followed by substantial recovery in adulthood. This developmental delay might give rise to cognitive and behavioural comorbidities typical for early-onset TLE.
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Affiliation(s)
- Petra Bencurova
- CEITEC - Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic; Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekarska 53, 656 91 Brno, Czech Republic.
| | - Hanne Laakso
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland
| | - Raimo A Salo
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland
| | - Ekaterina Paasonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland
| | - Eppu Manninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland
| | - Jaakko Paasonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland
| | - Shalom Michaeli
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Silvia Mangia
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Martin Bares
- Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekarska 53, 656 91 Brno, Czech Republic; Department of Neurology, School of Medicine, University of Minnesota, Minneapolis, MN, United States
| | - Milan Brazdil
- CEITEC - Central European Institute of Technology, Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic; Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Pekarska 53, 656 91 Brno, Czech Republic
| | - Hana Kubova
- Academy of Sciences Czech Republic, Institute of Physiology, Department of Developmental Epileptology, Videnska 1083, 14220 Prague, Czech Republic.
| | - Olli Gröhn
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, PO Box 1627, FI-70211 Kuopio, Finland
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5
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Cui Y, Li M, Biswal B, Jing W, Zhou C, Liu H, Guo D, Xia Y, Yao D. Dynamic Configuration of Coactive Micropatterns in the Default Mode Network During Wakefulness and Sleep. Brain Connect 2021; 11:471-482. [PMID: 33403904 DOI: 10.1089/brain.2020.0827] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Background: The default mode network (DMN) is a prominent intrinsic network that is observable in many mammalian brains. However, a few studies have investigated the temporal dynamics of this network based on direct physiological recordings. Methods: Herein, we addressed this issue by characterizing the dynamics of local field potentials from the rat DMN during wakefulness and sleep with an exploratory analysis. We constructed a novel coactive micropattern (CAMP) algorithm to evaluate the configurations of rat DMN dynamics, and further revealed the relationship between DMN dynamics with different wakefulness and alertness levels. Results: From the gamma activity (40-80 Hz) in the DMN across wakefulness and sleep, three spatially stable CAMPs were detected: a common low-activity level micropattern (cDMN), an anterior high-activity level micropattern (aDMN), and a posterior high-activity level micropattern (pDMN). A dynamic balance across CAMPs emerged during wakefulness and was disrupted in sleep stages. In the slow-wave sleep (SWS) stage, cDMN became the primary activity pattern, whereas aDMN and pDMN were the major activity patterns in the rapid eye movement sleep stage. In addition, further investigation revealed phasic relationships between CAMPs and the up-down states of the slow DMN activity in the SWS stage. Conclusion: Our study revealed that the dynamic configurations of CAMPs were highly associated with different stages of wakefulness, and provided a potential three-state model to describe the DMN dynamics for wakefulness and alertness. Impact statement In the current study, a novel coactive micropattern (CAMP) method was developed to elucidate fast default mode network (DMN) dynamics during wakefulness and sleep. Our findings demonstrated that the dynamic configurations of DMN activity are specific to different wakefulness stages and provided a three-state DMN CAMP model to depict wakefulness levels, thus revealing a potentially new neurophysiological representation of alertness levels. This work could elucidate the DMN dynamics underlying different stages of wakefulness and have important implications for the theoretical understanding of the neural mechanism of wakefulness and alertness.
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Affiliation(s)
- Yan Cui
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Min Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
| | - Wei Jing
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China.,Department of Physiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Huixiao Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Daqing Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China
| | - Yang Xia
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, 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.,Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China.,School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
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6
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Hao J, Cui Y, Niu B, Yu L, Lin Y, Xia Y, Yao D, Guo D. Roles of Very Fast Ripple (500-1000[Formula: see text]Hz) in the Hippocampal Network During Status Epilepticus. Int J Neural Syst 2020; 31:2150002. [PMID: 33357153 DOI: 10.1142/s0129065721500027] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Very fast ripples (VFRs, 500-1000[Formula: see text]Hz) are considered more specific than high-frequency oscillations (80-500[Formula: see text]Hz) as biomarkers of epileptogenic zones. Although VFRs are frequent abnormal phenomena in epileptic seizures, their functional roles remain unclear. Here, we detected the VFRs in the hippocampal network and tracked their roles during status epilepticus (SE) in rats with pilocarpine-induced temporal lobe epilepsy (TLE). All regions in the hippocampal network exhibited VFRs in the baseline, preictal, ictal and postictal states, with the ictal state containing the most VFRs. Moreover, strong phase-locking couplings existed between VFRs and slow oscillations (1-12[Formula: see text]Hz) in the ictal and postictal states for all regions. Further investigation indicated that during VFRs, the build-up of slow oscillations in the ictal state began from the temporal lobe and then spread through the whole hippocampal network via two different pathways, which might be associated with the underlying propagation of epileptiform discharges in the hippocampal network. Overall, we provide a functional description of the emergence of VFRs in the hippocampal network during SE, and we also establish that VFRs may be the physiological representation of the pathological alterations in hippocampal network activity during SE in TLE.
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Affiliation(s)
- Jianmin Hao
- 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 Sichuan 611731, P. R. China
| | - Yan Cui
- 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 Sichuan 611731, P. R. China
| | - Bochao Niu
- 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 Sichuan 611731, P. R. China
| | - Liang Yu
- Department of Neurology, Sichuan Academy of Medical, Sciences and Sichuan Provincial People's Hospital, Chengdu Sichuan, P. R. China
| | - Yuhang Lin
- 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 Sichuan 611731, P. R. China
| | - Yang Xia
- 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 Sichuan 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 Sichuan 611731, P. R. China.,School of Electrical Engineering, Zhengzhou University, Zhengzhou, Henan 450001, P. R. China
| | - Daqing Guo
- 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 Sichuan 611731, P. R. China
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7
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Altered Coactive Micropattern Connectivity in the Default-Mode Network during the Sleep-Wake Cycle. Neural Plast 2020. [DOI: 10.1155/2020/8876131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The default-mode network (DMN) is believed to be associated with levels of consciousness, but how the functional connectivity (FC) of the DMN changes across different states of consciousness is still unclear. In the current work, we addressed this issue by exploring the coactive micropattern (CAMP) networks of the DMN according to the CAMPs of rat DMN activity during the sleep-wake cycle and tracking their topological alterations among different states of consciousness. Three CAMP networks were observed in DMN activity, and they displayed greater FC and higher efficiency than the original DMN structure in all states of consciousness, implying more efficient information processing in the CAMP networks. Furthermore, no significant differences in FC or network properties were found among the three CAMP networks in the waking state. However, the three networks were distinct in their characteristics in two sleep states, indicating that different CAMP networks played specific roles in distinct sleep states. In addition, we found that the changes in the FC and network properties of the CAMP networks were similar to those in the original DMN structure, suggesting intrinsic effects of various states of consciousness on DMN dynamics. Our findings revealed three underlying CAMP networks within the DMN dynamics and deepened the current knowledge concerning FC alterations in the DMN during conscious changes in the sleep-wake cycle.
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8
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Cui Y, Liu J, Luo Y, He S, Xia Y, Zhang Y, Yao D, Guo D. Aberrant Connectivity During Pilocarpine-Induced Status Epilepticus. Int J Neural Syst 2019; 30:1950029. [PMID: 31847633 DOI: 10.1142/s0129065719500291] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Status epilepticus (SE) is a common, life-threatening neurological disorder that may lead to permanent brain damage. In rodent models, SE is an acute phase of seizures that could be reproduced by injecting with pilocarpine and then induce chronic temporal lobe epilepsy (TLE) seizures. However, how SE disrupts brain activity, especially communications among brain regions, is still unclear. In this study, we aimed to identify the characteristic abnormalities of network connections among the frontal cortex, hippocampus and thalamus during the SE episodes in a pilocarpine model with functional and effective connectivity measurements. We showed that the coherence connectivity among these regions increased significantly during the SE episodes in almost all frequency bands (except the alpha band) and that the frequency band with enhanced connections was specific to different stages of SE episodes. Moreover, with the effective analysis, we revealed a closed neural circuit of bidirectional effective interactions between the frontal regions and the hippocampus and thalamus in both ictal and post-ictal stages, implying aberrant enhancement of communication across these brain regions during the SE episodes. Furthermore, an effective connection from the hippocampus to the thalamus was detected in the delta band during the pre-ictal stage, which shifted in an inverse direction during the ictal stage in the theta band and in the theta, alpha, beta and low-gamma bands during the post-ictal stage. This specificity of the effective connection between the hippocampus and thalamus illustrated that the hippocampal structure is critical for the initiation of SE discharges, while the thalamus is important for the propagation of SE discharges. Overall, our results demonstrated enhanced interaction among the frontal cortex, hippocampus and thalamus during the SE episodes and suggested the modes of information flow across these structures for the initiation and propagation of SE discharges. These findings may reveal an underlying mechanism of aberrant network communication during pilocarpine-induced SE discharges and deepen our knowledge of TLE seizures.
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Affiliation(s)
- Yan Cui
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
| | - Jie Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
| | - Yan Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
| | - Shan He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
| | - Yang Xia
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
| | - Yangsong Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. 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, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
| | - Daqing Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
- Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, P. R. China
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