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Feng T, Yang Y, Wang Y, Wei PH, Fan X, Zhang H, An Y, Wang T, Huang Y, Chen S, Piao Y, Xiao F, Duncan JS, Shan Y, Zhao G. Delineating structural and metabolic abnormalities in amygdala and hippocampal subfields for different seizure-onset patterns via stereotactic electroencephalography. CNS Neurosci Ther 2024; 30:e14905. [PMID: 39248455 PMCID: PMC11382356 DOI: 10.1111/cns.14905] [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: 05/01/2024] [Revised: 07/06/2024] [Accepted: 07/23/2024] [Indexed: 09/10/2024] Open
Abstract
AIMS We aimed to investigate mesial temporal lobe abnormalities in mesial temporal lobe epilepsy (MTLE) patients with hypersynchronous (HYP) and low-voltage fast rhythms (LVF) onset identified by stereotactic electroencephalography (SEEG) and evaluate their diagnostic and prognostic value. METHODS Fifty-one MTLE patients were categorized as HYP or LVF by SEEG. High-resolution MRI volume-based analysis and 18F-FDG-PET standard uptake values of hippocampal and amygdala subfields were quantified and compared with 57 matched controls. Further analyses were conducted to delineate the distinct pathological characteristics differentiating the two groups. Diagnostic and prognostic prediction performance of these biomarkers were assessed using receiver operating characteristic curves. RESULTS LVF-onset individuals demonstrated ipsilateral amygdala enlargement (p = 0.048) and contralateral hippocampus hypermetabolism (p = 0.042), pathological results often accompany abnormalities in the temporal lobe cortex, while HYP-onset subjects had significant atrophy (p < 0.001) and hypometabolism (p = 0.013) in ipsilateral hippocampus and its subfields, as well as amygdala atrophy (p < 0.001), pathological results are highly correlated with hippocampal sclerosis. Severe fimbria atrophy was observed in cases of HYP-onset MTLE with poor prognosis (AUC = 0.874). CONCLUSION Individuals with different seizure-onset patterns display specific morphological and metabolic abnormalities in the amygdala and hippocampus. Identifying these subfield abnormalities can improve diagnostic and prognostic precision, guiding surgical strategies for MTLE.
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Affiliation(s)
- Tao Feng
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Yanfeng Yang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Yihe Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Peng-Hu Wei
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Xiaotong Fan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Huaqiang Zhang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Yang An
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Tianren Wang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Yuda Huang
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Sichang Chen
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Yueshan Piao
- China International Neuroscience Institute (CHINA-INI), Beijing, China
- Department of Pathology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Fenglai Xiao
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - John S Duncan
- Department of Clinical & Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
- MRI Unit, Chalfont Centre for Epilepsy, Chalfont Saint Peter, UK
| | - Yongzhi Shan
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
- China International Neuroscience Institute (CHINA-INI), Beijing, China
- Institute for Brain Disorder, Beijing, China
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Qin L, Pan L, Chen Z, Zhou Q, Zhou X, Zheng J. Connectome-based prediction of cognitive performance in patients with temporal lobe epilepsy. Neuroreport 2024; 35:734-743. [PMID: 38829953 DOI: 10.1097/wnr.0000000000002064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/05/2024]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) patients often exhibit varying degrees of cognitive impairments. This study aims to predict cognitive performance in TLE patients by applying a connectome-based predictive model (CPM) to whole-brain resting-state functional connectivity (RSFC) data. METHODS A CPM was established and leave-one-out cross-validation was employed to decode the cognitive performance of patients with TLE based on the whole-brain RSFC. RESULTS Our findings indicate that cognitive performance in TLE can be predicted through the internal and network connections of the parietal lobe, limbic lobe, and cerebellum systems. These systems play crucial roles in cognitive control, emotion processing, and social perception and communication, respectively. In the subgroup analysis, CPM successfully predicted TLE patients with and without focal to bilateral tonic-clonic seizures (FBCTS). Additionally, significant differences were noted between the two TLE patient groups and the normal control group. CONCLUSION This data-driven approach provides evidence for the potential of predicting brain features based on the inherent resting-state brain network organization. Our study offers an initial step towards an individualized prediction of cognitive performance in TLE patients, which may be beneficial for diagnosis, prognosis, and treatment planning.
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Affiliation(s)
- Lu Qin
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Liya Pan
- Department of Neurology, The Fourth Affiliated Hospital of Guangxi Medical University/Liuzhou Workers' hospital, Liuzhou, China
| | - Zirong Chen
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Qin Zhou
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Jinou Zheng
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning
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3
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Foss KD, Billhymer AC. Magnetic resonance imaging in canine idiopathic epilepsy: a mini-review. Front Vet Sci 2024; 11:1427403. [PMID: 39021411 PMCID: PMC11251927 DOI: 10.3389/fvets.2024.1427403] [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: 05/03/2024] [Accepted: 06/19/2024] [Indexed: 07/20/2024] Open
Abstract
Magnetic resonance imaging (MRI) in an integral part of the diagnostic workup in canines with idiopathic epilepsy (IE). While highly sensitive and specific in identifying structural lesions, conventional MRI is unable to detect changes at the microscopic level. Utilizing more advanced neuroimaging techniques may provide further information on changes at the neuronal level in the brain of canines with IE, thus providing crucial information on the pathogenesis of canine epilepsy. Additionally, earlier detection of these changes may aid clinicians in the development of improved and targeted therapies. Advances in MRI techniques are being developed which can assess metabolic, cellular, architectural, and functional alterations; as well alterations in neuronal tissue mechanical properties, some of which are currently being applied in research on canine IE. This mini-review focuses on novel MRI techniques being utilized to better understand canine epilepsy, which include magnetic resonance spectroscopy, diffusion-weighted imaging, diffusion tensor imaging, perfusion-weighted imaging, voxel based morphometry, and functional MRI; as well as techniques applied in human medicine and their potential use in veterinary species.
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Affiliation(s)
- Kari D. Foss
- Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois Urbana-Champaign, Urbana, IL, United States
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Huo Z, Chen Z, Zhang R, Xu J, Feng T. The functional connectivity between right parahippocampal gyrus and precuneus underlying the association between reward sensitivity and procrastination. Cortex 2024; 171:153-164. [PMID: 38000138 DOI: 10.1016/j.cortex.2023.10.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 09/18/2023] [Accepted: 10/12/2023] [Indexed: 11/26/2023]
Abstract
Procrastination has adverse effects on personal growth and social development. Behavior research has found reward sensitivity is positively correlated with procrastination. However, it remains unclear that the neural substrates underlie the relationship between reward sensitivity and procrastination. To address this issue, the present study used voxel-based morphometry (VBM) and resting-state functional connectivity (RSFC) analyses to investigate the neural substrates underlying the association with reward sensitivity and procrastination in two independent samples (N1 = 388, N2 = 330). In Sample 1, the behavioral result indicated reward sensitivity was positively correlated with procrastination. Moreover, the VBM analysis showed that reward sensitivity was positively associated with the gray matter volume (GMV) of the right parahippocampal gyrus. Furthermore, the RSFC result found reward sensitivity was negatively associated with the functional connectivity of the right parahippocampal gyrus-precuneus. Crucially, the mediation analysis revealed that functional connectivity of the right parahippocampal gyrus-precuneus mediated the relationship between reward sensitivity and procrastination. To verify the robustness of the results, confirmatory analysis was carried out in Sample 2. The results of Sample 1 (i.e., the behavioral, VBM, RSFC, and mediation results) can be verified in Sample 2. In brief, these findings suggested that the functional connectivity of the right parahippocampal gyrus-precuneus involved in reward impulsive control could modulate the relationship between reward sensitivity and procrastination, which is the first to reveal the neural underpinning of the association between reward sensitivity and procrastination.
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Affiliation(s)
- Zhenzhen Huo
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Zhiyi Chen
- Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China; Experimental Research Center for Medical and Psychological Science (ERC-MPS), School of Psychology, Army Medical University, China
| | - Rong Zhang
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Junye Xu
- Faculty of Psychology, Southwest University, Chongqing, China
| | - Tingyong Feng
- Faculty of Psychology, Southwest University, Chongqing, China; Key Laboratory of Cognition and Personality, Ministry of Education, Chongqing, China.
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Yu H, Kim W, Park DK, Phi JH, Lim BC, Chae JH, Kim SK, Kim KJ, Provenzano FA, Khodagholy D, Gelinas JN. Interaction of interictal epileptiform activity with sleep spindles is associated with cognitive deficits and adverse surgical outcome in pediatric focal epilepsy. Epilepsia 2024; 65:190-203. [PMID: 37983643 PMCID: PMC10873110 DOI: 10.1111/epi.17810] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 10/20/2023] [Accepted: 10/20/2023] [Indexed: 11/22/2023]
Abstract
OBJECTIVE Temporal coordination between oscillations enables intercortical communication and is implicated in cognition. Focal epileptic activity can affect distributed neural networks and interfere with these interactions. Refractory pediatric epilepsies are often accompanied by substantial cognitive comorbidity, but mechanisms and predictors remain mostly unknown. Here, we investigate oscillatory coupling across large-scale networks in the developing brain. METHODS We analyzed large-scale intracranial electroencephalographic recordings in children with medically refractory epilepsy undergoing presurgical workup (n = 25, aged 3-21 years). Interictal epileptiform discharges (IEDs), pathologic high-frequency oscillations (HFOs), and sleep spindles were detected. Spatiotemporal metrics of oscillatory coupling were determined and correlated with age, cognitive function, and postsurgical outcome. RESULTS Children with epilepsy demonstrated significant temporal coupling of both IEDs and HFOs to sleep spindles in discrete brain regions. HFOs were associated with stronger coupling patterns than IEDs. These interactions involved tissue beyond the clinically identified epileptogenic zone and were ubiquitous across cortical regions. Increased spatial extent of coupling was most prominent in older children. Poor neurocognitive function was significantly correlated with high IED-spindle coupling strength and spatial extent; children with strong pathologic interactions additionally had decreased likelihood of postoperative seizure freedom. SIGNIFICANCE Our findings identify pathologic large-scale oscillatory coupling patterns in the immature brain. These results suggest that such intercortical interactions could predict risk for adverse neurocognitive and surgical outcomes, with the potential to serve as novel therapeutic targets to restore physiologic development.
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Affiliation(s)
- Han Yu
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Woojoong Kim
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - David K. Park
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Ji Hoon Phi
- Division of Pediatric Neurosurgery, Department of Neurosurgery, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Byung Chan Lim
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Jong-Hee Chae
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Seung-Ki Kim
- Division of Pediatric Neurosurgery, Department of Neurosurgery, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Ki Joong Kim
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | | | - Dion Khodagholy
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Jennifer N. Gelinas
- Departments of Neurology, Columbia University, New York, NY, USA
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
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6
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Guo Z, Mo J, Zhang J, Hu W, Zhang C, Wang X, Zhao B, Zhang K. Altered Metabolic Networks in Mesial Temporal Lobe Epilepsy with Focal to Bilateral Seizures. Brain Sci 2023; 13:1239. [PMID: 37759840 PMCID: PMC10526398 DOI: 10.3390/brainsci13091239] [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: 06/30/2023] [Revised: 08/23/2023] [Accepted: 08/24/2023] [Indexed: 09/29/2023] Open
Abstract
This study was designed to identify whether the metabolic network changes in mesial temporal lobe epilepsy (MTLE) patients with focal to bilateral tonic-clonic seizures (FBTCS) differ from changes in patients without FBTCS. This retrospective analysis enrolled 30 healthy controls and 54 total MTLE patients, of whom 27 had FBTCS. Fluorodeoxyglucose positron emission tomography (FDG-PET) data and graph theoretical analyses were used to examine metabolic connectivity. The differences in metabolic networks between the three groups were compared. Significant changes in both local and global network topology were evident in FBTCS+ patients as compared to healthy controls, with a lower assortative coefficient and altered betweenness centrality in 15 brain regions. While global network measures did not differ significantly when comparing FBTCS- patients to healthy controls, alterations in betweenness centrality were evident in 13 brain regions. Significantly altered betweenness centrality was also observed in four brain regions when comparing patients with and without FBTCS. The study revealed greater metabolic network abnormalities in MTLE patients with FBTCS as compared to FBTCS- patients, indicating the existence of distinct epileptogenic networks. These findings can provide insight into the pathophysiological basis of FBTCS.
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Affiliation(s)
- Zhihao Guo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; (Z.G.); (J.M.); (J.Z.); (W.H.); (C.Z.); (X.W.); (B.Z.)
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
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Rijal S, Corona L, Perry MS, Tamilia E, Madsen JR, Stone SSD, Bolton J, Pearl PL, Papadelis C. Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy. Sci Rep 2023; 13:9622. [PMID: 37316544 PMCID: PMC10267141 DOI: 10.1038/s41598-023-36551-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 06/06/2023] [Indexed: 06/16/2023] Open
Abstract
Normal brain functioning emerges from a complex interplay among regions forming networks. In epilepsy, these networks are disrupted causing seizures. Highly connected nodes in these networks are epilepsy surgery targets. Here, we assess whether functional connectivity (FC) using intracranial electroencephalography can quantify brain regions epileptogenicity and predict surgical outcome in children with drug resistant epilepsy (DRE). We computed FC between electrodes on different states (i.e. interictal without spikes, interictal with spikes, pre-ictal, ictal, and post-ictal) and frequency bands. We then estimated the electrodes' nodal strength. We compared nodal strength between states, inside and outside resection for good- (n = 22, Engel I) and poor-outcome (n = 9, Engel II-IV) patients, respectively, and tested their utility to predict the epileptogenic zone and outcome. We observed a hierarchical epileptogenic organization among states for nodal strength: lower FC during interictal and pre-ictal states followed by higher FC during ictal and post-ictal states (p < 0.05). We further observed higher FC inside resection (p < 0.05) for good-outcome patients on different states and bands, and no differences for poor-outcome patients. Resection of nodes with high FC was predictive of outcome (positive and negative predictive values: 47-100%). Our findings suggest that FC can discriminate epileptogenic states and predict outcome in patients with DRE.
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Affiliation(s)
- Sakar Rijal
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children's Health Care System, 1500 Cooper St., Fort Worth, TX, 76104, USA
- Department of Bioengineering, The University of Texas at Arlington, Arlington, TX, 76010, USA
| | - Ludovica Corona
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children's Health Care System, 1500 Cooper St., Fort Worth, TX, 76104, USA
- Department of Bioengineering, The University of Texas at Arlington, Arlington, TX, 76010, USA
| | - M Scott Perry
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children's Health Care System, 1500 Cooper St., Fort Worth, TX, 76104, USA
| | - Eleonora Tamilia
- Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Joseph R Madsen
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Scellig S D Stone
- Division of Epilepsy Surgery, Department of Neurosurgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Jeffrey Bolton
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Phillip L Pearl
- Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Christos Papadelis
- Jane and John Justin Institute for Mind Health Neurosciences Center, Cook Children's Health Care System, 1500 Cooper St., Fort Worth, TX, 76104, USA.
- Department of Bioengineering, The University of Texas at Arlington, Arlington, TX, 76010, USA.
- School of Medicine, Texas Christian University, Fort Worth, TX, 76129, USA.
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Wang M, Cheng X, Shi Q, Xu B, Hou X, Zhao H, Gui Q, Wu G, Dong X, Xu Q, Shen M, Cheng Q, Xue S, Feng H, Ding Z. Brain diffusion tensor imaging reveals altered connections and networks in epilepsy patients. Front Hum Neurosci 2023; 17:1142408. [PMID: 37033907 PMCID: PMC10073437 DOI: 10.3389/fnhum.2023.1142408] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 02/28/2023] [Indexed: 04/11/2023] Open
Abstract
Introduction Accumulating evidence shows that epilepsy is a disease caused by brain network dysfunction. This study explored changes in brain network structure in epilepsy patients based on graph analysis of diffusion tensor imaging data. Methods The brain structure networks of 42 healthy control individuals and 26 epilepsy patients were constructed. Using graph theory analysis, global and local network topology parameters of the brain structure network were calculated, and changes in global and local characteristics of the brain network in epilepsy patients were quantitatively analyzed. Results Compared with the healthy control group, the epilepsy patient group showed lower global efficiency, local efficiency, clustering coefficient, and a longer shortest path length. Both healthy control individuals and epilepsy patients showed small-world attributes, with no significant difference between groups. The epilepsy patient group showed lower nodal local efficiency and nodal clustering coefficient in the right olfactory cortex and right rectus and lower nodal degree centrality in the right olfactory cortex and the left paracentral lobular compared with the healthy control group. In addition, the epilepsy patient group showed a smaller fiber number of edges in specific regions of the frontal lobe, temporal lobe, and default mode network, indicating reduced connection strength. Discussion Epilepsy patients exhibited lower global and local brain network properties as well as reduced white matter fiber connectivity in key brain regions. These findings further support the idea that epilepsy is a brain network disorder.
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Affiliation(s)
- Meixia Wang
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoyu Cheng
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Qianru Shi
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Bo Xu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaoxia Hou
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Huimin Zhao
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qian Gui
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Guanhui Wu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Xiaofeng Dong
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qinrong Xu
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Mingqiang Shen
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Qingzhang Cheng
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Shouru Xue
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hongxuan Feng
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
- *Correspondence: Hongxuan Feng,
| | - Zhiliang Ding
- Department of Neurology, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
- Zhiliang Ding,
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Altered Resting State Networks Before and After Temporal Lobe Epilepsy Surgery. Brain Topogr 2022; 35:692-701. [PMID: 36074203 DOI: 10.1007/s10548-022-00912-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 08/27/2022] [Indexed: 11/02/2022]
Abstract
OBJECTIVES To explore the resting state networks (RSNs) alterations in patients with unilateral mesial temporal lobe epilepsy (mTLE) before and after successful surgery. METHODS Resting-state functional MRI and T1-weighted structural MRI were obtained in 37 mTLE patients who achieved seizure freedom after anterior temporal lobectomy. Patients were scanned before surgery and at two years after surgery. Twenty-eight age- and sex-matched healthy controls were scanned once. Functional connectivity (FC) changes within and between ten common RSNs before and after surgery, and FC changes between hippocampus and RSNs were explored. RESULTS Before surgery, decreased FC was found within visual network and basal ganglia network, while after surgery, FC within basal ganglia network further decreased but FC within sensorimotor network and dorsal attention network increased. Before surgery, between-network FC related to basal ganglia network, visual network and dorsal attention network decreased, while between-network FC related to default mode network increased. After surgery, between-network FC related to visual network and dorsal attention network significantly increased. In addition, before surgery, ipsilateral hippocampus showed decreased FC with visual network, basal ganglia network, sensorimotor network, default mode network and frontoparietal network, while contralateral rostral hippocampus showed increased FC with salience network. After surgery, no obvious FC changes were found between contralateral hippocampus and these RSNs. CONCLUSION MTLE patients showed significant RSNs alterations before and after surgery. Basal ganglia network showed progressive decline in functional connectivity. Successful surgery may lead to RSNs reorganization. These results provide preliminary evidence for postoperative functional remodeling at whole-brain-network level.
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Aslam AR, Hafeez N, Heidari H, Altaf MAB. Channels and Features Identification: A Review and a Machine-Learning Based Model With Large Scale Feature Extraction for Emotions and ASD Classification. Front Neurosci 2022; 16:844851. [PMID: 35937896 PMCID: PMC9355483 DOI: 10.3389/fnins.2022.844851] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
Autism Spectrum Disorder (ASD) is characterized by impairments in social and cognitive skills, emotional disorders, anxiety, and depression. The prolonged conventional ASD diagnosis raises the sheer need for early meaningful intervention. Recently different works have proposed potential for ASD diagnosis and intervention through emotions prediction using deep neural networks (DNN) and machine learning algorithms. However, these systems lack an extensive large-scale feature extraction (LSFE) analysis through multiple benchmark data sets. LSFE analysis is required to identify and utilize the most relevant features and channels for emotion recognition and ASD prediction. Considering these challenges, for the first time, we have analyzed and evaluated an extensive feature set to select the optimal features using LSFE and feature selection algorithms (FSA). A set of up to eight most suitable channels was identified using different best-case FSA. The subject-wise importance of channels and features is also identified. The proposed method provides the best-case accuracies, precision, and recall of 95, 92, and 90%, respectively, for emotions prediction using a linear support vector machine (LSVM) classifier. It also provides the best-case accuracy, precision, and recall of 100% for ASD classification. This work utilized the largest number of benchmark data sets (5) and subjects (99) for validation reported till now in the literature. The LSVM classification algorithm proposed and utilized in this work has significantly lower complexity than the DNN, convolutional neural network (CNN), Naïve Bayes, and dynamic graph CNN used in recent ASD and emotion prediction systems.
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Affiliation(s)
- Abdul Rehman Aslam
- Department of Electrical Engineering, Lahore University of Management Sciences, Lahore, Pakistan
- James Watt School of Engineering, University of Glasgow, Glasgow, United Kingdom
- Department of Computer Engineering, University of Engineering and Technology-Taxila, Taxila, Pakistan
- *Correspondence: Abdul Rehman Aslam
| | - Nauman Hafeez
- Institute of Environment, Health and Societies, Brunel University, London, United Kingdom
| | - Hadi Heidari
- James Watt School of Engineering, University of Glasgow, Glasgow, United Kingdom
| | - Muhammad Awais Bin Altaf
- Department of Electrical Engineering, Lahore University of Management Sciences, Lahore, Pakistan
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11
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Li R, Deng C, Wang X, Zou T, Biswal B, Guo D, Xiao B, Zhang X, Cheng JL, Liu D, Yang M, Chen H, Wu Q, Feng L. Interictal dynamic network transitions in mesial temporal lobe epilepsy. Epilepsia 2022; 63:2242-2255. [PMID: 35699346 DOI: 10.1111/epi.17325] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/09/2022] [Accepted: 06/10/2022] [Indexed: 12/21/2022]
Abstract
OBJECTIVE To reveal the possible routine of brain network dynamic alterations in patients with mesial temporal lobe epilepsy (mTLE) and to establish a predicted model of seizure recurrence during interictal periods. METHODS Seventy-nine unilateral mTLE patients with hippocampal sclerosis and 97 healthy controls from two centers were retrospectively enrolled. Dynamic brain configuration analyses were performed with resting-state functional magnetic resonance imaging (MRI) data to quantify the functional stability over time and the dynamic interactions between brain regions. Relationships between seizure frequency and ipsilateral hippocampal module allegiance were evaluated using a machine learning predictive model. RESULTS Compared to the healthy controls, patients with mTLE displayed an overall higher dynamic network, switching mainly in the epileptogenic regions (false discovery rate [FDR] corrected p-FDR < .05). Moreover, the dynamic network configuration in mTLE was characterized by decreased recruitment (intra-network communication), and increased integration (inter-network communication) among hippocampal systems and large-scale higher-order brain networks (p-FDR < .05). We further found that the dynamic interactions between the hippocampal system and the default-mode network (DMN) or control networks exhibited an opposite distribution pattern (p-FDR < .05). Strikingly, we showed that there was a robust association between predicted seizure frequency based on the ipsilateral hippocampal-DMN dynamics model and actual seizure frequency (p-perm < .001). SIGNIFICANCE These findings suggest that the interictal brain of mTLE is characterized by dynamical shifts toward unstable state. Our study provides novel insights into the brain dynamic network alterations and supports the potential use of DMN dynamic parameters as candidate neuroimaging markers in monitoring the seizure frequency clinically during interictal periods.
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Affiliation(s)
- Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Chijun Deng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xuyang Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ting Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Bharat Biswal
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.,Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA
| | - Danni Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jing Liang Cheng
- Department of Magnetic Resonance, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ding Liu
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Mi Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Qian Wu
- Department of Neurology, First Affiliated Hospital, Kunming Medical University, Kunming, China
| | - Li Feng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
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12
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Ranasinghe KG, Kudo K, Hinkley L, Beagle A, Lerner H, Mizuiri D, Findlay A, Miller BL, Kramer JH, Gorno-Tempini ML, Rabinovici GD, Rankin KP, Garcia PA, Kirsch HE, Vossel K, Nagarajan SS. Neuronal synchrony abnormalities associated with subclinical epileptiform activity in early-onset Alzheimer's disease. Brain 2022; 145:744-753. [PMID: 34919638 PMCID: PMC9630715 DOI: 10.1093/brain/awab442] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 09/27/2021] [Accepted: 11/09/2021] [Indexed: 11/12/2022] Open
Abstract
Since the first demonstrations of network hyperexcitability in scientific models of Alzheimer's disease, a growing body of clinical studies have identified subclinical epileptiform activity and associated cognitive decline in patients with Alzheimer's disease. An obvious problem presented in these studies is lack of sensitive measures to detect and quantify network hyperexcitability in human subjects. In this study we examined whether altered neuronal synchrony can be a surrogate marker to quantify network hyperexcitability in patients with Alzheimer's disease. Using magnetoencephalography (MEG) at rest, we studied 30 Alzheimer's disease patients without subclinical epileptiform activity, 20 Alzheimer's disease patients with subclinical epileptiform activity and 35 age-matched controls. Presence of subclinical epileptiform activity was assessed in patients with Alzheimer's disease by long-term video-EEG and a 1-h resting MEG with simultaneous EEG. Using the resting-state source-space reconstructed MEG signal, in patients and controls we computed the global imaginary coherence in alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillatory frequencies. We found that Alzheimer's disease patients with subclinical epileptiform activity have greater reductions in alpha imaginary coherence and greater enhancements in delta-theta imaginary coherence than Alzheimer's disease patients without subclinical epileptiform activity, and that these changes can distinguish between Alzheimer's disease patients with subclinical epileptiform activity and Alzheimer's disease patients without subclinical epileptiform activity with high accuracy. Finally, a principal component regression analysis showed that the variance of frequency-specific neuronal synchrony predicts longitudinal changes in Mini-Mental State Examination in patients and controls. Our results demonstrate that quantitative neurophysiological measures are sensitive biomarkers of network hyperexcitability and can be used to improve diagnosis and to select appropriate patients for the right therapy in the next-generation clinical trials. The current results provide an integrative framework for investigating network hyperexcitability and network dysfunction together with cognitive and clinical correlates in patients with Alzheimer's disease.
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Affiliation(s)
- Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
- Medical Imaging Business Center, Ricoh Company, Ltd, Kanazawa 920-0177, Japan
| | - Leighton Hinkley
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Alexander Beagle
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Hannah Lerner
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Danielle Mizuiri
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Anne Findlay
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Katherine P Rankin
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Paul A Garcia
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Heidi E Kirsch
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
- Epilepsy Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Keith Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
- Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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13
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Ballistocardiogram artifact removal in simultaneous EEG-fMRI using generative adversarial network. J Neurosci Methods 2022; 371:109498. [DOI: 10.1016/j.jneumeth.2022.109498] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 01/20/2022] [Accepted: 02/08/2022] [Indexed: 11/18/2022]
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14
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Wang K, Zhang X, Song C, Ma K, Bai M, Zheng R, Wei Y, Chen J, Cheng J, Zhang Y, Han S. Decreased Intrinsic Neural Timescales in Mesial Temporal Lobe Epilepsy. Front Hum Neurosci 2021; 15:772365. [PMID: 34955790 PMCID: PMC8693765 DOI: 10.3389/fnhum.2021.772365] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 11/16/2021] [Indexed: 01/02/2023] Open
Abstract
It is well established that epilepsy is characterized by the destruction of the information capacity of brain network and the interference with information processing in regions outside the epileptogenic focus. However, the potential mechanism remains poorly understood. In the current study, we applied a recently proposed approach on the basis of resting-state fMRI data to measure altered local neural dynamics in mesial temporal lobe epilepsy (mTLE), which represents how long neural information is stored in a local brain area and reflect an ability of information integration. Using resting-state-fMRI data recorded from 36 subjects with mTLE and 36 healthy controls, we calculated the intrinsic neural timescales (INT) of neural signals by summing the positive magnitude of the autocorrelation of the resting-state brain activity. Compared to healthy controls, the INT values were significantly lower in patients in the right orbitofrontal cortices, right insula, and right posterior lobe of cerebellum. Whereas, we observed no statistically significant changes between patients with long- and short-term epilepsy duration or between left-mTLE and right-mTLE. Our study provides distinct insight into the brain abnormalities of mTLE from the perspective of the dynamics of the brain activity, highlighting the significant role of intrinsic timescale in understanding neurophysiological mechanisms. And we postulate that altered intrinsic timescales of neural signals in specific cortical brain areas may be the neurodynamic basis of cognitive impairment and emotional comorbidities in mTLE patients.
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Affiliation(s)
- Kefan Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Chengru Song
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Keran Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Man Bai
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingli Chen
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.,Key Laboratory for Functional Magnetic Resonance Imaging and Molecular Imaging of Henan Province, Zhengzhou, China.,Engineering Technology Research Center for Detection and Application of Brain Function of Henan Province, Zhengzhou, China.,Engineering Research Center of Medical Imaging Intelligent Diagnosis and Treatment of Henan Province, Zhengzhou, China.,Key Laboratory of Magnetic Resonance and Brain Function of Henan Province, Zhengzhou, China.,Key Laboratory of Brain Function and Cognitive Magnetic Resonance Imaging of Zhengzhou, Zhengzhou, China.,Key Laboratory of Imaging Intelligence Research Medicine of Henan Province, Zhengzhou, China
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15
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Mirandola L, Ballotta D, Talami F, Giovannini G, Pavesi G, Vaudano AE, Meletti S. Temporal Lobe Spikes Affect Distant Intrinsic Connectivity Networks. Front Neurol 2021; 12:746468. [PMID: 34975714 PMCID: PMC8718871 DOI: 10.3389/fneur.2021.746468] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/22/2021] [Indexed: 11/22/2022] Open
Abstract
Objective: To evaluate local and distant blood oxygen level dependent (BOLD) signal changes related to interictal epileptiform discharges (IED) in drug-resistant temporal lobe epilepsy (TLE). Methods: Thirty-three TLE patients undergoing EEG–functional Magnetic Resonance Imaging (fMRI) as part of the presurgical workup were consecutively enrolled. First, a single-subject spike-related analysis was performed: (a) to verify the BOLD concordance with the presumed Epileptogenic Zone (EZ); and (b) to investigate the Intrinsic Connectivity Networks (ICN) involvement. Then, a group analysis was performed to search for common BOLD changes in TLE. Results: Interictal epileptiform discharges were recorded in 25 patients and in 19 (58%), a BOLD response was obtained at the single-subject level. In 42% of the cases, BOLD changes were observed in the temporal lobe, although only one patient had a pure concordant finding, with a single fMRI cluster overlapping (and limited to) the EZ identified by anatomo-electro-clinical correlations. In the remaining 58% of the cases, BOLD responses were localized outside the temporal lobe and the presumed EZ. In every patient, with a spike-related fMRI map, at least one ICN appeared to be involved. Four main ICNs were preferentially involved, namely, motor, visual, auditory/motor speech, and the default mode network. At the single-subject level, EEG–fMRI proved to have high specificity (above 65%) in detecting engagement of an ICN and the corresponding ictal/postictal symptom, and good positive predictive value (above 67%) in all networks except the visual one. Finally, in the group analysis of BOLD changes related to IED revealed common activations at the right precentral gyrus, supplementary motor area, and middle cingulate gyrus. Significance: Interictal temporal spikes affect several distant extra-temporal areas, and specifically the motor/premotor cortex. EEG–fMRI in patients with TLE eligible for surgery is recommended not for strictly localizing purposes rather it might be useful to investigate ICNs alterations at the single-subject level.
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Affiliation(s)
- Laura Mirandola
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, “San Giovanni Bosco” Hospital, Torino, Italy
- *Correspondence: Laura Mirandola ; ; orcid.org/0000-0002-1626-2932
| | - Daniela Ballotta
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Francesca Talami
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
| | - Giada Giovannini
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
- PhD Program in Clinical and Experimental Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Giacomo Pavesi
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurosurgery Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic, and Neural Sciences, Center for Neuroscience and Neurotechnology, University of Modena and Reggio Emilia, Modena, Italy
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, Ospedale Civile Baggiovara (OCB) Hospital, Modena, Italy
- Stefano Meletti ; orcid.org/0000-0003-0334-539X
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16
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Integrating Optimized Multiscale Entropy Model with Machine Learning for the Localization of Epileptogenic Hemisphere in Temporal Lobe Epilepsy Using Resting-State fMRI. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:1834123. [PMID: 34745491 PMCID: PMC8566056 DOI: 10.1155/2021/1834123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 09/20/2021] [Accepted: 09/28/2021] [Indexed: 11/17/2022]
Abstract
The bottleneck associated with the validation of the parameters of the entropy model has limited the application of this model to modern functional imaging technologies such as the resting-state functional magnetic resonance imaging (rfMRI). In this study, an optimization algorithm that could choose the parameters of the multiscale entropy (MSE) model was developed, while the optimized effectiveness for localizing the epileptogenic hemisphere was validated through the classification rate with a supervised machine learning method. The rfMRI data of 20 mesial temporal lobe epilepsy patients with positive indicators (the indicators of epileptogenic hemisphere in clinic) in the hippocampal formation on either left or right hemisphere (equally divided into two groups) on the structural MRI were collected and preprocessed. Then, three parameters in the MSE model were statistically optimized by both receiver operating characteristic (ROC) curve and the area under the ROC curve value in the sensitivity analysis, and the intergroup significance of optimized entropy values was utilized to confirm the biomarked brain areas sensitive to the epileptogenic hemisphere. Finally, the optimized entropy values of these biomarked brain areas were regarded as the feature vectors input for a support vector machine to classify the epileptogenic hemisphere, and the classification effectiveness was cross-validated. Nine biomarked brain areas were confirmed by the optimized entropy values, including medial superior frontal gyrus and superior parietal gyrus (p < .01). The mean classification accuracy was greater than 90%. It can be concluded that combination of the optimized MSE model with the machine learning model can accurately confirm the epileptogenic hemisphere by rfMRI. With the powerful information interaction capabilities of 5G communication, the epilepsy side-fixing algorithm that requires computing power can be integrated into a cloud platform. The demand side only needs to upload patient data to the service platform to realize the preoperative assessment of epilepsy.
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17
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Bragatti JA. Forced Normalization Revisited: New Concepts About a Paradoxical Phenomenon. Front Integr Neurosci 2021; 15:736248. [PMID: 34512281 PMCID: PMC8429494 DOI: 10.3389/fnint.2021.736248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 08/02/2021] [Indexed: 11/17/2022] Open
Abstract
The phenomenon of Forced Normalization (FN) was first described by Landolt in 1953, who described the disappearance of epileptiform discharges in the EEG of patients with epilepsy, concomitant with the development of psychotic symptoms. Later, Tellenbach coined the term “alternative psychosis” referring specifically to the alternation between clinical phenomena. Finally, in 1991, Wolf observed a degenerative process involved in the phenomenon, which he called “paradoxical normalization.” Initially, FN was explained through experimental models in animals and the demonstration of the kindling phenomenon, in its electrical and pharmacological subdivisions. At this stage of research on the epileptic phenomenon, repetitive electrical stimuli applied to susceptible regions of the brain (hippocampus and amygdala) were considered to explain the pathophysiological basis of temporal lobe epileptogenesis. Likewise, through pharmacological manipulation, especially of dopaminergic circuits, psychiatric comorbidities began to find their basic mechanisms. With the development of new imaging techniques (EEG/fMRI), studies in the area started to focus on the functional connectivity (FC) of different brain regions with specific neuronal networks, which govern emotions. Thus, a series of evidence was produced relating the occurrence of epileptic discharges in the limbic system and their consequent coactivation and deactivation of these resting-state networks. However, there are still many controversies regarding the basic mechanisms of network alterations related to emotional control, which will need to be studied with a more homogeneous methodology, in order to try to explain this interesting neuropsychiatric phenomenon with greater accuracy.
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Affiliation(s)
- José Augusto Bragatti
- Clinical Neurophysiology Unit, Service of Neurology, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil
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18
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Li Y, Zhu H, Chen Q, Yang L, Bao X, Chen F, Ma H, Xu H, Luo L, Zhang R. Evaluation of Brain Network Properties in Patients with MRI-Negative Temporal Lobe Epilepsy: An MEG Study. Brain Topogr 2021; 34:618-631. [PMID: 34173926 DOI: 10.1007/s10548-021-00856-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 06/13/2021] [Indexed: 11/25/2022]
Abstract
Abnormal functional brain networks of temporal lobe epilepsy (TLE) patients with structural abnormalities may partially reflect structural lesions rather than either TLE per se or functional compensatory processes. In this study, we sought to investigate the brain-network properties of intractable TLE patients apart from the effects of structural abnormalities. The brain network properties of 20 left and 23 right MRI-negative TLE patients and 22 healthy controls were evaluated using magnetoencephalographic recordings in six main frequency bands. A slowing of oscillatory brain activity was observed for the left or right TLE group vs. healthy controls. The TLE groups presented significantly increased functional connectivity in the delta, theta, lower alpha and beta bands, and significantly greater values in the normalized clustering coefficient and path length, and significantly smaller values in the weighted small-world measure in the theta band when compared to healthy controls. Alterations in global and regional band powers can be attributed to spectral slowing in TLE patients. The brain networks of TLE patients displayed abnormally high synchronization in multi-frequency bands and shifted toward a more regular architecture with worse network efficiency in the theta band. Without the contamination of structural lesions, these significant findings can be helpful for better understanding of the pathophysiological mechanism of TLE. The theta band can be considered as a preferred frequency band for investigating the brain-network dysfunction of MRI-negative intractable TLE patients.
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Affiliation(s)
- Yuejun Li
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Magnetoencephalography, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Haitao Zhu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Qiqi Chen
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Magnetoencephalography, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Lu Yang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Xincai Bao
- Library of Xinxiang Medical University, Xinxiang, 453003, Henan, China
| | - Fangqing Chen
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Haiyan Ma
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Honghao Xu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Lei Luo
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Rui Zhang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
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19
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Li W, Jiang Y, Qin Y, Zhou B, Lei D, Zhang H, Lei D, Yao D, Luo C, Gong Q, Zhou D, An D. Structural and functional reorganization of contralateral hippocampus after temporal lobe epilepsy surgery. NEUROIMAGE-CLINICAL 2021; 31:102714. [PMID: 34102537 PMCID: PMC8187253 DOI: 10.1016/j.nicl.2021.102714] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/06/2021] [Revised: 05/27/2021] [Accepted: 05/28/2021] [Indexed: 02/08/2023]
Abstract
Postoperative changes of contralateral hippocampus in temporal lobe epilepsy. No obvious hippocampal volume change was observed after successful surgery. Surgical manipulation may lead to a transient functional connectivity reduction. Increased functional connectivity mostly involved bilateral frontal regions.
Objective To explore the structural and functional reorganization of contralateral hippocampus in patients with unilateral mesial temporal lobe epilepsy (mTLE) who achieved seizure-freedom after anterior temporal lobectomy (ATL). Methods We obtained high-resolution structural MRI and resting-state functional MRI data in 28 unilateral mTLE patients and 29 healthy controls. Patients were scanned before and three and 24 months after surgery while controls were scanned only once. Hippocampal gray matter volume (GMV) and functional connectivity (FC) were assessed. Results No obvious GMV changes were observed in contralateral hippocampus before and after successful surgery. Before surgery, ipsilateral hippocampus showed increased FC with ipsilateral insula (INS) and temporoparietal junction (TPJ), but decreased FC with widespread bilateral regions, as well as contralateral hippocampus. After successful ATL, contralateral hippocampus showed: (1) decreased FC with ipsilateral INS at three months follow-up, without further changes; (2) decreased FC with ipsilateral TPJ, postcentral gyrus and rolandic operculum at three months, with an obvious increase at 24 months follow-up; (3) increased FC with bilateral medial prefrontal cortex (MPFC) and superior frontal gyrus (SFG) at three months follow-up, without further changes. Conclusions Successful ATL may not lead to an obvious structural reorganization in contralateral hippocampus. Surgical manipulation may lead to a transient FC reduction of contralateral hippocampus. Increased FC between contralateral hippocampus and bilateral MPFC and SFG may be related to postoperative functional remodeling.
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Affiliation(s)
- Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yuchao 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, Sichuan, China
| | - Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Baiwan Zhou
- 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
| | - Heng Zhang
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ding Lei
- Department of Neurosurgery, West China Hospital, Sichuan University, Chengdu, Sichuan, 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, 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, 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.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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20
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Qin Y, Tong X, Li W, Zhang L, Zhang Y, Li X, Yang J, Qin K, Lei D, Gong Q, Zhou D, An D. Divergent Anatomical Correlates and Functional Network Connectivity Patterns in Temporal Lobe Epilepsy with and Without Depression. Brain Topogr 2021; 34:525-536. [PMID: 33973138 DOI: 10.1007/s10548-021-00848-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 05/05/2021] [Indexed: 02/05/2023]
Abstract
Epilepsy and depression were proposed to facilitate each other reciprocally through common neurobiological anomalies, especially the prefrontal-limbic-subcortical abnormalities. Yet neuroimaging patterns of higher-order cognitive networks and neuroanatomical correlates were rarely compared in temporal lobe epilepsy patients with (TLE-D) and without depression (TLE-N). We collected T1-weighted structural and resting-state functional MRI data from 20 TLE-D, 31 TLE-N and 20 healthy controls (HCs) and performed analyses including hippocampal volume (HCV), cortical thickness, gray matter volume (GMV) and whole-brain functional network connectivity (FNC) across three groups. Imaging differences were related to clinical and psychological measurements. TLE-D demonstrated disrupted functional role of subcortical (SUB) and higher-order cognitive networks compared to TLE-N and HCs. In TLE-D, GMV in the right supplementary motor area (SMA) and FNC between the dorsal attention (DAN) and SUB were attenuated compared to TLE-N and HCs, FNC between SUB and the visual network (VIS) decreased compared to HCs. GMV in the right SMA was negatively correlated with depression severity and some symptoms. Combined, explicit emotion regulation may be impaired in TLE-D. Meanwhile, compared to HCs, TLE-N showed smaller HCVs, TLE-D and TLE-N showed smaller GMV in the medial orbital frontal gyrus and right hippocampus and hippocampal gyrus, possibly implying predisposition of epileptic activities to co-morbid depression. Our findings suggest distinct anatomical and FNC patterns in TLE-D and TLE-N. More than prefrontal-limbic-subcortical anomalies, disrupted higher-order cognitive network may contribute to depression in TLE, providing new potential treatment targets for depression and calling attention to relation between cognitive dysfunction and co-morbid depression.
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Affiliation(s)
- Yingjie Qin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xin Tong
- Department of Neurology, West China Second Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Le 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
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jing Yang
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kun Qin
- 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.
| | - Dongmei An
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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21
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Factors affecting interictal unilateral and bilateral discharges and ictal diffusion patterns of scalp electroencephalogram in temporal lobe epilepsy. Neurol Sci 2021; 43:507-515. [PMID: 33942172 DOI: 10.1007/s10072-021-05293-0] [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: 12/28/2020] [Accepted: 04/26/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND The interictal discharges of temporal lobe epilepsy (TLE) can be unilateral or bilateral. In addition, the ictal electroencephalogram (EEG) showed the discharges also tend to spread to the contralateral brain in TLE. OBJECTIVE The factors influencing unilateral and bilateral interictal discharges in TLE as well as ictal diffusion patterns in scalp EEG during onset of seizure were evaluated in the present study. MATERIALS AND METHODS This was a retrospective analysis of 129 patients with TLE. Cases were classified into unilateral and bilateral discharge groups based on interictal discharge patterns in the EEG. Differences between the two groups in age, gender, disease duration, seizure frequency, magnetic resonance imaging (MRI) findings, origin of TLE, antiepileptic drug (AED) administration, and ictal diffusion patterns during seizures were statistically analyzed. In addition, the differences in ictal diffusion patterns between left and right TLE were statistically analyzed. RESULTS Statistically significant differences were not observed in gender, disease duration, seizure frequency, MRI findings, administration of AEDs, and ictal diffusion patterns between interictal unilateral and bilateral discharge groups but with statistically significant differences in age and side of origin of the TLE. In addition, whether the EEG-recorded diffusion pattern was confined to the same hemisphere or spread to both hemispheres was investigated and shown statistically significant differences between the left and right temporal lobes. CONCLUSIONS Age and side of origin of TLE affects the TLE interictal discharge patterns. Older patients are more prone to bilateral discharges. Bilateral discharges are more common in right TLE, and the onset of EEG more likely to bilateral diffusion in right TLE.
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22
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Mo J, Zhao B, Adler S, Zhang J, Shao X, Ma Y, Sang L, Hu W, Zhang C, Wang Y, Wang X, Liu C, Zhang K. Quantitative assessment of structural and functional changes in temporal lobe epilepsy with hippocampal sclerosis. Quant Imaging Med Surg 2021; 11:1782-1795. [PMID: 33936964 DOI: 10.21037/qims-20-624] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Background Magnetic resonance imaging (MRI) changes in hippocampal sclerosis (HS) could be subtle in a significant proportion of mesial temporal lobe epilepsy (mTLE) patients. In this study, we aimed to document the structural and functional changes in the hippocampus and amygdala seen in HS patients. Methods Quantitative features of the hippocampus and amygdala were extracted from structural MRI data in 66 mTLE patients and 28 controls. Structural covariance analysis was undertaken using volumetric data from the amygdala and hippocampus. Functional connectivity (FC) measured using resting intracranial electroencephalography (EEG) was analyzed in 22 HS patients and 16 non-HS disease controls. Results Hippocampal atrophy was present in both MRI-positive and MRI-negative HS groups (Mann-Whitney U: 7.61, P<0.01; Mann-Whitney U: 6.51, P<0.01). Amygdala volumes were decreased in the patient group (Mann-Whitney U: 2.92, P<0.05), especially in MRI-negative HS patients (Mann-Whitney U: 2.75, P<0.05). The structural covariance analysis showed the normalized volumes of the amygdala and hippocampus were tightly coupled in both controls and HS patients (ρSpearman =0.72, P<0.01). FC analysis indicated that HS patients had significantly increased connectivity (Student's t: 2.58, P=0.03) within the hippocampus but decreased connectivity between the hippocampus and amygdala (Student's t: 3.33, P=0.01), particularly for MRI-negative HS patients. Conclusions Quantitative structural changes, including hippocampal atrophy and temporal pole blurring, are present in both MRI-positive and MRI-negative HS patients, suggesting the potential usefulness of incorporating quantitative analyses into clinical practice. HS is characterized by increased intra-hippocampal EEG synchronization and decreased coupling between the hippocampus and amygdala.
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Affiliation(s)
- Jiajie Mo
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Sophie Adler
- Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiaoqiu Shao
- China National Clinical Research Center for Neurological Diseases, Beijing, China.,Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yanshan Ma
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yao Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Chang Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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23
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Sadjadi SM, Ebrahimzadeh E, Shams M, Seraji M, Soltanian-Zadeh H. Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data. Front Neurol 2021; 12:645594. [PMID: 33986718 PMCID: PMC8110922 DOI: 10.3389/fneur.2021.645594] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 03/11/2021] [Indexed: 02/01/2023] Open
Abstract
Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.
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Affiliation(s)
- Seyyed Mostafa Sadjadi
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Elias Ebrahimzadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Mohammad Shams
- Neural Engineering Laboratory, Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, United States
| | - Masoud Seraji
- Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, United States.,Behavioral and Neural Sciences Graduate Program, Rutgers University, Newark, NJ, United States
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Neuroimage Signal and Image Analysis Group, School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran.,Medical Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
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Ding D, Zhou D, Sander JW, Wang W, Li S, Hong Z. Epilepsy in China: major progress in the past two decades. Lancet Neurol 2021; 20:316-326. [PMID: 33743240 DOI: 10.1016/s1474-4422(21)00023-5] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Revised: 12/15/2020] [Accepted: 01/07/2021] [Indexed: 02/08/2023]
Abstract
China has approximately 10 million people with epilepsy. There is a vast epilepsy treatment gap in China, mainly driven by deficiencies in health-care delivery and social discrimination resulting from cultural beliefs about epilepsy. WHO's Global Campaign Against Epilepsy project in China showed that it was possible to treat epilepsy in primary care settings, which was a notable milestone. The China Association Against Epilepsy has been a necessary force to stimulate interest in epilepsy care and research by the medical and scientific community. Nearly 20 different anti-seizure medications are now available in China. Non-pharmacological options are also available, but there are still unmet needs for epilepsy management. The Chinese epilepsy research portfolio is varied, but the areas in which there are the most concentrated focus and expertise are epidemiology and clinical research. The challenges for further improvement in delivering care for people with epilepsy in China are primarily related to public health and reducing inequalities within this vast country.
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Affiliation(s)
- Ding Ding
- Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Josemir W Sander
- NIHR University College London Hospitals Biomedical Research Centre, UCL Queen Square Institute of Neurology, London, UK; Chalfont Centre for Epilepsy, Chalfont St Peter, Buckinghamshire, UK; Stichting Epilepsie Instellingen Nederland, Heemstede, Netherlands.
| | - Wenzhi Wang
- Department of Neuroepidemiology, Beijing Neurosurgical Institute, Beijing, China
| | - Shichuo Li
- China Association against Epilepsy, Beijing, China
| | - Zhen Hong
- Institute of Neurology, Huashan Hospital, Fudan University, Shanghai, China
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25
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Li R, Zhang L, Guo D, Zou T, Wang X, Wang H, Li J, Wang C, Liu D, Yang Z, Xiao B, Chen H, Feng L. Temporal Lobe Epilepsy Shows Distinct Functional Connectivity Patterns in Different Thalamic Nuclei. Brain Connect 2021; 11:119-131. [PMID: 33317410 DOI: 10.1089/brain.2020.0826] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022] Open
Abstract
Background: The thalamus, as a key relay of neuronal information flow between subcortical structures and cortical networks, has been implicated in focal limbic seizures propagation, awareness maintenance, and seizure-related cognitive deficits. However, the specific functional alterations between different thalamic nuclei and subcortical-cortical systems in temporal lobe epilepsy (TLE) remain largely unknown. Methods: We examined thalamic functional connectivity (FC) in 26 TLE patients and 30 healthy controls matched for sex, age, and education. The anterior (ANT), ventral posterior medial, and central lateral nuclei of thalamus were employed to establish whole-brain seed-to-voxel thalamic FC maps. Secondary Pearson's correlation analysis was conducted to assess associations between the abnormal thalamic FC and the memory performance in TLE. Results: Seed-based FC analyses revealed typical distinct FC patterns within each thalamic nuclei in both controls and TLE patients. The TLE showed significantly decreased FC between different thalamic nuclei and subcortical-cortical networks, including the limbic structures, midbrain, sensorimotor network, medial prefrontal cortex, temporal-occipital fusiform gyrus, and cerebellum. Verification analyses yielded similar patterns of thalamic FC changes in TLE. Importantly, the decreased FC between the ANT and hippocampal pathway was correlated with the poorer memory performance of TLE. Conclusion: These findings suggest that the distinct thalamocortical FC patterns are damaged to some extent in TLE patients. Importantly, the specific pathology of the ANT-hippocampal pathway in TLE may be a potential factor that contributes to memory deficits. Our study may pave the way for improved treatments and cognitive function by directly targeting different thalamocortical circuits for TLE.
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Affiliation(s)
- Rong Li
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Leiyao Zhang
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Danni Guo
- Department of Neurology and Xiangya Hospital, Central South University, Changsha, P.R. China
| | - Ting Zou
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Xuyang Wang
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Hongyu Wang
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Jiyi Li
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Chong Wang
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Dingyang Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, P.R. China
| | - Zhiquan Yang
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, P.R. China
| | - Bo Xiao
- Department of Neurology and Xiangya Hospital, Central South University, Changsha, P.R. China
| | - Huafu Chen
- MOE Key Lab for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, P.R. China.,Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, P.R. China
| | - Li Feng
- Department of Neurology and Xiangya Hospital, Central South University, Changsha, P.R. China
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Guo Z, Zhao B, Hu W, Zhang C, Wang X, Wang Y, Liu C, Mo J, Sang L, Ma Y, Shao X, Zhang J, Zhang K. Effective connectivity among the hippocampus, amygdala, and temporal neocortex in epilepsy patients: A cortico-cortical evoked potential study. Epilepsy Behav 2021; 115:107661. [PMID: 33434884 DOI: 10.1016/j.yebeh.2020.107661] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 08/08/2020] [Accepted: 11/21/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Mesial temporal lobe epilepsy (MTLE) is one of the most common types of intractable epilepsy. The hippocampus and amygdala are two crucial structures of the mesial temporal lobe and play important roles in the epileptogenic network of MTLE. This study aimed to explore the effective connectivity among the hippocampus, amygdala, and temporal neocortex and to determine whether differences in effective connectivity exist between MTLE patients and non-MTLE patients. METHODS This study recruited 20 patients from a large cohort of drug-resistant epilepsy patients, of whom 14 were MTLE patients. Single-pulse electrical stimulation (SPES) was performed to acquire cortico-cortical evoked potentials (CCEPs). The root mean square (RMS) was used as the metric of the magnitude of CCEP to represent the effective connectivity. We then conducted paired and independent sample t-tests to assess the directionality of the effective connectivity. RESULTS In both MTLE patients and non-MTLE patients, the directional connectivity from the amygdala to the hippocampus was stronger than that from the hippocampus to the amygdala (P < 0.01); the outward connectivity from the amygdala to the cortex was stronger than the inward connectivity from the cortex to the amygdala (P < 0.01); the amygdala had stronger connectivity to the neocortex than the hippocampus (P < 0.01). In MTLE patients, the neocortex had stronger connectivity to the hippocampus than to the amygdala (P < 0.01). No significant differences in directional connectivity were noted between the two groups. CONCLUSIONS A unique effective connectivity pattern among the hippocampus, amygdala, and temporal neocortex was identified through CCEPs analysis. This study may aid in our understanding of physiological and pathological networks in the brain and inspire neurostimulation protocols for neurological and psychiatric disorders.
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Affiliation(s)
- Zhihao Guo
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Wenhan Hu
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Chao Zhang
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Xiu Wang
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Yao Wang
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Chang Liu
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Jiajie Mo
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Lin Sang
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Yanshan Ma
- Department of Neurosurgery, Beijing Fengtai Hospital, Beijing, China
| | - Xiaoqiu Shao
- Department of Neurology, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China.
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tian Tan Hospital, Capital Medical University, Beijing, China; Stereotactic and Functional Neurosurgery Laboratory, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China; Beijing Key Laboratory of Neurostimulation, Beijing, China.
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Lambert I, Tramoni-Negre E, Lagarde S, Pizzo F, Trebuchon-Da Fonseca A, Bartolomei F, Felician O. Accelerated long-term forgetting in focal epilepsy: Do interictal spikes during sleep matter? Epilepsia 2021; 62:563-569. [PMID: 33476422 DOI: 10.1111/epi.16823] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 12/19/2020] [Accepted: 01/05/2021] [Indexed: 12/21/2022]
Abstract
Accelerated long-term forgetting (ALF) is a particular form of amnesia mostly encountered in focal epilepsy, particularly in temporal lobe epilepsy. This type of memory loss is characterized by an impairment of long-term consolidation of declarative memory, and its mechanisms remain poorly understood. In particular, the respective contribution of lesion, seizures, interictal epileptic discharges, and sleep is still debated. Here, we provide an overview of the relationships intertwining epilepsy, sleep, and memory consolidation and, based on recent findings from intracranial electroencephalographic recordings, we propose a model of ALF pathophysiology that integrates the differential role of interictal spikes during wakefulness and sleep. This model provides a framework to account for the different timescales at which ALF may occur.
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Affiliation(s)
- Isabelle Lambert
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Eve Tramoni-Negre
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Neurology and Neuropsychology Department, Timone Hospital, Marseille, France
| | - Stanislas Lagarde
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Francesca Pizzo
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Agnès Trebuchon-Da Fonseca
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Fabrice Bartolomei
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Epileptology and Clinical Neurophysiology Department, Timone Hospital, Marseille, France
| | - Olivier Felician
- System Neurosciences Institute, Aix Marseille University, INSERM, INS, Marseille, France.,Neurology and Neuropsychology Department, Timone Hospital, Marseille, France
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28
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Pina LTS, Guimarães AG, Santos WBDR, Oliveira MA, Rabelo TK, Serafini MR. Monoterpenes as a perspective for the treatment of seizures: A Systematic Review. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2021; 81:153422. [PMID: 33310306 DOI: 10.1016/j.phymed.2020.153422] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/03/2020] [Revised: 10/15/2020] [Accepted: 11/19/2020] [Indexed: 06/12/2023]
Abstract
BACKGROUND Epilepsy affects more than 65 million people worldwide. Treatment for epileptic seizures is ineffective and has many adverse effects. For this reason, the search for new therapeutic options capable of filling these limitations is necessary. HYPOTHESIS/PURPOSE In this sense, natural products, such as monoterpenes, have been indicated as a new option to control neurological disorders such as epilepsy. STUDY DESIGN Therefore, the objective of this study was to review the monoterpenes that have anticonvulsive activity in animal models. METHODS The searches were performed in the PubMed, Web of Science and Scopus databases in September, 2020 and compiled studies using monoterpenes as an alternative to seizure. Two independent reviewers performed the study selection, data extraction and methodological quality assessment using the Syrcle tool. RESULTS 51 articles that described the anticonvulsant activity of 35 monoterpenes were selected with action on the main pharmacological target, including GABAA receptors, glutamate, calcium channels, sodium and potassium. In addition, these compounds are capable of reducing neuronal inflammation and oxidative stress caused by seizure. CONCLUSION These compounds stand out as a promising alternative for acting through different pharmacological mechanisms, which may not only reduce seizure, but also promote neuroprotective effect by reducing toxicity in brain regions. However, further studies are needed to determine the mechanism of action and safety assessment of these compounds.
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Affiliation(s)
- Lícia T S Pina
- Graduate Program in Health Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil.
| | - Adriana G Guimarães
- Graduate Program in Pharmaceutical Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil
| | - Wagner B da R Santos
- Graduate Program in Pharmaceutical Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil
| | - Marlange A Oliveira
- Graduate Program in Health Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil
| | - Thallita K Rabelo
- Graduate Program in Health Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil
| | - Mairim R Serafini
- Graduate Program in Health Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil; Graduate Program in Pharmaceutical Sciences, Universidade Federal de Sergipe, São Cristóvão, Sergipe, Brazil
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29
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Yang R, Zhao X, Liu J, Yao X, Hou F, Xu Y, Feng Q. Functional connectivity changes of nucleus Accumbens Shell portion in left mesial temporal lobe epilepsy patients. Brain Imaging Behav 2020; 14:2659-2667. [PMID: 32318911 DOI: 10.1007/s11682-019-00217-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Growing evidence has supported that the nucleus accumbens (NAc), especially its shell portion, has been involved in epileptogenesis. However, relevant studies on vivo human brain are quite limited. In this study, we investigated left mesial temporal lobe epilepsy (MTLE) related function connectivity (FC) changes of NAc subregions using resting-state functional magnetic resonance imaging. We calculated functional connectivity from two NAc subregions to both whole brain and 16 related targets. Two-sample t-test (Alphasim multiple comparisons corrected) was performed to identify the effect of the disease on each seed's whole brain network. Repeated-measures ANOVA and Post hoc pairwise t test (Bonferroni corrections) were performed to visualize the seed to target FC group differences in each subdivision. In whole brain FC networks, neither the left or right core show different FC changes. The left shell showed decreased FC with a cluster located around the right inferior frontal gyrus. The right shell portion showed increased FC with a cluster located around the left inferior temporal gyrus. The seed to targets results showed that the left shell of LTLE group exhibited lower FC with left posterior-parahippocampal gyrus and right caudate, putamen, thalamus, paracingulate gyrus but higher FC with right subcallosal cortex. The right core of LTLE group exhibited higher FC with right frontal pole and the right shell exhibited lower FC with left thalamus and left anterior-parahippocampal gyrus. This is the first study to investigate the functional connectivity changes of NAc subdivisions of epilepsy in vivo human brain. Our results showed that the left MTLE related FC changes on NAc are mainly on shell portion rather than core. The decrease FC between the left shell and right frontal area and the decrease FC between the right shell and left temporal area suggested they serve vital roles for MTLE.
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Affiliation(s)
- Ru Yang
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, 510,515, China
- Department of Radiology, The second Xiangya Hospital, Central South University, Changsha, 410,011, China
| | - Xixi Zhao
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510,515, China
| | - Jun Liu
- Department of Radiology, The second Xiangya Hospital, Central South University, Changsha, 410,011, China
| | - Xufeng Yao
- School of Radiology, Shanghai University of Medicine & Health Science, Shanghai, 201,318, China
| | - Feng Hou
- Department of Radiology, The second Xiangya Hospital, Central South University, Changsha, 410,011, China
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510,515, China.
| | - Qianjin Feng
- Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, 510,515, China.
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30
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Reh R, Williams LJ, Todd RM, Ward LM. Warped rhythms: Epileptic activity during critical periods disrupts the development of neural networks for human communication. Behav Brain Res 2020; 399:113016. [PMID: 33212087 DOI: 10.1016/j.bbr.2020.113016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 12/27/2022]
Abstract
It is well established that temporal lobe epilepsy-the most common and well-studied form of epilepsy-can impair communication by disrupting social-emotional and language functions. In pediatric epilepsy, where seizures co-occur with the development of critical brain networks, age of onset matters: The earlier in life seizures begin, the worse the disruption in network establishment, resulting in academic hardship and social isolation. Yet, little is known about the processes by which epileptic activity disrupts developing human brain networks. Here we take a synthetic perspective-reviewing a range of research spanning studies on molecular and oscillatory processes to those on the development of large-scale functional networks-in support of a novel model of how such networks can be disrupted by epilepsy. We seek to bridge the gap between research on molecular processes, on the development of human brain circuitry, and on clinical outcomes to propose a model of how epileptic activity disrupts brain development.
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Affiliation(s)
- Rebecca Reh
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada
| | - Lynne J Williams
- BC Children's Hospital MRI Research Facility, 4480 Oak Street, Vancouver, BC V6H 0B3, Canada
| | - Rebecca M Todd
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada; University of British Columbia, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada.
| | - Lawrence M Ward
- University of British Columbia, Department of Psychology, 2136 West Mall, Vancouver BC V6T 1Z4, Canada; University of British Columbia, Djavad Mowafaghian Centre for Brain Health, 2215 Wesbrook Mall, Vancouver, BC V6T 1Z3, Canada
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31
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Chauvière L. Potential causes of cognitive alterations in temporal lobe epilepsy. Behav Brain Res 2020; 378:112310. [DOI: 10.1016/j.bbr.2019.112310] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 10/15/2019] [Accepted: 10/15/2019] [Indexed: 12/11/2022]
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32
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Dahal P, Ghani N, Flinker A, Dugan P, Friedman D, Doyle W, Devinsky O, Khodagholy D, Gelinas JN. Interictal epileptiform discharges shape large-scale intercortical communication. Brain 2019; 142:3502-3513. [PMID: 31501850 PMCID: PMC6821283 DOI: 10.1093/brain/awz269] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 06/28/2019] [Accepted: 07/11/2019] [Indexed: 01/07/2023] Open
Abstract
Dynamic interactions between remote but functionally specialized brain regions enable complex information processing. This intercortical communication is disrupted in the neural networks of patients with focal epilepsy, and epileptic activity can exert widespread effects within the brain. Using large-scale human intracranial electroencephalography recordings, we show that interictal epileptiform discharges (IEDs) are significantly coupled with spindles in discrete, individualized brain regions outside of the epileptic network. We found that a substantial proportion of these localized spindles travel across the cortical surface. Brain regions that participate in this IED-driven oscillatory coupling express spindles that have a broader spatial extent and higher tendency to propagate than spindles occurring in uncoupled regions. These altered spatiotemporal oscillatory properties identify areas that are shaped by epileptic activity independent of IED or seizure detection. Our findings suggest that IED-spindle coupling may be an important mechanism of interictal global network dysfunction that could be targeted to prevent disruption of normal neural activity.
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Affiliation(s)
- Prawesh Dahal
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Naureen Ghani
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
| | - Adeen Flinker
- Department of Neurology, NYU Langone, New York, NY, USA
- Comprehensive Epilepsy Center, NYU Langone, New York, NY, USA
| | - Patricia Dugan
- Department of Neurology, NYU Langone, New York, NY, USA
- Comprehensive Epilepsy Center, NYU Langone, New York, NY, USA
| | - Daniel Friedman
- Department of Neurology, NYU Langone, New York, NY, USA
- Comprehensive Epilepsy Center, NYU Langone, New York, NY, USA
| | - Werner Doyle
- Comprehensive Epilepsy Center, NYU Langone, New York, NY, USA
- Department of Neurosurgery, NYU Langone, New York, NY, USA
| | - Orrin Devinsky
- Department of Neurology, NYU Langone, New York, NY, USA
- Comprehensive Epilepsy Center, NYU Langone, New York, NY, USA
| | - Dion Khodagholy
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Jennifer N Gelinas
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
- Department of Neurology, Columbia University Medical Center, New York, NY, USA
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Shamshiri EA, Sheybani L, Vulliemoz S. The Role of EEG-fMRI in Studying Cognitive Network Alterations in Epilepsy. Front Neurol 2019; 10:1033. [PMID: 31608007 PMCID: PMC6771300 DOI: 10.3389/fneur.2019.01033] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/11/2019] [Indexed: 02/01/2023] Open
Abstract
Brain functions do not arise from isolated brain regions, but from interactions in widespread networks necessary for both normal and pathological conditions. These Intrinsic Connectivity Networks (ICNs) support cognitive processes such as language, memory, or executive functions, but can be disrupted by epileptic activity. Simultaneous EEG-fMRI can help explore the hemodynamic changes associated with focal or generalized epileptic discharges, thus providing information about both transient and non-transient impairment of cognitive networks related to spatio-temporal overlap with epileptic activity. In the following review, we discuss the importance of interictal discharges and their impact on cognition in different epilepsy syndromes. We explore the cognitive impact of interictal activity in both animal models and human connectivity networks in order to confirm that this effect could have a possible clinical impact for prescribing medication and characterizing post-surgical outcome. Future work is needed to further investigate electrophysiological changes, such as amplitude/latency of single evoked responses or spontaneous epileptic activity in either scalp or intracranial EEG and determine its relative change in hemodynamic response with subsequent network modifications.
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Affiliation(s)
- Elhum A Shamshiri
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Laurent Sheybani
- Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland.,Neurology Clinic, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland
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34
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Tully HM. Broken connections. Sci Transl Med 2019. [DOI: 10.1126/scitranslmed.aaw5333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Interictal discharges affect functional connectivity in patients with temporal lobe epilepsy.
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Affiliation(s)
- Hannah M. Tully
- Division of Pediatric Neurology, Seattle Children’s Hospital/University of Washington, Seattle, WA 98105, USA
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