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Bu J, Yin H, Ren N, Zhu H, Xu H, Zhang R, Zhang S. Structural and functional changes in the default mode network in drug-resistant epilepsy. Epilepsy Behav 2024; 151:109593. [PMID: 38157823 DOI: 10.1016/j.yebeh.2023.109593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 11/25/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE To investigate brain network properties and connectivity abnormalities of the default mode network (DMN) in drug-resistant epilepsy (DRE). The study was based on probabilistic fiber tracking and functional connectivity (FC) analysis, to explore the structural and functional connectivity patterns change between frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). METHODS A total of 33 DRE patients (18 TLE and 15 FLE) and 30 healthy controls (HCs) were recruited. The volume fraction of the septal brain region of the DMN in DRE was calculated using FreeSurfer. The FC analysis was performed using Data Processing and Analysis for Brain Imaging in MATLAB. The structural connections between brain regions of the DMN were calculated based on probabilistic fiber tracking. RESULTS The left precuneus (PCUN) volumes in epilepsy groups were lower than that in HCs. Compared with FLE, TLE showed reduced FC between the left hippocampus (HIP) and PCUN/medial frontal gyrus, and between the right inferior parietal lobule (IPL) and right superior temporal gyrus. Compared with HCs, FLE showed increased FCs between the right IPL and occipital lobe, and between the left superior frontal gyrus (SFG) and bilateral superior temporal gyrus. In terms of structural connectivity, TLE exhibited increased connectivity strength between the left SFG and left PCUN, and showed reduced connection strength between the left HIP and left posterior cingulate gyrus/left PCUN, when compared with the FLE. CONCLUSIONS TLE and FLE patients showed structural and functional changes in the DMN. Compared with FLE patients, the TLE patients showed reduced structural and functional connection strengths between the left HIP and PCUN. These alterations in connection strengths holds promise for the identification of TLE and FLE.
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Affiliation(s)
- Jinxin Bu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Hangxing Yin
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Nanxiao Ren
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Haitao Zhu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Honghao Xu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Rui Zhang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
| | - Shugang Zhang
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
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2
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Süß AM, Hug M, Conradi N, Kienitz R, Rosenow F, Rampp S, Merkel N. Lateralization of delta band power in magnetoencephalography (MEG) in patients with unilateral focal epilepsy and its relation to verbal fluency. Brain Behav 2023; 13:e3257. [PMID: 37752097 PMCID: PMC10636394 DOI: 10.1002/brb3.3257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 08/22/2023] [Accepted: 08/31/2023] [Indexed: 09/28/2023] Open
Abstract
INTRODUCTION Delta power is a clinically established biomarker for abnormal brain processes. However, in patients with unilateral focal epilepsy (FE) it is still not well understood, how it relates to the epileptogenic zone and to neurocognitive functioning. The aim of the present study was thus to assess how delta power relates to the affected hemisphere, whether lateralization strength differs between the patients, and how changes in delta power correlate with cognitive functioning. METHOD We retrospectively studied patients with left (LFE) and right FE (RFE) who had undergone a resting-state magnetoencephalography measurement. We computed global and hemispheric delta power and lateralization indices and examined whether delta power correlates with semantic and letter verbal fluency (former being a marker for language and verbal memory, latter for executive functions) in 26 FE patients (15 LFE, 11 RFE) and 10 healthy controls. RESULTS Delta power was increased in FE patients compared to healthy controls. However, the increase across hemispheres was related to the site of the epileptic focus: On group level, LFE patients showed higher delta power in both hemispheres, whereas RFE patients primarily exhibited higher delta power in the ipsilateral right hemisphere. Both groups showed co-fluctuations of delta power between the hemispheres. Besides, delta power correlated negatively only with letter verbal fluency. CONCLUSION The findings confirm and provide further evidence that delta power is a marker of pathological activity and abnormal brain processes in FE. Delta power dynamics differ between patient groups, indicating that delta power could offer additional diagnostic value. The negative association of delta power and letter verbal fluency suggests that executive dysfunctions are related to low frequency abnormalities.
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Affiliation(s)
- Annika Melissa Süß
- Epilepsy Center Frankfurt Rhine‐MainCenter of Neurology and NeurosurgeryUniversity Hospital FrankfurtFrankfurt am MainGermany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University FrankfurtFrankfurt am MainGermany
| | - Marion Hug
- Department of NeurologyUniversity Hospital Frankfurt and Goethe UniversityFrankfurt am MainGermany
| | - Nadine Conradi
- Epilepsy Center Frankfurt Rhine‐MainCenter of Neurology and NeurosurgeryUniversity Hospital FrankfurtFrankfurt am MainGermany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University FrankfurtFrankfurt am MainGermany
| | - Ricardo Kienitz
- Epilepsy Center Frankfurt Rhine‐MainCenter of Neurology and NeurosurgeryUniversity Hospital FrankfurtFrankfurt am MainGermany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University FrankfurtFrankfurt am MainGermany
| | - Felix Rosenow
- Epilepsy Center Frankfurt Rhine‐MainCenter of Neurology and NeurosurgeryUniversity Hospital FrankfurtFrankfurt am MainGermany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University FrankfurtFrankfurt am MainGermany
| | - Stefan Rampp
- Department of NeurosurgeryUniversity Hospital ErlangenErlangenGermany
- Department of NeurosurgeryUniversity Hospital Halle (Saale)Halle (Saale)Germany
| | - Nina Merkel
- Epilepsy Center Frankfurt Rhine‐MainCenter of Neurology and NeurosurgeryUniversity Hospital FrankfurtFrankfurt am MainGermany
- Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck SocietyFrankfurt am MainGermany
- LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University FrankfurtFrankfurt am MainGermany
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Di G, Tan M, Xu R, Zhou W, Duan K, Hu Z, Cao X, Zhang H, Jiang X. Altered Structural and Functional Patterns Within Executive Control Network Distinguish Frontal Glioma-Related Epilepsy. Front Neurosci 2022; 16:916771. [PMID: 35692418 PMCID: PMC9179179 DOI: 10.3389/fnins.2022.916771] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 05/05/2022] [Indexed: 11/27/2022] Open
Abstract
Background The tumor invasion of the frontal lobe induces changes in the executive control network (ECN). It remains unclear whether epileptic seizures in frontal glioma patients exacerbate the structural and functional alterations within the ECN, and whether these changes can be used to identify glioma-related seizures at an early stage. This study aimed to investigate the altered structural and functional patterns of ECN in frontal gliomas without epilepsy (non-FGep) and frontal gliomas with epilepsy (FGep) and to evaluate whether the patterns can accurately distinguish glioma-related epilepsy. Methods We measured gray matter (GM) volume, regional homogeneity (ReHo), and functional connectivity (FC) within the ECN to identify the structural and functional changes in 50 patients with frontal gliomas (29 non-FGep and 21 FGep) and 39 healthy controls (CN). We assessed the relationships between the structural and functional changes and cognitive function using partial correlation analysis. Finally, we applied a pattern classification approach to test whether structural and functional abnormalities within the ECN can distinguish non-FGep and FGep from CN subjects. Results Within the ECN, non-FGep and FGep showed increased local structure (GM) and function (ReHo), and decreased FC between brain regions compared to CN. Also, non-FGep and FGep showed differential patterns of structural and functional abnormalities within the ECN, and these abnormalities are more severe in FGep than in non-FGep. Lastly, FC between the right superior frontal gyrus and right dorsolateral prefrontal cortex was positively correlated with episodic memory scores in non-FGep and FGep. In particular, the support vector machine (SVM) classifier based on structural and functional abnormalities within ECN could accurately distinguish non-FGep and FGep from CN, and FGep from non-FGep on an individual basis with very high accuracy, area under the curve (AUC), sensitivity, and specificity. Conclusion Tumor invasion of the frontal lobe induces local structural and functional reorganization within the ECN, exacerbated by the accompanying epileptic seizures. The ECN abnormalities can accurately distinguish the presence or absence of epileptic seizures in frontal glioma patients. These findings suggest that differential ECN patterns can assist in the early identification and intervention of epileptic seizures in frontal glioma patients.
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Affiliation(s)
- Guangfu Di
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Mingze Tan
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Rui Xu
- Department of Radiology, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Wei Zhou
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Kaiqiang Duan
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Zongwen Hu
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Xiaoxiang Cao
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Hongchuang Zhang
- Department of Radiology, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
| | - Xiaochun Jiang
- Department of Neurosurgery, The Translational Research Institute for Neurological Disorders of Wannan Medical College, The First Affiliated Hospital of Wannan Medical College, Yijishan Hospital of Wannan Medical College, Wuhu, China
- *Correspondence: Xiaochun Jiang,
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Aung T, Tenney JR, Bagić AI. Contributions of Magnetoencephalography to Understanding Mechanisms of Generalized Epilepsies: Blurring the Boundary Between Focal and Generalized Epilepsies? Front Neurol 2022; 13:831546. [PMID: 35572923 PMCID: PMC9092024 DOI: 10.3389/fneur.2022.831546] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/08/2022] [Indexed: 12/31/2022] Open
Abstract
According to the latest operational 2017 ILAE classification of epileptic seizures, the generalized epileptic seizure is still conceptualized as "originating at some point within and rapidly engaging, bilaterally distributed networks." In contrast, the focal epileptic seizure is defined as "originating within networks limited to one hemisphere." Hence, one of the main concepts of "generalized" and "focal" epilepsy comes from EEG descriptions before the era of source localization, and a presumed simultaneous bilateral onset and bi-synchrony of epileptiform discharges remains a hallmark for generalized seizures. Current literature on the pathophysiology of generalized epilepsy supports the concept of a cortical epileptogenic focus triggering rapidly generalized epileptic discharges involving intact corticothalamic and corticocortical networks, known as the cortical focus theory. Likewise, focal epilepsy with rich connectivity can give rise to generalized spike and wave discharges resulting from widespread bilateral synchronization. Therefore, making this key distinction between generalized and focal epilepsy may be challenging in some cases, and for the first time, a combined generalized and focal epilepsy is categorized in the 2017 ILAE classification. Nevertheless, treatment options, such as the choice of antiseizure medications or surgical treatment, are the reason behind the importance of accurate epilepsy classification. Over the past several decades, plentiful scientific research on the pathophysiology of generalized epilepsy has been conducted using non-invasive neuroimaging and postprocessing of the electromagnetic neural signal by measuring the spatiotemporal and interhemispheric latency of bi-synchronous or generalized epileptiform discharges as well as network analysis to identify diagnostic and prognostic biomarkers for accurate diagnosis of the two major types of epilepsy. Among all the advanced techniques, magnetoencephalography (MEG) and multiple other methods provide excellent temporal and spatial resolution, inherently suited to analyzing and visualizing the propagation of generalized EEG activities. This article aims to provide a comprehensive literature review of recent innovations in MEG methodology using source localization and network analysis techniques that contributed to the literature of idiopathic generalized epilepsy in terms of pathophysiology and clinical prognosis, thus further blurring the boundary between focal and generalized epilepsy.
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Affiliation(s)
- Thandar Aung
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
| | - Jeffrey R. Tenney
- Division of Neurology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Anto I. Bagić
- Department of Neurology, University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical Center (UPMC), Pittsburgh, PA, United States
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5
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Fang S, Li L, Weng S, Guo Y, Zhang Z, Wang L, Fan X, Wang Y, Jiang T. Decreasing Shortest Path Length of the Sensorimotor Network Induces Frontal Glioma-Related Epilepsy. Front Oncol 2022; 12:840871. [PMID: 35252008 PMCID: PMC8888886 DOI: 10.3389/fonc.2022.840871] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 01/24/2022] [Indexed: 01/12/2023] Open
Abstract
Background Glioma-related epilepsy (GRE) is a common symptom in patients with prefrontal glioma. Epilepsy onset is associated with functional network alterations. This study investigated alterations of functional networks in patients with prefrontal glioma and GRE. Methods Sixty-five patients with prefrontal lobe gliomas were retrospectively assessed and classified into GRE and non-GRE groups. Additionally, 25 healthy participants were enrolled after matching for general information. Imaging data were acquired within 72 h in pre-operation. The sensorimotor network was used to delineate alterations in functional connectivity (FC) and topological properties. One-way analysis of variance and post-hoc analysis with Bonferroni correction were used to calculate differences of FC and topological properties. Results All significant alterations were solely found in the sensorimotor network. Irrespective of gliomas located in the left or right prefrontal lobes, the edge between medial Brodmann area 6 and caudal ventrolateral Brodmann area 6 decreased FC in the GRE group compared with the non-GRE group [p < 0.0001 (left glioma), p = 0.0002 (right glioma)]. Moreover, the shortest path length decrease was found in the GRE group compared with the non-GRE group [p = 0.0292 (left glioma) and p = 0.0129 (right glioma)]. Conclusions The reduction of FC between the medial BA 6 (supplementary motor area) and caudal ventrolateral BA 6 in the ipsilateral hemisphere and the shortening of the path length of the sensorimotor network were characteristics alterations in patients with GRE onset. These findings fill in the gap which is the relationship between GRE onset and the alterations of functional networks in patients with prefrontal glioma. Significance Statement Glioma related epilepsy is the most common symptom of prefrontal glioma. It is important to identify characteristic alterations in functional networks in patients with GRE. We found that all significant alterations occurred in the sensorimotor network. Moreover, a decreased FC in the supplementary motor area and a shortening of the path’s length are additional characteristics of glioma-related epilepsy. We believe that our findings indicate new directions of research that will contribute to future investigations of glioma-related epilepsy onset.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Lianwang Li
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Shimeng Weng
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yuhao Guo
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Zhong Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lei Wang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Xing Fan
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tao Jiang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors, Chinese Academy of Medical Sciences, Beijing, China
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6
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Beckmann KM, Wang-Leandro A, Richter H, Bektas RN, Steffen F, Dennler M, Carrera I, Haller S. Increased resting state connectivity in the anterior default mode network of idiopathic epileptic dogs. Sci Rep 2021; 11:23854. [PMID: 34903807 PMCID: PMC8668945 DOI: 10.1038/s41598-021-03349-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 11/30/2021] [Indexed: 12/11/2022] Open
Abstract
Epilepsy is one of the most common chronic, neurological diseases in humans and dogs and considered to be a network disease. In human epilepsy altered functional connectivity in different large-scale networks have been identified with functional resting state magnetic resonance imaging. Since large-scale resting state networks have been consistently identified in anesthetised dogs’ application of this technique became promising in canine epilepsy research. The aim of the present study was to investigate differences in large-scale resting state networks in epileptic dogs compared to healthy controls. Our hypothesis was, that large-scale networks differ between epileptic dogs and healthy control dogs. A group of 17 dogs (Border Collies and Greater Swiss Mountain Dogs) with idiopathic epilepsy was compared to 20 healthy control dogs under a standardized sevoflurane anaesthesia protocol. Group level independent component analysis with dimensionality of 20 components, dual regression and two-sample t test were performed and revealed significantly increased functional connectivity in the anterior default mode network of idiopathic epileptic dogs compared to healthy control dogs (p = 0.00060). This group level differences between epileptic dogs and healthy control dogs identified using a rather simple data driven approach could serve as a starting point for more advanced resting state network analysis in epileptic dogs.
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Affiliation(s)
- Katrin M Beckmann
- Section of Neurology, Department of Small Animals, Vetsuisse Faculty Zurich, University of Zurich, Zurich, Switzerland.
| | - Adriano Wang-Leandro
- Clinic for Diagnostic Imaging, Department of Diagnostics and Clinical Services, Vetsuisse-Faculty Zurich, University of Zurich, Zurich, Switzerland
| | - Henning Richter
- Clinic for Diagnostic Imaging, Department of Diagnostics and Clinical Services, Vetsuisse-Faculty Zurich, University of Zurich, Zurich, Switzerland.,Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Rima N Bektas
- Section of Anaesthesiology, Department of Diagnostics and Clinical Services, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland
| | - Frank Steffen
- Section of Neurology, Department of Small Animals, Vetsuisse Faculty Zurich, University of Zurich, Zurich, Switzerland
| | - Matthias Dennler
- Clinic for Diagnostic Imaging, Department of Diagnostics and Clinical Services, Vetsuisse-Faculty Zurich, University of Zurich, Zurich, Switzerland
| | - Ines Carrera
- Willows Veterinary Centre and Referral Service, Highlands Road, Shirley, UK
| | - Sven Haller
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.,Faculty of Medicine, University of Geneva, Geneva, Switzerland
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Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy. Brain Topogr 2021; 34:731-744. [PMID: 34652579 DOI: 10.1007/s10548-021-00875-9] [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: 05/26/2020] [Accepted: 09/28/2021] [Indexed: 10/20/2022]
Abstract
To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.
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8
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Structural and functional motor-network disruptions predict selective action-concept deficits: Evidence from frontal lobe epilepsy. Cortex 2021; 144:43-55. [PMID: 34637999 DOI: 10.1016/j.cortex.2021.08.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 07/12/2021] [Accepted: 08/05/2021] [Indexed: 12/22/2022]
Abstract
Built on neurodegenerative lesions models, the disrupted motor grounding hypothesis (DMGH) posits that motor-system alterations selectively impair action comprehension. However, major doubts remain concerning the dissociability, neural signatures, and etiological generalizability of such deficits. Few studies have compared action-concept outcomes between disorders affecting and sparing motor circuitry, and none has examined their multimodal network predictors via data-driven approaches. Here, we first assessed action- and object-concept processing in patients with frontal lobe epilepsy (FLE), patients with posterior cortex epilepsy (PCE), and healthy controls. Then, we examined structural and functional network signatures via diffusion tensor imaging and resting-state connectivity measures. Finally, we used these measures to predict behavioral performance with an XGBoost machine learning regression algorithm. Relative to controls, FLE (but not PCE) patients exhibited selective action-concept deficits together with structural and functional abnormalities along motor networks. The XGBoost model reached a significantly large effect size only for action-concept outcomes in FLE, mainly predicted by structural (cortico-spinal tract, anterior thalamic radiation, uncinate fasciculus) and functional (M1-parietal/supramarginal connectivity) motor networks. These results extend the DMGH, suggesting that action-concept deficits are dissociable markers of frontal/motor (relative to posterior) disruptions, directly related to the structural and functional integrity of motor networks, and traceable beyond canonical movement disorders.
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9
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Liu W, Yue Q, Gong Q, Zhou D, Wu X. Regional and remote connectivity patterns in focal extratemporal lobe epilepsy. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:1128. [PMID: 34430569 PMCID: PMC8350670 DOI: 10.21037/atm-21-1374] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 05/28/2021] [Indexed: 02/05/2023]
Abstract
Background Focal epilepsy accounts for most epilepsy cases, and frontal lobe epilepsy (FLE) accounts for the largest proportion of cases of extratemporal epilepsy syndrome. The epileptogenic zone is usually not easy to locate, contributing to a lack of imaging studies. The objective of this study was to evaluate functional connectivity patterns to explore the underlying pathological mechanisms of this disorder. Methods Forty-three patients with focal extratemporal epilepsy [mean age ± standard deviation (SD): 29.51±8.04 years, 19 males] and the same number of healthy controls (mean age ± SD: 29.56±8.02 years, 19 males) were recruited to undergo functional magnetic resonance imaging. Mean regional homogeneity (ReHo) was measured, and regions showing significant alterations in ReHo in patients were identified to examine functional connectivity (FC). In particular, FC within the default mode network (DMN) in patients was analyzed. Results Patients with extratemporal lobe epilepsy showed significantly higher ReHo in the bilateral precentral gyrus, and lower ReHo in frontal-cerebellum regions than healthy controls [P<0.05, Gaussian random field (GRF)-corrected]. FC analysis based on regions of interest showed significantly higher connectivity in the frontoparietal-insula region and lowered FC in the frontal-cerebellum regions (P<0.05, GRF-corrected). Altered FC within DMN was also demonstrated (P<0.05, GRF-corrected). Conclusions Analyses of ReHo and FC based on regions of interest suggest epilepsy-related neural networks are located mainly in frontal regions in extratemporal lobe epilepsy. These findings reveal disruptions of interactions and connectivity of large-scale neural networks and frontotemporal-cerebellar regions, suggesting connectivity-based pathophysiology.
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Affiliation(s)
- Wenyu Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiang Yue
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xintong Wu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
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10
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Moguilner S, Birba A, Fino D, Isoardi R, Huetagoyena C, Otoya R, Tirapu V, Cremaschi F, Sedeño L, Ibáñez A, García AM. Multimodal neurocognitive markers of frontal lobe epilepsy: Insights from ecological text processing. Neuroimage 2021; 235:117998. [PMID: 33789131 PMCID: PMC8272524 DOI: 10.1016/j.neuroimage.2021.117998] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/15/2021] [Accepted: 03/24/2021] [Indexed: 01/07/2023] Open
Abstract
The pressing call to detect sensitive cognitive markers of frontal lobe epilepsy (FLE) remains poorly addressed. Standard frameworks prove nosologically unspecific (as they reveal deficits that also emerge across other epilepsy subtypes), possess low ecological validity, and are rarely supported by multimodal neuroimaging assessments. To bridge these gaps, we examined naturalistic action and non-action text comprehension, combined with structural and functional connectivity measures, in 19 FLE patients, 19 healthy controls, and 20 posterior cortex epilepsy (PCE) patients. Our analyses integrated inferential statistics and data-driven machine-learning classifiers. FLE patients were selectively and specifically impaired in action comprehension, irrespective of their neuropsychological profile. These deficits selectively and specifically correlated with (a) reduced integrity of the anterior thalamic radiation, a subcortical structure underlying motoric and action-language processing as well as epileptic seizure spread in this subtype; and (b) hypoconnectivity between the primary motor cortex and the left-parietal/supramarginal regions, two putative substrates of action-language comprehension. Moreover, machine-learning classifiers based on the above neurocognitive measures yielded 75% accuracy rates in discriminating individual FLE patients from both controls and PCE patients. Briefly, action-text assessments, combined with structural and functional connectivity measures, seem to capture ecological cognitive deficits that are specific to FLE, opening new avenues for discriminatory characterizations among epilepsy types.
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Affiliation(s)
- Sebastian Moguilner
- Global Brain Health Institute, UCSF, California, US, & Trinity College Dublin, Dublin, Ireland; Nuclear Medicine School Foundation (FUESMEN), National Commission of Atomic Energy (CNEA), Mendoza, Argentina
| | - Agustina Birba
- University of San Andres, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Daniel Fino
- Nuclear Medicine School Foundation (FUESMEN), National Commission of Atomic Energy (CNEA), Mendoza, Argentina; Fundación Argentina para el Desarrollo en Salud, Mendoza, Argentina
| | - Roberto Isoardi
- Nuclear Medicine School Foundation (FUESMEN), National Commission of Atomic Energy (CNEA), Mendoza, Argentina
| | - Celeste Huetagoyena
- Neuromed, Clinical Neuroscience, Mendoza, Argentina; Universidad Católica Argentina
| | - Raúl Otoya
- Neuromed, Clinical Neuroscience, Mendoza, Argentina
| | - Viviana Tirapu
- Nuclear Medicine School Foundation (FUESMEN), National Commission of Atomic Energy (CNEA), Mendoza, Argentina; Neuromed, Clinical Neuroscience, Mendoza, Argentina
| | - Fabián Cremaschi
- Nuclear Medicine School Foundation (FUESMEN), National Commission of Atomic Energy (CNEA), Mendoza, Argentina; Neuroscience Department of the School of Medicine, National University of Cuyo, Mendoza, Argentina; Santa Isabel de Hungría Hospital, Mendoza, Argentina
| | - Lucas Sedeño
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Agustín Ibáñez
- Global Brain Health Institute, UCSF, California, US, & Trinity College Dublin, Dublin, Ireland; University of San Andres, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile
| | - Adolfo M García
- Global Brain Health Institute, UCSF, California, US, & Trinity College Dublin, Dublin, Ireland; University of San Andres, Buenos Aires, Argentina; National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina; Faculty of Education, National University of Cuyo (UNCuyo), Mendoza, Argentina; Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile.
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11
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Jiang S, Li H, Liu L, Yao D, Luo C. Voxel-wise functional connectivity of the default mode network in epilepsies: a systematic review and meta-analysis. Curr Neuropharmacol 2021; 20:254-266. [PMID: 33823767 PMCID: PMC9199542 DOI: 10.2174/1570159x19666210325130624] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 02/24/2021] [Accepted: 03/18/2021] [Indexed: 11/22/2022] Open
Abstract
Background: Default Mode Network (DMN) is recognized to be involved in the generation and propagation of epileptic activities in various epilepsies. Converging evidence has suggested disturbed Functional Connectivity (FC) in epilepsies, which was inferred to be related to underlying pathological mechanisms. However, abnormal changes of FC in DMN revealed by different studies are controversial, which obscures the role of DMN in distinct epilepsies. Objective: The present work aims to investigate the voxel-wise FC in DMN across epilepsies. Methods: A systematic review was conducted on 22 published articles before October 2020, indexed in PubMed and Web of Science. A meta-analysis with a random-effect model was performed using the effect-size signed differential mapping approach. Subgroup analyses were performed in three groups: Idiopathic Generalized Epilepsy (IGE), mixed Temporal Lobe Epilepsy (TLE), and mixed Focal Epilepsy (FE) with different foci. Results: The meta-analysis suggested commonly decreased FC in mesial prefrontal cortices across different epilepsies. Additionally decreased FC in posterior DMN was observed in IGE. The TLE showed decreased FC in temporal lobe regions and increased FC in the dorsal posterior cingulate cortex. Interestingly, an opposite finding in the ventral and dorsal middle frontal gyrus was observed in TLE. The FE demonstrated increased FC in the cuneus.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Linli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731. China
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12
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Jiang S, Li H, Pei H, Liu L, Li Z, Chen Y, Li X, Li Q, Yao D, Luo C. Connective profiles and antagonism between dynamic and static connectivity underlying generalized epilepsy. Brain Struct Funct 2021; 226:1423-1435. [PMID: 33730218 DOI: 10.1007/s00429-021-02248-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 02/27/2021] [Indexed: 11/28/2022]
Abstract
This study aims to characterize the connective profiles and the coupling relationship between dynamic and static functional connectivity (dFC and sFC) in large-scale brain networks in patients with generalized epilepsy (GE). Functional, structural and diffuse MRI data were collected from 83 patients with GE and 106 matched healthy controls (HC). Resting-state BOLD time course was deconvolved to neural time course using a blind hemodynamic deconvolution method. Then, five connective profiles, including the structural connectivity (SC) and BOLD/neural time course-derived sFC/dFC networks, were constructed based on the proposed whole brain atlas. Network-level weighted correlation probability (NWCP) were proposed to evaluate the association between dFC and sFC. Both the BOLD signal and neural time course showed highly concordant findings and the present study emphasized the consistent findings between two functional approaches. The patients with GE showed hypervariability and enhancement of FC, and notably decreased SC in the subcortical network. Besides, increased dFC, weaker anatomic links, and complex alterations of sFC were observed in the default mode network of GE. Moreover, significantly increased SC and predominantly increased sFC were found in the frontoparietal network. Remarkably, antagonism between dFC and sFC was observed in large-scale networks in HC, while patients with GE showed significantly decreased antagonism in core epileptic networks. In sum, our study revealed distinct connective profiles in different epileptic networks and provided new clues to the brain network mechanism of epilepsy from the perspective of antagonism between dynamic and static functional connectivity.
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Affiliation(s)
- Sisi Jiang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Hechun Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Haonan Pei
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Linli Liu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Zhiliang Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Yan Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Xiangkui Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China
| | - Qifu Li
- Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China.,Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, China.,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China.,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Cheng Luo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China. .,Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China. .,High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, Center for Information in Medicine, University of Electronic Science and Technology of China, Chengdu, People's Republic of China.
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13
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Ueda R, Kaga Y, Takeichi H, Iwasaki M, Takeshita E, Shimizu-Motohashi Y, Ishiyama A, Saito T, Nakagawa E, Sugai K, Sasaki M, Inagaki M. Association between lack of functional connectivity of the frontal brain region and poor response inhibition in children with frontal lobe epilepsy. Epilepsy Behav 2020; 113:107561. [PMID: 33232894 DOI: 10.1016/j.yebeh.2020.107561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 10/07/2020] [Accepted: 10/07/2020] [Indexed: 11/19/2022]
Abstract
PURPOSE We investigated the relationship between electroencephalographic (EEG) functional connectivity and executive function in children with frontal lobe epilepsy (FLE). METHODS We enrolled 24 children with FLE (mean age, 11.0 years; 13 boys) and 22 sex-, age-, and intelligence-matched typically developing children (TDC) to undergo 19-channel EEG during light sleep. We estimated functional connectivity using the phase lag index (PLI) that captures the synchronization of EEG. We also performed continuous performance tests (CPTs) on the children and obtained questionnaire responses on attention deficit hyperactivity disorder and oppositional defiant disorder (ODD). RESULTS The average gamma PLI was lower in the FLE group than in the TDC group, especially between long-distance frontoparietal pairs, between interhemispheric frontal pairs, and between interhemispheric parietotemporal pairs. Gamma PLIs with long-distance frontoparietal and interhemispheric frontal pairs were positively associated with inattention, ODD scores, omission error, and reaction time in the FLE group but not in the TDC group. Conversely, they were negatively associated with age, hyperactivity score, and commission error. CONCLUSIONS A lack of functional connectivity of the frontal brain regions in children with FLE was associated with poor response inhibition.
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Affiliation(s)
- Riyo Ueda
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Yoshimi Kaga
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Hiroshige Takeichi
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Masaki Iwasaki
- Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
| | - Eri Takeshita
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Yuko Shimizu-Motohashi
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Akihiko Ishiyama
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Takashi Saito
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Eiji Nakagawa
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Kenji Sugai
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Masayuki Sasaki
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Masumi Inagaki
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
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14
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Liu W, Yue Q, Wu X, Gong Q, Zhou D. Abnormal blood oxygen level-dependent fluctuations and remote connectivity in sleep-related hypermotor epilepsy. Acta Neurol Scand 2020; 143:514-520. [PMID: 33210736 DOI: 10.1111/ane.13379] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 11/16/2020] [Indexed: 02/05/2023]
Abstract
OBJECTIVE Sleep-related hypermotor epilepsy (SHE) is a form of the epileptic syndrome that involves stereotyped hypermotor seizures and presents as asymmetric tonic or dystonic posturing events. We aimed to investigate the brain activities of SHE patients using structural and functional magnetic resonance imaging (fMRI). METHODS A total of 41 patients with SHE and 41 age- and sex-matched healthy controls (HCs) were prospectively enrolled and assessed using fMRI. The two groups were compared in amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo), and potential correlations between these measures and clinical features were also examined. The involvement of functional network integration was explored by analyzing seed-based functional connectivity. RESULTS In SHE patients, ALFF in the right precentral gyrus was significantly higher than in HCs, and ReHo in the left postcentral and right precentral gyrus was higher. None of the brain regions had lower ALFF or ReHo compared to HCs. ReHo in the left postcentral gyrus and ALFF in the right precentral gyrus were both negatively correlated with epilepsy duration. Patients with SHE had higher functional connectivity mainly in the precuneus, postcentral gyrus, and supplementary motor area. However, none of the brain regions in SHE group presented lower functional connectivity than in HCs. SHE is associated with disrupted regional and interregional functional activities. CONCLUSIONS The patients showed abnormalities within the sensorimotor gyrus and supplementary motor area, suggesting spontaneous fluctuations correlated with remote functional brain network. These results at the whole-brain level argue for further investigation into connectivity disturbance in SHE.
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Affiliation(s)
- Wenyu Liu
- Department of Neurology West China Hospital Sichuan University Chengdu China
| | - Qiang Yue
- Department of Radiology Huaxi MR Research Center (HMRRC) West China Hospital Sichuan University Chengdu China
| | - Xintong Wu
- Department of Neurology West China Hospital Sichuan University Chengdu China
| | - Qiyong Gong
- Department of Radiology Huaxi MR Research Center (HMRRC) West China Hospital Sichuan University Chengdu China
| | - Dong Zhou
- Department of Neurology West China Hospital Sichuan University Chengdu China
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15
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Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach. Neurol Sci 2020; 42:2379-2390. [PMID: 33052576 DOI: 10.1007/s10072-020-04759-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Accepted: 09/23/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE). METHODS Six global graph measures are extracted from static and dynamic functional connectivity matrices using fMRI data of 35 unilateral TLE subjects. Alterations in the time trend of the graph measures are quantified. The random forest (RF) method is used for the determination of feature importance and selection of dynamic graph features including mean, variance, skewness, kurtosis, and Shannon entropy. The selected features are used in the support vector machine (SVM) classifier to identify the left and right epileptogenic sides in patients with TLE. RESULTS Our results for the performance of SVM demonstrate that the utility of dynamic features improves the classification outcome in terms of accuracy (88.5% for dynamic features compared with 82% for static features). Selecting the best dynamic features also elevates the accuracy to 91.5%. CONCLUSION Accounting for the non-stationary characteristics of functional connectivity, dynamic connectivity analysis of graph measures along with machine learning approach can identify the temporal trend of some specific network features. These network features may be used as potential imaging markers in determining the epileptogenic hemisphere in patients with TLE.
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16
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Fang S, Zhou C, Fan X, Jiang T, Wang Y. Epilepsy-Related Brain Network Alterations in Patients With Temporal Lobe Glioma in the Left Hemisphere. Front Neurol 2020; 11:684. [PMID: 32765403 PMCID: PMC7380082 DOI: 10.3389/fneur.2020.00684] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 06/08/2020] [Indexed: 12/12/2022] Open
Abstract
Background: Seizures are a common symptom in patients with temporal lobe gliomas and may result in brain network alterations. However, brain network changes caused by glioma-related epilepsy (GRE) remain poorly understood. Objective: In this study, we applied graph theory analysis to delineate topological networks with resting-state functional magnetic resonance images (rs-fMRI) and investigated characteristics of functional networks in patients with GRE. Methods: Thirty patients with low-grade gliomas in the left temporal lobe were enrolled and classified into GRE (n = 15) and non-GRE groups. Twenty healthy participants matched for age, sex, and education level were enrolled. All participants had rs-fMRI data. Sensorimotor, visual, default mode, auditory, and right executive control networks were used to construct connection matrices. Topological properties of those sub-networks were investigated. Results: Compared to that in the GRE group, four edges with higher functional connectivity were noted in the non-GRE group. Moreover, 21 edges with higher functional connectivity were identified in the non-GRE group compared to the healthy group. All significant alterations in functional edges belong to the visual network. Increased global efficiency and decreased shortest path lengths were noted in the non-GRE group compared to the GRE and healthy groups. Compared with that in the healthy group, nodal efficiency of three nodes was higher in the GRE and non-GRE groups and the degree centrality of six nodes was altered in the non-GRE group. Conclusion: Temporal lobe gliomas in the left hemisphere and GRE altered visual networks in an opposing manner. These findings provide a novel insight into brain network alterations induced by GRE.
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Affiliation(s)
- Shengyu Fang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunyao Zhou
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xing Fan
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
| | - Tao Jiang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Neurosurgical Institute, Beijing, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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17
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Jamali-Dinan SS, Soltanian-Zadeh H, Bowyer SM, Almohri H, Dehghani H, Elisevich K, Nazem-Zadeh MR. A Combination of Particle Swarm Optimization and Minkowski Weighted K-Means Clustering: Application in Lateralization of Temporal Lobe Epilepsy. Brain Topogr 2020; 33:519-532. [PMID: 32347472 DOI: 10.1007/s10548-020-00770-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 04/07/2020] [Indexed: 11/30/2022]
Abstract
K-Means is one of the most popular clustering algorithms that partitions observations into nonoverlapping subgroups based on a predefined similarity metric. Its drawbacks include a sensitivity to noisy features and a dependency of its resulting clusters upon the initial selection of cluster centroids resulting in the algorithm converging to local optima. Minkowski weighted K-Means (MWK-Means) addresses the issue of sensitivity to noisy features, but is sensitive to the initialization of clusters, and so the algorithm may similarly converge to local optima. Particle Swarm Optimization (PSO) uses a globalized search method to solve this issue. We present a hybrid Particle Swarm Optimization (PSO) + MWK-Means clustering algorithm to address all the above problems in a single framework, while maintaining benefits of PSO and MWK Means methods. This study investigated the utility of this approach in lateralizing the epileptogenic hemisphere for temporal lobe epilepsy (TLE) cases using magnetoencephalography (MEG) coherence source imaging (CSI) and diffusion tensor imaging (DTI). Using MEG-CSI, we analyzed preoperative resting state MEG data from 17 adults TLE patients with Engel class I outcomes to determine coherence at 54 anatomical sites and compared the results with 17 age- and gender-matched controls. Fiber-tracking was performed through the same anatomical sites using DTI data. Indices of both MEG coherence and DTI nodal degree were calculated. A PSO + MWK-Means clustering algorithm was applied to identify the side of temporal lobe epileptogenicity and distinguish between normal and TLE cases. The PSO module was aimed at identifying initial cluster centroids and assigning initial feature weights to cluster centroids and, hence, transferring to the MWK-Means module for the final optimal clustering solution. We demonstrated improvements with the use of the PSO + MWK-Means clustering algorithm compared to that of K-Means and MWK-Means independently. PSO + MWK-Means was able to successfully distinguish between normal and TLE in 97.2% and 82.3% of cases for DTI and MEG data, respectively. It also lateralized left and right TLE in 82.3% and 93.6% of cases for DTI and MEG data, respectively. The proposed optimization and clustering methodology for MEG and DTI features, as they relate to focal epileptogenicity, would enhance the identification of the TLE laterality in cases of unilateral epileptogenicity.
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Affiliation(s)
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran.,Research Administration, Radiology, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Susan M Bowyer
- Neurology Departments, Henry Ford Health System, Detroit, MI, 48202, USA
| | - Haidar Almohri
- Department of Industrial and Systems Engineering, Wayne State University, Detroit, MI, USA
| | - Hamed Dehghani
- Medical Physics, and Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Kost Elisevich
- Department of Clinical Neurosciences, Spectrum Health, College of Human Medicine, Michigan State University, Grand Rapids, MI, 49503, USA
| | - Mohammad-Reza Nazem-Zadeh
- Medical Physics, and Biomedical Engineering Department, Tehran University of Medical Sciences (TUMS), Tehran, Iran. .,Research Center for Molecular and Cellular Imaging, Research Center for Science and Technology in Medicine, Tehran University of Medical Sciences (TUMS), Tehran, Iran.
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18
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Alterations in intra- and internetwork functional connectivity associated with levetiracetam treatment in temporal lobe epilepsy. Neurol Sci 2020; 41:2165-2174. [PMID: 32152874 DOI: 10.1007/s10072-020-04322-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 02/29/2020] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Levetiracetam (LEV) is an antiepileptic drug with a novel pharmacological mechanism. Advances in functional magnetic resonance imaging (fMRI) enable researchers to explore the cognitive effects of antiepileptic drugs on the living brain. This study aimed to explore how the functional connectivity patterns of the cognitive networks changed in association with LEV treatment. METHODS Patients with temporal lobe epilepsy (TLE), including both users and nonusers of LEV, were included in this study along with healthy controls. Core cognitive networks were extracted using an independent component analysis approach. Functional connectivity patterns within and between networks were investigated. The relationships between functional connectivity patterns and clinical characteristics were also examined. RESULTS The patterns of intranetwork connectivity in the default mode network (DMN), left executive control network (lECN), and dorsal attention network (DAN) differed among the three groups. The internetwork interactions did not show intergroup differences once corrected for multiple comparisons. No correlation between functional connectivity and clinical characteristics was found in patients with TLE. CONCLUSIONS Changes in intranetwork connectivity are a key effect of LEV administration. SIGNIFICANCE Alterations in intranetwork connectivity patterns may underlie the cognitive effects of LEV administration; this finding improves our understanding of the neural mechanisms of LEV therapy.
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19
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Kamada K, Kapeller C, Takeuchi F, Gruenwald J, Guger C. Tailor-Made Surgery Based on Functional Networks for Intractable Epilepsy. Front Neurol 2020; 11:73. [PMID: 32117032 PMCID: PMC7031351 DOI: 10.3389/fneur.2020.00073] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 01/21/2020] [Indexed: 12/13/2022] Open
Abstract
Normal and pathological networks related to seizure propagation have got attention to elucide complex seizure semiology and contribute to diagnosis and surgical monitoring in epilepsy treatment. Since focal and generalized epileptogenic syndromes abnormalities might involve multiple foci and large-scale networks, we applied electrophysiolpgy (cortco-cortico evoked potential; CCEP), and tractography to make detailed diagnosis for complex syndrome. All 14 epilepsy patients with no or little abnormality on images investigations underwent subdural grid implantation for epilepsy diagnosis. To perform quick network analysis, we recorded and analyzed high gamma activity (HGA) of epileptogenic activity and CCEPs to identify pathological activity distribution and network connectivity. [Results] Pathological CCEPs showed two negative deflections consisting of early (>40 ms) and late (>150 ms) components in electrically stable circumstance at bed side and early CCEPs appeared in 57% of the patients. On the basis of the CCEP findings, tractography detected anatomical connections. Early components of pathological CCEPs diminished after complete disconnection of tractoography-based fibers between the foci in seven of eight cases. One case with residual pathological CCEPs showed poorer outcome. Thirteen (92.8%) patients with or without CCEPs who underwent network surgery had favorable prognosis except for a case with wide traumatic epilepsy. Intraoperative CCEP measurements and HGA mapping enabled visualization of pathological networks and clinical impotence as a biomarker to improve functional prognosis. HGA/CCEP recording should shed light on pathological and complex propagation for epilepsy surgery.
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Affiliation(s)
- Kyousuke Kamada
- Department of Neurosurgery, Megumino Hospital, Eniwa, Japan.,ATR Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Christoph Kapeller
- g.tec Guger Technologies OG/g.tec Medical Engineering GmbH, Schiedlberg, Austria
| | - Fumiya Takeuchi
- Department of Research Promotion Center, Asahikawa Medical University, Asahikawa, Japan
| | - Johannes Gruenwald
- g.tec Guger Technologies OG/g.tec Medical Engineering GmbH, Schiedlberg, Austria
| | - Christoph Guger
- g.tec Guger Technologies OG/g.tec Medical Engineering GmbH, Schiedlberg, Austria
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20
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Wu X, Liu W, Wang W, Gao H, Hao N, Yue Q, Gong Q, Zhou D. Altered intrinsic brain activity associated with outcome in frontal lobe epilepsy. Sci Rep 2019; 9:8989. [PMID: 31222073 PMCID: PMC6586796 DOI: 10.1038/s41598-019-45413-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2018] [Accepted: 06/06/2019] [Indexed: 02/05/2023] Open
Abstract
Frontal lobe epilepsy (FLE) is the second most common type of the focal epilepsies. Our understanding of this disease has been revolutionized over the past decade, but variable treatment outcomes persist and the underlying functional mechanisms responsible for this have yet to be deciphered. This study was designed to determine how intrinsic brain connectivity related to treatment response in patients with FLE. 50 patients with FLE and 28 healthy controls were enrolled in this study and underwent functional MRI at baseline. At the end of 12-month follow up period, all patients with FLE were classified, based on their responses to AEDs treatment, into drug-responsive and drug-refractory groups. The amplitude of low-frequency fluctuation (ALFF) was calculated amongst the three groups in order to detect regional neural function integration. The responsive group showed decreased ALFF only in the left ventromedial prefrontal cortex (vmPFC), while the refractory group showed decreased ALFF in the left vmPFC, right superior frontal gyrus (SFG), and supramarginal gyrus (SMG) relative to healthy controls. In addition, both the responsive and refractory groups showed increased ALFF in the precuneus and postcentral gyrus when compared to the healthy controls. Furthermore, the refractory group exhibited significantly decreased ALFF in the left vmPFC, right SFG and SMG, relative to the responsive group. Focal spontaneous activity, as assessed by ALFF, was associated with response to antiepileptic treatment in patients with FLE. Patients with refractory frontal lobe epilepsy exhibited decreased intrinsic brain activity. Our findings provide novel neuroimaging evidence into the mechanisms of medically-intractable FLE at the brain level.
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Affiliation(s)
- Xintong Wu
- Departments of Neurology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Wenyu Liu
- Departments of Neurology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Weina Wang
- Departments of Radiology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Hui Gao
- Departments of Neurology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Nanya Hao
- Departments of Neurology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Qiang Yue
- Departments of Radiology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China.
| | - Qiyong Gong
- Departments of Radiology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Dong Zhou
- Departments of Neurology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China.
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Jiang LW, Qian RB, Fu XM, Zhang D, Peng N, Niu CS, Wang YH. Altered attention networks and DMN in refractory epilepsy: A resting-state functional and causal connectivity study. Epilepsy Behav 2018; 88:81-86. [PMID: 30243110 DOI: 10.1016/j.yebeh.2018.06.045] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 06/21/2018] [Accepted: 06/21/2018] [Indexed: 12/19/2022]
Abstract
PURPOSE Epilepsy is considered a disorder of neural networks. Patients diagnosed with refractory epilepsy frequently experience attention impairments. Seizure activity in epilepsy may disturb brain networks and damage the brain function of attention. The aims of this study were to assess functional and causal connectivities of the attention networks and default mode network using resting-state functional magnetic resonance imaging (fMRI). METHOD Resting-state fMRI data were gathered from 19 patients with refractory epilepsy (mixed localization and aetiologies) and 21 healthy people. The fMRI data were analyzed by group independent component analysis (ICA) fMRI toolbox to extract dorsal attention network (DAN), ventral attention network (VAN), and default mode network (DMN). The components of the selected networks were compared between patients and healthy controls to explore the change in functional connectivity (FC). Granger causality analysis was performed by taking the aforementioned significant brain areas as regions of interest (ROIs) to calculate autoregression coefficients of each pair of ROIs. Comparisons were done to find the significantly different causal connectivity when FC was changed between patients and healthy controls. RESULTS In DAN, the FC values of the bilateral frontal eye field (FEF) and left intraparietal sulcus (IPS) were decreased. In VAN, the FC values of the double-side ventral prefrontal cortex (vPFC) and the temporoparietal junction (TPJ) were reduced. As for DMN, the FC values of the bilateral medial prefrontal cortices (mPFC) were decreased whereas those for the bilateral precuneus (PCUN) were increased. Granger causal connectivity values were correlated: causal influence was decreased significantly from the left IPS (in DAN) to the double side of the vPFC but remained the same for the right FEF (in DAN) to the right TPJ. The value was decreased from the left PCUN (in DMN) to the right TPJ and FEF, and the causal flow from the right PCUN to the right TPJ and bilateral vPFC was also significantly inhibited (p < 0.05). CONCLUSION Frequent seizures in patients with refractory epilepsy may damage the cortex and disturb DAN, VAN, and DMN, leading to functional and causal connectivity alteration. In addition, epileptic activity may disrupt network interactions and further influence information communication.
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Affiliation(s)
- Lu-Wei Jiang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; School of Neurosurgery, Anhui Medical University, 81 Meishan Road, Hefei, Anhui Province 230032, China
| | - Ruo-Bing Qian
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China.
| | - Xian-Ming Fu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Dong Zhang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Nan Peng
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Chao-Shi Niu
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China
| | - Ye-Han Wang
- Department of Neurosurgery, The First Affiliated Hospital of USTC, Anhui Provincial Hospital Affiliated to Anhui Medical University, 17 Lujiang Road, Hefei, Anhui Province 230001, China; Anhui Provincial Institute of Stereotactic Neurosurgery, 9 Lujiang Road, Hefei, Anhui Province 230001, China
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Bi XA, Zhao J, Xu Q, Sun Q, Wang Z. Abnormal Functional Connectivity of Resting State Network Detection Based on Linear ICA Analysis in Autism Spectrum Disorder. Front Physiol 2018; 9:475. [PMID: 29867534 PMCID: PMC5952255 DOI: 10.3389/fphys.2018.00475] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2017] [Accepted: 04/16/2018] [Indexed: 11/24/2022] Open
Abstract
Some functional magnetic resonance imaging (fMRI) researches in autism spectrum disorder (ASD) patients have shown that ASD patients have significant impairment in brain response. However, few researchers have studied the functional structure changes of the eight resting state networks (RSNs) in ASD patients. Therefore, research on statistical differences of RSNs between 42 healthy controls (HC) and 50 ASD patients has been studied using linear independent component analysis (ICA) in this paper. Our researches showed that there was abnormal functional connectivity (FC) of RSNs in ASD patients. The RSNs with the decreased FC and increased FC in ASD patients included default mode network (DMN), central executive network (CEN), core network (CN), visual network (VN), self-referential network (SRN) compared to HC. The RSNs with the increased FC in ASD patients included auditory network (AN), somato-motor network (SMN). The dorsal attention network (DAN) in ASD patients showed the decreased FC. Our findings indicate that the abnormal FC in RSNs extensively exists in ASD patients. Our results have important contribution for the study of neuro-pathophysiological mechanisms in ASD patients.
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Affiliation(s)
- Xia-An Bi
- College of Mathematics and Computer Science, Hunan Normal University, Changsha, China
| | - Junxia Zhao
- College of Mathematics and Computer Science, Hunan Normal University, Changsha, China
| | - Qian Xu
- College of Mathematics and Computer Science, Hunan Normal University, Changsha, China
| | - Qi Sun
- College of Mathematics and Computer Science, Hunan Normal University, Changsha, China
| | - Zhigang Wang
- College of Mathematics and Computer Science, Hunan Normal University, Changsha, China
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Evangelisti S, Testa C, Ferri L, Gramegna LL, Manners DN, Rizzo G, Remondini D, Castellani G, Naldi I, Bisulli F, Tonon C, Tinuper P, Lodi R. Brain functional connectivity in sleep-related hypermotor epilepsy. NEUROIMAGE-CLINICAL 2017. [PMID: 29527492 PMCID: PMC5842749 DOI: 10.1016/j.nicl.2017.12.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Objectives To evaluate functional connectivity (FC) in patients with sleep-related hypermotor epilepsy (SHE) compared to healthy controls. Methods Resting state fMRI was performed in 13 patients with a clinical diagnosis of SHE (age = 38.3 ± 11.8 years, 6 M) and 13 matched healthy controls (age = 38.5 ± 10.8 years, 6 M). Data were first analysed using probabilistic independent component analysis (ICA), then a graph theoretical approach was applied to assess topological and organizational properties at the whole brain level. We evaluated node degree (ND), betweenness centrality (BC), clustering coefficient (CC), local efficiency (LE) and global efficiency (GE). The differences between the two groups were evaluated non-parametrically. Results At the group level, we distinguished 16 RSNs (Resting State Networks). Patients showed a significantly higher FC in sensorimotor and thalamic regions (p < 0.05 corrected). Compared to controls, SHE patients showed no significant differences in network global efficiency, while ND and BC were higher in regions of the limbic system and lower in the occipital cortex, while CC and LE were higher in regions of basal ganglia and lower in limbic areas (p < 0.05 uncorrected). Discussion and conclusions The higher FC of the sensorimotor cortex and thalamus might be in agreement with the hypothesis of a peculiar excitability of the motor cortex during thalamic K-complexes. This sensorimotor-thalamic hyperconnection might be regarded as a consequence of an alteration of the arousal regulatory system in SHE. An altered topology has been found in structures like basal ganglia and limbic system, hypothesized to be involved in the pathophysiology of the disease as suggested by the dystonic-dyskinetic features and primitive behaviours observed during the seizures. Resting state functional connectivity was studied for the first time in SHE. SHE patients showed higher connectivity in thalamic and motor regions. Motor cortex might show a higher excitability in response to thalamic projections. Brain network topology was altered mainly in basal ganglia and limbic system.
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Affiliation(s)
- Stefania Evangelisti
- Functional MR Unit, Policlinico S.Orsola - Malpighi, via Massarenti 9, 40138, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy
| | - Claudia Testa
- Functional MR Unit, Policlinico S.Orsola - Malpighi, via Massarenti 9, 40138, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy; INFN- National Institute of Nuclear Physics, Bologna, Italy
| | - Lorenzo Ferri
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy; IRCCS Institute of Neurological Sciences of Bologna, via Altura 3, 40139, Bologna, Italy
| | - Laura Ludovica Gramegna
- Functional MR Unit, Policlinico S.Orsola - Malpighi, via Massarenti 9, 40138, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy
| | - David Neil Manners
- Functional MR Unit, Policlinico S.Orsola - Malpighi, via Massarenti 9, 40138, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy
| | - Giovanni Rizzo
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy; IRCCS Institute of Neurological Sciences of Bologna, via Altura 3, 40139, Bologna, Italy
| | - Daniel Remondini
- INFN- National Institute of Nuclear Physics, Bologna, Italy; Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Gastone Castellani
- INFN- National Institute of Nuclear Physics, Bologna, Italy; Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Ilaria Naldi
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy; IRCCS Institute of Neurological Sciences of Bologna, via Altura 3, 40139, Bologna, Italy
| | - Francesca Bisulli
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy; IRCCS Institute of Neurological Sciences of Bologna, via Altura 3, 40139, Bologna, Italy
| | - Caterina Tonon
- Functional MR Unit, Policlinico S.Orsola - Malpighi, via Massarenti 9, 40138, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy
| | - Paolo Tinuper
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy; IRCCS Institute of Neurological Sciences of Bologna, via Altura 3, 40139, Bologna, Italy
| | - Raffaele Lodi
- Functional MR Unit, Policlinico S.Orsola - Malpighi, via Massarenti 9, 40138, Bologna, Italy; Department of Biomedical and NeuroMotor Sciences, University of Bologna, via U. Foscolo 7, 40123, Bologna, Italy.
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Fu CH, Li KS, Ning YZ, Tan ZJ, Zhang Y, Liu HW, Han X, Zou YH. Altered effective connectivity of resting state networks by acupuncture stimulation in stroke patients with left hemiplegia: A multivariate granger analysis. Medicine (Baltimore) 2017; 96:e8897. [PMID: 29382021 PMCID: PMC5709020 DOI: 10.1097/md.0000000000008897] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The aim of this study was to explore the response feature of resting-state networks (RSNs) of stroke patients with left hemiplegia by acupuncture stimulation.Nineteen stroke patients with left hemiplegia and 17 controls were recruited in this study. Resting-state functional magnetic resonance imaging data before and after acupuncture were acquired using magnetic scanning. The independent component analysis (ICA) was employed to extract RSNs related to motion, sensation, cognition, and execution, including sensorimotor network (SMN), left and right frontoparietal network (LFPN and RFPN), anterior and posterior default mode network (aDMN, pDMN), visual network (VN), and salience network (SN). Granger causality method was used to explore how acupuncture stimulation affects the causality between intrinsic RSNs in stroke patients. Compared with healthy subjects, stroke patients presented the more complex effective connectivity. Before acupuncture stimulation, LFPN inputted most information from other networks while DMN outputted most information to other networks; however, the above results were reversal by acupuncture. In addition, we found aDMN reside in between SMN and LFPN after acupuncture.The finding suggested that acupuncture probably integrated the effective connectivity internetwork by modulating multiple networks and transferring information between LFPN and SMN by DMN as the relay station.
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Affiliation(s)
- Cai-Hong Fu
- Department of Neurology and Stroke Center, Dongzhimen Hospital, the First Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
- Shunyi Hospital Affiliated to Beijing Hospital of Traditional Chinese Medicine
| | - Kuang-Shi Li
- Department of Emergency, Beijing GuLou Hospital of Traditional Chinese Medicine
| | - Yan-Zhe Ning
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University
| | - Zhong-Jian Tan
- Department of Radiology, Dongzhimen Hospital, the First Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
| | - Yong Zhang
- Department of Neurology and Stroke Center, Dongzhimen Hospital, the First Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
| | - Hong-Wei Liu
- Department of Neurology and Stroke Center, Dongzhimen Hospital, the First Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
- Shunyi Hospital Affiliated to Beijing Hospital of Traditional Chinese Medicine
| | - Xiao Han
- Department of Neurology and Stroke Center, Dongzhimen Hospital, the First Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
| | - Yi-Huai Zou
- Department of Neurology and Stroke Center, Dongzhimen Hospital, the First Affiliated Hospital of Beijing University of Chinese Medicine, Beijing, China
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Richard AE, Scheffer IE, Wilson SJ. Features of the broader autism phenotype in people with epilepsy support shared mechanisms between epilepsy and autism spectrum disorder. Neurosci Biobehav Rev 2017; 75:203-233. [DOI: 10.1016/j.neubiorev.2016.12.036] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2016] [Revised: 12/15/2016] [Accepted: 12/20/2016] [Indexed: 12/29/2022]
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Dong L, Li H, He Z, Jiang S, Klugah-Brown B, Chen L, Wang P, Tan S, Luo C, Yao D. Altered local spontaneous activity in frontal lobe epilepsy: a resting-state functional magnetic resonance imaging study. Brain Behav 2016; 6:e00555. [PMID: 27843705 PMCID: PMC5102650 DOI: 10.1002/brb3.555] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Revised: 07/11/2016] [Accepted: 08/01/2016] [Indexed: 11/09/2022] Open
Abstract
PURPOSE The purpose of this study was to investigate the local spatiotemporal consistency of spontaneous brain activity in patients with frontal lobe epilepsy (FLE). METHOD Eyes closed resting-state functional magnetic resonance imaging (fMRI) data were collected from 19 FLE patients and 19 age- and gender-matched healthy controls. A novel measure, named FOur-dimensional (spatiotemporal) Consistency of local neural Activities (FOCA) was used to assess the spatiotemporal consistency of local spontaneous activity (emphasizing both local temporal homogeneity and regional stability of brain activity states). Then, two-sample t test was performed to detect the FOCA differences between two groups. Partial correlations between the FOCA values and durations of epilepsy were further analyzed. KEY FINDINGS Compared with controls, FLE patients demonstrated increased FOCA in distant brain regions including the frontal and parietal cortices, as well as the basal ganglia. The decreased FOCA was located in the temporal cortex, posterior default model regions, and cerebellum. In addition, the FOCA measure was linked to the duration of epilepsy in basal ganglia. SIGNIFICANCE Our study suggested that alterations of local spontaneous activity in frontoparietal cortex and basal ganglia was associated with the pathophysiology of FLE; and the abnormality in frontal and default model regions might account for the potential cognitive impairment in FLE. We also presumed that the FOCA measure had potential to provide important insights into understanding epilepsy such as FLE.
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Affiliation(s)
- Li Dong
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Hechun Li
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Zhongqiong He
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Sisi Jiang
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Benjamin Klugah-Brown
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Lin Chen
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Pu Wang
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Song Tan
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education Center for Information in Medicine, 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
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Dong L, Wang P, Peng R, Jiang S, Klugah-Brown B, Luo C, Yao D. Altered basal ganglia-cortical functional connections in frontal lobe epilepsy: A resting-state fMRI study. Epilepsy Res 2016; 128:12-20. [PMID: 27792884 DOI: 10.1016/j.eplepsyres.2016.10.011] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2016] [Revised: 10/05/2016] [Accepted: 10/24/2016] [Indexed: 10/20/2022]
Abstract
OBJECTIVES The purpose of this study was to investigate alterations of basal ganglia-cortical functional connections in patients with frontal lobe epilepsy (FLE). METHOD Resting-state functional magnetic resonance imaging (fMRI) data were gathered from 19 FLE patients and 19 age- and gender-matched healthy controls. Functional connectivity (FC) analysis was used to assess the functional connections between basal ganglia and cerebral cortex. Regions of interest, including the left/right caudate, putamen, pallidum and thalamus, were selected as the seeds. Two sample t-test was used to determine the difference between patients and controls, while controlling the age, gender and head motions. RESULTS Compared with controls, FLE patients demonstrated increased FCs between basal ganglia and regions including the right fusiform gyrus, the bilateral cingulate gyrus, the precuneus and anterior cingulate gyrus. Reduced FCs were mainly located in a range of brain regions including the bilateral middle occipital gyrus, the ventral frontal lobe, the right putamen, the left fusiform gyrus and right rolandic operculum. In addition, the relationships between basal ganglia-cingulate connections and durations of epilepsy were also found. CONCLUSION The alterations of functional integrity within the basal ganglia, as well as its connections to limbic and ventral frontal areas, indicate the important roles of the basal ganglia-cortical functional connections in FLE, and provide new insights in the pathophysiological mechanism of FLE.
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Affiliation(s)
- Li Dong
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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
| | - Pu Wang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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
| | - Rui Peng
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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
| | - Sisi Jiang
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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
| | - Benjamin Klugah-Brown
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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
| | - Cheng Luo
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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.
| | - Dezhong Yao
- Key Laboratory for NeuroInformation of Ministry of Education, Center for Information in Medicine, 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
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Englot DJ, Konrad PE, Morgan VL. Regional and global connectivity disturbances in focal epilepsy, related neurocognitive sequelae, and potential mechanistic underpinnings. Epilepsia 2016; 57:1546-1557. [PMID: 27554793 DOI: 10.1111/epi.13510] [Citation(s) in RCA: 145] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/27/2016] [Indexed: 12/19/2022]
Abstract
Epilepsy is among the most common brain network disorders, and it is associated with substantial morbidity and increased mortality. Although focal epilepsy was traditionally considered a regional brain disorder, growing evidence has demonstrated widespread network alterations in this disorder that extend beyond the epileptogenic zone from which seizures originate. The goal of this review is to summarize recent investigations examining functional and structural connectivity alterations in focal epilepsy, including neuroimaging and electrophysiologic studies utilizing model-based or data-driven analytic methods. A significant subset of studies in both mesial temporal lobe epilepsy and focal neocortical epilepsy have demonstrated patterns of increased connectivity related to the epileptogenic zone, coupled with decreased connectivity in widespread distal networks. Connectivity patterns appear to be related to the duration and severity of disease, suggesting progressive connectivity reorganization in the setting of recurrent seizures over time. Global resting-state connectivity disturbances in focal epilepsy have been linked to neurocognitive problems, including memory and language disturbances. Although it is possible that increased connectivity in a particular brain region may enhance the propensity for seizure generation, it is not clear if global reductions in connectivity represent the damaging consequences of recurrent seizures, or an adaptive mechanism to prevent seizure propagation away from the epileptogenic zone. Overall, studying the connectome in focal epilepsy is a critical endeavor that may lead to improved strategies for epileptogenic-zone localization, surgical outcome prediction, and a better understanding of the neuropsychological implications of recurrent seizures.
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Affiliation(s)
- Dario J Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A..
| | - Peter E Konrad
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A
| | - Victoria L Morgan
- Department of Radiology and Radiological Sciences, Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, U.S.A
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Gleichgerrcht E, Kocher M, Bonilha L. Connectomics and graph theory analyses: Novel insights into network abnormalities in epilepsy. Epilepsia 2015; 56:1660-8. [DOI: 10.1111/epi.13133] [Citation(s) in RCA: 79] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/04/2015] [Indexed: 12/31/2022]
Affiliation(s)
- Ezequiel Gleichgerrcht
- Department of Neurology; Medical University of South Carolina; Charleston South Carolina U.S.A
| | - Madison Kocher
- Department of Neurology; Medical University of South Carolina; Charleston South Carolina U.S.A
| | - Leonardo Bonilha
- Department of Neurology; Medical University of South Carolina; Charleston South Carolina U.S.A
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