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Akbarian B, Sainburg LE, Janson A, Johnson G, Doss DJ, Rogers BP, Englot DJ, Morgan VL. Association Between Postsurgical Functional Connectivity and Seizure Outcome in Patients With Temporal Lobe Epilepsy. Neurology 2024; 103:e209816. [PMID: 39226517 PMCID: PMC11373675 DOI: 10.1212/wnl.0000000000209816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Despite the success of presurgical network connectivity studies in predicting short-term (1-year) seizure outcomes, later seizure recurrence occurs in some patients with temporal lobe epilepsy (TLE). To uncover contributors to this recurrence, we investigated the relationship between functional connectivity and seizure outcomes at different time points after surgery in these patients. METHODS Patients included were clinically diagnosed with unilateral mesial TLE after a standard clinical evaluation and underwent selective amygdalohippocampectomy. Healthy controls had no history of seizures or head injury. Using resting-state fMRI, we assessed the postsurgical functional connectivity node strength, computed as the node's total strength to all other nodes, between seizure-free (Engel Ia-Ib) and nonseizure-free (Engel Ic-IV) acquisitions. The change over time after surgery in different outcome groups in these nodes was also characterized. RESULTS Patients with TLE (n = 32, mean age: 43.1 ± 11.9 years; 46.8% female) and 85 healthy controls (mean age: 37.7 ± 13.5 years; 48.2% female) were included. Resting fMRI was acquired before surgery and at least once after surgery in each patient (range 1-4 scans, 5-60 months). Differences between patients with (n = 30) and without (n = 18) seizure freedom were detected in the posterior insula ipsilateral to the resection (I-PIns: 95% CI -154.8 to -50.1, p = 2.8 × 10-4) and the bilateral central operculum (I-CO: 95% CI -163.2 to -65.1, p = 2.6 × 10-5, C-CO: 95% CI -172.7 to -55.8, p = 2.8 × 10-4). In these nodes, only those who were seizure-free had increased node strength after surgery that increased linearly over time (I-CO: 95% CI 1.0-5.2, p = 4.2 × 10-3, C-CO: 95% CI 1.0-5.2, p = 5.5 × 10-3, I-PIns: 95% CI 1.6-5.5, p = 0.9 × 10-3). Different outcome groups were not distinguished by node strength before surgery. DISCUSSION The findings suggest that network evolution in the first 5 years after selective amygdalohippocampectomy surgery is related to seizure outcomes in TLE. This highlights the need to identify presurgical and surgical conditions that lead to disparate postsurgical trajectories between seizure-free and nonseizure-free patients to identify potential contributors to long-term seizure outcomes. However, the lack of including other surgical approaches may affect the generalizability of the results.
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Affiliation(s)
- Behnaz Akbarian
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Lucas E Sainburg
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Andrew Janson
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Graham Johnson
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Derek J Doss
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Baxter P Rogers
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Dario J Englot
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
| | - Victoria L Morgan
- From the Department of Biomedical Engineering (B.A., L.E.S., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Vanderbilt University; and Vanderbilt University Institute of Imaging Science (B.A., L.E.S., A.J., G.J., D.J.D., B.P.R., D.J.E., V.L.M.), Department of Radiology and Radiological Sciences, and Department of Neurological Surgery (D.J.E., V.L.M.), Vanderbilt University Medical Center, Nashville, TN
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Gong R, Bickel S, Tostaeva G, Lado FA, Metha AD, Kuzniecky RI, Bonilha L, Gleichgerrcht E. Optimizing Surgical Planning for Epilepsy Patients With Multimodal Neuroimaging and Neurophysiology Integration: A Case Study. J Clin Neurophysiol 2024; 41:317-321. [PMID: 38376938 PMCID: PMC11073903 DOI: 10.1097/wnp.0000000000001071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024] Open
Abstract
SUMMARY Current preoperative evaluation of epilepsy can be challenging because of the lack of a comprehensive view of the network's dysfunctions. To demonstrate the utility of our multimodal neurophysiology and neuroimaging integration approach in the presurgical evaluation, we present a proof-of-concept for using this approach in a patient with nonlesional frontal lobe epilepsy who underwent two resective surgeries to achieve seizure control. We conducted a post-hoc investigation using four neuroimaging and neurophysiology modalities: diffusion tensor imaging, resting-state functional MRI, and stereoelectroencephalography at rest and during seizures. We computed region-of-interest-based connectivity for each modality and applied betweenness centrality to identify key network hubs across modalities. Our results revealed that despite seizure semiology and stereoelectroencephalography indicating dysfunction in the right orbitofrontal region, the maximum overlap on the hubs across modalities extended to right temporal areas. Notably, the right middle temporal lobe region served as an overlap hub across diffusion tensor imaging, resting-state functional MRI, and rest stereoelectroencephalography networks and was only included in the resected area in the second surgery, which led to long-term seizure control of this patient. Our findings demonstrated that transmodal hubs could help identify key areas related to epileptogenic network. Therefore, this case presents a promising perspective of using a multimodal approach to improve the presurgical evaluation of patients with epilepsy.
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Affiliation(s)
- Ruxue Gong
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA
| | - Stephan Bickel
- Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Gelana Tostaeva
- Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Fred A. Lado
- Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Ashesh Dinesh Metha
- Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | | | - Leonardo Bonilha
- School of Medicine Columbia, University of South Carolina, Columbia, SC, USA
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Song C, Xie S, Zhang X, Han S, Lian Y, Ma K, Mao X, Zhang Y, Cheng J. Similarities and differences of dynamic and static spontaneous brain activity between left and right temporal lobe epilepsy. Brain Imaging Behav 2024; 18:352-367. [PMID: 38087148 DOI: 10.1007/s11682-023-00835-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/01/2023] [Indexed: 06/07/2024]
Abstract
To comprehensively investigate the potential temporal dynamic and static abnormalities of spontaneous brain activity (SBA) in left temporal lobe epilepsy (LTLE) and right temporal lobe epilepsy (RTLE) and to detect whether these alterations correlate with cognition. Twelve SBA metrics, including ALFF, dALFF, fALFF, dfALFF, ReHo, dReHo, DC, dDC, GSCorr, dGSCorr, VMHC, and dVMHC, in 46 LTLE patients, 43 RTLE patients, and 53 healthy volunteers were compared in the voxel-wise analysis. Correlation analyses between metrics in regions showing statistic differences and epilepsy duration, epilepsy severity, and cognition scores were also performed. Compared with the healthy volunteers, the alteration of SBA was identified both in LTLE and RTLE patients. The ALFF, fALFF, and dALFF values in LTLE, as well as the fALFF values in RTLE, increased in the bilateral thalamus, basal ganglia, mesial temporal lobe, cerebellum, and vermis. Increased dfALFF in the bilateral basal ganglia, increased ReHo and dReHo in the bilateral thalamus in the LTLE group, increased ALFF and dALFF in the pons, and increased ReHo and dReHo in the right hippocampus in the RTLE group were also detected. However, the majority of deactivation clusters were in the ipsilateral lateral temporal lobe. For LTLE, the fALFF, DC, dDC, and GSCorr values in the left lateral temporal lobe and the ReHo and VMHC values in the bilateral lateral temporal lobe all decreased. For RTLE, the ALFF, fALFF, dfALFF, ReHo, dReHo, and DC values in the right lateral temporal lobe and the VMHC values in the bilateral lateral temporal lobe all decreased. Moreover, for both the LTLE and RTLE groups, the dVMHC values decreased in the calcarine cortex. The most significant difference between LTLE and RTLE was the higher activation in the cerebellum of the LTLE group. The alterations of many SBA metrics were correlated with cognition and epilepsy duration. The patterns of change in SBA abnormalities in the LTLE and RTLE patients were generally similar. The integrated application of temporal dynamic and static SBA metrics might aid in the investigation of the propagation and suppression pathways of seizure activity as well as the cognitive impairment mechanisms in TLE.
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Affiliation(s)
- Chengru Song
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Shanshan Xie
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Xiaonan Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Yajun Lian
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Keran Ma
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Xinyue Mao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe Dong Road, Zhengzhou, 450052, China.
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Audrain S, Barnett A, Mouseli P, McAndrews MP. Leveraging the resting brain to predict memory decline after temporal lobectomy. Epilepsia 2023; 64:3061-3072. [PMID: 37643922 DOI: 10.1111/epi.17767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 08/28/2023] [Accepted: 08/28/2023] [Indexed: 08/31/2023]
Abstract
OBJECTIVE Predicting memory morbidity after temporal lobectomy in patients with temporal lobe epilepsy (TLE) relies on indices of preoperative temporal lobe structural and functional integrity. However, epilepsy is increasingly considered a network disorder, and memory a network phenomenon. We assessed the utility of functional network measures to predict postoperative memory changes. METHODS Seventy-two adults with TLE (37 left/35 right) underwent preoperative resting-state functional magnetic resonance imaging and pre- and postoperative neuropsychological assessment. We compared functional connectivity throughout the memory network of each patient to a healthy control template (n = 19) to identify differences in global organization. A second metric indicated the degree of integration of the to-be-resected temporal lobe with the rest of the memory network. We included these measures in a linear regression model alongside standard clinical variables as predictors of memory change after surgery. RESULTS Left TLE patients with more atypical memory networks, and with greater functional integration of the to-be-resected region with the rest of the memory network preoperatively, experienced the greatest decline in verbal memory after surgery. Together, these two measures explained 44% of variance in verbal memory change, outperforming standard clinical and demographic variables. None of the variables examined was associated with visuospatial memory change in patients with right TLE. SIGNIFICANCE Resting-state connectivity provides valuable information concerning both the integrity of to-be-resected tissue and functional reserve across memory-relevant regions outside of the to-be-resected tissue. Intrinsic functional connectivity has the potential to be useful for clinical decision-making regarding memory outcomes in left TLE, and more work is needed to identify the factors responsible for differences seen in right TLE.
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Affiliation(s)
- Sam Audrain
- Division of Clinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Alexander Barnett
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Pedram Mouseli
- Division of Clinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Centre for Multimodal Sensorimotor and Pain Research, Faculty of Dentistry, University of Toronto, Toronto, Ontario, Canada
| | - Mary Pat McAndrews
- Division of Clinical and Computational Neuroscience, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Psychology, University of Toronto, Toronto, Ontario, Canada
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Huang X, Du Y, Guo D, Xie F, Zhou C. Structural-functional coupling abnormalities in temporal lobe epilepsy. Front Neurosci 2023; 17:1272514. [PMID: 37928725 PMCID: PMC10620528 DOI: 10.3389/fnins.2023.1272514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/04/2023] [Indexed: 11/07/2023] Open
Abstract
Background Nowadays, researchers are using advanced multimodal neuroimaging techniques to construct the brain network connectome to elucidate the complex relationship among the networks of brain functions and structure. The objective of this study was to evaluate the coupling of structural connectivity (SC) and functional connectivity (FC) in the entire brain of healthy controls (HCs), and to investigate modifications in SC-FC coupling in individuals suffering from temporal lobe epilepsy (TLE). Methods We evaluated 65 patients with TLE matched for age and gender with 48 healthy controls. The SC-FC coupling between regions was determined, based on which whole-brain nodes were clustered. Differences in the coupling among the three groups of nodes were compared. To further validate the results obtained, the within-cluster coupling indices of the three groups were compared to determine the inter-group differences. Results Nodes were divided into five clusters. Cluster 1 was primarily located in the limbic system (n = 9/27), whereas cluster 5 was mainly within the visual network (n = 12/29). By comparing average cluster SC-FC coupling in each cluster of the three groups, we identified marked discrepancies within the three cohorts in Cluster 3 (p = 0.001), Cluster 4 (p < 0.001), and Cluster 5 (p < 0.001). Post-hoc analysis revealed that the SC-FC coupling strengths in LTLE and RTLE were significantly lower than that in HCs in Cluster 3 (PL = 0.001/PR = 0.003), Cluster 4 (PL = 0.001/PR < 0.001), and Cluster 5 (PL < 0.001/PR < 0.001). We also observed that the within-cluster SC-FC coupling in cluster 5 of left- and right TLE was significantly lower than in HCs (PL = 0.0001, PR = 0.0005). Conclusion The SC and FC are inconsistently coupled across the brain with spatial heterogeneity. In the fifth cluster with the highest degree of coupling in HCs, the average SC-FC coupling index of individuals with TLE was notably less than that of HCs, manifesting that brain regions with high coupling may be more delicate and prone to pathological disruption.
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Affiliation(s)
- Xiaoting Huang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Yangsa Du
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Danni Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, China
| | - Fangfang Xie
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Chunyao Zhou
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China
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da Silveira RV, Li LM, Castellano G. Texture-based brain networks for characterization of healthy subjects from MRI. Sci Rep 2023; 13:16421. [PMID: 37775531 PMCID: PMC10541866 DOI: 10.1038/s41598-023-43544-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 09/25/2023] [Indexed: 10/01/2023] Open
Abstract
Brain networks have been widely used to study the relationships between brain regions based on their dynamics using, e.g. fMRI or EEG, and to characterize their real physical connections using DTI. However, few studies have investigated brain networks derived from structural properties; and those have been based on cortical thickness or gray matter volume. The main objective of this work was to investigate the feasibility of obtaining useful information from brain networks derived from structural MRI, using texture features. We also wanted to verify if texture brain networks had any relation with established functional networks. T1-MR images were segmented using AAL and texture parameters from the gray-level co-occurrence matrix were computed for each region, for 760 subjects. Individual texture networks were used to evaluate the structural connections between regions of well-established functional networks; assess possible gender differences; investigate the dependence of texture network measures with age; and single out brain regions with different texture-network characteristics. Although around 70% of texture connections between regions belonging to the default mode, attention, and visual network were greater than the mean connection value, this effect was small (only between 7 and 15% of these connections were larger than one standard deviation), implying that texture-based morphology does not seem to subside function. This differs from cortical thickness-based morphology, which has been shown to relate to functional networks. Seventy-five out of 86 evaluated regions showed significant (ANCOVA, p < 0.05) differences between genders. Forty-four out of 86 regions showed significant (ANCOVA, p < 0.05) dependence with age; however, the R2 indicates that this is not a linear relation. Thalamus and putamen showed a very unique texture-wise structure compared to other analyzed regions. Texture networks were able to provide useful information regarding gender and age-related differences, as well as for singling out specific brain regions. We did not find a morphological texture-based subsidy for the evaluated functional brain networks. In the future, this approach will be extended to neurological patients to investigate the possibility of extracting biomarkers to help monitor disease evolution or treatment effectiveness.
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Affiliation(s)
- Rafael Vinícius da Silveira
- Department of Cosmic Rays and Chronology, Gleb Wataghin Physics Institute, University of Campinas - UNICAMP, R. Sérgio Buarque de Holanda, 777, Cidade Universitária Zeferino Vaz, Campinas, SP, 13083-859, Brazil.
- Brazilian Institute of Neuroscience and Neurotechnology - BRAINN, Campinas, SP, 13083-887, Brazil.
| | - Li Min Li
- Department of Neurology, School of Medical Sciences, University of Campinas - UNICAMP, R. Tessália Vieira de Camargo, 126, Cidade Universitária Zeferino Vaz, Campinas, SP, 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology - BRAINN, Campinas, SP, 13083-887, Brazil
| | - Gabriela Castellano
- Department of Cosmic Rays and Chronology, Gleb Wataghin Physics Institute, University of Campinas - UNICAMP, R. Sérgio Buarque de Holanda, 777, Cidade Universitária Zeferino Vaz, Campinas, SP, 13083-859, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology - BRAINN, Campinas, SP, 13083-887, Brazil
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Fallahi A, Hashemi-Fesharaki SS, Hoseini-Tabatabaei N, Pooyan M, Nazem-Zadeh MR. Dynamic Functional Connectivity Analysis Using Network-Based Brain State Identification, Application on Temporal Lobe Epilepsy. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38082832 DOI: 10.1109/embc40787.2023.10339957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Epilepsy is a brain network disorder caused by discharges of interconnected groups of neurons and resulting brain dysfunction. The brain network can be characterized by intra- and inter-regional functional connectivity (FC). However, since the BOLD signal is inherently non-stationary, the FC is evidenced to be varying over time. Considering the dynamic characteristics of the functional network, we aimed to obtain dynamic brain states and their properties using network-based analyses for the comparison of healthy control and temporal lobe epilepsy (TLE) groups and also lateralization of TLE patients. We used dwelling time, transition time, and brain network connection in each state as the dynamic features for this purpose. Results showed a significant difference in dwelling time and transition time between the healthy control group and both left TLE and right TLE groups and also a significant difference in brain network connections between the left and right TLE groups.
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Amiri S, Mirfazeli FS, Grafman J, Mohammadsadeghi H, Eftekhar M, Karimzad N, Mohebbi M, Nohesara S. Alternation in functional connectivity within default mode network after psychodynamic psychotherapy in borderline personality disorder. Ann Gen Psychiatry 2023; 22:18. [PMID: 37170093 PMCID: PMC10176869 DOI: 10.1186/s12991-023-00449-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 04/25/2023] [Indexed: 05/13/2023] Open
Abstract
BACKGROUND Borderline personality disorder (BPD) is characterized by impairments in emotion regulation, impulse control, and interpersonal and social functioning along with a deficit in emotional awareness and empathy. In this study, we investigated whether functional connectivity (FC) within the default mode network (DMN) is affected by 1-year psychodynamic psychotherapy in patients with BPD. METHODS Nine BPD patients filled out the demography, Interpersonal Reactive Index (IRI), Toronto Alexithymia Scale 20 (TAS 20), the Alcohol, Smoking, and Substance Involvement Screening Test (ASSIST), and the Borderline Evaluation Severity over Time (BEST) questionnaire. The BPD group (9F) and the control group (9F) had a mean ± SD age of 28.2 ± 5.3 years and 30.4 ± 6.1 years, respectively. BPD subjects underwent longitudinal resting-state fMRI before psychodynamic psychotherapy and then every 4 months for a year after initiating psychotherapy. FC in DMN was characterized by calculating the nodal degree, a measure of centrality in the graph theory. RESULTS The results indicated that patients with BPD present with aberrant DMN connectivity compared to healthy controls. Over a year of psychotherapy, the patients with BPD showed both FC changes (decreasing nodal degree in the dorsal anterior cingulate cortex and increasing in other cingulate cortex regions) and behavioral improvement in their symptoms and substance use. There was also a significant positive association between the decreased nodal degree in regions of the dorsal cingulate cortex and a decrease in the score of the TAS-20 indicating difficulty in identifying feelings after psychotherapy. CONCLUSION In BPD, there is altered FC within the DMN and disruption in self-processing and emotion regulation. Psychotherapy may modify the DMN connectivity and that modification is associated with positive changes in BPD emotional symptoms.
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Affiliation(s)
- Saba Amiri
- Neuroscience Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran
| | - Fatemeh Sadat Mirfazeli
- Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Jordan Grafman
- Department of Physical Medicine & Rehabilitation, Neurology, Cognitive Neurology and Alzheimer's Center, Department of Psychiatry, Feinberg School of Medicine & Department of Psychology, Weinberg College of Arts and Sciences, Northwestern University, Chicago, IL, USA
| | - Homa Mohammadsadeghi
- Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences (IUMS), Tehran, Iran.
| | - Mehrdad Eftekhar
- Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Nazila Karimzad
- Iran Psychiatric Hospital, Iran University of Medical Sciences (IUMS), Tehran, Iran
| | - Maryam Mohebbi
- Islamic Azad University Science and Research Branch Qazvin, Qazvin, Iran
| | - Shabnam Nohesara
- Department of Psychiatry, School of Medicine, Mental Health Research Center, Psychosocial Health Research Institute, Iran University of Medical Sciences (IUMS), Tehran, Iran.
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Lucas A, Mouchtaris S, Cornblath EJ, Sinha N, Caciagli L, Hadar P, Gugger JJ, Das S, Stein JM, Davis KA. Subcortical functional connectivity gradients in temporal lobe epilepsy. Neuroimage Clin 2023; 38:103418. [PMID: 37187042 PMCID: PMC10196948 DOI: 10.1016/j.nicl.2023.103418] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 04/20/2023] [Accepted: 04/22/2023] [Indexed: 05/17/2023]
Abstract
BACKGROUND AND MOTIVATION Functional gradients have been used to study differences in connectivity between healthy and diseased brain states, however this work has largely focused on the cortex. Because the subcortex plays a key role in seizure initiation in temporal lobe epilepsy (TLE), subcortical functional-connectivity gradients may help further elucidate differences between healthy brains and TLE, as well as differences between left (L)-TLE and right (R)-TLE. METHODS In this work, we calculated subcortical functional-connectivity gradients (SFGs) from resting-state functional MRI (rs-fMRI) by measuring the similarity in connectivity profiles of subcortical voxels to cortical gray matter voxels. We performed this analysis in 24 R-TLE patients and 31 L-TLE patients (who were otherwise matched for age, gender, disease specific characteristics, and other clinical variables), and 16 controls. To measure differences in SFGs between L-TLE and R-TLE, we quantified deviations in the average functional gradient distributions, as well as their variance, across subcortical structures. RESULTS We found an expansion, measured by increased variance, in the principal SFG of TLE relative to controls. When comparing the gradient across subcortical structures between L-TLE and R-TLE, we found that abnormalities in the ipsilateral hippocampal gradient distributions were significantly different between L-TLE and R-TLE. CONCLUSION Our results suggest that expansion of the SFG is characteristic of TLE. Subcortical functional gradient differences exist between left and right TLE and are driven by connectivity changes in the hippocampus ipsilateral to the seizure onset zone.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania, United States; Department of Bioengineering, University of Pennsylvania, United States.
| | - Sofia Mouchtaris
- Department of Bioengineering, University of Pennsylvania, United States
| | - Eli J Cornblath
- Department of Neurology, University of Pennsylvania, United States
| | - Nishant Sinha
- Department of Neurology, University of Pennsylvania, United States
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, United States
| | - Peter Hadar
- Department of Neurology, Massachusetts General Hospital, United States
| | - James J Gugger
- Department of Neurology, University of Pennsylvania, United States
| | - Sandhitsu Das
- Department of Neurology, University of Pennsylvania, United States
| | - Joel M Stein
- Department of Radiology, University of Pennsylvania, United States
| | - Kathryn A Davis
- Department of Neurology, University of Pennsylvania, United States
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Lucas A, Mouchtaris S, Cornblath EJ, Sinha N, Caciagli L, Hadar P, Gugger JJ, Das S, Stein JM, Davis KA. Subcortical Functional Connectivity Gradients in Temporal Lobe Epilepsy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.08.23284313. [PMID: 36711498 PMCID: PMC9882434 DOI: 10.1101/2023.01.08.23284313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background and Motivation Functional gradients have been used to study differences in connectivity between healthy and diseased brain states, however this work has largely focused on the cortex. Because the subcortex plays a key role in seizure initiation in temporal lobe epilepsy (TLE), subcortical functional-connectivity gradients may help further elucidate differences between healthy brains and TLE, as well as differences between left (L)-TLE and right (R)-TLE. Methods In this work, we calculated subcortical functional-connectivity gradients (SFGs) from resting-state functional MRI (rs-fMRI) by measuring the similarity in connectivity profiles of subcortical voxels to cortical gray matter voxels. We performed this analysis in 23 R-TLE patients and 32 L-TLE patients (who were otherwise matched for age, gender, disease specific characteristics, and other clinical variables), and 16 controls. To measure differences in SFGs between L-TLE and R-TLE, we quantified deviations in the average functional gradient distributions, as well as their variance, across subcortical structures. Results We found an expansion, measured by increased variance, in the principal SFG of TLE relative to controls. When comparing the gradient across subcortical structures between L-TLE and R-TLE, we found that abnormalities in the ipsilateral hippocampal gradient distributions were significantly different between L-TLE and R-TLE. Conclusion Our results suggest that expansion of the SFG is characteristic of TLE. Subcortical functional gradient differences exist between left and right TLE and are driven by connectivity changes in the hippocampus ipsilateral to the seizure onset zone.
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Affiliation(s)
- Alfredo Lucas
- Perelman School of Medicine, University of Pennsylvania,Department of Bioengineering, University of Pennsylvania
| | | | | | | | | | - Peter Hadar
- Department of Neurology, Massachusetts General Hospital
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11
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Gholipour T, You X, Stufflebeam SM, Loew M, Koubeissi MZ, Morgan VL, Gaillard WD. Common functional connectivity alterations in focal epilepsies identified by machine learning. Epilepsia 2022; 63:629-640. [PMID: 34984672 PMCID: PMC9022014 DOI: 10.1111/epi.17160] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/20/2021] [Accepted: 12/21/2021] [Indexed: 02/04/2023]
Abstract
OBJECTIVE This study was undertaken to identify shared functional network characteristics among focal epilepsies of different etiologies, to distinguish epilepsy patients from controls, and to lateralize seizure focus using functional connectivity (FC) measures derived from resting state functional magnetic resonance imaging (MRI). METHODS Data were taken from 103 adult and 65 pediatric focal epilepsy patients (with or without lesion on MRI) and 109 controls across four epilepsy centers. We used three whole-brain FC measures: parcelwise connectivity matrix, mean FC, and degree of FC. We trained support vector machine models with fivefold cross-validation (1) to distinguish patients from controls and (2) to lateralize the hemisphere of seizure onset in patients. We reported the regions and connections with the highest importance from each model as the common FC differences between the compared groups. RESULTS FC measures related to the default mode and limbic networks had higher importance relative to other networks for distinguishing epilepsy patients from controls. In lateralization models, regions related to somatosensory, visual, default mode, and basal ganglia showed higher importance. The epilepsy versus control classification model trained using a 400-parcel connectivity matrix achieved a median testing accuracy of 75.6% (median area under the curve [AUC] = .83) in repeated independent testing. Lateralization accuracy using the 400-parcel connectivity matrix reached a median accuracy of 64.0% (median AUC = .69). SIGNIFICANCE Machine learning models revealed common FC alterations in a heterogeneous group of patients with focal epilepsies. The distribution of the most altered regions supports the hypothesis that shared functional alteration exists beyond the seizure onset zone and its epileptic network. We showed that FC measures can distinguish patients from controls, and further lateralize focal epilepsies. Future studies are needed to confirm these findings by using larger numbers of epilepsy patients.
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Affiliation(s)
- Taha Gholipour
- Department of Neurology, George Washington University, Washington, District of Columbia, USA.,Center for Neuroscience, Children's National Hospital, Washington, District of Columbia, USA.,Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Xiaozhen You
- Center for Neuroscience, Children's National Hospital, Washington, District of Columbia, USA
| | - Steven M Stufflebeam
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Murray Loew
- Department of Biomedical Engineering, George Washington University, Washington, District of Columbia, USA
| | - Mohamad Z Koubeissi
- Department of Neurology, George Washington University, Washington, District of Columbia, USA
| | | | - William D Gaillard
- Department of Neurology, George Washington University, Washington, District of Columbia, USA.,Center for Neuroscience, Children's National Hospital, Washington, District of Columbia, USA
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12
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Zhao X, Kang H, Zhou Z, Hu Y, Li J, Li S, Li J, Zhu W. Interhemispheric functional connectivity asymmetry is distinctly affected in left and right mesial temporal lobe epilepsy. Brain Behav 2022; 12:e2484. [PMID: 35166072 PMCID: PMC8933759 DOI: 10.1002/brb3.2484] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 11/15/2021] [Accepted: 12/14/2021] [Indexed: 11/09/2022] Open
Abstract
INTRODUCTION The differences of functional connectivity (FC) and functional asymmetry between left and right mesial temporal lobe epilepsy with hippocampal sclerosis (LMTLE and RMTLE) have not been completely clarified yet. The purpose of the present study is to investigate the FC changes and the FC asymmetric patterns of MTLE, and to compare the differences in FC and functional asymmetry between LMTLE and RMTLE. METHODS In total, 12 LMTLE, 11 RMTLE patients, and 23 healthy controls (HC) were included. Region of interest (ROI)-based analysis was used to evaluate FC. The right functional connectivity (rFC) and left functional connectivity (lFC) of each ROI were calculated. Asymmetry index (AI) was calculated based on the following formula: AI=100×(rFC-lFC)/[(rFC+lFC)/2]${\rm{AI\ }} = {\rm{\ }}100{\rm{\ }} \times {\rm{\ }}( {{\rm{rFC}} - {\rm{lFC}}} )/[ {( {{\rm{rFC}} + {\rm{lFC}}} )/2} ]$ . Paired t-test and univariate analysis of variance were used to analyze FC asymmetry. Linear correlation analysis was performed between significant FC changes and lateralized ROIs and epilepsy onset age and duration. RESULTS LMTLE and RMTLE patients showed different patterns of alteration in FC and functional asymmetry when compared with controls. RMTLE presented more extensive FC abnormalities than LMTLE. Regions in ipsilateral temporal lobe presented as central regions of abnormalities in both patient groups. In addition, the asymmetric characteristics of FC were reduced in MTLE compared with HC, with even more pronounced reduction for RMTLE group. Meanwhile, ROIs presented FC AI differences among the three groups were mostly involving left temporal lobe (L_hippo, L_amyg, L_TP, L_aMTG, and L_pTFusC). No correlation was found between significant FC changes and lateralized ROIs and epilepsy onset age and duration. CONCLUSION The FC and asymmetric features of MTLE are altered and involve both the temporal lobe and extra-temporal lobe. Furthermore, the altered FC and asymmetric features were distinctly affected in LMTLE and RMTLE compared to controls.
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Affiliation(s)
- Xu Zhao
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huicong Kang
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhiqiang Zhou
- Department of Anesthesiology and Pain Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Juan Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jia Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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Fallahi A, Pooyan M, Habibabadi JM, Hashemi-Fesharaki SS, Tabatabaei NH, Ay M, Nazem-Zadeh MR. A novel approach for extracting functional brain networks involved in mesial temporal lobe epilepsy based on self organizing maps. INFORMATICS IN MEDICINE UNLOCKED 2022. [DOI: 10.1016/j.imu.2022.100876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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14
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Gautham BK, Mukherjee J, Narayanan M, Kenchaiah R, Mundlamuri RC, Asranna A, Lakshminarayanapuram VG, Bharath RD, Saini J, Nagaraj C, Mangalore S, Kulanthaivelu K, Sadashiva N, Mahadevan A, Rajan J, Kumar K, Arimappamagan A, Malla BR, Sinha S. Automated lateralization of temporal lobe epilepsy with cross frequency coupling using magnetoencephalography. Biomed Signal Process Control 2022. [DOI: 10.1016/j.bspc.2021.103294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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15
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Pang X, Liang X, Zhao J, Wu P, Li X, Wei W, Nie L, Chang W, Lv Z, Zheng J. Abnormal Static and Dynamic Functional Connectivity in Left and Right Temporal Lobe Epilepsy. Front Neurosci 2022; 15:820641. [PMID: 35126048 PMCID: PMC8813030 DOI: 10.3389/fnins.2021.820641] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 12/28/2021] [Indexed: 12/13/2022] Open
Abstract
Objective Temporal lobe epilepsy (TLE) can be conceptualized as a network disease. However, the network characteristics in lateralization remain controversial. Methods In this study, resting-state functional MRI scans were acquired from 53 TLE patients [22 with left-side TLE (LTLE) and 31 with right-side TLE (RTLE)] and 37 matched healthy controls. We focused on the characteristics of static and dynamic functional connectivity, including static connectivity patterns and topological properties, as well as temporal properties of the dynamic connectivity state and the variability of the dynamic connectivity and network topological organization. Correlation analyses were conducted between abnormal static and dynamic properties and cognitive performances. Results The static functional connectivity analysis presented a significantly decreased cortical-cortical connectivity pattern and increased subcortical-cortical connectivity pattern in RTLE. The global-level network in RTLE showed a significant decrease in global efficiency. The dynamic functional connectivity analysis revealed that RTLE patients exhibited aberrant connectivity states, as well as increased variability in the subcortical-cortical connectivity. The global-level network in RTLE revealed increased variance in global efficiency and local efficiency. The static or dynamic functional connectivity in LTLE did not show any significant abnormalities. The altered dynamic properties were associated with worsening cognitive performance in language and conceptual thinking by the TLE patients. Conclusion Our findings demonstrated the presence of abnormalities in the static and dynamic functional connectivity of TLE patients. RTLE patients exhibited more pronounced aberrant connectivity patterns and topological properties, which might represent a mechanism for reconfiguration of brain networks in RTLE patients. These observations extended our understanding of the pathophysiological network mechanisms of TLE.
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Nie L, Jiang Y, Lv Z, Pang X, Liang X, Chang W, Zheng J. A study of brain functional network and alertness changes in temporal lobe epilepsy with and without focal to bilateral tonic-clonic seizures. BMC Neurol 2022; 22:14. [PMID: 34996377 PMCID: PMC8740350 DOI: 10.1186/s12883-021-02525-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 12/13/2021] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Temporal lobe epilepsy (TLE) is commonly refractory. Epilepsy surgery is an effective treatment strategy for refractory epilepsy, but patients with a history of focal to bilateral tonic-clonic seizures (FBTCS) have poor outcomes. Previous network studies on epilepsy have found that TLE and idiopathic generalized epilepsy with generalized tonic-clonic seizures (IGE-GTCS) showed altered global and nodal topological properties. Alertness deficits also were found in TLE. However, FBTCS is a common type of seizure in TLE, and the implications for alertness as well as the topological rearrangements associated with this seizure type are not well understood. METHODS We obtained rs-fMRI data and collected the neuropsychological assessment data from 21 TLE patients with FBTCS (TLE- FBTCS), 18 TLE patients without FBTCS (TLE-non- FBTCS) and 22 controls, and constructed their respective functional brain networks. The topological properties were analyzed using the graph theoretical approach and correlations between altered topological properties and alertness were analyzed. RESULTS We found that TLE-FBTCS patients showed more serious impairment in alertness effect, intrinsic alertness and phasic alertness than the patients with TLE-non-FBTCS. They also showed significantly higher small-worldness, normalized clustering coefficient (γ) and a trend of higher global network efficiency (gE) compared to TLE-non-FBTCS patients. The gE showed a significant negative correlation with intrinsic alertness for TLE-non-FBTCS patients. CONCLUSION Our findings show different impairments in brain network information integration, segregation and alertness between the patients with TLE-FBTCS and TLE-non-FBTCS, demonstrating that impairments of the brain network may underlie the disruptions in alertness functions.
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Affiliation(s)
- Liluo Nie
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China
| | - Yanchun Jiang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China
| | - Zongxia Lv
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China
| | - Xiaomin Pang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China
| | - Xiulin Liang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China
| | - Weiwei Chang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China
| | - Jinou Zheng
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, No.6, Shuangyong Road, Nanning, 530021, China.
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17
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Chu Y, Wu J, Wang D, Huang J, Li W, Zhang S, Ren H. Altered voxel-mirrored homotopic connectivity in right temporal lobe epilepsy as measured using resting-state fMRI and support vector machine analyses. Front Psychiatry 2022; 13:958294. [PMID: 35958657 PMCID: PMC9360423 DOI: 10.3389/fpsyt.2022.958294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 06/28/2022] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Prior reports revealed abnormalities in voxel-mirrored homotopic connectivity (VMHC) when analyzing neuroimaging data from patients with various psychiatric conditions, including temporal lobe epilepsy (TLE). Whether these VHMC changes can be leveraged to aid in the diagnosis of right TLE (rTLE), however, remains to be established. This study was thus developed to examine abnormal VMHC findings associated with rTLE to determine whether these changes can be used to guide rTLE diagnosis. METHODS The resultant imaging data of resting-state functional MRI (rs-fMRI) analyses of 59 patients with rTLE and 60 normal control individuals were analyzed using VMHC and support vector machine (SVM) approaches. RESULTS Relative to normal controls, patients with rTLE were found to exhibit decreased VMHC values in the bilateral superior and the middle temporal pole (STP and MTP), the bilateral middle and inferior temporal gyri (MTG and ITG), and the bilateral orbital portion of the inferior frontal gyrus (OrbIFG). These patients further exhibited increases in VMHC values in the bilateral precentral gyrus (PreCG), the postcentral gyrus (PoCG), and the supplemental motor area (SMA). The ROC curve of MTG VMHC values showed a great diagnostic efficacy in the diagnosis of rTLE with AUCs, sensitivity, specificity, and optimum cutoff values of 0.819, 0.831, 0.717, and 0.465. These findings highlight the value of the right middle temporal gyrus (rMTG) when differentiating between rTLE and control individuals, with a corresponding SVM analysis yielding respective accuracy, sensitivity, and specificity values of 70.59% (84/119), 78.33% (47/60), and 69.49% (41/59). CONCLUSION In summary, patients with rTLE exhibit various forms of abnormal functional connectivity, and SVM analyses support the potential value of abnormal VMHC values as a neuroimaging biomarker that can aid in the diagnosis of this condition.
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Affiliation(s)
- Yongqiang Chu
- Department of Imaging Center, Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, China.,Key Laboratory of Occupational Hazards and Identification, Wuhan University of Science and Technology, Wuhan, China
| | - Jun Wu
- Department of Neurosurgery, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Du Wang
- Department of Imaging Center, Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Junli Huang
- Department of Imaging Center, Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, China
| | - Wei Li
- Department of Otolaryngology-Head and Neck Surgery, Wuhan Asia General Hospital, Wuhan, China
| | - Sheng Zhang
- Department of Psychiatry, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hongwei Ren
- Department of Imaging Center, Tianyou Hospital, Affiliated to Wuhan University of Science and Technology, Wuhan, China
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Slinger G, Otte WM, Braun KPJ, van Diessen E. An updated systematic review and meta-analysis of brain network organization in focal epilepsy: Looking back and forth. Neurosci Biobehav Rev 2021; 132:211-223. [PMID: 34813826 DOI: 10.1016/j.neubiorev.2021.11.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 06/23/2021] [Accepted: 11/17/2021] [Indexed: 01/10/2023]
Abstract
Abnormalities of the brain network organization in focal epilepsy have been extensively quantified. However, the extent and directionality of abnormalities are highly variable and subtype insensitive. We conducted meta-analyses to obtain a more accurate and epilepsy type-specific quantification of the interictal global brain network organization in focal epilepsy. By using random-effects models, we estimated differences in average clustering coefficient, average path length, and modularity between patients with focal epilepsy and controls, based on 45 studies with a total sample size of 1,468 patients and 1,021 controls. Structural networks had a significant lower level of integration in patients with epilepsy as compared to controls, with a standardized mean difference of -0.334 (95 % confidence interval -0.631 to -0.038; p-value 0.027). Functional networks did not differ between patients and controls, except for the beta band clustering coefficient. Our meta-analyses show that differences in the brain network organization are not as well defined as individual studies often propose. We discuss potential pitfalls and suggestions to enhance the yield and clinical value of network studies.
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Affiliation(s)
- Geertruida Slinger
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.
| | - Willem M Otte
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Kees P J Braun
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Eric van Diessen
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
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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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Tan G, Li X, Wang H, Chen D, Zhu L, Xiao H, Gong Q, Liu L. Brain function and network features in patients with chronic epilepsy before and after antiseizure medication withdrawal. Epilepsy Res 2021; 176:106740. [PMID: 34419771 DOI: 10.1016/j.eplepsyres.2021.106740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 06/28/2021] [Accepted: 08/12/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES A considerable proportion of epilepsy patients who achieved long-term seizure freedom with standardized treatment of antiseizure medication will attempt to withdraw medications. Epilepsy is currently considered as a network disease, however, the characteristics of brain function and neural network before and after medication withdrawal remain to be discovered. METHODS Resting-state functional magnetic resonance imaging was obtained for 32 healthy controls, 32 seizure-free patients initiating medication tapering (PG1 group), and 16 seizure-free patients that had completely discontinued medications (PG2 group). Amplitude of low-frequency fluctuation and regional homogeneity were calculated to measure local functional activity. Global and nodal metrics of small-world network were calculated based on Graph theory. One-way analysis of variance was applied to analyze intergroup difference, withpost hoc analysis being conducted for each pair of groups. RESULTS Sex, age at scanning and other clinical variables showed no significant difference between groups. As compared to control, the amplitude of low-frequency fluctuation, regional homogeneity or nodal metrics of neural network in some brain areas were abnormal in the PG1 or PG2 group; when compared between patient groups, significant between-group differences were also found in the amplitude of low-frequency fluctuation, regional homogeneity or nodal metrics. But, the global metrics of neural network showed no differences among groups. CONCLUSIONS The global metrics of patients with long-term seizure freedom were normal either before or after antiseizure medication withdrawal, while the local functional activity and nodal metrics in some brain areas were abnormal and differed between before and after antiseizure medication withdrawal.
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Affiliation(s)
- Ge Tan
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China
| | - Xiuli Li
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China
| | - Haijiao Wang
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China
| | - Deng Chen
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China
| | - Lina Zhu
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China
| | - Hong Xiao
- Department of Pain Management, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China.
| | - Qiyong Gong
- Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China.
| | - Ling Liu
- Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu, 610041, Sichuan Province, China.
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Li Y, Zhu H, Chen Q, Yang L, Bao X, Chen F, Ma H, Xu H, Luo L, Zhang R. Evaluation of Brain Network Properties in Patients with MRI-Negative Temporal Lobe Epilepsy: An MEG Study. Brain Topogr 2021; 34:618-631. [PMID: 34173926 DOI: 10.1007/s10548-021-00856-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 06/13/2021] [Indexed: 11/25/2022]
Abstract
Abnormal functional brain networks of temporal lobe epilepsy (TLE) patients with structural abnormalities may partially reflect structural lesions rather than either TLE per se or functional compensatory processes. In this study, we sought to investigate the brain-network properties of intractable TLE patients apart from the effects of structural abnormalities. The brain network properties of 20 left and 23 right MRI-negative TLE patients and 22 healthy controls were evaluated using magnetoencephalographic recordings in six main frequency bands. A slowing of oscillatory brain activity was observed for the left or right TLE group vs. healthy controls. The TLE groups presented significantly increased functional connectivity in the delta, theta, lower alpha and beta bands, and significantly greater values in the normalized clustering coefficient and path length, and significantly smaller values in the weighted small-world measure in the theta band when compared to healthy controls. Alterations in global and regional band powers can be attributed to spectral slowing in TLE patients. The brain networks of TLE patients displayed abnormally high synchronization in multi-frequency bands and shifted toward a more regular architecture with worse network efficiency in the theta band. Without the contamination of structural lesions, these significant findings can be helpful for better understanding of the pathophysiological mechanism of TLE. The theta band can be considered as a preferred frequency band for investigating the brain-network dysfunction of MRI-negative intractable TLE patients.
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Affiliation(s)
- Yuejun Li
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Magnetoencephalography, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Haitao Zhu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Qiqi Chen
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
- Department of Magnetoencephalography, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Lu Yang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Xincai Bao
- Library of Xinxiang Medical University, Xinxiang, 453003, Henan, China
| | - Fangqing Chen
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Haiyan Ma
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Honghao Xu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Lei Luo
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China
| | - Rui Zhang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, 210029, Jiangsu, China.
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22
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Pan JW, Antony A, Tal A, Yushmanov V, Fong J, Richardson M, Schirda C, Bagic A, Gonen O, Hetherington HP. MR spectroscopic imaging at 3 T and outcomes in surgical epilepsy. NMR IN BIOMEDICINE 2021; 34:e4492. [PMID: 33751687 PMCID: PMC8122073 DOI: 10.1002/nbm.4492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 01/23/2021] [Indexed: 05/09/2023]
Abstract
For the spectroscopic assessment of brain disorders that require large-volume coverage, the requirements of RF performance and field homogeneity are high. For epilepsy, this is also challenging given the inter-patient variation in location, severity and subtlety of anatomical identification and its tendency to involve the temporal region. We apply a targeted method to examine the utility of large-volume MR spectroscopic imaging (MRSI) in surgical epilepsy patients, implementing a two-step acquisition, comprised of a 3D acquisition to cover the fronto-parietal regions, and a contiguous parallel two-slice Hadamard-encoded acquisition to cover the temporal-occipital region, both with TR /TE = 2000/40 ms and matched acquisition times. With restricted (static, first/second-order) B0 shimming in their respective regions, the Cramér-Rao lower bounds for creatine from the temporal lobe two-slice Hadamard and frontal-parietal 3D acquisition are 8.1 ± 2.2% and 6.3 ± 1.9% respectively. The datasets are combined to provide a total 60 mm axial coverage over the frontal, parietal and superior temporal to middle temporal-occipital regions. We applied these acquisitions at a nominal 400 mm3 voxel resolution in n = 27 pre-surgical epilepsy patients and n = 20 controls. In controls, 86.6 ± 3.2% voxels with at least 50% tissue (white + gray matter, excluding CSF) survived spectral quality inclusion criteria. Since all patients were clinically followed for at least 1 year after surgery, seizure frequency outcome was available for all. The MRSI measurements of the total fractional metabolic dysfunction (characterized by the Cr/NAA metric) in FreeSurfer MRI gray matter segmented regions, in the patients compared with the controls, exhibited a significant Spearman correlation with post-surgical outcome. This finding suggests that a larger burden of metabolic dysfunction is seen in patients with poorer post-surgical seizure control.
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Affiliation(s)
- Jullie W Pan
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Arun Antony
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Assaf Tal
- Department of Chemical and Biological Physics, Weizmann Institute, Rehovot, Israel
| | - Victor Yushmanov
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Joanna Fong
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Mark Richardson
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Claud Schirda
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Anto Bagic
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Oded Gonen
- Department of Radiology, New York University, New York, New York
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23
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Factors affecting interictal unilateral and bilateral discharges and ictal diffusion patterns of scalp electroencephalogram in temporal lobe epilepsy. Neurol Sci 2021; 43:507-515. [PMID: 33942172 DOI: 10.1007/s10072-021-05293-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 04/26/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND The interictal discharges of temporal lobe epilepsy (TLE) can be unilateral or bilateral. In addition, the ictal electroencephalogram (EEG) showed the discharges also tend to spread to the contralateral brain in TLE. OBJECTIVE The factors influencing unilateral and bilateral interictal discharges in TLE as well as ictal diffusion patterns in scalp EEG during onset of seizure were evaluated in the present study. MATERIALS AND METHODS This was a retrospective analysis of 129 patients with TLE. Cases were classified into unilateral and bilateral discharge groups based on interictal discharge patterns in the EEG. Differences between the two groups in age, gender, disease duration, seizure frequency, magnetic resonance imaging (MRI) findings, origin of TLE, antiepileptic drug (AED) administration, and ictal diffusion patterns during seizures were statistically analyzed. In addition, the differences in ictal diffusion patterns between left and right TLE were statistically analyzed. RESULTS Statistically significant differences were not observed in gender, disease duration, seizure frequency, MRI findings, administration of AEDs, and ictal diffusion patterns between interictal unilateral and bilateral discharge groups but with statistically significant differences in age and side of origin of the TLE. In addition, whether the EEG-recorded diffusion pattern was confined to the same hemisphere or spread to both hemispheres was investigated and shown statistically significant differences between the left and right temporal lobes. CONCLUSIONS Age and side of origin of TLE affects the TLE interictal discharge patterns. Older patients are more prone to bilateral discharges. Bilateral discharges are more common in right TLE, and the onset of EEG more likely to bilateral diffusion in right TLE.
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24
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Drenthen GS, Jansen JFA, Gommer E, Gupta L, Hofman PAM, van Kranen-Mastenbroek VH, Hilkman DM, Vlooswijk MCG, Rouhl RPW, Backes WH. Predictive value of functional MRI and EEG in epilepsy diagnosis after a first seizure. Epilepsy Behav 2021; 115:107651. [PMID: 33309424 DOI: 10.1016/j.yebeh.2020.107651] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Revised: 11/18/2020] [Accepted: 11/18/2020] [Indexed: 02/07/2023]
Abstract
It is often difficult to predict seizure recurrence in subjects who have suffered a first-ever epileptic seizure. In this study, the predictive value of physiological signals measured using Electroencephalography (EEG) and functional MRI (fMRI) is assessed. In particular those patients developing epilepsy (i.e. a second unprovoked seizure) that were initially evaluated as having a low risk of seizure recurrence are of interest. In total, 26 epilepsy patients, of which 8 were initially evaluated as having a low risk of seizure recurrence (i.e. converters), and 17 subjects with only a single seizure were included. All subjects underwent routine EEG as well as fMRI measurements. For diagnostic classification, features related to the temporal dynamics were determined for both the processed EEG and fMRI data. Subsequently, a logistic regression classifier was trained on epilepsy and first-seizure subjects. The trained model was tested using the clinically relevant converters group. The sensitivity, specificity, and AUC (mean ± SD) of the regression model including metrics from both modalities were 74 ± 19%, 82 ± 18%, and 0.75 ± 0.12, respectively. Positive and negative predictive values (mean ± SD) of the regression model with both EEG and fMRI features are 84 ± 14% and 78 ± 12%. Moreover, this EEG/fMRI model showed significant improvements compared to the clinical diagnosis, whereas the models using metrics from either EEG or fMRI do not reach significance (p > 0.05). Temporal metrics computationally derived from EEG and fMRI time signals may clinically aid and synergistically improve the predictive value in a first-seizure sample.
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Affiliation(s)
- Gerhard S Drenthen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands.
| | - Jacobus F A Jansen
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Electrical Engineering, Eindhoven University of Technology, De Rondom 70, Eindhoven, the Netherlands
| | - Erik Gommer
- Department of Clinical Neurophysiology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | - Lalit Gupta
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | - Paul A M Hofman
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | | | - Danny M Hilkman
- Department of Clinical Neurophysiology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | - Marielle C G Vlooswijk
- Department of Neurology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
| | - Rob P W Rouhl
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Neurology, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Academic Center for Epileptology Kempenhaeghe/MUMC+ Heeze and Maastricht, the Netherlands
| | - Walter H Backes
- School for Mental Health and Neuroscience, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, the Netherlands
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25
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Nakai Y, Nishibayashi H, Donishi T, Terada M, Nakao N, Kaneoke Y. Regional abnormality of functional connectivity is associated with clinical manifestations in individuals with intractable focal epilepsy. Sci Rep 2021; 11:1545. [PMID: 33452388 PMCID: PMC7810833 DOI: 10.1038/s41598-021-81207-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 01/04/2021] [Indexed: 01/29/2023] Open
Abstract
We explored regional functional connectivity alterations in intractable focal epilepsy brains using resting-state functional MRI. Distributions of the network parameters (corresponding to degree and eigenvector centrality) measured at each brain region for all 25 patients were significantly different from age- and sex-matched control data that were estimated by a healthy control dataset (n = 582, 18-84 years old). The number of abnormal regions whose parameters exceeded the mean + 2 SD of age- and sex-matched data for each patient were associated with various clinical parameters such as the duration of illness and seizure severity. Furthermore, abnormal regions for each patient tended to have functional connections with each other (mean ± SD = 58.6 ± 20.2%), the magnitude of which was negatively related to the quality of life. The abnormal regions distributed within the default mode network with significantly higher probability (p < 0.05) in 7 of 25 patients. We consider that the detection of abnormal regions by functional connectivity analysis using a large number of control datasets is useful for the numerical assessment of each patient's clinical conditions, although further study is necessary to elucidate etiology-specific abnormalities.
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Affiliation(s)
- Yasuo Nakai
- Department of Neurological Surgery, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan.
| | - Hiroki Nishibayashi
- Department of Neurological Surgery, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan
| | - Tomohiro Donishi
- Department of System Neurophysiology, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan
| | - Masaki Terada
- Wakayama-Minami Radiology Clinic, 870-2 Kimiidera, Wakayama, 641-0012, Japan
| | - Naoyuki Nakao
- Department of Neurological Surgery, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan
| | - Yoshiki Kaneoke
- Department of System Neurophysiology, Wakayama Medical University, 811-1 Kimiidera, Wakayama, 641-8509, Japan
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26
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Liu W, Yue Q, Tian Y, Gong Q, Zhou D, Wu X. Neural functional connectivity in patients with periventricular nodular heterotopia-mediated epilepsy. Epilepsy Res 2021; 170:106548. [PMID: 33454660 DOI: 10.1016/j.eplepsyres.2021.106548] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 12/10/2020] [Accepted: 12/30/2020] [Indexed: 02/08/2023]
Abstract
Periventricular nodular heterotopia (PNH) is characterized by disabled neural migration and is usually associated with epilepsy. Despite awareness of PNH-related epilepsy, little is known about the brain-level underlying functional neural bases. Thus, we used functional magnetic resonance imaging (MRI) to examine the neurobiology of 42 subjects with PNH-related epilepsy and 42 sex- and age-matched healthy controls. Measurements of functional connectivity (FC) and whole-brain graph theory analysis of data in the resting state were performed to assess neurological organization and topology. PNH patients exhibited significantly higher FC in the parietal lobe, cingulum and thalamus, as well as significantly lower FC in frontoparietal, hippocampal, and precentral regions. Graph theory analysis identified no significant differences between patients and controls, while patients showed lower network global efficiency in the limbic and cerebellum network and occipital cortex. Seed-based FC analysis confirmed disruption of activities and interregional connectivity in remote epileptic networks of patients, which may point to underlying pathological mechanisms. The cerebellum and limbic system of patients showed altered topology, suggesting that these regions or hubs may contribute to whole-brain circuits in PNH and epilepsy.
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Affiliation(s)
- Wenyu Liu
- Department of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Qiang Yue
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China.
| | - Yun Tian
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, 400715, China; Key Laboratory of Cognition and Personality (Ministry of Education), Chongqing, 400715, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China
| | - Dong Zhou
- Department of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China.
| | - Xintong Wu
- Department of Neurology, West China Hospital, Sichuan University, No. 37 GuoXue Alley, Chengdu, 610041, China.
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Shu T, Xiao X, Long Z, Zhang R. Reduced structural covariance connectivity of defaut mode network and salience network in MRI-normal focal epilepsy. Neuroreport 2020; 31:1289-1295. [PMID: 33165193 DOI: 10.1097/wnr.0000000000001541] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Neuroimaging studies have found altered functional connectivity of default mode network (DMN) and salience network (SN) in patients with focal epilepsy (FE). However, the structural basis underlying the functional connectivity disturbance in the patients is still unclear. Sixteen MRI-normal FE and 22 healthy controls were included in the current study. The T1 structural image of each participant was obtained. Seed-based structural covariance connectivity was employed to investigate changes of structural covariance connectivity of DMN and SN in FE patients. We further evaluated gray matter volume changes of brain areas showing altered structural connectivity in the patients. We found that patients with FE showed reduced connectivity of posterior cingulate cortex and left medial prefrontal cortex, hippocampus and orbitofrontal cortex, and reduced connectivity of right fronto-insula cortex with left insula, orbitofrontal cortex, opercum part of inferior frontal cortex and right medial prefrontal cortex compared with healthy controls. Moreover, those brain areas showing significant reduced structural covariance connectivity in patients with FE also had a loss of gray matter volume, indicating that reduced structural connectivity of DMN and SN might be associated with gray matter atrophy in the patients. Those results highlight the crucial role of DMN and SN in the pathology of patients with FE, and provided structural basis for the functional disturbance of the two networks in this disease.
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Affiliation(s)
- Ting Shu
- Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang
| | - Xinlan Xiao
- Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang
| | - Zhiliang Long
- Sleep and NeuroImaging Center, Faculty of Psychology, Southwest University, Chongqing, China
| | - Ran Zhang
- Medical Imaging Center, Second Affiliated Hospital of Nanchang University, Nanchang
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28
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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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29
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Amiri S, Mehvari-Habibabadi J, Mohammadi-Mobarakeh N, Hashemi-Fesharaki SS, Mirbagheri MM, Elisevich K, Nazem-Zadeh MR. Graph theory application with functional connectivity to distinguish left from right temporal lobe epilepsy. Epilepsy Res 2020; 167:106449. [PMID: 32937221 DOI: 10.1016/j.eplepsyres.2020.106449] [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: 03/16/2020] [Revised: 07/29/2020] [Accepted: 08/18/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To investigate the application of graph theory with functional connectivity to distinguish left from right temporal lobe epilepsy (TLE). METHODS Alterations in functional connectivity within several brain networks - default mode (DMN), attention (AN), limbic (LN), sensorimotor (SMN) and visual (VN) - were examined using resting-state functional MRI (rs-fMRI). The study accrued 21 left and 14 right TLE as well as 17 nonepileptic control subjects. The local nodal degree, a feature of graph theory, was calculated foreach of the brain networks. Multivariate logistic regression analysis was performed to determine the accuracy of identifying seizure laterality based on significant differences in local nodal degree in the selected networks. RESULTS Left and right TLE patients showed dissimilar patterns of alteration in functional connectivity when compared to control subjects. Compared with right TLE, patients with left TLE exhibited greater nodal degree' (i.e. hyperconnectivity) with right superomedial frontal gyrus (in DMN), inferior frontal gyrus pars triangularis (in AN), right caudate and left superior temporal gyrus (in LN) and left paracentral lobule (in SMN), while showing lesser nodal degree (i.e. hypoconnectivity) with left temporal pole (in DMN), right insula (in LN), left supplementary motor area (in SMN), and left fusiform gyrus (in VN). The LN showed the highest accuracy of 82.9% among all considered networks in determining laterality of the TLE. By combinations of local degree attributes in the DMN, AN, LN, and VN, logistic regression analysis demonstrated an accuracy of 94.3% by comparison. CONCLUSION Our study demonstrates the utility of graph theory application to brain network analysis as a potential biomarker to assist in the determination of TLE laterality and improve the confidence in presurgical decision-making in cases of TLE.
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Affiliation(s)
- Saba Amiri
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences(TUMS), Tehran, Iran
| | | | - Neda Mohammadi-Mobarakeh
- 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
| | | | - Mehdi M Mirbagheri
- Medical Physics and Biomedical Engineering Department, Tehran University of Medical Sciences(TUMS), Tehran, Iran; Physical Medicine and Rehabilitation Department, Northwestern University, USA.
| | - 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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30
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Laurent A, Artiges E, Mellerio C, Boutin-Watine M, Landré E, Semah F, Chassoux F. Metabolic correlates of cognitive impairment in mesial temporal lobe epilepsy. Epilepsy Behav 2020; 105:106948. [PMID: 32062107 DOI: 10.1016/j.yebeh.2020.106948] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 01/07/2020] [Accepted: 01/24/2020] [Indexed: 12/12/2022]
Abstract
PURPOSE The purpose of the study was to determine the correlations between brain metabolism and cognitive impairment in patients with drug-resistant mesial temporal lobe epilepsy (MTLE). METHODS [18F]-FluoroDeoxyGlucose positron emission tomography ([18F]-FDG-PET) and neuropsychological assessment were performed in 97 patients with MTLE (53 females, 15-56 years old, mean: 31.6 years, standard deviation (SD) = 10.4) with unilateral hippocampal sclerosis (HS, 49 left). We compared brain metabolism and gray matter volume (GMV) between patients with cognitive impairment (intelligence quotient (IQ) and memory index <80) and patients with normal cognition, using statistical parametric mapping (SPM), in the whole population then in right and left HS (RHS, LHS) separately. RESULTS Intelligence quotient (40-121, mean: 83.7 ± 16.9) and memory index (45-133, mean: 80.7 ± 19.3) were impaired in 43% and 51% of the patients, respectively, similarly in RHS and LHS. We did not find any correlations between IQ and clinical factors related to epilepsy; however, there was a significant correlation between low memory index and early age of onset in LHS (p = 0.021), and widespread epileptogenic zone in the whole population (p = 0.033). Impaired IQ correlated with extratemporal hypometabolism, involving frontoparietal networks implicated in the default mode network (DMN), predominantly in the midline cortices. Metabolic asymmetry regarding HS lateralization included the precuneus (pC) in LHS and the anterior cingulate cortex (ACC) in RHS, both areas corresponding to key nodes of the DMN. Memory index correlated with the same frontoparietal networks as for IQ, with an additional involvement of the temporal lobes, which was ipsilateral in RHS and contralateral in LHS. A diffuse decrease of GMV including the ipsilateral hippocampus correlated with cognitive impairment; however, the structural alterations did not match with the hypometabolic areas. CONCLUSIONS Cognitive impairment in MTLE correlates with extratemporal hypometabolism, involving the mesial frontoparietal networks implicated in the DMN and suggesting a disconnection with the affected hippocampus. Asymmetric alterations of connectivity may sustain the predominant ACC and pC metabolic decrease in patients with cognitive impairment.
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Affiliation(s)
- Agathe Laurent
- Epilepsy Unit, Department of Neurosurgery, GHU Paris Sainte-Anne, 75014 Paris, France
| | - Eric Artiges
- INSERM U1000 "Neuroimaging and Psychiatry,", Paris Sud University-Paris Saclay University, Psychiatry Department, 91G16 Orsay, France
| | - Charles Mellerio
- Department of Neuroradiology, GHU Paris Sainte-Anne, 75014 Paris, France
| | - Magali Boutin-Watine
- Epilepsy Unit, Department of Neurosurgery, GHU Paris Sainte-Anne, 75014 Paris, France
| | - Elisabeth Landré
- Epilepsy Unit, Department of Neurosurgery, GHU Paris Sainte-Anne, 75014 Paris, France
| | - Franck Semah
- Department of Nuclear Medicine and INSERM U1171, CHU Lille, F-59000 Lille, France
| | - Francine Chassoux
- Epilepsy Unit, Department of Neurosurgery, GHU Paris Sainte-Anne, 75014 Paris, France; Nuclear Medicine Department, SHFJ, Orsay, France; University Paris-Saclay, CEA, CNRS, Inserm, BioMaps, Orsay, 91401, France.
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31
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Zhang Z, Zhou X, Liu J, Qin L, Ye W, Zheng J. Aberrant functional connectivity of the cingulate subregions in right-sided temporal lobe epilepsy. Exp Ther Med 2020; 19:2901-2912. [PMID: 32256775 PMCID: PMC7086282 DOI: 10.3892/etm.2020.8551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Accepted: 12/09/2019] [Indexed: 11/17/2022] Open
Abstract
Patients with temporal lobe epilepsy (TLE) have been indicated to exhibit abnormal resting-state functional connectivity (rsFC) of the cingulate cortex. However, it has remained elusive whether cingulate subregions show different connectivity patterns in TLE. The present study aimed to investigate the differences in rsFC of each cingulate subregion between patients with right-sided TLE (rTLE) and healthy controls (HCs), as well as their association with executive control performance in rTLE. A total of 27 patients with rTLE and 20 age-, sex- and education-matched healthy controls were recruited and all participants underwent resting-state functional MRI and an attention network test for the assessment executive control function. In each hemisphere, the cingulate gyrus (CG) was divided into CG-1 (dorsal area 23; A23d), CG-2 (rostroventral area 24; A24rv), CG-3 (pregenual area 32; A32p), CG-4 (ventral area 23; A23v), CG-5 (caudodorsal area 24; A24cd), CG-6 (caudal area 24; A23c) and CG-7 (subgenual area 32; A32sg). Pearson's correlation analysis was performed to assess the correlation between the altered FCs of the cingulate subregions and clinical variables. In patients with rTLE, the majority of the cingulate subregions exhibited decreased rsFC; this was primarily restricted to the right CG-2, the bilateral CG-6 and the bilateral CG-7. Increased rsFC was only detected in rTLE restricted to the left CG-1. Impairments in executive control efficiency were identified in patients with rTLE in comparison with the HCs. Significant alterations in rsFC between the cingulate subregion and the brain regions were mostly decreased (and some slightly increased), suggesting that FC may potentially have a left-side advantage in patients with rTLE. FC variations of the cingulate subregions were indicated to be specific to rTLE. In addition, increased connectivity in the left CG-1 and left superior frontal gyrus were negatively correlated with executive control performance, suggesting a compensatory mechanism on executive control deficits in pathological conditions. This information on differentially altered FC patterns of the cingulate subregions may provide a deeper understanding of the complex neurological mechanisms and executive control dysfunctions underlying rTLE.
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Affiliation(s)
- Zhao Zhang
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Xia Zhou
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jinping Liu
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Lu Qin
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Wei Ye
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
| | - Jinou Zheng
- Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China
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Sleep modulates effective connectivity: A study using intracranial stimulation and recording. Clin Neurophysiol 2019; 131:529-541. [PMID: 31708382 DOI: 10.1016/j.clinph.2019.09.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Revised: 08/30/2019] [Accepted: 09/03/2019] [Indexed: 10/25/2022]
Abstract
OBJECTIVE Sleep is an active process with an important role in memory. Epilepsy patients often display a disturbed sleep architecture, with consequences on cognition. We aimed to investigate the effect of sleep on cortical networks' organization. METHODS We analyzed cortico-cortical evoked responses elicited by single pulse electrical stimulation (SPES) using intracranial depth electrodes in 25 patients with drug-resistant focal epilepsy explored using stereo-EEG. We applied the SPES protocol during wakefulness and NREM - N2 sleep. We analyzed 31,710 significant responses elicited by 799 stimulations covering most brain structures, epileptogenic or non-epileptogenic. We analyzed effective connectivity between structures using a graph-theory approach. RESULTS Sleep increases excitability in the brain, regardless of epileptogenicity. Local and distant connections are differently modulated by sleep, depending on the tissue epileptogenicity. In non-epileptogenic areas, frontal lobe connectivity is enhanced during sleep. There is increased connectivity between the hippocampus and temporal neocortex, while perisylvian structures are disconnected from the temporal lobe. In epileptogenic areas, we found a clear interhemispheric difference, with decreased connectivity in the right hemisphere during sleep. CONCLUSIONS Sleep modulates brain excitability and reconfigures functional brain networks, depending on tissue epileptogenicity. SIGNIFICANCE We found specific patterns of information flow during sleep in physiologic and pathologic structures, with possible implications for cognition.
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Benito-León J, Sanz-Morales E, Melero H, Louis ED, Romero JP, Rocon E, Malpica N. Graph theory analysis of resting-state functional magnetic resonance imaging in essential tremor. Hum Brain Mapp 2019; 40:4686-4702. [PMID: 31332912 DOI: 10.1002/hbm.24730] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 07/05/2019] [Accepted: 07/08/2019] [Indexed: 11/10/2022] Open
Abstract
Essential tremor (ET) is a neurological disease with both motor and nonmotor manifestations; however, little is known about its underlying brain basis. Furthermore, the overall organization of the brain network in ET remains largely unexplored. We investigated the topological properties of brain functional network, derived from resting-state functional magnetic resonance imaging (MRI) data, in 23 ET patients versus 23 healthy controls. Graph theory analysis was used to assess the functional network organization. At the global level, the functional network of ET patients was characterized by lower small-worldness values than healthy controls-less clustered functionality of the brain. At the regional level, compared with the healthy controls, ET patients showed significantly higher values of global efficiency, cost and degree, and a shorter average path length in the left inferior frontal gyrus (pars opercularis), right inferior temporal gyrus (posterior division and temporo-occipital part), right inferior lateral occipital cortex, left paracingulate, bilateral precuneus bilaterally, left lingual gyrus, right hippocampus, left amygdala, nucleus accumbens bilaterally, and left middle temporal gyrus (posterior part). In addition, ET patients showed significant higher local efficiency and clustering coefficient values in frontal medial cortex bilaterally, subcallosal cortex, posterior cingulate cortex, parahippocampal gyri bilaterally (posterior division), right lingual gyrus, right cerebellar flocculus, right postcentral gyrus, right inferior semilunar lobule of cerebellum and culmen of vermis. Finally, the right intracalcarine cortex and the left orbitofrontal cortex showed a shorter average path length in ET patients, while the left frontal operculum and the right planum polare showed a higher betweenness centrality in ET patients. In conclusion, the efficiency of the overall brain functional network in ET is disrupted. Further, our results support the concept that ET is a disorder that disrupts widespread brain regions, including those outside of the brain regions responsible for tremor.
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Affiliation(s)
- Julián Benito-León
- Department of Neurology, University Hospital 12 de Octubre, Madrid, Spain.,Center of Biomedical Network Research on Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Department of Medicine, Faculty of Medicine, Complutense University, Madrid, Spain
| | - Emilio Sanz-Morales
- Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain
| | - Helena Melero
- Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain
| | - Elan D Louis
- Department of Neurology, Yale School of Medicine, Yale University, New Haven, Connecticut.,Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, Connecticut.,Center for Neuroepidemiology and Clinical Neurological Research, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Juan P Romero
- Faculty of Biosanitary Sciences, Francisco de Vitoria University, Madrid, Spain.,Brain Damage Unit, Hospital Beata Maria Ana, Madrid, Spain
| | - Eduardo Rocon
- Neural and Cognitive Engineering group, Center for Automation and Robotics (CAR) CSIC-UPM, Arganda del Rey, Spain
| | - Norberto Malpica
- Medical Image Analysis Laboratory (LAIMBIO), Rey Juan Carlos University, Madrid, Spain
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Wykes RC, Khoo HM, Caciagli L, Blumenfeld H, Golshani P, Kapur J, Stern JM, Bernasconi A, Dedeurwaerdere S, Bernasconi N. WONOEP appraisal: Network concept from an imaging perspective. Epilepsia 2019; 60:1293-1305. [PMID: 31179547 DOI: 10.1111/epi.16067] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 05/16/2019] [Accepted: 05/16/2019] [Indexed: 02/01/2023]
Abstract
Neuroimaging techniques applied to a variety of organisms-from zebrafish, to rodents to humans-can offer valuable insights into neuronal network properties and their dysfunction in epilepsy. A wide range of imaging methods used to monitor neuronal circuits and networks during evoked seizures in animal models and advances in functional magnetic resonance imaging (fMRI) applied to patients with epilepsy were discussed during the XIV Workshop on Neurobiology of Epilepsy (XIV WONOEP) organized in 2017 by the Neurobiology Commission of the International League Against Epilepsy (ILAE). We review the growing number of technological approaches developed, as well as the current state of knowledge gained from studies applying these advanced imaging approaches to epilepsy research.
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Affiliation(s)
- Robert C Wykes
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK
| | - Hui Ming Khoo
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.,Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita, Japan
| | - Lorenzo Caciagli
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK.,Neuroimaging of Epilepsy Laboratory, Department of Neurosciences and McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Hal Blumenfeld
- Department of Neurology, Neuroscience and Neurosurgery, Yale University School of Medicine, New Haven, Connecticut
| | - Peyman Golshani
- Department of Neurology, Geffen School of Medicine, UCLA, Los Angeles, California
| | - Jaideep Kapur
- School of Medicine, University of Virginia, Charlottesville, Virginia
| | - John M Stern
- Department of Neurology, Geffen School of Medicine, UCLA, Los Angeles, California
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, Department of Neurosciences and McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | | | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, Department of Neurosciences and McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
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Jo HJ, Kenney-Jung DL, Balzekas I, Welker KM, Jones DT, Croarkin PE, Benarroch EE, Worrell GA. Relationship Between Seizure Frequency and Functional Abnormalities in Limbic Network of Medial Temporal Lobe Epilepsy. Front Neurol 2019; 10:488. [PMID: 31133978 PMCID: PMC6517503 DOI: 10.3389/fneur.2019.00488] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Accepted: 04/23/2019] [Indexed: 11/29/2022] Open
Abstract
Background: We compared resting-state functional connectivity (RSFC) among limbic and temporal lobe regions between patients with medial temporal lobe epilepsy (mTLE) and healthy control subjects to identify imaging evidence of functional networks related to seizure frequency, age of seizure onset, and duration of epilepsy. Methods: Twelve patients with drug-resistant, unilateral medial temporal lobe epilepsy and 12 healthy control subjects matched for age, sex, and handedness participated in the imaging experiments. We used network-based statistics to compare functional connectivity graphs in patients with mTLE and healthy controls to investigate the relationship between functional connectivity abnormalities and seizure frequency. Results: Among mTLE patients, we found functional network abnormalities throughout the limbic system, but primarily in the hemisphere ipsilateral to the seizure focus. The RSFCs between ipsilateral hypothalamus and ventral anterior cingulate cortex and between ipsilateral subiculum and contralateral posterior cingulate cortex were highly correlated with seizure frequency. Discussion: These findings suggest that in mTLE, changes in limbic networks ipsilateral to the epileptic focus are common. The pathological changes in connectivity between cingulate cortex, hypothalamus and subiculum ipsilateral to the seizure focus were correlated with increased seizure frequency.
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Affiliation(s)
- Hang Joon Jo
- Department of Neurology, Mayo Clinic, Rochester, MN, United States.,Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States.,Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | | | - Irena Balzekas
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Kirk M Welker
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, United States.,Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Paul E Croarkin
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
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36
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Liang X, Vaughan DN, Connelly A, Calamante F. A Novel Group-Fused Sparse Partial Correlation Method for Simultaneous Estimation of Functional Networks in Group Comparison Studies. Brain Topogr 2017; 31:364-379. [PMID: 29288387 DOI: 10.1007/s10548-017-0615-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2017] [Accepted: 12/26/2017] [Indexed: 11/24/2022]
Abstract
The conventional way to estimate functional networks is primarily based on Pearson correlation along with classic Fisher Z test. In general, networks are usually calculated at the individual-level and subsequently aggregated to obtain group-level networks. However, such estimated networks are inevitably affected by the inherent large inter-subject variability. A joint graphical model with Stability Selection (JGMSS) method was recently shown to effectively reduce inter-subject variability, mainly caused by confounding variations, by simultaneously estimating individual-level networks from a group. However, its benefits might be compromised when two groups are being compared, given that JGMSS is blinded to other groups when it is applied to estimate networks from a given group. We propose a novel method for robustly estimating networks from two groups by using group-fused multiple graphical-lasso combined with stability selection, named GMGLASS. Specifically, by simultaneously estimating similar within-group networks and between-group difference, it is possible to address inter-subject variability of estimated individual networks inherently related with existing methods such as Fisher Z test, and issues related to JGMSS ignoring between-group information in group comparisons. To evaluate the performance of GMGLASS in terms of a few key network metrics, as well as to compare with JGMSS and Fisher Z test, they are applied to both simulated and in vivo data. As a method aiming for group comparison studies, our study involves two groups for each case, i.e., normal control and patient groups; for in vivo data, we focus on a group of patients with right mesial temporal lobe epilepsy.
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Affiliation(s)
- Xiaoyun Liang
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia.
| | - David N Vaughan
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia.,Department of Neurology, Austin Health, Melbourne, VIC, Australia.,The Florey Department of Neuroscience and Mental Health Medicine, University of Melbourne, Melbourne, VIC, Australia
| | - Alan Connelly
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia.,The Florey Department of Neuroscience and Mental Health Medicine, University of Melbourne, Melbourne, VIC, Australia.,Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, VIC, Australia
| | - Fernando Calamante
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia.,The Florey Department of Neuroscience and Mental Health Medicine, University of Melbourne, Melbourne, VIC, Australia.,Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, VIC, Australia
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37
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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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Lai C, Guo S, Cheng L, Wang W. A Comparative Study of Feature Selection Methods for the Discriminative Analysis of Temporal Lobe Epilepsy. Front Neurol 2017; 8:633. [PMID: 29375459 PMCID: PMC5770628 DOI: 10.3389/fneur.2017.00633] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 11/13/2017] [Indexed: 01/09/2023] Open
Abstract
It is crucial to differentiate patients with temporal lobe epilepsy (TLE) from the healthy population and determine abnormal brain regions in TLE. The cortical features and changes can reveal the unique anatomical patterns of brain regions from structural magnetic resonance (MR) images. In this study, structural MR images from 41 patients with left TLE, 34 patients with right TLE, and 58 normal controls (NC) were acquired, and four kinds of cortical measures, namely cortical thickness, cortical surface area, gray matter volume (GMV), and mean curvature, were explored for discriminative analysis. Three feature selection methods including the independent sample t-test filtering, the sparse-constrained dimensionality reduction model (SCDRM), and the support vector machine-recursive feature elimination (SVM-RFE) were investigated to extract dominant features among the compared groups for classification using the support vector machine (SVM) classifier. The results showed that the SVM-RFE achieved the highest performance (most classifications with more than 84% accuracy), followed by the SCDRM, and the t-test. Especially, the surface area and GMV exhibited prominent discriminative ability, and the performance of the SVM was improved significantly when the four cortical measures were combined. Additionally, the dominant regions with higher classification weights were mainly located in the temporal and the frontal lobe, including the entorhinal cortex, rostral middle frontal, parahippocampal cortex, superior frontal, insula, and cuneus. This study concluded that the cortical features provided effective information for the recognition of abnormal anatomical patterns and the proposed methods had the potential to improve the clinical diagnosis of TLE.
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Affiliation(s)
- Chunren Lai
- Department of Biomedical Engineering, South China University of Technology, Guangzhou, China.,Department of Radiation Oncology, The People's Hospital of Gaozhou, Gaozhou, China
| | - Shengwen Guo
- Department of Biomedical Engineering, South China University of Technology, Guangzhou, China
| | - Lina Cheng
- Medical Imaging Center, Guangdong 999 Brain Hospital, Guangzhou, China
| | - Wensheng Wang
- Medical Imaging Center, Guangdong 999 Brain Hospital, Guangzhou, China
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Reorganization of anterior and posterior hippocampal networks associated with memory performance in mesial temporal lobe epilepsy. Clin Neurophysiol 2017; 128:830-838. [DOI: 10.1016/j.clinph.2017.02.018] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Revised: 02/14/2017] [Accepted: 02/23/2017] [Indexed: 11/23/2022]
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Výtvarová E, Mareček R, Fousek J, Strýček O, Rektor I. Large-scale cortico-subcortical functional networks in focal epilepsies: The role of the basal ganglia. NEUROIMAGE-CLINICAL 2016; 14:28-36. [PMID: 28123951 PMCID: PMC5222946 DOI: 10.1016/j.nicl.2016.12.014] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Revised: 11/02/2016] [Accepted: 12/15/2016] [Indexed: 12/02/2022]
Abstract
Objectives The aim was to describe the contribution of basal ganglia (BG) thalamo-cortical circuitry to the whole-brain functional connectivity in focal epilepsies. Methods Interictal resting-state fMRI recordings were acquired in 46 persons with focal epilepsies. Of these 46, 22 had temporal lobe epilepsy: 9 left temporal (LTLE), 13 right temporal (RTLE); 15 had frontal lobe epilepsy (FLE); and 9 had parietal/occipital lobe epilepsy (POLE). There were 20 healthy controls. The complete weighted network was analyzed based on correlation matrices of 90 and 194 regions. The network topology was quantified on a global and regional level by measures based on graph theory, and connection-level changes were analyzed by the partial least square method. Results In all patient groups except RTLE, the shift of the functional network topology away from random was observed (normalized clustering coefficient and characteristic path length were higher in patient groups than in controls). Links contributing to this change were found in the cortico-subcortical connections. Weak connections (low correlations) consistently contributed to this modification of the network. The importance of regions changed: decreases in the subcortical areas and both decreases and increases in the cortical areas were observed in node strength, clustering coefficient and eigenvector centrality in patient groups when compared to controls. Node strength decreases of the basal ganglia, i.e. the putamen, caudate, and pallidum, were displayed in LTLE, FLE, and POLE. The connectivity within the basal ganglia–thalamus circuitry was not disturbed; the disturbance concerned the connectivity between the circuitry and the cortex. Significance Focal epilepsies affect large-scale brain networks beyond the epileptogenic zones. Cortico-subcortical functional connectivity disturbance was displayed in LTLE, FLE, and POLE. Significant changes in the resting-state functional connectivity between cortical and subcortical structures suggest an important role of the BG and thalamus in focal epilepsies. Focal epilepsies affect large-scale brain networks beyond the epileptogenic zones. The functional network topology shifted away from random in focal epilepsies. Subcortico-cortical connectivity decreased in epilepsy due to changes in weak links. Basal ganglia–thalamus circuitry connectivity was not disturbed in focal epilepsy. The connectivity between basal ganglia-thalamus circuitry and cortex was affected.
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Affiliation(s)
- Eva Výtvarová
- Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Radek Mareček
- Brain and Mind Research Program, Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Jan Fousek
- Faculty of Informatics, Masaryk University, Botanická 68a, 602 00 Brno, Czech Republic
| | - Ondřej Strýček
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Pekařská 53, 656 91 Brno, Czech Republic; Brain and Mind Research Program, Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
| | - Ivan Rektor
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital, Faculty of Medicine, Masaryk University, Pekařská 53, 656 91 Brno, Czech Republic; Brain and Mind Research Program, Central European Institute of Technology (CEITEC), Masaryk University, Kamenice 5, 625 00 Brno, Czech Republic
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41
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Zweiphenning W, van ‘t Klooster M, van Diessen E, van Klink N, Huiskamp G, Gebbink T, Leijten F, Gosselaar P, Otte W, Stam C, Braun K, Zijlmans G. High frequency oscillations and high frequency functional network characteristics in the intraoperative electrocorticogram in epilepsy. Neuroimage Clin 2016; 12:928-939. [PMID: 27882298 PMCID: PMC5114532 DOI: 10.1016/j.nicl.2016.09.014] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2016] [Revised: 08/29/2016] [Accepted: 09/21/2016] [Indexed: 11/21/2022]
Abstract
OBJECTIVE High frequency oscillations (HFOs; > 80 Hz), especially fast ripples (FRs, 250-500 Hz), are novel biomarkers for epileptogenic tissue. The pathophysiology suggests enhanced functional connectivity within FR generating tissue. Our aim was to determine the relation between brain areas showing FRs and 'baseline' functional connectivity within EEG networks, especially in the high frequency bands. METHODS We marked FRs, ripples (80-250 Hz) and spikes in the electrocorticogram of 14 patients with refractory temporal lobe epilepsy. We assessed 'baseline' functional connectivity in epochs free of epileptiform events within these recordings, using the phase lag index. We computed the Eigenvector Centrality (EC) per channel in the FR and gamma band network. We compared EC between channels that did or did not show events at other moments in time. RESULTS FR-band EC was higher in channels with than without spikes. Gamma-band EC was lower in channels with ripples and FRs. CONCLUSIONS We confirmed previous findings of functional isolation in the gamma-band and found a first proof of functional integration in the FR-band network of channels covering presumed epileptogenic tissue. SIGNIFICANCE 'Baseline' high-frequency network parameters might help intra-operative recognition of epileptogenic tissue without the need for waiting for events. These findings can increase our understanding of the 'architecture' of epileptogenic networks and help unravel the pathophysiology of HFOs.
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Key Words
- (io)ECoG, (intra-operative) electrocorticography
- EC, eigenvector centrality
- EEG, electroencephalography
- Epilepsy
- Epilepsy surgery
- Epileptogenic zone
- FR, fast ripple, 250–500 Hz
- Functional network analysis
- HFO, high frequency oscillation, > 80 Hz
- High Frequency Oscillations
- IPSP, inhibitory postsynaptic potential
- PLI, phase lag index
- SOZ, seizure onset zone
- TLE, temporal lobe epilepsy
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Affiliation(s)
- W.J.E.M. Zweiphenning
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - M.A. van ‘t Klooster
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - E. van Diessen
- Brain Center Rudolf Magnus, Department of Pediatric Neurology, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - N.E.C. van Klink
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - G.J.M. Huiskamp
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - T.A. Gebbink
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - F.S.S. Leijten
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - P.H. Gosselaar
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - W.M. Otte
- Brain Center Rudolf Magnus, Department of Pediatric Neurology, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
- Stichting Epilepsie Instellingen Nederland, Heemstede, P.O. box 540, 2130 AM Hoofddorp, The Netherlands
| | - C.J. Stam
- Department of Clinical Neurophysiology, Neuroscience Campus Amsterdam, VU University Medical Center, Postbus 7057, 1007 MB Amsterdam, The Netherlands
| | - K.P.J. Braun
- Brain Center Rudolf Magnus, Department of Pediatric Neurology, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
| | - G.J.M. Zijlmans
- Brain Center Rudolf Magnus, Department of Neurology and Neurosurgery, UMC Utrecht, P.O. box 85500, 3508 GA Utrecht, The Netherlands
- Stichting Epilepsie Instellingen Nederland, Heemstede, P.O. box 540, 2130 AM Hoofddorp, The Netherlands
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Gill RS, Mirsattari SM, Leung LS. Resting state functional network disruptions in a kainic acid model of temporal lobe epilepsy. Neuroimage Clin 2016; 13:70-81. [PMID: 27942449 PMCID: PMC5133653 DOI: 10.1016/j.nicl.2016.11.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Revised: 10/19/2016] [Accepted: 11/01/2016] [Indexed: 12/16/2022]
Abstract
We studied the graph topological properties of brain networks derived from resting-state functional magnetic resonance imaging in a kainic acid induced model of temporal lobe epilepsy (TLE) in rats. Functional connectivity was determined by temporal correlation of the resting-state Blood Oxygen Level Dependent (BOLD) signals between two brain regions during 1.5% and 2% isoflurane, and analyzed as networks in epileptic and control rats. Graph theoretical analysis revealed a significant increase in functional connectivity between brain areas in epileptic than control rats, and the connected brain areas could be categorized as a limbic network and a default mode network (DMN). The limbic network includes the hippocampus, amygdala, piriform cortex, nucleus accumbens, and mediodorsal thalamus, whereas DMN involves the medial prefrontal cortex, anterior and posterior cingulate cortex, auditory and temporal association cortex, and posterior parietal cortex. The TLE model manifested a higher clustering coefficient, increased global and local efficiency, and increased small-worldness as compared to controls, despite having a similar characteristic path length. These results suggest extensive disruptions in the functional brain networks, which may be the basis of altered cognitive, emotional and psychiatric symptoms in TLE.
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Affiliation(s)
- Ravnoor Singh Gill
- Graduate Program in Neuroscience, Western University, London, Ontario, Canada
- Department of Physiology & Pharmacology, Western University, London, Ontario, Canada
| | - Seyed M. Mirsattari
- Graduate Program in Neuroscience, Western University, London, Ontario, Canada
- Clinical Neurological Sciences, Western University, London, Ontario, Canada
- Department of Biomedical Imaging, Western University, London, Ontario, Canada
- Department of Biomedical Physics, Western University, London, Ontario, Canada
- Department of Psychology, Western University, London, Ontario, Canada
| | - L. Stan Leung
- Graduate Program in Neuroscience, Western University, London, Ontario, Canada
- Department of Physiology & Pharmacology, Western University, London, Ontario, Canada
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43
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Sone D, Matsuda H, Ota M, Maikusa N, Kimura Y, Sumida K, Yokoyama K, Imabayashi E, Watanabe M, Watanabe Y, Okazaki M, Sato N. Impaired cerebral blood flow networks in temporal lobe epilepsy with hippocampal sclerosis: A graph theoretical approach. Epilepsy Behav 2016; 62:239-45. [PMID: 27497065 DOI: 10.1016/j.yebeh.2016.07.016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2016] [Revised: 07/06/2016] [Accepted: 07/07/2016] [Indexed: 12/19/2022]
Abstract
Graph theory is an emerging method to investigate brain networks. Altered cerebral blood flow (CBF) has frequently been reported in temporal lobe epilepsy (TLE), but graph theoretical findings of CBF are poorly understood. Here, we explored graph theoretical networks of CBF in TLE using arterial spin labeling imaging. We recruited patients with TLE and unilateral hippocampal sclerosis (HS) (19 patients with left TLE, and 21 with right TLE) and 20 gender- and age-matched healthy control subjects. We obtained all participants' CBF maps using pseudo-continuous arterial spin labeling and analyzed them using the Graph Analysis Toolbox (GAT) software program. As a result, compared to the controls, the patients with left TLE showed a significantly low clustering coefficient (p=0.024), local efficiency (p=0.001), global efficiency (p=0.010), and high transitivity (p=0.015), whereas the patients with right TLE showed significantly high assortativity (p=0.046) and transitivity (p=0.011). The group with right TLE also had high characteristic path length values (p=0.085), low global efficiency (p=0.078), and low resilience to targeted attack (p=0.101) at a trend level. Lower normalized clustering coefficient (p=0.081) in the left TLE and higher normalized characteristic path length (p=0.089) in the right TLE were found also at a trend level. Both the patients with left and right TLE showed significantly decreased clustering in similar areas, i.e., the cingulate gyri, precuneus, and occipital lobe. Our findings revealed differing left-right network metrics in which an inefficient CBF network in left TLE and vulnerability to irritation in right TLE are suggested. The left-right common finding of regional decreased clustering might reflect impaired default-mode networks in TLE.
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Affiliation(s)
- Daichi Sone
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo, Japan; Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Hiroshi Matsuda
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Miho Ota
- Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Norihide Maikusa
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Yukio Kimura
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Kaoru Sumida
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Kota Yokoyama
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Etsuko Imabayashi
- Integrative Brain Imaging Center, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Masako Watanabe
- Department of Psychiatry, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Yutaka Watanabe
- Department of Psychiatry, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Mitsutoshi Okazaki
- Department of Psychiatry, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Noriko Sato
- Department of Radiology, National Center of Neurology and Psychiatry, Tokyo, Japan.
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Insights into Intrinsic Brain Networks based on Graph Theory and PET in right- compared to left-sided Temporal Lobe Epilepsy. Sci Rep 2016; 6:28513. [PMID: 27349503 PMCID: PMC4923886 DOI: 10.1038/srep28513] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2015] [Accepted: 06/03/2016] [Indexed: 11/08/2022] Open
Abstract
The human brain exhibits marked hemispheric differences, though it is not fully understood to what extent lateralization of the epileptic focus is relevant. Preoperative [(18)F]FDG-PET depicts lateralization of seizure focus in patients with temporal lobe epilepsy and reveals dysfunctional metabolic brain connectivity. The aim of the present study was to compare metabolic connectivity, inferred from inter-regional [(18)F]FDG PET uptake correlations, in right-sided (RTLE; n = 30) and left-sided TLE (LTLE; n = 32) with healthy controls (HC; n = 31) using graph theory based network analysis. Comparing LTLE and RTLE and patient groups separately to HC, we observed higher lobar connectivity weights in RTLE compared to LTLE for connections of the temporal and the parietal lobe of the contralateral hemisphere (CH). Moreover, especially in RTLE compared to LTLE higher local efficiency were found in the temporal cortices and other brain regions of the CH. The results of this investigation implicate altered metabolic networks in patients with TLE specific to the lateralization of seizure focus, and describe compensatory mechanisms especially in the CH of patients with RTLE. We propose that graph theoretical analysis of metabolic connectivity using [(18)F]FDG-PET offers an important additional modality to explore brain networks.
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45
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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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46
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Ridley BGY, Rousseau C, Wirsich J, Le Troter A, Soulier E, Confort-Gouny S, Bartolomei F, Ranjeva JP, Achard S, Guye M. Nodal approach reveals differential impact of lateralized focal epilepsies on hub reorganization. Neuroimage 2015; 118:39-48. [PMID: 26070261 DOI: 10.1016/j.neuroimage.2015.05.096] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2014] [Revised: 04/30/2015] [Accepted: 05/21/2015] [Indexed: 02/07/2023] Open
Abstract
The impact of the hemisphere affected by impairment in models of network disease is not fully understood. Among such models, focal epilepsies are characterised by recurrent seizures generated in epileptogenic areas also responsible for wider network dysfunction between seizures. Previous work focusing on functional connectivity within circumscribed networks suggests a divergence of network integrity and compensatory capacity between epilepsies as a function of the laterality of seizure onset. We evaluated the ability of complex network theory to reveal changes in focal epilepsy in global and nodal parameters using graph theoretical analysis of functional connectivity data obtained with resting-state fMRI. Graphs of functional connectivity networks were derived from 19 right and 13 left focal epilepsy patients and 15 controls. Topological metrics (degree, local efficiency, global efficiency and modularity) were computed for a whole-brain, atlas-defined network. We also calculated a hub disruption index for each graph metric, measuring the capacity of the brain network to demonstrate increased connectivity in some nodes for decreased connectivity in others. Our data demonstrate that the patient group as a whole is characterised by network-wide pattern of reorganization, even while global parameters fail to distinguish between groups. Furthermore, multiple metrics indicate that epilepsies with differently lateralized epileptic networks are asymmetric in their burden on functional brain networks; with left epilepsy patients being characterised by reduced efficiency and modularity, while in right epilepsy patients we provide the first evidence that functional brain networks are characterised by enhanced connectivity and efficiency at some nodes whereas reduced in others.
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Affiliation(s)
- Ben Gendon Yeshe Ridley
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Celia Rousseau
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Jonathan Wirsich
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Arnaud Le Troter
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Elisabeth Soulier
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Sylvianne Confort-Gouny
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Fabrice Bartolomei
- APHM, Hôpital de la Timone, Service de Neurophysiologie Clinique, 13005 Marseille, France; Aix-Marseille Université, INSERM, Institut de Neuroscience des Systèmes U1106, 13005 Marseille, France.
| | - Jean-Philippe Ranjeva
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
| | - Sophie Achard
- Centre National de la Recherche Scientifique, Grenoble Image Parole Signal Automatique, 38402 Grenoble, France.
| | - Maxime Guye
- Aix-Marseille Université, CNRS, CRMBM UMR 7339, 13005 Marseille, France; APHM, Hôpital de la Timone, Pôle d'Imagerie Médicale, CEMEREM, 13005 Marseille, France.
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47
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Chiang S, Stern JM, Engel J, Haneef Z. Structural-functional coupling changes in temporal lobe epilepsy. Brain Res 2015; 1616:45-57. [PMID: 25960346 DOI: 10.1016/j.brainres.2015.04.052] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2015] [Revised: 04/24/2015] [Accepted: 04/28/2015] [Indexed: 12/13/2022]
Abstract
Alterations in both structural connectivity (SC) and functional connectivity (FC) have been reported in temporal lobe epilepsy (TLE). However, the relationship between FC and SC remains less understood. This study used functional connectivity MRI and diffusion tensor imaging to examine coupling of FC and SC within the limbic network of TLE, as well as its relation to epilepsy duration, regional changes, and disease laterality in 14 patients with left TLE, 10 with right TLE, and 11 healthy controls. Structural and functional networks were separately constructed and the correlation estimated between structural and functional connectivity. This measure of SC-FC coupling was compared between left/right TLE and controls, and correlated with epilepsy duration. Elastic net regression was used to investigate regional structural and functional changes associated with SC-FC coupling. SC-FC coupling was decreased in left TLE compared to controls, and accompanied by reductions in FC for left and right TLE and in SC for left TLE. When examined in relation to disease duration, an increase in SC-FC coupling with longer epilepsy duration was observed, associated predominantly with structural loss of the fusiform and frontal inferior orbital gyrus in left TLE and functional hub redistribution in right TLE. These results suggest that decoupling between structural and functional networks in TLE is modulated by several factors, including epilepsy duration and regional changes in the fusiform, frontal inferior orbital gyrus, posterior cingulate, and hippocampus. SC-FC coupling may provide a more sensitive biomarker of disease burden in TLE than biomarkers based on single imaging modalities.
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Affiliation(s)
- Sharon Chiang
- Department of Statistics, Rice University, Houston, TX, USA
| | - John M Stern
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Jerome Engel
- Department of Neurology, University of California, Los Angeles, CA, USA; Department of Neurobiology, University of California, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, CA, USA; The Brain Research Institute, University of California, Los Angeles, CA, USA
| | - Zulfi Haneef
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA; Neurology Care Line, VA Medical Center, Houston, TX, USA.
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48
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Haneef Z, Chiang S, Yeh HJ, Engel J, Stern JM. Functional connectivity homogeneity correlates with duration of temporal lobe epilepsy. Epilepsy Behav 2015; 46:227-33. [PMID: 25873437 PMCID: PMC4458387 DOI: 10.1016/j.yebeh.2015.01.025] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2014] [Revised: 01/19/2015] [Accepted: 01/21/2015] [Indexed: 10/23/2022]
Abstract
Temporal lobe epilepsy (TLE) is often associated with progressive changes to seizures, memory, and mood during its clinical course. However, the cerebral changes related to this progression are not well understood. Because the changes may be related to changes in brain networks, we used functional connectivity MRI (fcMRI) to determine whether brain network parameters relate to the duration of TLE. Graph theory-based analysis of the sites of reported regions of TLE abnormality was performed on resting-state fMRI data in 48 subjects: 24 controls, 13 patients with left TLE, and 11 patients with right TLE. Various network parameters were analyzed including betweenness centrality (BC), clustering coefficient (CC), path length (PL), small-world index (SWI), global efficiency (GE), connectivity strength (CS), and connectivity diversity (CD). These were compared for patients with TLE as a group, compared to controls, and for patients with left and right TLE separately. The association of changes in network parameters with epilepsy duration was also evaluated. We found that CC, CS, and CD decreased in subjects with TLE compared to control subjects. Analyzed according to epilepsy duration, patients with TLE showed a progressive reduction in CD. In conclusion, we found that several network parameters decreased in patients with TLE compared to controls, which suggested reduced connectivity in TLE. Reduction in CD associated with epilepsy duration suggests a homogenization of connections over time in TLE, indicating a reduction of the normal repertoire of stronger and weaker connections to other brain regions.
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Affiliation(s)
- Zulfi Haneef
- Department of Neurology, Baylor College of Medicine, Houston, TX, USA; Neurology Care Line, Michael E DeBakey VA Medical Center, Houston, TX, USA.
| | - Sharon Chiang
- Department of Statistics, Rice University, Houston, Texas, USA
| | - Hsiang J. Yeh
- Department of Neurology, University of California, Los Angeles, California, USA
| | - Jerome Engel
- Department of Neurology, University of California, Los Angeles, California, USA
| | - John M. Stern
- Department of Neurology, University of California, Los Angeles, California, USA
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Haneef Z, Levin HS, Chiang S. Brain Graph Topology Changes Associated with Anti-Epileptic Drug Use. Brain Connect 2015; 5:284-91. [PMID: 25492633 DOI: 10.1089/brain.2014.0304] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Neuroimaging studies of functional connectivity using graph theory have furthered our understanding of the network structure in temporal lobe epilepsy (TLE). Brain network effects of anti-epileptic drugs could influence such studies, but have not been systematically studied. Resting-state functional MRI was analyzed in 25 patients with TLE using graph theory analysis. Patients were divided into two groups based on anti-epileptic medication use: those taking carbamazepine/oxcarbazepine (CBZ/OXC) (n=9) and those not taking CBZ/OXC (n=16) as a part of their medication regimen. The following graph topology metrics were analyzed: global efficiency, betweenness centrality (BC), clustering coefficient, and small-world index. Multiple linear regression was used to examine the association of CBZ/OXC with graph topology. The two groups did not differ from each other based on epilepsy characteristics. Use of CBZ/OXC was associated with a lower BC. Longer epilepsy duration was also associated with a lower BC. These findings can inform graph theory-based studies in patients with TLE. The changes observed are discussed in relation to the anti-epileptic mechanism of action and adverse effects of CBZ/OXC.
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Affiliation(s)
- Zulfi Haneef
- 1 Department of Neurology, Baylor College of Medicine , Houston, Texas.,2 Neurology Care Line, VA Medical Center , Houston, Texas
| | - Harvey S Levin
- 3 Department of Physical Medicine, Baylor College of Medicine , Houston, Texas
| | - Sharon Chiang
- 4 Department of Statistics, Rice University , Houston, Texas
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