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Cabalo DG, DeKraker J, Royer J, Xie K, Tavakol S, Rodríguez-Cruces R, Bernasconi A, Bernasconi N, Weil A, Pana R, Frauscher B, Caciagli L, Jefferies E, Smallwood J, Bernhardt BC. Differential reorganization of episodic and semantic memory systems in epilepsy-related mesiotemporal pathology. Brain 2024; 147:3918-3932. [PMID: 39054915 PMCID: PMC11531848 DOI: 10.1093/brain/awae197] [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: 02/20/2024] [Revised: 05/07/2024] [Accepted: 06/05/2024] [Indexed: 07/27/2024] Open
Abstract
Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, whereas semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE) as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE and 60 age- and sex-matched healthy controls, and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient-mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, in both the MTL and neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. Neocortical alterations were characterized by reduced functional differentiation in TLE across lateral temporal and midline parietal cortices in both hemispheres. In the MTL, in contrast, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, whereas hippocampal functional topographies were unaffected. Furthermore, leveraging MRI proxies of MTL pathology, we observed alterations in hippocampal microstructure and morphology that were associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic memory, but again not in semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, whereas episodic processes are supported by a network involving both the hippocampus and the neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.
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Affiliation(s)
- Donna Gift Cabalo
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jordan DeKraker
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Ke Xie
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Andrea Bernasconi
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Neda Bernasconi
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Alexander Weil
- Research Centre, CHU St Justine, Montreal, QC H3T 1C5, Canada
| | - Raluca Pana
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
- Analytical Neurophysiology Laboratory, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | | | - Jonathan Smallwood
- Department of Psychology, Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
- Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A 2B4, Canada
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Liu X, Han J, Zhang X, Zhou Q, Huang Z, Wang Y, Zhang J, Lin Y. Dynamic evolution of frontal-temporal network connectivity in temporal lobe epilepsy: A magnetoencephalography study. Hum Brain Mapp 2024; 45:e70033. [PMID: 39319686 PMCID: PMC11423264 DOI: 10.1002/hbm.70033] [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: 04/03/2024] [Revised: 09/06/2024] [Accepted: 09/11/2024] [Indexed: 09/26/2024] Open
Abstract
Temporal lobe epilepsy (TLE) frequently involves an intricate, extensive epileptic frontal-temporal network. This study aimed to investigate the interactions between temporal and frontal regions and the dynamic patterns of the frontal-temporal network in TLE patients with different disease durations. The magnetoencephalography data of 36 postoperative seizure-free patients with long-term follow-up of at least 1 year, and 21 age- and sex-matched healthy subjects were included in this study. Patients were initially divided into LONG-TERM (n = 18, DURATION >10 years) and SHORT-TERM (n = 18, DURATION ≤10 years) groups based on 10-year disease duration. For reliability, supplementary analyses were conducted with alternative cutoffs, creating three groups: 0 < DURATION ≤7 years (n = 11), 7 < DURATION ≤14 years (n = 11), and DURATION >14 years (n = 14). This study examined the intraregional phase-amplitude coupling (PAC) between theta phase and alpha amplitude across the whole brain. The interregional directed phase transfer entropy (dPTE) between frontal and temporal regions in the alpha and theta bands, and the interregional cross-frequency directionality (CFD) between temporal and frontal regions from the theta phase to the alpha amplitude were further computed and compared among groups. Partial correlation analysis was conducted to investigate correlations between intraregional PAC, interregional dPTE connectivity, interregional CFD, and disease duration. Whole-brain intraregional PAC analyses revealed enhanced theta phase-alpha amplitude coupling within the ipsilateral temporal and frontal regions in TLE patients, and the ipsilateral temporal PAC was positively correlated with disease duration (r = 0.38, p <.05). Interregional dPTE analyses demonstrated a gradual increase in frontal-to-temporal connectivity within the alpha band, while the direction of theta-band connectivity reversed from frontal-to-temporal to temporal-to-frontal as the disease duration increased. Interregional CFD analyses revealed that the inhibitory effect of frontal regions on temporal regions gradually increased with prolonged disease duration (r = -0.36, p <.05). This study clarified the intrinsic reciprocal connectivity between temporal and frontal regions with TLE duration. We propose a dynamically reorganized triple-stage network that transitions from balanced networks to constrained networks and further develops into imbalanced networks as the disease duration increases.
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Affiliation(s)
- Xinyan Liu
- School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
- Beijing Advanced Innovation Center for Big Data‐Based Precision MedicineBeihang UniversityBeijingChina
- Beijing Advanced Innovation Centre for Biomedical EngineeringBeihang UniversityBeijingChina
| | - Jiaqi Han
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xiating Zhang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
| | - Qilin Zhou
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Zhaoyang Huang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
| | - Yuping Wang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
- Beijing Key Laboratory of NeuromodulationXuanwu Hospital, Capital Medical UniversityBeijingChina
| | - Jicong Zhang
- School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
- Beijing Advanced Innovation Center for Big Data‐Based Precision MedicineBeihang UniversityBeijingChina
- Beijing Advanced Innovation Centre for Biomedical EngineeringBeihang UniversityBeijingChina
- Hefei Innovation Research InstituteBeihang UniversityBeijingChina
| | - Yicong Lin
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
- Department of Neurologythe First Hospital of Hebei Medical UniversityShijiazhuangHebeiChina
- Beijing Key Laboratory of NeuromodulationXuanwu Hospital, Capital Medical UniversityBeijingChina
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Aiello G, Ledergerber D, Dubcek T, Stieglitz L, Baumann C, Polanìa R, Imbach L. Functional network dynamics between the anterior thalamus and the cortex in deep brain stimulation for epilepsy. Brain 2023; 146:4717-4735. [PMID: 37343140 DOI: 10.1093/brain/awad211] [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: 01/13/2023] [Revised: 05/10/2023] [Accepted: 06/08/2023] [Indexed: 06/23/2023] Open
Abstract
Owing to its unique connectivity profile with cortical brain regions, and its suggested role in the subcortical propagation of seizures, the anterior nucleus of the thalamus (ANT) has been proposed as a key deep brain stimulation (DBS) target in drug-resistant epilepsy. However, the spatio-temporal interaction dynamics of this brain structure, and the functional mechanisms underlying ANT DBS in epilepsy remain unknown. Here, we study how the ANT interacts with the neocortex in vivo in humans and provide a detailed neurofunctional characterization of mechanisms underlying the effectiveness of ANT DBS, aiming at defining intraoperative neural biomarkers of responsiveness to therapy, assessed at 6 months post-implantation as the reduction in seizure frequency. A cohort of 15 patients with drug-resistant epilepsy (n = 6 males, age = 41.6 ± 13.79 years) underwent bilateral ANT DBS implantation. Using intraoperative cortical and ANT simultaneous electrophysiological recordings, we found that the ANT is characterized by high amplitude θ (4-8 Hz) oscillations, mostly in its superior part. The strongest functional connectivity between the ANT and the scalp EEG was also found in the θ band in ipsilateral centro-frontal regions. Upon intraoperative stimulation in the ANT, we found a decrease in higher EEG frequencies (20-70 Hz) and a generalized increase in scalp-to-scalp connectivity. Crucially, we observed that responders to ANT DBS treatment were characterized by higher EEG θ oscillations, higher θ power in the ANT, and stronger ANT-to-scalp θ connectivity, highlighting the crucial role of θ oscillations in the dynamical network characterization of these structures. Our study provides a comprehensive characterization of the interaction dynamic between the ANT and the cortex, delivering crucial information to optimize and predict clinical DBS response in patients with drug-resistant epilepsy.
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Affiliation(s)
- Giovanna Aiello
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Debora Ledergerber
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Tena Dubcek
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Lennart Stieglitz
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Christian Baumann
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Rafael Polanìa
- Decision Neuroscience Lab, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
| | - Lukas Imbach
- Swiss Epilepsy Center (Klinik Lengg), 8008 Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, 8057 Zurich, Switzerland
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González HFJ, Narasimhan S, Goodale SE, Johnson GW, Doss DJ, Paulo DL, Morgan VL, Chang C, Englot DJ. Arousal and salience network connectivity alterations in surgical temporal lobe epilepsy. J Neurosurg 2023; 138:810-820. [PMID: 35901709 PMCID: PMC10127440 DOI: 10.3171/2022.5.jns22837] [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: 04/09/2022] [Accepted: 05/12/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE It is poorly understood why patients with mesial temporal lobe epilepsy (TLE) have cognitive deficits and brain network changes that extend beyond the temporal lobe, including altered extratemporal intrinsic connectivity networks (ICNs). However, subcortical arousal structures project broadly to the neocortex, are affected by TLE, and thus may contribute to these widespread network effects. The authors' objective was to examine functional connectivity (FC) patterns between subcortical arousal structures and neocortical ICNs, possible neurocognitive relationships, and FC changes after epilepsy surgery. METHODS The authors obtained resting-state functional magnetic resonance imaging (fMRI) in 50 adults with TLE and 50 controls. They compared nondirected FC (correlation) and directed FC (Granger causality laterality index) within the salience network, default mode network, and central executive network, as well as between subcortical arousal structures; these 3 ICNs were also compared between patients and controls. They also used an fMRI-based vigilance index to relate alertness to arousal center FC. Finally, fMRI was repeated in 29 patients > 12 months after temporal lobe resection. RESULTS Nondirected FC within the salience (p = 0.042) and default mode (p = 0.0008) networks, but not the central executive network (p = 0.79), was decreased in patients in comparison with controls (t-tests, corrected). Nondirected FC between the salience network and subcortical arousal structures (nucleus basalis of Meynert, thalamic centromedian nucleus, and brainstem pedunculopontine nucleus) was reduced in patients in comparison with controls (p = 0.0028-0.015, t-tests, corrected), and some of these connectivity abnormalities were associated with lower processing speed index, verbal comprehension, and full-scale IQ. Interestingly, directed connectivity measures suggested a loss of top-down influence from the salience network to the arousal nuclei in patients. After resection, certain FC patterns between the arousal nuclei and salience network moved toward control values in the patients, suggesting that some postoperative recovery may be possible. Although an fMRI-based vigilance measure suggested that patients exhibited reduced alertness over time, FC abnormalities between the salience network and arousal structures were not influenced by the alertness levels during the scans. CONCLUSIONS FC abnormalities between subcortical arousal structures and ICNs, such as the salience network, may be related to certain neurocognitive deficits in TLE patients. Although TLE patients demonstrated vigilance abnormalities, baseline FC perturbations between the arousal and salience networks are unlikely to be driven solely by alertness level, and some may improve after surgery. Examination of the arousal network and ICN disturbances may improve our understanding of the downstream clinical effects of TLE.
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Affiliation(s)
- Hernán F. J. González
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Saramati Narasimhan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sarah E. Goodale
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Graham W. Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Derek J. Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Victoria L. Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Departments of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Catie Chang
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Departments of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Dario J. Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee
- Departments of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Departments of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
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Gholipour T, DeMarco A, You X, Englot DJ, Turkeltaub PE, Koubeissi MZ, Gaillard WD, Morgan VL. Functional anomaly mapping lateralizes temporal lobe epilepsy with high accuracy in individual patients. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.05.23285034. [PMID: 36798218 PMCID: PMC9934715 DOI: 10.1101/2023.02.05.23285034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE) is associated with variable dysfunction beyond the temporal lobe. We used functional anomaly mapping (FAM), a multivariate machine learning approach to resting state fMRI analysis to measure subcortical and cortical functional aberrations in patients with mTLE. We also examined the value of individual FAM in lateralizing the hemisphere of seizure onset in mTLE patients. Methods: Patients and controls were selected from an existing imaging and clinical database. After standard preprocessing of resting state fMRI, time-series were extracted from 400 cortical and 32 subcortical regions of interest (ROIs) defined by atlases derived from functional brain organization. Group-level aberrations were measured by contrasting right (RTLE) and left (LTLE) patient groups to controls in a support vector regression models, and tested for statistical reliability using permutation analysis. Individualized functional anomaly maps (FAMs) were generated by contrasting individual patients to the control group. Half of patients were used for training a classification model, and the other half for estimating the accuracy to lateralize mTLE based on individual FAMs. Results: Thirty-two right and 14 left mTLE patients (33 with evidence of hippocampal sclerosis on MRI) and 94 controls were included. At group levels, cortical regions affiliated with limbic and somatomotor networks were prominent in distinguishing RTLE and LTLE from controls. At individual levels, most TLE patients had high anomaly in bilateral mesial temporal and medial parietooccipital default mode regions. A linear support vector machine trained on 50% of patients could accurately lateralize mTLE in remaining patients (median AUC =1.0 [range 0.97-1.0], median accuracy = 96.87% [85.71-100Significance: Functional anomaly mapping confirms widespread aberrations in function, and accurately lateralizes mTLE from resting state fMRI. Future studies will evaluate FAM as a non-invasive localization method in larger datasets, and explore possible correlations with clinical characteristics and disease course.
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Narasimhan S, González HFJ, Johnson GW, Wills KE, Paulo DL, Morgan VL, Englot DJ. Functional connectivity between mesial temporal and default mode structures may help lateralize surgical temporal lobe epilepsy. J Neurosurg 2022; 137:1571-1581. [PMID: 35364587 PMCID: PMC9525455 DOI: 10.3171/2022.1.jns212031] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 01/31/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE The most common surgically treatable epilepsy syndrome is mesial temporal lobe epilepsy (mTLE). Preoperative noninvasive lateralization of mTLE is challenging in part due to rapid contralateral seizure spread. Abnormal connections in both the mesial temporal lobe and resting-state networks have been described in mTLE, but it is unclear if connectivity between these networks may aid in lateralization. METHODS In 52 patients with left mTLE (LmTLE) or right mTLE (RmTLE) and 52 matched control subjects, the authors acquired 20 minutes of resting-state functional MRI (fMRI) and evaluated functional connectivity of bilateral hippocampi and amygdalae with selected resting-state networks. They used Pearson correlation, network-based statistic, and dynamic causal modeling. Also, to evaluate the clinical utility of a resting-state connectivity model in lateralizing unilateral presurgical mTLE patients, they used receiver operating characteristic curve analysis. RESULTS RmTLE patients demonstrated decreased nondirected connectivity between the right hippocampus and default mode network compared with LmTLE patients and control subjects. Network-based statistic analysis revealed that the network with most decreased connectivity that distinguished LmTLE from RmTLE patients included the right hippocampus and amygdala, right lateral orbitofrontal cortices, and bilateral inferior parietal lobules, precuneus, and medial orbitofrontal cortices. Dynamic causal modeling analysis revealed that cross-hemispheric connectivity between hippocampi and amygdalae was predominantly inward toward the epileptogenic side. A regression model incorporating these connectivity patterns was used to accurately lateralize mTLE patients with an area under the receiver operating characteristic curve of 0.87. CONCLUSIONS Evaluating fMRI connectivity between mesial temporal structures and default mode network may aid in mTLE lateralization, reduce need for intracranial monitoring, and guide surgical planning.
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Affiliation(s)
- Saramati Narasimhan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Hernán F. J. González
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Graham W. Johnson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Kristin E. Wills
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Victoria L. Morgan
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
| | - Dario J. Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, Tennessee
- Vanderbilt Institute for Surgery and Engineering, Nashville, Tennessee
- Department of Biomedical, Nashville, Tennessee
- Department of Electrical Engineering and Computer Science at Vanderbilt University, Nashville, Tennessee
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Amplitude synchronization of spontaneous activity of medial and lateral temporal gyri reveals altered thalamic connectivity in patients with temporal lobe epilepsy. Sci Rep 2022; 12:18389. [PMID: 36319701 PMCID: PMC9626490 DOI: 10.1038/s41598-022-23297-4] [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: 07/31/2022] [Accepted: 10/29/2022] [Indexed: 12/02/2022] Open
Abstract
In this study, we examined whether amplitude synchronization of medial (MTL) and lateral (LTL) temporal lobes can detect unique alterations in patients with MTL epilepsy (mTLE) with mesial temporal sclerosis (MTS). This was a retrospective study of preoperative resting-state fMRI (rsfMRI) data from 31 patients with mTLE with MTS (age 23-69) and 16 controls (age 21-35). fMRI data were preprocessed based on a multistep preprocessing pipeline and registered to a standard space. Using each subject's T1-weighted scan, the MTL and LTL were automatically segmented, manually revised and then fit to a standard space using a symmetric normalization registration algorithm. Dual regression analysis was applied on preprocessed rsfMRI data to detect amplitude synchronization of medial and lateral temporal segments with the rest of the brain. We calculated the overlapped volume ratio of synchronized voxels within specific target regions including the thalamus (total and bilateral). A general linear model was used with Bonferroni correction for covariates of epilepsy duration and age of patient at scan to statistically compare synchronization in patients with mTLE with MTS and controls, as well as with respect to whether patients remained seizure-free (SF) or not (NSF) after receiving epilepsy surgery. We found increased ipsilateral positive connectivity between the LTLs and the thalamus and contralateral negative connectivity between the MTLs and the thalamus in patients with mTLE with MTS compared to controls. We also found increased asymmetry of functional connectivity between temporal lobe subregions and the thalamus in patients with mTLE with MTS, with increased positive connectivity between the LTL and the lesional-side thalamus as well as increased negative connectivity between the MTL and the nonlesional-side thalamus. This asymmetry was also seen in NSF patients but was not seen in SF patients and controls. Amplitude synchronization was an effective method to detect functional connectivity alterations in patients with mTLE with MTS. Patients with mTLE with MTS overall showed increased temporal-thalamic connectivity. There was increased functional involvement of the thalamus in MTS, underscoring its role in seizure spread. Increased functional thalamic asymmetry patterns in NSF patients may have a potential role in prognosticating patient response to surgery. Elucidating regions with altered functional connectivity to temporal regions can improve understanding of the involvement of different regions in the disease to potentially target for intervention or use for prognosis for surgery. Future studies are needed to examine the effectiveness of using patient-specific abnormalities in patterns to predict surgical outcome.
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Bernabei JM, Sinha N, Arnold TC, Conrad E, Ong I, Pattnaik AR, Stein JM, Shinohara RT, Lucas TH, Bassett DS, Davis KA, Litt B. Normative intracranial EEG maps epileptogenic tissues in focal epilepsy. Brain 2022; 145:1949-1961. [PMID: 35640886 PMCID: PMC9630716 DOI: 10.1093/brain/awab480] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2021] [Revised: 11/14/2021] [Accepted: 11/26/2021] [Indexed: 07/25/2023] Open
Abstract
Planning surgery for patients with medically refractory epilepsy often requires recording seizures using intracranial EEG. Quantitative measures derived from interictal intracranial EEG yield potentially appealing biomarkers to guide these surgical procedures; however, their utility is limited by the sparsity of electrode implantation as well as the normal confounds of spatiotemporally varying neural activity and connectivity. We propose that comparing intracranial EEG recordings to a normative atlas of intracranial EEG activity and connectivity can reliably map abnormal regions, identify targets for invasive treatment and increase our understanding of human epilepsy. Merging data from the Penn Epilepsy Center and a public database from the Montreal Neurological Institute, we aggregated interictal intracranial EEG retrospectively across 166 subjects comprising >5000 channels. For each channel, we calculated the normalized spectral power and coherence in each canonical frequency band. We constructed an intracranial EEG atlas by mapping the distribution of each feature across the brain and tested the atlas against data from novel patients by generating a z-score for each channel. We demonstrate that for seizure onset zones within the mesial temporal lobe, measures of connectivity abnormality provide greater distinguishing value than univariate measures of abnormal neural activity. We also find that patients with a longer diagnosis of epilepsy have greater abnormalities in connectivity. By integrating measures of both single-channel activity and inter-regional functional connectivity, we find a better accuracy in predicting the seizure onset zones versus normal brain (area under the curve = 0.77) compared with either group of features alone. We propose that aggregating normative intracranial EEG data across epilepsy centres into a normative atlas provides a rigorous, quantitative method to map epileptic networks and guide invasive therapy. We publicly share our data, infrastructure and methods, and propose an international framework for leveraging big data in surgical planning for refractory epilepsy.
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Affiliation(s)
- John M Bernabei
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Nishant Sinha
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104 USA
| | - T Campbell Arnold
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Erin Conrad
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Ian Ong
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Akash R Pattnaik
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Joel M Stein
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Timothy H Lucas
- Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104 USA
- Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Physics & Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- The Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104 USA
| | - Brian Litt
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
- Department of Neurology, Penn Epilepsy Center, Hospital of the University of Pennsylvania, Philadelphia, PA 19104 USA
- Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia, PA 19104, USA
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9
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Khalife MR, Scott RC, Hernan AE. Mechanisms for Cognitive Impairment in Epilepsy: Moving Beyond Seizures. Front Neurol 2022; 13:878991. [PMID: 35645970 PMCID: PMC9135108 DOI: 10.3389/fneur.2022.878991] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 04/19/2022] [Indexed: 11/13/2022] Open
Abstract
There has been a major emphasis on defining the role of seizures in the causation of cognitive impairments like memory deficits in epilepsy. Here we focus on an alternative hypothesis behind these deficits, emphasizing the mechanisms of information processing underlying healthy cognition characterized as rate, temporal and population coding. We discuss the role of the underlying etiology of epilepsy in altering neural networks thereby leading to both the propensity for seizures and the associated cognitive impairments. In addition, we address potential treatments that can recover the network function in the context of a diseased brain, thereby improving both seizure and cognitive outcomes simultaneously. This review shows the importance of moving beyond seizures and approaching the deficits from a system-level perspective with the guidance of network neuroscience.
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Affiliation(s)
- Mohamed R. Khalife
- Division of Neuroscience, Nemours Children's Health, Wilmington, DE, United States
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
| | - Rod C. Scott
- Division of Neuroscience, Nemours Children's Health, Wilmington, DE, United States
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
- Institute of Child Health, Neurosciences Unit University College London, London, United Kingdom
| | - Amanda E. Hernan
- Division of Neuroscience, Nemours Children's Health, Wilmington, DE, United States
- Psychological and Brain Sciences, University of Delaware, Newark, DE, United States
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10
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Cao M, Vogrin SJ, Peterson ADH, Woods W, Cook MJ, Plummer C. Dynamical Network Models From EEG and MEG for Epilepsy Surgery—A Quantitative Approach. Front Neurol 2022; 13:837893. [PMID: 35422755 PMCID: PMC9001937 DOI: 10.3389/fneur.2022.837893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 03/01/2022] [Indexed: 11/16/2022] Open
Abstract
There is an urgent need for more informative quantitative techniques that non-invasively and objectively assess strategies for epilepsy surgery. Invasive intracranial electroencephalography (iEEG) remains the clinical gold standard to investigate the nature of the epileptogenic zone (EZ) before surgical resection. However, there are major limitations of iEEG, such as the limited spatial sampling and the degree of subjectivity inherent in the analysis and clinical interpretation of iEEG data. Recent advances in network analysis and dynamical network modeling provide a novel aspect toward a more objective assessment of the EZ. The advantage of such approaches is that they are data-driven and require less or no human input. Multiple studies have demonstrated success using these approaches when applied to iEEG data in characterizing the EZ and predicting surgical outcomes. However, the limitations of iEEG recordings equally apply to these studies—limited spatial sampling and the implicit assumption that iEEG electrodes, whether strip, grid, depth or stereo EEG (sEEG) arrays, are placed in the correct location. Therefore, it is of interest to clinicians and scientists to see whether the same analysis and modeling techniques can be applied to whole-brain, non-invasive neuroimaging data (from MRI-based techniques) and neurophysiological data (from MEG and scalp EEG recordings), thus removing the limitation of spatial sampling, while safely and objectively characterizing the EZ. This review aims to summarize current state of the art non-invasive methods that inform epilepsy surgery using network analysis and dynamical network models. We also present perspectives on future directions and clinical applications of these promising approaches.
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Affiliation(s)
- Miao Cao
- Center for MRI Research, Peking University, Beijing, China
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
| | - Simon J. Vogrin
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
- School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Andre D. H. Peterson
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
| | - William Woods
- School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
| | - Mark J. Cook
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
| | - Chris Plummer
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
- Centre for Clinical Neurosciences and Neurological Research, St Vincent's Hospital Melbourne, Melbourne, VIC, Australia
- School of Health Sciences, Swinburne University of Technology, Melbourne, VIC, Australia
- *Correspondence: Chris Plummer
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11
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Functional connectivity of hippocampus in temporal lobe epilepsy depends on hippocampal dominance: a systematic review of the literature. J Neurol 2022; 269:221-232. [PMID: 33564915 DOI: 10.1007/s00415-020-10391-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 12/27/2020] [Accepted: 12/28/2020] [Indexed: 01/03/2023]
Abstract
BACKGROUND Lateralized alterations in hippocampal function in the resting-state have been demonstrated for patients with temporal lobe epilepsy (TLE). However, resting-state fMRI of the hippocampus has yet to be substantiated as an adjunct to standard pre-operative assessments of the seizure focus. OBJECTIVE Here we report the results of a systematic review of resting-state fMRI studies investigating laterality of hippocampal network connectivity in TLE patients. METHODS A search of the PubMed, SCOPUS, Web of Science, and Embase databases for full-length articles written in English was conducted through June 2020 using the following terms: 'resting state fMRI,' 'hippocampus,' 'epilepsy,' and 'laterality.' RESULTS Our literature search yielded a total of 42 papers. After excluding studies that did not include patients with epilepsy, utilize resting-state fMRI, or explore the relationship between functional connectivity and disease lateralization, 20 publications were selected for inclusion. From these studies, a total of 528 patients, 258 with left TLE and 270 with right TLE, and 447 healthy controls were included. Of the 20 studies included, 18 found that patients with TLE demonstrated decreased hippocampal functional connectivity ipsilateral to the epileptogenic focus and 10 additionally reported increased hippocampal functional connectivity contralateral to the epileptogenic focus. Several studies demonstrated that the duration of disease was correlated with these changes in functional connectivity. This implies that a compensatory mechanism may be present in patients with treatment-refractory TLE. CONCLUSION The consistency of this hippocampal connectivity pattern across multiple studies suggests resting-state fMRI may be useful as a non-invasive diagnostic tool for preoperative evaluation of TLE patients.
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12
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Strýček O, Lamoš M, Rektor I. Memory retrieval in temporal lobe epilepsy is related to functional segregation of the mesiotemporal structures. Epilepsy Behav 2021; 122:108196. [PMID: 34256340 DOI: 10.1016/j.yebeh.2021.108196] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 06/16/2021] [Accepted: 06/24/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE We analyzed the impact of temporal lobe epilepsy (TLE) with hippocampal sclerosis (HS) on functional connectivity (FC) between mesiotemporal structures. Functional connectivity modifications related to word retrieval were investigated. METHODS High-density EEG of 21 patients with TLE with HS (12 left TLE and 9 right TLE) and 10 healthy controls (HCs) were recorded during a verbal subsequent memory paradigm. Electroencephalography data were reconstructed into the source space and FC was calculated from the source activity of regions of interest. RESULTS A significant decrease in FC between the right- and left-sided mesiotemporal structures in TLE was observed. The decrease was significant only with words that were correctly recognized. The decrease in interhemispheric FC between mesiotemporal structures was found in the 8- to 20-Hz frequency range in both left and right TLE. SIGNIFICANCE The decreased FC between the mesiotemporal structures in TLE is a condition for successful performance of a memory retrieval task. The successful memory retrieval in TLE is related to functional segregation of lesional from nonlesional mesiotemporal structures. This decrease was absent in non-successful responses.
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Affiliation(s)
- Ondřej Strýček
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic; Central European Institute of Technology (CEITEC), Masaryk University, Brain and Mind Research Program, Brno, Czech Republic
| | - Martin Lamoš
- Central European Institute of Technology (CEITEC), Masaryk University, Brain and Mind Research Program, Brno, Czech Republic
| | - Ivan Rektor
- First Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic; Central European Institute of Technology (CEITEC), Masaryk University, Brain and Mind Research Program, Brno, Czech Republic.
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13
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Balzekas I, Sladky V, Nejedly P, Brinkmann BH, Crepeau D, Mivalt F, Gregg NM, Pal Attia T, Marks VS, Wheeler L, Riccelli TE, Staab JP, Lundstrom BN, Miller KJ, Van Gompel J, Kremen V, Croarkin PE, Worrell GA. Invasive Electrophysiology for Circuit Discovery and Study of Comorbid Psychiatric Disorders in Patients With Epilepsy: Challenges, Opportunities, and Novel Technologies. Front Hum Neurosci 2021; 15:702605. [PMID: 34381344 PMCID: PMC8349989 DOI: 10.3389/fnhum.2021.702605] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 06/29/2021] [Indexed: 01/10/2023] Open
Abstract
Intracranial electroencephalographic (iEEG) recordings from patients with epilepsy provide distinct opportunities and novel data for the study of co-occurring psychiatric disorders. Comorbid psychiatric disorders are very common in drug-resistant epilepsy and their added complexity warrants careful consideration. In this review, we first discuss psychiatric comorbidities and symptoms in patients with epilepsy. We describe how epilepsy can potentially impact patient presentation and how these factors can be addressed in the experimental designs of studies focused on the electrophysiologic correlates of mood. Second, we review emerging technologies to integrate long-term iEEG recording with dense behavioral tracking in naturalistic environments. Third, we explore questions on how best to address the intersection between epilepsy and psychiatric comorbidities. Advances in ambulatory iEEG and long-term behavioral monitoring technologies will be instrumental in studying the intersection of seizures, epilepsy, psychiatric comorbidities, and their underlying circuitry.
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Affiliation(s)
- Irena Balzekas
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States
- Mayo Clinic Alix School of Medicine, Rochester, MN, United States
- Mayo Clinic Medical Scientist Training Program, Rochester, MN, United States
| | - Vladimir Sladky
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Faculty of Biomedical Engineering, Czech Technical University in Prague, Kladno, Czechia
| | - Petr Nejedly
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- The Czech Academy of Sciences, Institute of Scientific Instruments, Brno, Czechia
| | - Benjamin H. Brinkmann
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Daniel Crepeau
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Filip Mivalt
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering, Brno University of Technology, Brno, Czechia
| | - Nicholas M. Gregg
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Tal Pal Attia
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Victoria S. Marks
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States
| | - Lydia Wheeler
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Biomedical Engineering and Physiology Graduate Program, Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, United States
- Mayo Clinic Alix School of Medicine, Rochester, MN, United States
| | - Tori E. Riccelli
- Mayo Clinic Alix School of Medicine, Rochester, MN, United States
| | - Jeffrey P. Staab
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
- Department of Otorhinolaryngology, Mayo Clinic, Rochester, MN, United States
| | - Brian Nils Lundstrom
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
| | - Kai J. Miller
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
| | - Jamie Van Gompel
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Neurosurgery, Mayo Clinic, Rochester, MN, United States
| | - Vaclav Kremen
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Czech Institute of Informatics, Robotics and Cybernetics, Czech Technical University in Prague, Prague, Czechia
| | - Paul E. Croarkin
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, United States
| | - Gregory A. Worrell
- Bioelectronics, Neurophysiology, and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
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14
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Liang X, Pang X, Zhao J, Yu L, Wu P, Li X, Wei W, Zheng J. Altered static and dynamic functional network connectivity in temporal lobe epilepsy with different disease duration and their relationships with attention. J Neurosci Res 2021; 99:2688-2705. [PMID: 34269468 DOI: 10.1002/jnr.24915] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/13/2021] [Accepted: 06/14/2021] [Indexed: 11/09/2022]
Abstract
The brain network alterations associated with temporal lobe epilepsy (TLE) progression are still unclear. The purpose of this study was to investigate altered patterns of static and dynamic functional network connectivity (sFNC and dFNC) in TLE with different durations of disease. In this study, 19 TLE patients with a disease duration of ≤5 years (TLE-SD), 24 TLE patients with a disease duration of >5 years (TLE-LD), and 21 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging and attention network test. We used group independent component analysis to determine the target resting-state networks. Sliding window correlation and k-means clustering analysis methods were used to obtain different dFNC states, temporal properties, and temporal variability. We then compared sFNC and dFNC between groups and found that compared with HCs, TLE-SD patients had increased sFNC between the dorsal attention network and sensorimotor network/visual network (VN), but decreased sFNC between the inferior-posterior default mode network and VN. In the strongly connected dFNC state, TLE-SD patients spent more time, had greater mean dwell time, and showed greater inconsistent abnormal network connectivity. There was a significant negative correlation between the temporal variability of auditory network- left fronto-parietal network connectivity and orienting effect. No significant differences in sFNC and dFNC were detected between TLE-LD and HC groups. These findings suggest that the damage and functional brain network abnormalities gradually occur in TLE patients after the onset of epilepsy, which might lead to functional network reorganization and compensatory remodeling as the disease progresses.
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Affiliation(s)
- Xiulin Liang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiaomin Pang
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jingyuan Zhao
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Lu Yu
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Peirong Wu
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xinrong Li
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wutong Wei
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jinou Zheng
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
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15
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Davis KA, Jirsa VK, Schevon CA. Wheels Within Wheels: Theory and Practice of Epileptic Networks. Epilepsy Curr 2021; 21:15357597211015663. [PMID: 33988042 PMCID: PMC8512917 DOI: 10.1177/15357597211015663] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Affiliation(s)
- Kathryn A. Davis
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Viktor K. Jirsa
- Aix-Marseille Universite, Marseille, Provence-Alpes-Cote d’Azu, France
- INSERM, Paris, Ile-de-France, France
- Institute de Neurosciences des Systemes,
Marseille, Provence-Alpes-Cote d’Azu, France
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16
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Morgan VL, Johnson GW, Cai LY, Landman BA, Schilling KG, Englot DJ, Rogers BP, Chang C. MRI network progression in mesial temporal lobe epilepsy related to healthy brain architecture. Netw Neurosci 2021; 5:434-450. [PMID: 34189372 PMCID: PMC8233120 DOI: 10.1162/netn_a_00184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2020] [Accepted: 01/11/2021] [Indexed: 11/04/2022] Open
Abstract
We measured MRI network progression in mesial temporal lobe epilepsy (mTLE) patients as a function of healthy brain architecture. Resting-state functional MRI and diffusion-weighted MRI were acquired in 40 unilateral mTLE patients and 70 healthy controls. Data were used to construct region-to-region functional connectivity, structural connectivity, and streamline length connectomes per subject. Three models of distance from the presumed seizure focus in the anterior hippocampus in the healthy brain were computed using the average connectome across controls. A fourth model was defined using regions of transmodal (higher cognitive function) to unimodal (perceptual) networks across a published functional gradient in the healthy brain. These models were used to test whether network progression in patients increased when distance from the anterior hippocampus or along a functional gradient in the healthy brain decreases. Results showed that alterations of structural and functional networks in mTLE occur in greater magnitude in regions of the brain closer to the seizure focus based on healthy brain topology, and decrease as distance from the focus increases over duration of disease. Overall, this work provides evidence that changes across the brain in focal epilepsy occur along healthy brain architecture.
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Affiliation(s)
- Victoria L. Morgan
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Graham W. Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Leon Y. Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A. Landman
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Kurt G. Schilling
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dario J. Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Baxter P. Rogers
- Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Catie Chang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN, USA
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17
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Shih YC, Lin FH, Liou HH, Tseng WYI. Seizure Frequency Is Associated with Effective Connectivity of the Hippocampal-Diencephalic-Cingulate in Epilepsy with Unilateral Mesial Temporal Sclerosis. Brain Connect 2021; 11:457-470. [PMID: 33403892 DOI: 10.1089/brain.2020.0835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background: Temporal lobe epilepsy (TLE) with mesial temporal sclerosis (MTS) is a common intractable epilepsy. To seek neural correlates of seizure recurrence, this study investigated aberrant intrinsic effective connectivity (iEC) in TLE with unilateral MTS and their associations with seizure frequency. Methods: Thirty patients with unilateral MTS (left/right MTS = 14/16) and 37 age-matched healthy controls underwent resting-state functional magnetic resonance imaging (rsfMRI) on a 3-Tesla magnetic resonance imaging (MRI) system. The structural equation modeling was employed to estimate the iEC of the three candidate epilepsy models, including the Papez circuit, hippocampal-diencephalic-cingulate (HDC) model, and simplified HDC model. After comparing the performance of model fitting, the best model was selected to compare iEC among the study groups. The linear regression analysis was performed to associate abnormal iEC with seizure frequency. Results: The simplified HDC model was the best model to estimate iEC across the three study groups (p < 0.05), and it composed of the 26 interconnected pathway between the mesial temporal lobe, thalamus, and cingulate cortices. The linear regression analysis revealed a significant relationship between the shared iEC alterations in both patient groups and seizure frequency (adjusted-R2 = 0.350; p = 0.037), including the three paths of mammillary body (MB) → bilateral anterior thalamic nuclei (left: standardized β-value = 0.580, p = 0.013; right: standardized β-value = -0.711, p = 0.006) and right hippocampus → MB (standardized β-value = 0.541, p = 0.045). Conclusions: Our findings provide new insights into neurophysiological significance relevant to seizure recurrence. Aberrant iEC on the neural paths connected to the MB can be a potential imaging marker, aiding the therapeutic management in TLE with unilateral MTS. Impact statement Within the simplified hippocampal-diencephalic-cingulate model, we identified that altered intrinsic effective connectivity (iEC) on the three paths connecting to the mammillary body was common in temporal lobe epilepsy (TLE) with left and right mesial temporal sclerosis (MTS) and was associated with seizure frequency. Therefore, these common iEC alterations could be a potential imaging marker, aiding the therapeutic management in patients with TLE with unilateral MTS.
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Affiliation(s)
- Yao-Chia Shih
- Institute of Biomedical Engineering, National Taiwan University, Taipei, Taiwan.,Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Diagnostic Radiology, Singapore General Hospital, Singapore, Singapore
| | - Fa-Hsuan Lin
- Department of Medical Biophysics, University of Toronto, Toronto, Canada.,Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Canada
| | - Horng-Huei Liou
- Department of Neurology, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Wen-Yih Isaac Tseng
- Institute of Medical Device and Imaging, College of Medicine, National Taiwan University, Taipei, Taiwan.,Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan.,Department of Medical Imaging, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan.,Molecular Imaging Center, National Taiwan University, Taipei, Taiwan
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18
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Bou Assi E, Zerouali Y, Robert M, Lesage F, Pouliot P, Nguyen DK. Large-Scale Desynchronization During Interictal Epileptic Discharges Recorded With Intracranial EEG. Front Neurol 2020; 11:529460. [PMID: 33424733 PMCID: PMC7785800 DOI: 10.3389/fneur.2020.529460] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 11/27/2020] [Indexed: 11/13/2022] Open
Abstract
It is increasingly recognized that deep understanding of epileptic seizures requires both localizing and characterizing the functional network of the region where they are initiated, i. e., the epileptic focus. Previous investigations of the epileptogenic focus' functional connectivity have yielded contrasting results, reporting both pathological increases and decreases during resting periods and seizures. In this study, we shifted paradigm to investigate the time course of connectivity in relation to interictal epileptiform discharges. We recruited 35 epileptic patients undergoing intracranial EEG (iEEG) investigation as part of their presurgical evaluation. For each patient, 50 interictal epileptic discharges (IEDs) were marked and iEEG signals were epoched around those markers. Signals were narrow-band filtered and time resolved phase-locking values were computed to track the dynamics of functional connectivity during IEDs. Results show that IEDs are associated with a transient decrease in global functional connectivity, time-locked to the peak of the discharge and specific to the high range of the gamma frequency band. Disruption of the long-range connectivity between the epileptic focus and other brain areas might be an important process for the generation of epileptic activity. Transient desynchronization could be a potential biomarker of the epileptogenic focus since 1) the functional connectivity involving the focus decreases significantly more than the connectivity outside the focus and 2) patients with good surgical outcome appear to have a significantly more disconnected focus than patients with bad outcomes.
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Affiliation(s)
- Elie Bou Assi
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada.,Department of Neuroscience, University of Montreal, Montreal, QC, Canada
| | - Younes Zerouali
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada.,Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada
| | - Manon Robert
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada
| | - Frederic Lesage
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
| | - Philippe Pouliot
- Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, QC, Canada.,Montreal Heart Institute, Montreal, QC, Canada
| | - Dang K Nguyen
- University of Montreal Hospital Research Center (CRCHUM), University of Montreal, Montreal, QC, Canada.,Department of Neuroscience, University of Montreal, Montreal, QC, Canada
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Larivière S, Rodríguez-Cruces R, Royer J, Caligiuri ME, Gambardella A, Concha L, Keller SS, Cendes F, Yasuda C, Bonilha L, Gleichgerrcht E, Focke NK, Domin M, von Podewills F, Langner S, Rummel C, Wiest R, Martin P, Kotikalapudi R, O'Brien TJ, Sinclair B, Vivash L, Desmond PM, Alhusaini S, Doherty CP, Cavalleri GL, Delanty N, Kälviäinen R, Jackson GD, Kowalczyk M, Mascalchi M, Semmelroch M, Thomas RH, Soltanian-Zadeh H, Davoodi-Bojd E, Zhang J, Lenge M, Guerrini R, Bartolini E, Hamandi K, Foley S, Weber B, Depondt C, Absil J, Carr SJA, Abela E, Richardson MP, Devinsky O, Severino M, Striano P, Tortora D, Hatton SN, Vos SB, Duncan JS, Whelan CD, Thompson PM, Sisodiya SM, Bernasconi A, Labate A, McDonald CR, Bernasconi N, Bernhardt BC. Network-based atrophy modeling in the common epilepsies: A worldwide ENIGMA study. SCIENCE ADVANCES 2020; 6:eabc6457. [PMID: 33208365 PMCID: PMC7673818 DOI: 10.1126/sciadv.abc6457] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 10/05/2020] [Indexed: 06/10/2023]
Abstract
Epilepsy is increasingly conceptualized as a network disorder. In this cross-sectional mega-analysis, we integrated neuroimaging and connectome analysis to identify network associations with atrophy patterns in 1021 adults with epilepsy compared to 1564 healthy controls from 19 international sites. In temporal lobe epilepsy, areas of atrophy colocalized with highly interconnected cortical hub regions, whereas idiopathic generalized epilepsy showed preferential subcortical hub involvement. These morphological abnormalities were anchored to the connectivity profiles of distinct disease epicenters, pointing to temporo-limbic cortices in temporal lobe epilepsy and fronto-central cortices in idiopathic generalized epilepsy. Negative effects of age on atrophy further revealed a strong influence of connectome architecture in temporal lobe, but not idiopathic generalized, epilepsy. Our findings were reproduced across individual sites and single patients and were robust across different analytical methods. Through worldwide collaboration in ENIGMA-Epilepsy, we provided deeper insights into the macroscale features that shape the pathophysiology of common epilepsies.
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Affiliation(s)
- Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Raúl Rodríguez-Cruces
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | | | - Antonio Gambardella
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Luis Concha
- Institute of Neurobiology, Universidad Nacional Autónoma de México, Querétaro, México
| | - Simon S Keller
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK
- Walton Centre NHS Foundation Trust, Liverpool, UK
| | - Fernando Cendes
- Department of Neurology, University of Campinas-UNICAMP, Campinas, São Paulo, Brazil
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas-UNICAMP, Campinas, São Paulo, Brazil
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, SC, USA
| | | | - Niels K Focke
- Department of Clinical Neurophysiology, University of Medicine Göttingen, Göttingen, Germany
| | - Martin Domin
- Institute of Diagnostic Radiology and Neuroradiology, Functional Imaging Unit, University Medicine Greifswald, Greifswald, Germany
| | - Felix von Podewills
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Soenke Langner
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Christian Rummel
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Roland Wiest
- Support Center for Advanced Neuroimaging (SCAN), University Institute of Diagnostic and Interventional Neuroradiology, University Hospital Bern, Bern, Switzerland
| | - Pascal Martin
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Raviteja Kotikalapudi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Benjamin Sinclair
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, Alfred Hospital, Monash University, Melbourne, Victoria, Australia
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Patricia M Desmond
- Departments of Medicine and Radiology, The Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Saud Alhusaini
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- Department of Neurology, Yale University School of Medicine, New Haven, CT, USA
| | - Colin P Doherty
- Department of Neurology, St. James' Hospital, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Gianpiero L Cavalleri
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Norman Delanty
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, Dublin, Ireland
| | - Reetta Kälviäinen
- Epilepsy Center, Neuro Center, Kuopio University Hospital, European Reference Network for Rare and Complex Epilepsies EpiCARE, Kuopio, Finland
- Faculty of Health Sciences, School of Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Magdalena Kowalczyk
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Mario Mascalchi
- Neuroradiology Research Program, Meyer Children Hospital of Florence, University of Florence, Florence, Italy
| | - Mira Semmelroch
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Rhys H Thomas
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Hamid Soltanian-Zadeh
- Control and Intelligent Processing Center of Excellence (CIPCE), School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
- Departments of Research Administration and Radiology, Henry Ford Health System, Detroit, MI, USA
| | | | - Junsong Zhang
- Cognitive Science Department, Xiamen University, Xiamen, China
| | - Matteo Lenge
- Child Neurology Unit and Laboratories, Neuroscience Department, Children's Hospital A. Meyer-University of Florence, Italy
- Functional and Epilepsy Neurosurgery Unit, Neurosurgery Department, Children's Hospital A. Meyer-University of Florence, Italy
| | - Renzo Guerrini
- Child Neurology Unit and Laboratories, Neuroscience Department, Children's Hospital A. Meyer-University of Florence, Italy
| | - Emanuele Bartolini
- USL Centro Toscana, Neurology Unit, Nuovo Ospedale Santo Stefano, Prato, Italy
| | - Khalid Hamandi
- Cardiff University Brain Research Imaging Centre (CUBRIC), College of Biomedical Sciences, Cardiff University, Cardiff, UK
- Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Sonya Foley
- Welsh Epilepsy Unit, Department of Neurology, University Hospital of Wales, Cardiff, UK
| | - Bernd Weber
- Institute of Experimental Epileptology and Cognition Research, University Hospital Bonn, Bonn, Germany
| | - Chantal Depondt
- Department of Neurology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Julie Absil
- Department of Radiology, Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Sarah J A Carr
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Eugenio Abela
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Mark P Richardson
- Division of Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Orrin Devinsky
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | | | | | | | - Sean N Hatton
- Department of Neurosciences, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Sjoerd B Vos
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
- Centre for Medical Image Computing, University College London, London, UK
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Christopher D Whelan
- Department of Molecular and Cellular Therapeutics, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Institute for Neuroimaging and Informatics, USC Keck School of Medicine, Los Angeles, CA, USA
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Institute of Neurology, London, UK
- Chalfont Centre for Epilepsy, Bucks, UK
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Angelo Labate
- Neuroscience Research Center, University Magna Græcia, Catanzaro, CZ, Italy
- Institute of Neurology, University Magna Græcia, Catanzaro, CZ, Italy
| | - Carrie R McDonald
- Department of Psychiatry, Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, CA, USA
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
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Longitudinal analysis of structural connectivity in patients with newly diagnosed focal epilepsy of unknown origin. Clin Neurol Neurosurg 2020; 199:106264. [PMID: 33031991 DOI: 10.1016/j.clineuro.2020.106264] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/06/2020] [Accepted: 09/29/2020] [Indexed: 11/21/2022]
Abstract
OBJECTIVES The aim of this longitudinal study was to clarify whether significant alterations in structural connectivity occur over time in patients with newly diagnosed focal epilepsy of unknown origin. METHODS A total of 40 patients with newly diagnosed focal epilepsy of unknown origin and with normal brain magnetic resonance imaging (MRI) on visual inspection were enrolled. All subjects underwent MRI twice involving three-dimensional volumetric T1-weighted imaging, which were suitable for structural volume analysis. Gray matter volumes were obtained using the FreeSurfer image analysis suite, and structural connectivity analyses were performed using Matlab-based BRain Analysis using graPH theory software. RESULTS The median interval between the two MRI scans was 18.5 months in patients with epilepsy. There was a general tendency toward decreased gray matter volumes on the second scan compared with the initial scan. However, the volumes of the right and left thalamus and brainstem on the second MRI scan had an increased tendency compared with those on the initial MRI scan. In measures of connectivity, there were significant differences between the two MRI scans. The mean clustering coefficient, global efficiency, local efficiency, and the small-worldness index were significantly increased, whereas the characteristic path length was decreased on the second MRI scan compared with the initial MRI scan. CONCLUSIONS The structural connectivity in patients with newly diagnosed focal epilepsy of unknown origin increases over time in the initial stage. These alterations and increases in structural connectivity may be related to underlying epileptogenicity in the initial stages of epilepsy.
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Marcián V, Mareček R, Pail M, Brázdil M. Cerebrocerebellar structural covariance in temporal lobe epilepsy with hippocampal sclerosis. Epilepsy Behav 2020; 111:107180. [PMID: 32599430 DOI: 10.1016/j.yebeh.2020.107180] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 05/12/2020] [Accepted: 05/20/2020] [Indexed: 11/24/2022]
Abstract
PURPOSE The purpose of the study was to evaluate cerebral morphological changes in temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) and their relationship to the cerebellum. METHODS The study cohort included 21 patients with intractable TLE-HS (14 left-sided, 7 right-sided) and 38 healthy controls (HC). All patients later underwent anteromedial temporal lobe resection. All subjects were examined using a 1.5-T magnetic resonance imaging (MRI). Volumes of distinct cerebral and cerebellar structures were measured using voxel-based morphometry. The structural covariance of temporal lobe structures, insula, and thalamus with cerebellar substructures was examined using partial least squares regression. RESULTS Morphological changes were more significant in the group with left TLE-HS when comparing left-sided with right-sided structures as well as when comparing patients with controls. The gray matter volume (GMV) of the temporal lobe structures was smaller ipsilaterally to the seizure onset side in most cases. There was a significant amygdala enlargement contralateral to the side of hippocampal sclerosis in both patients with right and left TLE-HS as compared with controls. Selected vermian structures in patients with left but not right TLE-HS had significantly larger GMV than the identical substructures in controls. The structural covariance differed significantly between patients with left and right TLE-HS as compared with HC. The analysis revealed significant negative covariance between anterior vermis and mesial temporal structures in the group with left TLE-HS. No significance was observed for the group with right TLE-HS. CONCLUSION There is significant asymmetry in the GMV of cerebral and cerebellar structures in patients with TLE-HS. Morphological changes are distinctly more pronounced in patients with left TLE-HS. The observed structural covariance between the cerebellum and supratentorial structures in TLE-HS suggests associations beyond the mesial temporal lobe structures and thalamus.
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Affiliation(s)
- Václav Marcián
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic; University Hospital Ostrava, Department of Neurology, Ostrava, Czech Republic.
| | - Radek Mareček
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic; Multimodal and Functional Neuroimaging Research Group, CEITEC (Central European Institute of Technology), Masaryk University, Brno, Czech Republic
| | - Martin Pail
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | - Milan Brázdil
- Brno Epilepsy Center, First Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic; Behavioral and Social Neuroscience Research Group, CEITEC (Central European Institute of Technology), Masaryk University, Brno, Czech Republic
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Morgan VL, Rogers BP, González HFJ, Goodale SE, Englot DJ. Characterization of postsurgical functional connectivity changes in temporal lobe epilepsy. J Neurosurg 2020; 133:392-402. [PMID: 31200384 PMCID: PMC6911037 DOI: 10.3171/2019.3.jns19350] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2019] [Accepted: 03/24/2019] [Indexed: 02/02/2023]
Abstract
OBJECTIVE Seizure outcome after mesial temporal lobe epilepsy (mTLE) surgery is complex and diverse, even across patients with homogeneous presurgical clinical profiles. The authors hypothesized that this is due in part to variations in network connectivity across the brain before and after surgery. Although presurgical network connectivity has been previously characterized in these patients, the objective of this study was to characterize presurgical to postsurgical functional network connectivity changes across the brain after mTLE surgery. METHODS Twenty patients with drug-refractory unilateral mTLE (5 left side, 10 female, age 39.3 ± 13.5 years) who underwent either selective amygdalohippocampectomy (n = 13) or temporal lobectomy (n = 7) were included in the study. Presurgical and postsurgical (36.6 ± 14.3 months after surgery) functional connectivity (FC) was measured with 3-T MRI and compared with findings in age-matched healthy controls (n = 44, 21 female, age 39.3 ± 14.3 years). Postsurgical connectivity changes were then related to seizure outcome, type of surgery, and presurgical disease parameters. RESULTS The results demonstrated significant decreases of FC from control group values across the brain after surgery that were not present before surgery, including many contralateral hippocampal connections distal to the surgical site. Postsurgical impairment of contralateral precuneus to ipsilateral occipital connectivity was associated with seizure recurrence. Presurgical impairment of the contralateral precuneus to contralateral temporal lobe connectivity was associated with those who underwent selective amygdalohippocampectomy compared to those who had temporal lobectomy. Finally, changes in thalamic connectivity after surgery were linearly related to duration of epilepsy and frequency of consciousness-impairing seizures prior to surgery. CONCLUSIONS The widespread contralateral hippocampal FC changes after surgery may be a reflection of an ongoing epileptogenic progression that has been altered by the surgery, rather than a direct result of the surgery itself. This network evolution may contribute to long-term seizure outcome. Therefore, the combination of presurgical network mapping with the understanding of the dynamic effects of surgery on the networks may ultimately be used to create predictors of the likelihood of long-term seizure recurrence in individual patients after mTLE surgery.
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Affiliation(s)
- Victoria L. Morgan
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
- Department of Biomedical Engineering, Vanderbilt University
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Baxter P. Rogers
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
| | | | | | - Dario J. Englot
- Vanderbilt University Institute of Imaging Science, Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
- Department of Biomedical Engineering, Vanderbilt University
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
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Human brain connectivity: Clinical applications for clinical neurophysiology. Clin Neurophysiol 2020; 131:1621-1651. [DOI: 10.1016/j.clinph.2020.03.031] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 03/13/2020] [Accepted: 03/17/2020] [Indexed: 12/12/2022]
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Larivière S, Weng Y, Vos de Wael R, Royer J, Frauscher B, Wang Z, Bernasconi A, Bernasconi N, Schrader DV, Zhang Z, Bernhardt BC. Functional connectome contractions in temporal lobe epilepsy: Microstructural underpinnings and predictors of surgical outcome. Epilepsia 2020; 61:1221-1233. [PMID: 32452574 DOI: 10.1111/epi.16540] [Citation(s) in RCA: 59] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 04/27/2020] [Accepted: 04/27/2020] [Indexed: 01/02/2023]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is the most common drug-resistant epilepsy in adults. Although it is commonly related to hippocampal pathology, increasing evidence suggests structural changes beyond the mesiotemporal lobe. Functional anomalies and their link to underlying structural alterations, however, remain incompletely understood. METHODS We studied 30 drug-resistant TLE patients and 57 healthy controls using multimodal magnetic resonance imaging (MRI) analyses. All patients had histologically verified hippocampal sclerosis and underwent postoperative imaging to outline the extent of their surgical resection. Our analysis leveraged a novel resting-state functional MRI framework that parameterizes functional connectivity distance, consolidating topological and physical properties of macroscale brain networks. Functional findings were integrated with morphological and microstructural metrics, and utility for surgical outcome prediction was assessed using machine learning techniques. RESULTS Compared to controls, TLE patients showed connectivity distance reductions in temporoinsular and prefrontal networks, indicating topological segregation of functional networks. Testing for morphological and microstructural associations, we observed that functional connectivity contractions occurred independently from TLE-related cortical atrophy but were mediated by microstructural changes in the underlying white matter. Following our imaging study, all patients underwent an anterior temporal lobectomy as a treatment of their seizures, and postsurgical seizure outcome was determined at a follow-up at least 1 year after surgery. Using a regularized supervised machine learning paradigm with fivefold cross-validation, we demonstrated that patient-specific functional anomalies predicted postsurgical seizure outcome with 76 ± 4% accuracy, outperforming classifiers operating on clinical and structural imaging features. SIGNIFICANCE Our findings suggest connectivity distance contractions as a macroscale substrate of TLE. Functional topological isolation may represent a microstructurally mediated network mechanism that tilts the balance toward epileptogenesis in affected networks and that may assist in patient-specific surgical prognostication.
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Affiliation(s)
- Sara Larivière
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Yifei Weng
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Reinder Vos de Wael
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Zhengge Wang
- Department of Radiology, Nanjing Drum Tower Hospital, Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Dewi V Schrader
- Department of Pediatrics, BC Children's Hospital, University of British Columbia, Vancouver, British Columbia, Canada
| | - Zhiqiang Zhang
- Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Functional Activation Patterns of Deep Brain Stimulation of the Anterior Nucleus of the Thalamus. World Neurosurg 2020; 136:357-363.e2. [DOI: 10.1016/j.wneu.2020.01.108] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 01/15/2020] [Accepted: 01/16/2020] [Indexed: 11/23/2022]
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Middlebrooks EH, Grewal SS, Stead M, Lundstrom BN, Worrell GA, Van Gompel JJ. Differences in functional connectivity profiles as a predictor of response to anterior thalamic nucleus deep brain stimulation for epilepsy: a hypothesis for the mechanism of action and a potential biomarker for outcomes. Neurosurg Focus 2019; 45:E7. [PMID: 30064322 DOI: 10.3171/2018.5.focus18151] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) of the anterior nucleus of the thalamus (ANT) is a promising therapy for refractory epilepsy. Unfortunately, the variability in outcomes from ANT DBS is not fully understood. In this pilot study, the authors assess potential differences in functional connectivity related to the volume of tissue activated (VTA) in ANT DBS responders and nonresponders as a means for better understanding the mechanism of action and potentially improving DBS targeting. METHODS This retrospective analysis consisted of 6 patients who underwent ANT DBS for refractory epilepsy. Patients were classified as responders (n = 3) if their seizure frequency decreased by at least 50%. The DBS electrodes were localized postoperatively and VTAs were computationally generated based on DBS programming settings. VTAs were used as seed points for resting-state functional MRI connectivity analysis performed using a control dataset. Differences in cortical connectivity to the VTA were assessed between the responder and nonresponder groups. RESULTS The ANT DBS responders showed greater positive connectivity with the default mode network compared to nonresponders, including the posterior cingulate cortex, medial prefrontal cortex, inferior parietal lobule, and precuneus. Interestingly, there was also a consistent anticorrelation with the hippocampus seen in responders that was not present in nonresponders. CONCLUSIONS Based on their pilot study, the authors observed that successful ANT DBS in patients with epilepsy produces increased connectivity in the default mode network, which the authors hypothesize increases the threshold for seizure propagation. Additionally, an inhibitory effect on the hippocampus mediated through increased hippocampal γ-aminobutyric acid (GABA) concentration may contribute to seizure suppression. Future studies are planned to confirm these findings.
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Affiliation(s)
- Erik H Middlebrooks
- Departments of1Radiology and.,2Neurosurgery, Mayo Clinic, Jacksonville, Florida; and
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Shi H, Wang Y, Liu X, Xia L, Chen Y, Lu Q, Nguchu BA, Wang H, Qiu B, Wang X, Feng L. Cortical Alterations by the Abnormal Visual Experience beyond the Critical Period: A Resting-state fMRI Study on Constant Exotropia. Curr Eye Res 2019; 44:1386-1392. [PMID: 31280612 DOI: 10.1080/02713683.2019.1639767] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Purpose: The pathological mechanisms of constant exotropia (XT) are still not understood. This study aimed to critically investigate whether patients with XT express neuronal activity changes after the critical period of visual development and further explore how these alterations are associated with behavioral performance.Materials and methods: Fourteen patients with XT and 16 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). The regional homogeneity (ReHo) method was used to evaluate spontaneous brain activities. The association between significantly altered mean ReHo values and behavioral performance was assessed using Pearson's correlation analysis.Results: Compared with HCs, the right secondary visual cortex (V2) in patients with XT exhibited increased ReHo values, whereas the left Brodmann area 47 (BA47) demonstrated decreased spontaneous ReHo values. In patients with XT, the correlation between the left BA47's mean ReHo value and duration of strabismus was positively significant.Conclusions: These findings indicate that patients with XT have severe neural dysfunction in the right V2 and left BA47, and pathological severity in the left BA47 is likely influenced by duration of ongoing strabismus. Therefore, these results may provide clinically important information toward understanding the underlying pathological mechanisms of XT and thus can be fundamental in future XT research.
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Affiliation(s)
- Hongmei Shi
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yanming Wang
- Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Xuemei Liu
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Lin Xia
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yao Chen
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Qinlin Lu
- CAS Key Laboratory of Brain Function and Diseases and School of Life Sciences, University of Science and Technology of China, Hefei, People's Republic of China
| | | | - Huijuan Wang
- Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Bensheng Qiu
- Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Xiaoxiao Wang
- Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, China
| | - Lixia Feng
- Department of Ophthalmology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
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Abstract
Epilepsy is a chronic neurological condition, following some trigger, transforming a normal brain to one that produces recurrent unprovoked seizures. In the search for the mechanisms that best explain the epileptogenic process, there is a growing body of evidence suggesting that the epilepsies are network level disorders. In this review, we briefly describe the concept of neuronal networks and highlight 2 methods used to analyse such networks. The first method, graph theory, is used to describe general characteristics of a network to facilitate comparison between normal and abnormal networks. The second, dynamic causal modelling, is useful in the analysis of the pathways of seizure spread. We concluded that the end results of the epileptogenic process are best understood as abnormalities of neuronal circuitry and not simply as molecular or cellular abnormalities. The network approach promises to generate new understanding and more targeted treatment of epilepsy.
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Affiliation(s)
- Aminu T Abdullahi
- Department of Psychiatry, Aminu Kano Teaching Hospital, Kano, Nigeria
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Tavakol S, Royer J, Lowe AJ, Bonilha L, Tracy JI, Jackson GD, Duncan JS, Bernasconi A, Bernasconi N, Bernhardt BC. Neuroimaging and connectomics of drug-resistant epilepsy at multiple scales: From focal lesions to macroscale networks. Epilepsia 2019; 60:593-604. [PMID: 30889276 PMCID: PMC6447443 DOI: 10.1111/epi.14688] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 02/13/2019] [Accepted: 02/14/2019] [Indexed: 01/03/2023]
Abstract
Epilepsy is among the most common chronic neurologic disorders, with 30%-40% of patients having seizures despite antiepileptic drug treatment. The advent of brain imaging and network analyses has greatly improved the understanding of this condition. In particular, developments in magnetic resonance imaging (MRI) have provided measures for the noninvasive characterization and detection of lesions causing epilepsy. MRI techniques can probe structural and functional connectivity, and network analyses have shaped our understanding of whole-brain anomalies associated with focal epilepsies. This review considers the progress made by neuroimaging and connectomics in the study of drug-resistant epilepsies due to focal substrates, particularly temporal lobe epilepsy related to mesiotemporal sclerosis and extratemporal lobe epilepsies associated with malformations of cortical development. In these disorders, there is evidence of widespread disturbances of structural and functional connectivity that may contribute to the clinical and cognitive prognosis of individual patients. It is hoped that studying the interplay between macroscale network anomalies and lesional profiles will improve our understanding of focal epilepsies and assist treatment choices.
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Affiliation(s)
- Shahin Tavakol
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jessica Royer
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Alexander J Lowe
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, Charleston, South Carolina
| | - Joseph I Tracy
- Cognitive Neuroscience and Brain Mapping Laboratory, Thomas Jefferson University Hospitals/Sidney Kimmel Medical College, Philadelphia, Pennsylvania
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | | | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Neda Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Boris C Bernhardt
- Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
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Larivière S, Vos de Wael R, Paquola C, Hong SJ, Mišić B, Bernasconi N, Bernasconi A, Bonilha L, Bernhardt BC. Microstructure-Informed Connectomics: Enriching Large-Scale Descriptions of Healthy and Diseased Brains. Brain Connect 2018; 9:113-127. [PMID: 30079754 DOI: 10.1089/brain.2018.0587] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Rapid advances in neuroimaging and network science have produced powerful tools and measures to appreciate human brain organization at multiple spatial and temporal scales. It is now possible to obtain increasingly meaningful representations of whole-brain structural and functional brain networks and to formally assess macroscale principles of network topology. In addition to its utility in characterizing healthy brain organization, individual variability, and life span-related changes, there is high promise of network neuroscience for the conceptualization and, ultimately, management of brain disorders. In the current review, we argue for a science of the human brain that, while strongly embracing macroscale connectomics, also recommends awareness of brain properties derived from meso- and microscale resolutions. Such features include MRI markers of tissue microstructure, local functional properties, as well as information from nonimaging domains, including cellular, genetic, or chemical data. Integrating these measures with connectome models promises to better define the individual elements that constitute large-scale networks, and clarify the notion of connection strength among them. By enriching the description of large-scale networks, this approach may improve our understanding of fundamental principles of healthy brain organization. Notably, it may also better define the substrate of prevalent brain disorders, including stroke, autism, as well as drug-resistant epilepsies that are each characterized by intriguing interactions between local anomalies and network-level perturbations.
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Affiliation(s)
- Sara Larivière
- 1 Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Reinder Vos de Wael
- 1 Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Casey Paquola
- 1 Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Seok-Jun Hong
- 1 Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada.,2 NeuroImaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Bratislav Mišić
- 3 Network Neuroscience Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Neda Bernasconi
- 2 NeuroImaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Andrea Bernasconi
- 2 NeuroImaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Leonardo Bonilha
- 4 Department of Neurosciences, Medical University of South Carolina, Charleston, South Carolina
| | - Boris C Bernhardt
- 1 Multimodal Imaging and Connectome Analysis Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
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Zanirati G, Azevedo PN, Venturin GT, Greggio S, Alcará AM, Zimmer ER, Feltes PK, DaCosta JC. Depression comorbidity in epileptic rats is related to brain glucose hypometabolism and hypersynchronicity in the metabolic network architecture. Epilepsia 2018; 59:923-934. [PMID: 29600825 DOI: 10.1111/epi.14057] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/19/2018] [Indexed: 12/16/2022]
Abstract
OBJECTIVE Temporal lobe epilepsy (TLE) is one of the most common types of epilepsy syndromes in the world. Depression is an important comorbidity of epilepsy, which has been reported in patients with TLE and in different experimental models of epilepsy. However, there is no established consensus on which brain regions are associated with the manifestation of depression in epilepsy. Here, we investigated the alterations in cerebral glucose metabolism and the metabolic network in the pilocarpine-induced rat model of epilepsy and correlated it with depressive behavior during the chronic phase of epilepsy. METHODS Fluorodeoxyglucose (18 F-FDG) was used to investigate the cerebral metabolism, and a cross-correlation matrix was used to examine the metabolic network in chronically epileptic rats using micro-positron emission tomography (microPET) imaging. An experimental model of epilepsy was induced by pilocarpine injection (320 mg/kg, ip). Forced swim test (FST), sucrose preference test (SPT), and eating-related depression test (ERDT) were used to evaluate depression-like behavior. RESULTS Our results show an association between epilepsy and depression comorbidity based on changes in both cerebral glucose metabolism and the functional metabolic network. In addition, we have identified a significant correlation between brain glucose hypometabolism and depressive-like behavior in chronically epileptic rats. Furthermore, we found that the epileptic depressed group presents a hypersynchronous brain metabolic network in relation to the epileptic nondepressed group. SIGNIFICANCE This study revealed relevant alterations in glucose metabolism and the metabolic network among the brain regions of interest for both epilepsy and depression pathologies. Thus it seems that depression in epileptic animals is associated with a more diffuse hypometabolism and altered metabolic network architecture and plays an important role in chronic epilepsy.
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Affiliation(s)
- Gabriele Zanirati
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Pamella Nunes Azevedo
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Gianina Teribele Venturin
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Samuel Greggio
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Allan Marinho Alcará
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Eduardo R Zimmer
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil.,Department of Biochemistry, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.,Department of Pharmacology, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Paula Kopschina Feltes
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
| | - Jaderson Costa DaCosta
- Brain Institute of Rio Grande do Sul (BraIns), Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil
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Wang GB, Long W, Li XD, Xu GY, Lu JX. Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) Combined with Positron Emission Tomography-Computed Tomography (PET-CT) and Video-Electroencephalography (VEEG) Have Excellent Diagnostic Value in Preoperative Localization of Epileptic Foci in Children with Epilepsy. Med Sci Monit 2017; 23:1-10. [PMID: 28040805 PMCID: PMC5223780 DOI: 10.12659/msm.898316] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Background To investigate the effect that dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has on surgical decision making relative to video-electroencephalography (VEEG) and positron emission tomography-computed tomography (PET-CT), and if the differences in these variables translates to differences in surgical outcomes. Material/Methods A total of 166 children with epilepsy undergoing preoperative DCE-MRI, VEEG, and PET-CT examinations, surgical resection of epileptic foci, and intraoperative electrocorticography (ECoG) monitoring were enrolled. All children were followed up for 12 months and grouped by Engles prognostic classification for epilepsy. Based on intraoperative ECoG as gold standard, the diagnostic values of DCE-MRI, VEEG, PET-CT, DCE-MRI combined with VEEG, DCE-MRI combined with PET-CT, and combined application of DCE-MRI, VEEG, and PET-CT in preoperative localization for epileptic foci were evaluated. Results The sensitivity of DCE-MRI, VEEG, and PET-CT was 59.64%, 76.51%, and 93.98%, respectively; the accuracy of DCE-MRI, VEEG, PET-CT, DCE-MRI combined with VEEG, and DCE-MRI combined with PET-CT was 57.58%, 67.72%, 91.03%, 91.23%, and 96.49%, respectively. Localization accuracy rate of the combination of DCE-MRI, VEEG, and PET-CT was 98.25% (56/57), which was higher than that of DCE-MRI combined with VEEG and of DCE-MRI combined with PET-CT. No statistical difference was found in the accuracy rate of localization between these three combined techniques. During the 12-month follow-up, children were grouped into Engles grade I (n=106), II (n=31), III (n=21), and IV (n=8) according to postoperative conditions. Conclusions All DCE-MRI combined with VEEG, DCE-MRI combined with PET-CT, and DCE-MRI combined with VEEG and PET-CT examinations have excellent accuracy in preoperative localization of epileptic foci and present excellent postoperative efficiency, suggesting that these combined imaging methods are suitable for serving as the reference basis in preoperative localization of epileptic foci in children with epilepsy.
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Affiliation(s)
- Gui-Bin Wang
- Department of Medical Imaging, Linyi People's Hospital, Linyi, Shandong, China (mainland)
| | - Wei Long
- Department of Medical Imaging, Linyi People's Hospital, Linyi, Shandong, China (mainland)
| | - Xiao-Dong Li
- Department of Medical Imaging, Linyi People's Hospital, Linyi, Shandong, China (mainland)
| | - Guang-Yin Xu
- Department of Neurology, Linyi People's Hospital, Linyi, Shandong, China (mainland)
| | - Ji-Xiang Lu
- Department of Medical Imaging, Linyi People's Hospital, Linyi, Shandong, China (mainland)
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33
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Relationship between resting state functional magnetic resonance imaging and memory function in mesial temporal lobe epilepsy. J Neurol Sci 2017; 372:117-125. [DOI: 10.1016/j.jns.2016.10.048] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Revised: 09/27/2016] [Accepted: 10/27/2016] [Indexed: 11/23/2022]
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34
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Yan H, Feng Y, Wang Q. Altered Effective Connectivity of Hippocampus-Dependent Episodic Memory Network in mTBI Survivors. Neural Plast 2016; 2016:6353845. [PMID: 28074162 PMCID: PMC5198188 DOI: 10.1155/2016/6353845] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 11/14/2016] [Indexed: 11/29/2022] Open
Abstract
Traumatic brain injuries (TBIs) are generally recognized to affect episodic memory. However, less is known regarding how external force altered the way functionally connected brain structures of the episodic memory system interact. To address this issue, we adopted an effective connectivity based analysis, namely, multivariate Granger causality approach, to explore causal interactions within the brain network of interest. Results presented that TBI induced increased bilateral and decreased ipsilateral effective connectivity in the episodic memory network in comparison with that of normal controls. Moreover, the left anterior superior temporal gyrus (aSTG, the concept forming hub), left hippocampus (the personal experience binding hub), and left parahippocampal gyrus (the contextual association hub) were no longer network hubs in TBI survivors, who compensated for hippocampal deficits by relying more on the right hippocampus (underlying perceptual memory) and the right medial frontal gyrus (MeFG) in the anterior prefrontal cortex (PFC). We postulated that the overrecruitment of the right anterior PFC caused dysfunction of the strategic component of episodic memory, which caused deteriorating episodic memory in mTBI survivors. Our findings also suggested that the pattern of brain network changes in TBI survivors presented similar functional consequences to normal aging.
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Affiliation(s)
- Hao Yan
- Neuroimaging Laboratory, School of Biomedical Engineering, Shenzhen University Health Science Center, Shenzhen 518060, China
- Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China
- Departments of Linguistics and Psychology, Xidian University, Xi'an 710071, China
| | - Yanqin Feng
- Departments of Linguistics and Psychology, Xidian University, Xi'an 710071, China
| | - Qian Wang
- School of Foreign Languages, Northwestern Polytechnical University, Xi'an 710029, China
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35
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Abstract
SummaryIntroduction.Medial temporal lobe epilepsy (MTLE) is the most frequent form of epilepsy in adulthood. It is classified as local/regional epilepsy. However, there is increasing evidence of the involvement of both temporal lobes and this provides abundant arguments to question this view, and consider MTLE as one of the typical bilateral system epilepsies.Aim.To provide a contemporary review of medial temporal lobe epilepsy, discussing the bilateral aspects, with reference to epilepsy surgery.Methods.A literature review and a resume of the author’s own experiences with MTLE patients.Results.Recent electrophysiological and neuroimaging data provide convincing data supporting that MTLE is a bilateral disease. The uni-and bilateral features form a continuum and the participation rate of the two temporal lobes determine course and surgical perspective of the individual patient.Conclusions.The contradictory data of invasive presurgical evaluations of MTLE patients suggest that there need to identify further indicatory markers of bilaterality and thus change the presurgical evaluation from the non-invasive towards the invasive ways. The mechanisms of the interrelationship between the two temporal lobes in MTLE warrants further research.
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36
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Chiang S, Guindani M, Yeh HJ, Haneef Z, Stern JM, Vannucci M. Bayesian vector autoregressive model for multi-subject effective connectivity inference using multi-modal neuroimaging data. Hum Brain Mapp 2016; 38:1311-1332. [PMID: 27862625 DOI: 10.1002/hbm.23456] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Revised: 10/13/2016] [Accepted: 10/25/2016] [Indexed: 11/05/2022] Open
Abstract
In this article a multi-subject vector autoregressive (VAR) modeling approach was proposed for inference on effective connectivity based on resting-state functional MRI data. Their framework uses a Bayesian variable selection approach to allow for simultaneous inference on effective connectivity at both the subject- and group-level. Furthermore, it accounts for multi-modal data by integrating structural imaging information into the prior model, encouraging effective connectivity between structurally connected regions. They demonstrated through simulation studies that their approach resulted in improved inference on effective connectivity at both the subject- and group-level, compared with currently used methods. It was concluded by illustrating the method on temporal lobe epilepsy data, where resting-state functional MRI and structural MRI were used. Hum Brain Mapp 38:1311-1332, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Sharon Chiang
- Department of Statistics, Rice University, Houston, Texas
| | - Michele Guindani
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Hsiang J Yeh
- Department of Neurology, University of California Los Angeles, Los Angeles, California
| | - Zulfi Haneef
- Department of Neurology, Baylor College of Medicine, Houston, Texas
| | - John M Stern
- Department of Neurology, University of California Los Angeles, Los Angeles, California
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37
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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: 35] [Impact Index Per Article: 3.9] [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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38
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Robinson LF, He X, Barnett P, Doucet GE, Sperling MR, Sharan A, Tracy JI. The Temporal Instability of Resting State Network Connectivity in Intractable Epilepsy. Hum Brain Mapp 2016; 38:528-540. [PMID: 27628031 DOI: 10.1002/hbm.23400] [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: 05/04/2016] [Revised: 08/11/2016] [Accepted: 08/30/2016] [Indexed: 01/20/2023] Open
Abstract
OBJECTIVE Focal epilepsies, such as temporal lobe epilepsy (TLE), are known to disrupt network activity in areas outside the epileptogenic zone [Tracy et al., 2015]. We devised a measure of temporal instability of resting state functional connectivity (FC), capturing temporal variations of BOLD correlations between brain regions that is less confounded than the "sliding window" approach common in the literature. METHODS We investigated healthy controls and unilateral TLE patients (right and left seizure focus groups), utilizing group ICA to identify the default mode network (DMN), a network associated with episodic memory, a key cognitive deficit in TLE. Our instability analyses focused on: (1) connectivity between DMN region pairs, both within and between TLE patients and matched controls, (2) whole brain group differences between region pairs ipsilateral or contralateral to the epileptogenic temporal lobe. RESULTS For both the whole brain and a more focused analysis of DMN region pairs, temporal stability appears to characterize the healthy brain. The TLE patients displayed more FC instability compared to controls, with this instability more pronounced for the right TLE patients. SIGNIFICANCE Our findings challenge the view that the resting state signal is stable over time, providing a measure of signal coherence change that may generate insights into the temporal components of network organization. The precuneus was the region within the DMN consistently expressing this instability, suggesting this region plays a key role in large scale temporal dynamics of the DMN, with such dynamics disrupted in TLE, putting key cognitive functions at risk. Hum Brain Mapp 38:528-540, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Lucy F Robinson
- Department of Epidemiology and Biostatistics, Drexel University, Philadelphia, Pennsylvania
| | - Xiaosong He
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Paul Barnett
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Gaёlle E Doucet
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Michael R Sperling
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Ashwini Sharan
- Department of Neurosurgery, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Joseph I Tracy
- Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
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39
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Englot DJ, Konrad PE, Morgan VL. Regional and global connectivity disturbances in focal epilepsy, related neurocognitive sequelae, and potential mechanistic underpinnings. Epilepsia 2016; 57:1546-1557. [PMID: 27554793 DOI: 10.1111/epi.13510] [Citation(s) in RCA: 151] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/27/2016] [Indexed: 12/19/2022]
Abstract
Epilepsy is among the most common brain network disorders, and it is associated with substantial morbidity and increased mortality. Although focal epilepsy was traditionally considered a regional brain disorder, growing evidence has demonstrated widespread network alterations in this disorder that extend beyond the epileptogenic zone from which seizures originate. The goal of this review is to summarize recent investigations examining functional and structural connectivity alterations in focal epilepsy, including neuroimaging and electrophysiologic studies utilizing model-based or data-driven analytic methods. A significant subset of studies in both mesial temporal lobe epilepsy and focal neocortical epilepsy have demonstrated patterns of increased connectivity related to the epileptogenic zone, coupled with decreased connectivity in widespread distal networks. Connectivity patterns appear to be related to the duration and severity of disease, suggesting progressive connectivity reorganization in the setting of recurrent seizures over time. Global resting-state connectivity disturbances in focal epilepsy have been linked to neurocognitive problems, including memory and language disturbances. Although it is possible that increased connectivity in a particular brain region may enhance the propensity for seizure generation, it is not clear if global reductions in connectivity represent the damaging consequences of recurrent seizures, or an adaptive mechanism to prevent seizure propagation away from the epileptogenic zone. Overall, studying the connectome in focal epilepsy is a critical endeavor that may lead to improved strategies for epileptogenic-zone localization, surgical outcome prediction, and a better understanding of the neuropsychological implications of recurrent seizures.
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Affiliation(s)
- Dario J Englot
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A..
| | - Peter E Konrad
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, U.S.A
| | - Victoria L Morgan
- Department of Radiology and Radiological Sciences, Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, Tennessee, U.S.A
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40
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Shamshiri EA, Tierney TM, Centeno M, St Pier K, Pressler RM, Sharp DJ, Perani S, Cross JH, Carmichael DW. Interictal activity is an important contributor to abnormal intrinsic network connectivity in paediatric focal epilepsy. Hum Brain Mapp 2016; 38:221-236. [PMID: 27543883 DOI: 10.1002/hbm.23356] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Revised: 07/26/2016] [Accepted: 08/11/2016] [Indexed: 01/01/2023] Open
Abstract
Patients with focal epilepsy have been shown to have reduced functional connectivity in intrinsic connectivity networks (ICNs), which has been related to neurocognitive development and outcome. However, the relationship between interictal epileptiform discharges (IEDs) and changes in ICNs remains unclear, with evidence both for and against their influence. EEG-fMRI data was obtained in 27 children with focal epilepsy (mixed localisation and aetiologies) and 17 controls. A natural stimulus task (cartoon blocks verses blocks where the subject was told "please wait") was used to enhance the connectivity within networks corresponding to ICNs while reducing potential confounds of vigilance and motion. Our primary hypothesis was that the functional connectivity within visual and attention networks would be reduced in patients with epilepsy. We further hypothesized that controlling for the effects of IEDs would increase the connectivity in the patient group. The key findings were: (1) Patients with mixed epileptic foci showed a common connectivity reduction in lateral visual and attentional networks compared with controls. (2) Having controlled for the effects of IEDs there were no connectivity differences between patients and controls. (3) A comparison within patients revealed reduced connectivity between the attentional network and basal ganglia associated with interictal epileptiform discharges. We also found that the task activations were reduced in epilepsy patients but that this was unrelated to IED occurrence. Unexpectedly, connectivity changes in ICNs were strongly associated with the transient effects of interictal epileptiform discharges. Interictal epileptiform discharges were shown to have a pervasive transient influence on the brain's functional organisation. Hum Brain Mapp 38:221-236, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Elhum A Shamshiri
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom
| | - Tim M Tierney
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom
| | - Maria Centeno
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom
| | - Kelly St Pier
- Telemetry Unit, Department of Neurophysiology, Great Ormond Street Hospital, London, United Kingdom
| | - Ronit M Pressler
- Neuroscience Medicine, Great Ormond Street Hospital, London, United Kingdom.,Clinical Neurosciences, UCL Institute of Child Health, London, United Kingdom
| | - David J Sharp
- Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital Campus, London, United Kingdom
| | - Suejen Perani
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom.,Department of Basic and Clinical Neurosciences, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, United Kingdom
| | - J Helen Cross
- Neuroscience Medicine, Great Ormond Street Hospital, London, United Kingdom.,Clinical Neurosciences, UCL Institute of Child Health, London, United Kingdom
| | - David W Carmichael
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, London, United Kingdom
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41
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Liu HH, Wang J, Chen XM, Li JP, Ye W, Zheng J. Reduced local diffusion homogeneity as a biomarker for temporal lobe epilepsy. Medicine (Baltimore) 2016; 95:e4032. [PMID: 27472676 PMCID: PMC5265813 DOI: 10.1097/md.0000000000004032] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
In the present study, we adopted a novel method-local diffusion homogeneity (LDH)-to characterize the structure feature in mesial temporal lobe epilepsy (MTLE). Diffusion-weighted images were acquired from 11 left MTLE patients, 16 right MTLE patients, and 20 healthy controls from May 2014 to January 2015. Local diffusion homogeneity was compared among patient groups and controls by 2 sample t test. The discriminative value of LDH abnormalities was examined by receiver operating characteristic (ROC) curve analysis. Correlations with disease duration and onset age in both patient groups were assessed using Pearson's coefficient. Both patient groups exhibited lower LDH in the anterior corpus callosum (P < 0.05, corrected), and this regional anomaly exhibited excellent classification performance in left MTLE patients (sensitivity = 82%, specificity = 100%), right MTLE patients (sensitivity = 81%, specificity = 90%), and the entire patient cohort (sensitivity = 82%, specificity = 95%). In summary, left and right MTLE patients show common pathological changes in the anterior corpus callosum. This regional LDH abnormality is a potential quantitative biomarker for MTLE.
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Affiliation(s)
- Hui-hua Liu
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning
- Department of Neurology, the Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin
| | - Jun Wang
- Department of Neurology, the Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin
| | - Xue-mei Chen
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Jian-ping Li
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning
| | - Wei Ye
- Department of Radiology, the First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jinou Zheng
- Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning
- Correspondence: Jinou Zheng, Department of Neurology, the First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China (e-mail: )
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Feng Z, Xu S, Huang M, Shi Y, Xiong B, Yang H. Disrupted causal connectivity anchored on the anterior cingulate cortex in first-episode medication-naive major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry 2016; 64:124-30. [PMID: 26234517 DOI: 10.1016/j.pnpbp.2015.07.008] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2015] [Revised: 07/07/2015] [Accepted: 07/23/2015] [Indexed: 12/30/2022]
Abstract
In recent years, major depressive disorder (MDD) has been demonstrated to be associated with abnormalities in neural networks, particularly the prefrontal-limbic network (PLN). However, there are few current studies that have examined information flow in the PLN. In this study, Granger causality analysis (GCA), based on signed regression coefficient, was used to explore changes in causal connectivity in resting-state PLNs of MDD patients. A total of 23 first-episode medication-naïve MDD patients and 20 normal control participants were subjected to resting-state functional magnetic resonance imaging (RS-fMRI) scans. Increased causal effects of the right insular cortex, right putamen and right caudate on the rostral anterior cingulate cortex (rACC) and reduced causal effects of bilateral dorsolateral prefrontal cortex (DLPFC) and left orbitofrontal cortex (OFC) on the rACC were found in MDD patients compared to normal controls. The extensive reduction in the causal effect of the prefrontal cortex (PFC) demonstrates impaired top-down cognitive control in MDD patients. Changes in the causal relationship between the right insula and rACC suggest problems in coordination of the default mode network by the right anterior insular cortex (rAI). These findings provide valuable insight into MDD-related neural network disorders reported in previous RS-fMRI studies and may potentially guide clinical treatment of MDD in the future.
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Affiliation(s)
- Zhan Feng
- Department of Radiology, First Affiliated Hospital of College of Medical Science, Zhejiang University, Hangzhou, Zhejiang, China; The key laboratory of mental disorder's management of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Shunliang Xu
- Department of Radiology, First Affiliated Hospital of College of Medical Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Manli Huang
- Department of Psychiatry, First Affiliated Hospital of College of Medical Science, Zhejiang University, Hangzhou, Zhejiang, China; The key laboratory of mental disorder's management of Zhejiang Province, Hangzhou, Zhejiang, China
| | - Yushu Shi
- Department of Radiology, First Affiliated Hospital of College of Medical Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Bing Xiong
- Department of Radiology, First Affiliated Hospital of College of Medical Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Hong Yang
- Department of Radiology, First Affiliated Hospital of College of Medical Science, Zhejiang University, Hangzhou, Zhejiang, China.
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Stylianou P, Kimchi G, Hoffmann C, Blat I, Harnof S. Neuroimaging for patient selection for medial temporal lobe epilepsy surgery: Part 2 functional neuroimaging. J Clin Neurosci 2016; 23:23-33. [DOI: 10.1016/j.jocn.2015.04.031] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Revised: 04/11/2015] [Accepted: 04/18/2015] [Indexed: 11/17/2022]
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Nedic S, Stufflebeam SM, Rondinoni C, Velasco TR, dos Santos AC, Leite JP, Gargaro AC, Mujica-Parodi LR, Ide JS. Using network dynamic fMRI for detection of epileptogenic foci. BMC Neurol 2015; 15:262. [PMID: 26689596 PMCID: PMC4687299 DOI: 10.1186/s12883-015-0514-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Accepted: 12/04/2015] [Indexed: 01/21/2023] Open
Abstract
Background Epilepsy is one of the most prevalent neurological disorders. It remains medically intractable for about one-third of patients with focal epilepsy, for whom precise localization of the epileptogenic zone responsible for seizure initiation may be critical for successful surgery. Existing fMRI literature points to widespread network disturbances in functional connectivity. Per previous scalp and intracranial EEG studies and consistent with excessive local synchronization during interictal discharges, we hypothesized that, relative to same regions in healthy controls, epileptogenic foci would exhibit less chaotic dynamics, identifiable via entropic analyses of resting state fMRI time series. Methods In order to first validate this hypothesis on a cohort of patients with known ground truth, here we test individuals with well-defined epileptogenic foci (left mesial temporal lobe epilepsy). We analyzed voxel-wise resting-state fMRI time-series using the autocorrelation function (ACF), an entropic measure of regulation and feedback, and performed follow-up seed-to-voxel functional connectivity analysis. Disruptions in connectivity of the region exhibiting abnormal dynamics were examined in relation to duration of epilepsy and patients’ cognitive performance using a delayed verbal memory recall task. Results ACF analysis revealed constrained (less chaotic) functional dynamics in left temporal lobe epilepsy patients, primarily localized to ipsilateral temporal pole, proximal to presumed focal points. Autocorrelation decay rates differentiated, with 100 % accuracy, between patients and healthy controls on a subject-by-subject basis within a leave-one-subject out classification framework. Regions identified via ACF analysis formed a less efficient network in patients, as compared to controls. Constrained dynamics were linked with locally increased and long-range decreased connectivity that, in turn, correlated significantly with impaired memory (local left temporal connectivity) and epilepsy duration (left temporal – posterior cingulate cortex connectivity). Conclusions Our current results suggest that data driven functional MRI methods that target network dynamics hold promise in providing clinically valuable tools for identification of epileptic regions.
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Affiliation(s)
- Sanja Nedic
- Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY, 11794, USA. .,Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
| | - Steven M Stufflebeam
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
| | - Carlo Rondinoni
- Department of Neurosciences and Behavior, University of Sao Paulo (USP), Ribeirao Preto, SP, 14049, Brazil.
| | - Tonicarlo R Velasco
- Department of Neurosciences and Behavior, University of Sao Paulo (USP), Ribeirao Preto, SP, 14049, Brazil.
| | - Antonio C dos Santos
- Department of Neurosciences and Behavior, University of Sao Paulo (USP), Ribeirao Preto, SP, 14049, Brazil.
| | - Joao P Leite
- Department of Neurosciences and Behavior, University of Sao Paulo (USP), Ribeirao Preto, SP, 14049, Brazil.
| | - Ana C Gargaro
- Department of Neurosciences and Behavior, University of Sao Paulo (USP), Ribeirao Preto, SP, 14049, Brazil.
| | - Lilianne R Mujica-Parodi
- Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY, 11794, USA. .,Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
| | - Jaime S Ide
- Department of Biomedical Engineering, Stony Brook University School of Medicine, Stony Brook, NY, 11794, USA. .,Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA. .,Department of Science and Technology, Federal University of Sao Paulo, Sao Jose dos Campos, SP, 12231, Brazil.
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Resting-state functional connectivity in epilepsy: growing relevance for clinical decision making. Curr Opin Neurol 2015; 28:158-65. [PMID: 25734954 DOI: 10.1097/wco.0000000000000178] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
PURPOSE OF REVIEW Seizures produce dysfunctional, maladaptive networks, making functional connectivity an ideal technique for identifying complex brain effects of epilepsy. We review the current status of resting-state functional connectivity (rsFC) research, highlighting its potential added value to epilepsy surgery programs. RECENT FINDINGS RsFC research has demonstrated that the brain impact of seizures goes beyond the epileptogenic zone, changing connectivity patterns in widespread cortical regions. There is evidence for abnormal connectivity, but the degree to which these represent adaptive or maladaptive plasticity responses is unclear. Empirical associations with cognitive performance and psychiatric symptoms have helped understand deleterious impacts of seizures outside the epileptogenic zone. Studies in the prediction of outcome suggest that there are identifiable presurgical patterns of functional connectivity associated with a greater likelihood of positive cognitive or seizure outcomes. SUMMARY The role of rsFC remains limited in most clinical settings, but shows great promise for identifying epileptic circuits and foci, predicting outcomes following surgery, and explaining cognitive deficits and psychiatric symptoms of epilepsy. RsFC has demonstrated that even focal epilepsies constitute a network and brain systems disorder. By providing a tool to both identify and characterize the brain network impact of epileptiform activity, rsFC can make a strong contribution to presurgical algorithms in epilepsy.
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46
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Li H, Fan W, Yang J, Song S, Liu Y, Lei P, Shrestha L, Mella G, Chen W, Xu H. Asymmetry in cross-hippocampal connectivity in unilateral mesial temporal lobe epilepsy. Epilepsy Res 2015; 118:14-21. [PMID: 26561924 DOI: 10.1016/j.eplepsyres.2015.10.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 09/15/2015] [Accepted: 10/25/2015] [Indexed: 01/06/2023]
Abstract
Mesial temporal lobe epilepsy (mTLE) is mostly characterized by hippocampal sclerosis (HS) changes. Although considerable progress has been made in understanding the altered functional network of mTLE patients, whether one side of the abnormal hippocampal (HP) structure will affect the other healthy side of the hippocampal network is still unclear. Here, we used a seed-based method to explore the commonly alterative hippocampal network in mTLE patients by comparing the bilateral hippocampal network of unilateral mTLE patients with healthy control participants. We observed that both sides of the hippocampal network in unilateral mTLE patients were changed independent of the affected or "healthy" side, which may suggest a common plasticity network for both sides of hippocampal sclerosis mesial temporal lobe epilepsy patients. Furthermore, using the HP as the ROI, we found that the functional connectivity of the intra-HP in the left mTLE-HS group was moderately positively correlated with the duration of the disease, while a strong negative correlation between functional connectivity of the intra-HP and duration were detected in the right mTLE-HS group, which suggested that it was easier for the right HP than the left HP to communicate with the contralateral HP according to the progression of mTLE disease because the hippocampus plays different roles in the communication and compensatory mechanism associated with the contralateral side of the hemisphere. We hope that this potential relevance may help us to better characterize mTLE with hippocampal sclerosis and ultimately assist in providing a better diagnosis and more accurate invasive treatments of mTLE.
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Affiliation(s)
- Hong Li
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Wenliang Fan
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Jie Yang
- Department of Communication Sciences and Disorders, Massachusetts General Hospital Institute of Health Professions, Boston, MA, USA.
| | - Shuyan Song
- School of Life Science and Technology, Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Yuan Liu
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Ping Lei
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Lochan Shrestha
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Grace Mella
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China.
| | - Wei Chen
- Department of Radiology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China; Radiology and Medical Imaging Center, The First People's Hospital of Yibin, Sichuan 644000, China.
| | - Haibo Xu
- Department of Radiology, Union Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China; Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
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Guo W, Liu F, Xiao C, Yu M, Zhang Z, Liu J, Zhang J, Zhao J. Increased Causal Connectivity Related to Anatomical Alterations as Potential Endophenotypes for Schizophrenia. Medicine (Baltimore) 2015; 94:e1493. [PMID: 26496253 PMCID: PMC4620791 DOI: 10.1097/md.0000000000001493] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Anatomical and functional abnormalities in the cortico-cerebellar-thalamo-cortical circuit have been observed in schizophrenia patients and their unaffected siblings. However, it remains unclear to the relationship between anatomical and functional abnormalities within this circuit in schizophrenia patients and their unaffected siblings, which may serve as potential endophenotypes for schizophrenia.Anatomical and resting-state functional magnetic resonance imaging data were acquired from 49 first-episode, drug-naive schizophrenia patients, 46 unaffected siblings, and 46 healthy controls. Data were analyzed by using voxel-based morphometry and Granger causality analysis.The patients and the siblings shared anatomical deficits in the left middle temporal gyrus (MTG) and increased left MTG-left angular gyrus (AG) connectivity. Moreover, the left MTG-left AG connectivity negatively correlates to the duration of untreated psychosis in the patients.The findings indicate that anatomical deficits in the left MTG and its increased causal connectivity with the left AG may serve as potential endophenotypes for schizophrenia with clinical implications.
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Affiliation(s)
- Wenbin Guo
- From the Mental Health Institute of the Second Xiangya Hospital, Key Laboratory of Psychiatry and Mental Health of Hunan Province, Central South University, Changsha, Hunan (GW, ZJ); Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan (LF); and Mental Health Center, The First Affiliated Hospital, Guangxi Medical University; Nanning, Guangxi, China (XC, YM, ZZ, LJ, ZJ)
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Bernhardt BC, Bonilha L, Gross DW. Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy. Epilepsy Behav 2015; 50:162-70. [PMID: 26159729 DOI: 10.1016/j.yebeh.2015.06.005] [Citation(s) in RCA: 195] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2015] [Revised: 06/03/2015] [Accepted: 06/04/2015] [Indexed: 01/01/2023]
Abstract
Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach.
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Affiliation(s)
- Boris C Bernhardt
- Neuroimaging of Epilepsy Laboratory, Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada; Department of Social Neuroscience, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Leonardo Bonilha
- Department of Neurology, Medical University of South Carolina, SC, USA
| | - Donald W Gross
- Division of Neurology, Department of Medicine, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada
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Bharath RD, Sinha S, Panda R, Raghavendra K, George L, Chaitanya G, Gupta A, Satishchandra P. Seizure Frequency Can Alter Brain Connectivity: Evidence from Resting-State fMRI. AJNR Am J Neuroradiol 2015; 36:1890-8. [PMID: 26294642 DOI: 10.3174/ajnr.a4373] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 02/25/2015] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE The frequency of seizures is an important factor that can alter functional brain connectivity. Analysis of this factor in patients with epilepsy is complex because of disease- and medication-induced confounders. Because patients with hot-water epilepsy generally are not on long-term drug therapy, we used seed-based connectivity analysis in these patients to assess connectivity changes associated with seizure frequency without confounding from antiepileptic drugs. MATERIALS AND METHODS Resting-state fMRI data from 36 patients with hot-water epilepsy (18 with frequent seizures [>2 per month] and 18 with infrequent seizures [≤2 per month]) and 18 healthy age- and sex-matched controls were analyzed for seed-to-voxel connectivity by using 106 seeds. Voxel wise paired t-test analysis (P < .005, corrected for false-discovery rate) was used to identify significant intergroup differences between these groups. RESULTS Connectivity analysis revealed significant differences between the 2 groups (P < .001). Patients in the frequent-seizure group had increased connectivity within the medial temporal structures and widespread areas of poor connectivity, even involving the default mode network, in comparison with those in the infrequent-seizure group. Patients in the infrequent-seizure group had focal abnormalities with increased default mode network connectivity and decreased left entorhinal cortex connectivity. CONCLUSIONS The results of this study suggest that seizure frequency can alter functional brain connectivity, which can be visualized by using resting-state fMRI. Imaging features such as diffuse network abnormalities, involvement of the default mode network, and recruitment of medial temporal lobe structures were seen only in patients with frequent seizures. Future studies in more common epilepsy groups, however, will be required to further establish this finding.
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Affiliation(s)
- R D Bharath
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.) Advanced Brain Imaging Facility (R.D.B., R.P.), Cognitive Neuroscience Center, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India
| | - S Sinha
- Neurology (S.S., K.R., G.C., P.S.)
| | - R Panda
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.) Advanced Brain Imaging Facility (R.D.B., R.P.), Cognitive Neuroscience Center, National Institute of Mental Health and Neuro Sciences, Bangalore, Karnataka, India
| | | | - L George
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.)
| | | | - A Gupta
- From the Departments of Neuroimaging and Interventional Radiology (R.D.B., R.P., L.G., A.G.)
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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: 2.2] [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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