1
|
Li Z, Hou X, Lu Y, Zhao H, Wang M, Xu B, Shi Q, Gui Q, Wu G, Shen M, Zhu W, Xu Q, Dong X, Cheng Q, Zhang J, Feng H. Study of brain network alternations in non-lesional epilepsy patients by BOLD-fMRI. Front Neurosci 2023; 16:1031163. [PMID: 36741055 PMCID: PMC9889547 DOI: 10.3389/fnins.2022.1031163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 12/30/2022] [Indexed: 01/20/2023] Open
Abstract
Objective To investigate the changes of brain network in epilepsy patients without intracranial lesions under resting conditions. Methods Twenty-six non-lesional epileptic patients and 42 normal controls were enrolled for BOLD-fMRI examination. The differences in brain network topological characteristics and functional network connectivity between the epilepsy group and the healthy controls were compared using graph theory analysis and independent component analysis. Results The area under the curve for local efficiency was significantly lower in the epilepsy patients compared with healthy controls, while there were no differences in global indicators. Patients with epilepsy had higher functional connectivity in 4 connected components than healthy controls (orbital superior frontal gyrus and medial superior frontal gyrus, medial superior frontal gyrus and angular gyrus, superior parietal gyrus and paracentral lobule, lingual gyrus, and thalamus). In addition, functional connectivity was enhanced in the default mode network, frontoparietal network, dorsal attention network, sensorimotor network, and auditory network in the epilepsy group. Conclusion The topological characteristics and functional connectivity of brain networks are changed in in non-lesional epilepsy patients. Abnormal functional connectivity may suggest reduced brain efficiency in epilepsy patients and also may be a compensatory response to brain function early at earlier stages of the disease.
Collapse
Affiliation(s)
- Zhisen Li
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaoxia Hou
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Yanli Lu
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Huimin Zhao
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Meixia Wang
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Bo Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qianru Shi
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qian Gui
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Guanhui Wu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Mingqiang Shen
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Wei Zhu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qinrong Xu
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Xiaofeng Dong
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Qingzhang Cheng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Jibin Zhang
- Department of Radiology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China
| | - Hongxuan Feng
- Department of Neurology, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China,*Correspondence: Hongxuan Feng,
| |
Collapse
|
2
|
Functional network connectivity imprint in febrile seizures. Sci Rep 2022; 12:3267. [PMID: 35228583 PMCID: PMC8885759 DOI: 10.1038/s41598-022-07173-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 01/10/2022] [Indexed: 11/11/2022] Open
Abstract
Complex febrile seizures (CFS), a subset of paediatric febrile seizures (FS), have been studied for their prognosis, epileptogenic potential and neurocognitive outcome. We evaluated their functional connectivity differences with simple febrile seizures (SFS) in children with recent-onset FS. Resting-state fMRI (rs-fMRI) datasets of 24 children with recently diagnosed FS (SFS-n = 11; CFS-n = 13) were analysed. Functional connectivity (FC) was estimated using time series correlation of seed region–to-whole-brain-voxels and network topology was assessed using graph theory measures. Regional connectivity differences were correlated with clinical characteristics (FDR corrected p < 0.05). CFS patients demonstrated increased FC of the bilateral middle temporal pole (MTP), and bilateral thalami when compared to SFS. Network topology study revealed increased clustering coefficient and decreased participation coefficient in basal ganglia and thalamus suggesting an inefficient-unbalanced network topology in patients with CFS. The number of seizure recurrences negatively correlated with the integration of Left Thalamus (r = − 0.58) and FC of Left MTP to 'Right Supplementary Motor and left Precentral' gyrus (r = − 0.53). The FC of Right MTP to Left Amygdala, Putamen, Parahippocampal, and Orbital Frontal Cortex (r = 0.61) and FC of Left Thalamus to left Putamen, Pallidum, Caudate, Thalamus Hippocampus and Insula (r 0.55) showed a positive correlation to the duration of the longest seizure. The findings of the current study report altered connectivity in children with CFS proportional to the seizure recurrence and duration. Regardless of the causal/consequential nature, such observations demonstrate the imprint of these disease-defining variables of febrile seizures on the developing brain.
Collapse
|
3
|
Zhu J, Xu C, Zhang X, Qiao L, Wang X, Zhang X, Yan X, Ni D, Yu T, Zhang G, Li Y. Altered topological properties of brain functional networks in drug-resistant epilepsy patients with vagus nerve stimulators. Seizure 2021; 92:149-154. [PMID: 34521062 DOI: 10.1016/j.seizure.2021.09.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 08/19/2021] [Accepted: 09/05/2021] [Indexed: 11/15/2022] Open
Abstract
PURPOSE To explore abnormalities of topological properties in drug-resistant epilepsy (DRE) patients after vagus nerve stimulation (VNS) by analyzing brain functional networks using graph theory. METHODS Fifteen patients and eight healthy controls (HC) were scanned separately with resting-state functional magnetic resonance imaging (rs-fMRI). Graph theoretical analyses were chosen to compare the global (small-world parameters [γ, λ, σ, Cp, and Lp], and network efficiency [Eg and Eloc]), and nodal (BC, DC, and NE) properties in preoperative patients (EPpre), postoperative patients (EPpost) and HC. RESULTS HC, EPpre and EPpost all satisfied the criteria for small-world properties (σ > 1) within the sparsity range of 0.05-0.5. Compared with EPpre, EPpost performed higher in λ and Eloc but lower in γ, σ, and Cp. Compared with HC, EPpre exhibited decreased BC, DC or NE in the right inferior frontal gyrus, right superior temporal gyrus, bilateral cingulate gyri, right supplementary motor area, right superior occipital gyrus, right Heschl gyrus, and left calcarine fissure; increased BC in the left postcentral/precentral gyrus, right paracentral lobule, left rolandic operculum, and left supramarginal gyrus, and increased NE in the right caudate nucleus. Compared with EPpre, EPpost showed increased BC, DC or NE in the bilateral inferior frontal gyrus, right middle frontal gyrus, bilateral cingulate gyri, right superior temporal gyrus, and right Heschl gyrus and decreased BC in the left fusiform gyrus. CONCLUSION VNS downregulated small-world properties in DRE, and caused changes in some key nodes to reorganize the transmission ability of the large-scale network.
Collapse
Affiliation(s)
- Jin Zhu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Cuiping Xu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Xi Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Liang Qiao
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Xueyuan Wang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Xiaohua Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Xiaoming Yan
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Duanyu Ni
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Tao Yu
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Guojun Zhang
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China
| | - Yongjie Li
- Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, No.45 Changchun Street, Xicheng District, Beijing, 100053, PR China.
| |
Collapse
|
4
|
Altered Small-World Functional Network Topology in Patients with Optic Neuritis: A Resting-State fMRI Study. DISEASE MARKERS 2021; 2021:9948751. [PMID: 34221189 PMCID: PMC8219459 DOI: 10.1155/2021/9948751] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/26/2021] [Accepted: 05/26/2021] [Indexed: 12/17/2022]
Abstract
Aim This study investigated changes in small-world topology and brain functional connectivity in patients with optic neuritis (ON) by resting-state functional magnetic resonance imaging (rs-fMRI) and based on graph theory. Methods A total of 21 patients with ON (8 males and 13 females) and 21 matched healthy control subjects (8 males and 13 females) were enrolled and underwent rs-fMRI. Data were preprocessed and the brain was divided into 116 regions of interest. Small-world network parameters and area under the integral curve (AUC) were calculated from pairwise brain interval correlation coefficients. Differences in brain network parameter AUCs between the 2 groups were evaluated with the independent sample t-test, and changes in brain connection strength between ON patients and control subjects were assessed by network-based statistical analysis. Results In the sparsity range from 0.08 to 0.48, both groups exhibited small-world attributes. Compared to the control group, global network efficiency, normalized clustering coefficient, and small-world value were higher whereas the clustering coefficient value was lower in ON patients. There were no differences in characteristic path length, local network efficiency, and normalized characteristic path length between groups. In addition, ON patients had lower brain functional connectivity strength among the rolandic operculum, medial superior frontal gyrus, insula, median cingulate and paracingulate gyri, amygdala, superior parietal gyrus, inferior parietal gyrus, supramarginal gyrus, angular gyrus, lenticular nucleus, pallidum, superior temporal gyrus, and cerebellum compared to the control group (P < 0.05). Conclusion Patients with ON show typical "small world" topology that differed from that detected in HC brain networks. The brain network in ON has a small-world attribute but shows reduced and abnormal connectivity compared to normal subjects and likely causes symptoms of cognitive impairment.
Collapse
|
5
|
Antonakakis M, Dimitriadis SI, Zervakis M, Papanicolaou AC, Zouridakis G. Aberrant Whole-Brain Transitions and Dynamics of Spontaneous Network Microstates in Mild Traumatic Brain Injury. Front Comput Neurosci 2020; 13:90. [PMID: 32009921 PMCID: PMC6974679 DOI: 10.3389/fncom.2019.00090] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2019] [Accepted: 12/19/2019] [Indexed: 12/18/2022] Open
Abstract
Dynamic Functional Connectivity (DFC) analysis is a promising approach for the characterization of brain electrophysiological activity. In this study, we investigated abnormal alterations due to mild Traumatic Brain Injury (mTBI) using DFC of the source reconstructed magnetoencephalographic (MEG) resting-state recordings. Brain activity in several well-known frequency bands was first reconstructed using beamforming of the MEG data to determine ninety anatomical brain regions of interest. A DFC graph was formulated using the imaginary part of phase-locking values, which were obtained from 30 mTBI patients and 50 healthy controls (HC). Subsequently, we estimated normalized Laplacian transformations of individual, statistically and topologically filtered quasi-static graphs. The corresponding eigenvalues of each node synchronization were then computed and through the neural-gas algorithm, we quantized the evolution of the eigenvalues resulting in distinct network microstates (NMstates). The discrimination level between the two groups was assessed using an iterative cross-validation classification scheme with features either the NMstates in each frequency band, or the combination of the so-called chronnectomics (flexibility index, occupancy time of NMstate, and Dwell time) with the complexity index over the evolution of the NMstates across all frequency bands. Classification performance based on chronnectomics showed 80% accuracy, 99% sensitivity, and 49% specificity. However, performance was much higher (accuracy: 91-97%, sensitivity: 100%, and specificity: 77-93%) when focusing on the microstates. Exploring the mean node degree within and between brain anatomical networks (default mode network, frontoparietal, occipital, cingulo-opercular, and sensorimotor), a reduced pattern occurred from lower to higher frequency bands, with statistically significant stronger degrees for the HC than the mTBI group. A higher entropic profile on the temporal evolution of the modularity index was observed for both NMstates for the mTBI group across frequencies. A significant difference in the flexibility index was observed between the two groups for the β frequency band. The latter finding may support a central role of the thalamus impairment in mTBI. The current study considers a complete set of frequency-dependent connectomic markers of mTBI-caused alterations in brain connectivity that potentially could serve as markers to assess the return of an injured subject back to normality.
Collapse
Affiliation(s)
- Marios Antonakakis
- Institute for Biomagnetism and Biosignal Analysis, University of Muenster, Muenster, Germany
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece
- Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Stavros I. Dimitriadis
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, United Kingdom
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- School of Psychology, Cardiff University, Cardiff, United Kingdom
- Neuroscience and Mental Health Research Institute, Cardiff University, Cardiff, United Kingdom
- MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Michalis Zervakis
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece
| | - Andrew C. Papanicolaou
- Departments of Pediatrics, and Anatomy and Neurobiology, Neuroscience Institute, University of Tennessee Health Science Center, Le Bonheur Children's Hospital, Memphis, TN, United States
| | - George Zouridakis
- Biomedical Imaging Lab, Departments of Engineering Technology, Computer Science, Biomedical Engineering, and Electrical and Computer Engineering, University of Houston, Houston, TX, United States
| |
Collapse
|
6
|
Schapira AHV. Advances and insights into neurological practice 2016−17. Eur J Neurol 2017; 24:1425-1434. [DOI: 10.1111/ene.13480] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
|
7
|
Bharath RD, Panda R, Reddam VR, Bhaskar MV, Gohel S, Bhardwaj S, Prajapati A, Pal PK. A Single Session of rTMS Enhances Small-Worldness in Writer's Cramp: Evidence from Simultaneous EEG-fMRI Multi-Modal Brain Graph. Front Hum Neurosci 2017; 11:443. [PMID: 28928648 PMCID: PMC5591831 DOI: 10.3389/fnhum.2017.00443] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2017] [Accepted: 08/21/2017] [Indexed: 12/27/2022] Open
Abstract
Background and Purpose: Repetitive transcranial magnetic stimulation (rTMS) induces widespread changes in brain connectivity. As the network topology differences induced by a single session of rTMS are less known we undertook this study to ascertain whether the network alterations had a small-world morphology using multi-modal graph theory analysis of simultaneous EEG-fMRI. Method: Simultaneous EEG-fMRI was acquired in duplicate before (R1) and after (R2) a single session of rTMS in 14 patients with Writer’s Cramp (WC). Whole brain neuronal and hemodynamic network connectivity were explored using the graph theory measures and clustering coefficient, path length and small-world index were calculated for EEG and resting state fMRI (rsfMRI). Multi-modal graph theory analysis was used to evaluate the correlation of EEG and fMRI clustering coefficients. Result: A single session of rTMS was found to increase the clustering coefficient and small-worldness significantly in both EEG and fMRI (p < 0.05). Multi-modal graph theory analysis revealed significant modulations in the fronto-parietal regions immediately after rTMS. The rsfMRI revealed additional modulations in several deep brain regions including cerebellum, insula and medial frontal lobe. Conclusion: Multi-modal graph theory analysis of simultaneous EEG-fMRI can supplement motor physiology methods in understanding the neurobiology of rTMS in vivo. Coinciding evidence from EEG and rsfMRI reports small-world morphology for the acute phase network hyper-connectivity indicating changes ensuing low-frequency rTMS is probably not “noise”.
Collapse
Affiliation(s)
- Rose D Bharath
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India.,Cognitive Neuroscience Centre, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| | - Rajanikant Panda
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India.,Cognitive Neuroscience Centre, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| | - Venkateswara Reddy Reddam
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India.,Cognitive Neuroscience Centre, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| | - M V Bhaskar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| | - Suril Gohel
- Department of Biomedical Engineering, New Jersey Institute of TechnologyNewark, NJ, United States
| | - Sujas Bhardwaj
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India.,Cognitive Neuroscience Centre, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| | - Arvind Prajapati
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India.,Cognitive Neuroscience Centre, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| | - Pramod Kumar Pal
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS)Bangalore, India
| |
Collapse
|
8
|
Antonakakis M, Dimitriadis SI, Zervakis M, Papanicolaou AC, Zouridakis G. Altered Rich-Club and Frequency-Dependent Subnetwork Organization in Mild Traumatic Brain Injury: A MEG Resting-State Study. Front Hum Neurosci 2017; 11:416. [PMID: 28912698 PMCID: PMC5582079 DOI: 10.3389/fnhum.2017.00416] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2017] [Accepted: 08/03/2017] [Indexed: 12/19/2022] Open
Abstract
Functional brain connectivity networks exhibit "small-world" characteristics and some of these networks follow a "rich-club" organization, whereby a few nodes of high connectivity (hubs) tend to connect more densely among themselves than to nodes of lower connectivity. The Current study followed an "attack strategy" to compare the rich-club and small-world network organization models using Magnetoencephalographic (MEG) recordings from mild traumatic brain injury (mTBI) patients and neurologically healthy controls to identify the topology that describes the underlying intrinsic brain network organization. We hypothesized that the reduction in global efficiency caused by an attack targeting a model's hubs would reveal the "true" underlying topological organization. Connectivity networks were estimated using mutual information as the basis for cross-frequency coupling. Our results revealed a prominent rich-club network organization for both groups. In particular, mTBI patients demonstrated hyper-synchronization among rich-club hubs compared to controls in the δ band and the δ-γ1, θ-γ1, and β-γ2 frequency pairs. Moreover, rich-club hubs in mTBI patients were overrepresented in right frontal brain areas, from θ to γ1 frequencies, and underrepresented in left occipital regions in the δ-β, δ-γ1, θ-β, and β-γ2 frequency pairs. These findings indicate that the rich-club organization of resting-state MEG, considering its role in information integration and its vulnerability to various disorders like mTBI, may have a significant predictive value in the development of reliable biomarkers to help the validation of the recovery from mTBI. Furthermore, the proposed approach might be used as a validation tool to assess patient recovery.
Collapse
Affiliation(s)
- Marios Antonakakis
- Institute of Biomagnetism and Biosignal Analysis, Westfalian Wilhelms-University MuensterMuenster, Germany
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of CreteChania, Greece
| | - Stavros I. Dimitriadis
- Institute of Psychological Medicine and Clinical Neurosciences, Cardiff University School of MedicineCardiff, United Kingdom
- Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff UniversityCardiff, United Kingdom
- Neuroinformatics Group, Cardiff University Brain Research Imaging Center (CUBRIC), School of Psychology, Cardiff UniversityCardiff, United Kingdom
- School of Psychology, Cardiff UniversityCardiff, United Kingdom
| | - Michalis Zervakis
- Digital Image and Signal Processing Laboratory, School of Electronic and Computer Engineering, Technical University of CreteChania, Greece
| | - Andrew C. Papanicolaou
- Departments of Pediatrics, and Anatomy and Neurobiology, Neuroscience Institute, University of Tennessee Health Science Center, Le Bonheur Children's HospitalMemphis, TN, United States
| | - George Zouridakis
- Biomedical Imaging Lab, Departments of Engineering Technology, Computer Science, Biomedical Engineering, and Electrical and Computer Engineering, University of HoustonHouston, TX, United States
| |
Collapse
|
9
|
Vecchio F. The importance of the family heritage in epilepsy. Eur J Neurol 2016; 23:1694-1695. [DOI: 10.1111/ene.13109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Accepted: 06/27/2016] [Indexed: 11/29/2022]
Affiliation(s)
- F. Vecchio
- Brain Connectivity Laboratory; IRCCS San Raffaele Pisana; Rome Italy
| |
Collapse
|