1
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Lee S, Deshpande SS, Merricks EM, Schlafly E, Goodman R, McKhann GM, Eskandar EN, Madsen JR, Cash SS, van Putten MJAM, Schevon CA, van Drongelen W. Spatiotemporal spike-centered averaging reveals symmetry of temporal and spatial components of the spike-LFP relationship during human focal seizures. Commun Biol 2023; 6:317. [PMID: 36966217 PMCID: PMC10039941 DOI: 10.1038/s42003-023-04696-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 03/10/2023] [Indexed: 03/27/2023] Open
Abstract
The electrographic manifestation of neural activity can reflect the relationship between the faster action potentials of individual neurons and the slower fluctuations of the local field potential (LFP). This relationship is typically examined in the temporal domain using the spike-triggered average. In this study, we add a spatial component to this relationship. Here we first derive a theoretical model of the spike-LFP relationship across a macroelectrode. This mathematical derivation showed a special symmetry in the spike-LFP relationship wherein a sinc function in the temporal domain predicts a sinc function in the spatial domain. We show that this theoretical result is observed in a real-world system by characterizing the spike-LFP relationship using microelectrode array (MEA) recordings of human focal seizures. To do this, we present a approach, termed the spatiotemporal spike-centered average (st-SCA), that allows for visualization of the spike-LFP relationship in both the temporal and spatial domains. We applied this method to 25 MEA recordings obtained from seven patients with pharmacoresistant focal epilepsy. Of the five patients with MEAs implanted in recruited territory, three exhibited spatiotemporal patterns consistent with a sinc function, and two exhibited spatiotemporal patterns resembling deep wells of excitation. These results suggest that in some cases characterization of the spike-LFP relationship in the temporal domain is sufficient to predict the underlying spatial pattern. Finally, we discuss the biological interpretation of these findings and propose that the sinc function may reflect the role of mid-range excitatory connections during seizure activity.
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Affiliation(s)
- Somin Lee
- Department of Pediatrics, University of Chicago, Chicago, IL, 60637, USA
- Medical Scientist Training Program, University of Chicago, Chicago, IL, 60637, USA
| | - Sarita S Deshpande
- Department of Pediatrics, University of Chicago, Chicago, IL, 60637, USA
- Medical Scientist Training Program, University of Chicago, Chicago, IL, 60637, USA
| | - Edward M Merricks
- Department of Neurology, Columbia University, New York, NY, 10032, USA
| | - Emily Schlafly
- Graduate Program in Neuroscience, Boston University, Boston, MA, 02215, USA
| | - Robert Goodman
- Department of Neurosurgery, Lenox Hill Hospital, New York, NY, 10075, USA
| | - Guy M McKhann
- Department of Neurological Surgery, Columbia University, New York, NY, 10032, USA
| | - Emad N Eskandar
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Nayef Al-Rodhan Laboratories for Cellular Neurosurgery and Neurosurgical Technology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Joseph R Madsen
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
- Department of Neurosurgery, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA
| | - Michel J A M van Putten
- Clinical Neurophysiology Group, MIRA Institute for Biomedical Engineering and Technical Medicine, University of Twente, 7500AE, Enschede, The Netherlands
| | | | - Wim van Drongelen
- Department of Pediatrics, University of Chicago, Chicago, IL, 60637, USA.
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2
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Fujiwara H, Kadis DS, Greiner HM, Holland KD, Arya R, Aungaroon G, Fong SL, Arthur TM, Kremer KM, Lin N, Liu W, Mangano DO FT, Skoch J, Horn PS, Tenney JR. Clinical validation of magnetoencephalography network analysis for presurgical epilepsy evaluation. Clin Neurophysiol 2022; 142:199-208. [DOI: 10.1016/j.clinph.2022.07.506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 06/29/2022] [Accepted: 07/20/2022] [Indexed: 11/27/2022]
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3
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Hale AT, Chari A, Scott RC, Cross JH, Rozzelle CJ, Blount JP, Tisdall MM. Expedited epilepsy surgery prior to drug resistance in children: a frontier worth crossing? Brain 2022; 145:3755-3762. [PMID: 35883201 DOI: 10.1093/brain/awac275] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Revised: 06/18/2022] [Accepted: 07/08/2022] [Indexed: 11/14/2022] Open
Abstract
Epilepsy surgery is an established safe and effective treatment for selected candidates with drug-resistant epilepsy. In this opinion piece, we outline the clinical and experimental evidence for selectively considering epilepsy surgery prior to drug resistance. Our rationale for expedited surgery is based on the observations that, 1) a high proportion of patients with lesional epilepsies (e.g. focal cortical dysplasia, epilepsy associated tumours) will progress to drug-resistance, 2) surgical treatment of these lesions, especially in non-eloquent areas of brain, is safe, and 3) earlier surgery may be associated with better seizure outcomes. Potential benefits beyond seizure reduction or elimination include less exposure to anti-seizure medications (ASM), which may lead to improved developmental trajectories in children and optimize long-term neurocognitive outcomes and quality of life. Further, there exists emerging experimental evidence that brain network dysfunction exists at the onset of epilepsy, where continuing dysfunctional activity could exacerbate network perturbations. This in turn could lead to expanded seizure foci and contribution to the comorbidities associated with epilepsy. Taken together, we rationalize that epilepsy surgery, in carefully selected cases, may be considered prior to drug resistance. Lastly, we outline the path forward, including the challenges associated with developing the evidence base and implementing this paradigm into clinical care.
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Affiliation(s)
- Andrew T Hale
- Division of Pediatric Neurosurgery, Children's of Alabama, Birmingham, AL, USA
| | - Aswin Chari
- Department of Neurosurgery, Great Ormond Street Hospital, London, UK.,Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Rod C Scott
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK.,Department of Paediatric Neurology, Nemours Children's Hospital, Wilmington, DE, USA.,Department of Paediatric Neurology, Great Ormond Street Hospital, London, UK
| | - J Helen Cross
- Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK.,Department of Paediatric Neurology, Great Ormond Street Hospital, London, UK
| | - Curtis J Rozzelle
- Division of Pediatric Neurosurgery, Children's of Alabama, Birmingham, AL, USA
| | - Jeffrey P Blount
- Division of Pediatric Neurosurgery, Children's of Alabama, Birmingham, AL, USA
| | - Martin M Tisdall
- Department of Neurosurgery, Great Ormond Street Hospital, London, UK.,Developmental Neurosciences, Great Ormond Street Institute of Child Health, University College London, London, UK
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4
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Avansini SH, Puppo F, Adams JW, Vieira AS, Coan AC, Rogerio F, Torres FR, Araújo PAOR, Martin M, Montenegro MA, Yasuda CL, Tedeschi H, Ghizoni E, França AFEC, Alvim MKM, Athié MC, Rocha CS, Almeida VS, Dias EV, Delay L, Molina E, Yaksh TL, Cendes F, Lopes Cendes I, Muotri AR. Junctional instability in neuroepithelium and network hyperexcitability in a focal cortical dysplasia human model. Brain 2022; 145:1962-1977. [PMID: 34957478 PMCID: PMC9336577 DOI: 10.1093/brain/awab479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/15/2021] [Accepted: 11/19/2021] [Indexed: 11/14/2022] Open
Abstract
Focal cortical dysplasia is a highly epileptogenic cortical malformation with few treatment options. Here, we generated human cortical organoids from patients with focal cortical dysplasia type II. Using this human model, we mimicked some focal cortical dysplasia hallmarks, such as impaired cell proliferation, the presence of dysmorphic neurons and balloon cells, and neuronal network hyperexcitability. Furthermore, we observed alterations in the adherens junctions zonula occludens-1 and partitioning defective 3, reduced polarization of the actin cytoskeleton, and fewer synaptic puncta. Focal cortical dysplasia cortical organoids showed downregulation of the small GTPase RHOA, a finding that was confirmed in brain tissue resected from these patients. Functionally, both spontaneous and optogenetically-evoked electrical activity revealed hyperexcitability and enhanced network connectivity in focal cortical dysplasia organoids. Taken together, our findings suggest a ventricular zone instability in tissue cohesion of neuroepithelial cells, leading to a maturational arrest of progenitors or newborn neurons, which may predispose to cellular and functional immaturity and compromise the formation of neural networks in focal cortical dysplasia.
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Affiliation(s)
- Simoni H Avansini
- Department of Pediatrics/Rady Children’s Hospital-San Diego, Department of Cellular & Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92037, USA
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Francesca Puppo
- Department of Pediatrics/Rady Children’s Hospital-San Diego, Department of Cellular & Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92037, USA
| | - Jason W Adams
- Department of Pediatrics/Rady Children’s Hospital-San Diego, Department of Cellular & Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92037, USA
| | - Andre S Vieira
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Structural and Functional Biology, Institute of Biology, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Ana C Coan
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Fabio Rogerio
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Pathology, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
| | - Fabio R Torres
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Patricia A O R Araújo
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Mariana Martin
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Maria A Montenegro
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Clarissa L Yasuda
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Helder Tedeschi
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Enrico Ghizoni
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Andréa F E C França
- Department of Clinical Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
| | - Marina K M Alvim
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Maria C Athié
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Cristiane S Rocha
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Vanessa S Almeida
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Elayne V Dias
- Department of Anesthesiology/Medical Center Hillcrest, School of Medicine, University of California San Diego, Hillcrest, CA 92103, USA
| | - Lauriane Delay
- Department of Anesthesiology/Medical Center Hillcrest, School of Medicine, University of California San Diego, Hillcrest, CA 92103, USA
| | - Elsa Molina
- Stem Cell Genomics and Microscopy Core, Sanford Consortium for Regenerative Medicine, University of California San Diego, La Jolla, CA 92037, USA
| | - Tony L Yaksh
- Department of Anesthesiology/Medical Center Hillcrest, School of Medicine, University of California San Diego, Hillcrest, CA 92103, USA
| | - Fernando Cendes
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
- Department of Neurology, School of Medical Sciences, University of Campinas, Campinas Sao Paulo 13083-887, Brazil
| | - Iscia Lopes Cendes
- Department of Translational Medicine, School of Medical Sciences, University of Campinas, Campinas, Sao Paulo 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas, Campinas, Sao Paulo 13083-888, Brazil
| | - Alysson R Muotri
- Department of Pediatrics/Rady Children’s Hospital-San Diego, Department of Cellular & Molecular Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92037, USA
- Kavli Institute for Brain and Mind, Archealization Center (ArchC), Center for Academic Research and Training in Anthropogeny (CARTA), University of California San Diego, La Jolla, CA 92093, USA
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5
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Nguyen LH, Xu Y, Mahadeo T, Zhang L, Lin TV, Born HA, Anderson AE, Bordey A. Expression of 4E-BP1 in juvenile mice alleviates mTOR-induced neuronal dysfunction and epilepsy. Brain 2022; 145:1310-1325. [PMID: 34849602 PMCID: PMC9128821 DOI: 10.1093/brain/awab390] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Revised: 09/01/2021] [Accepted: 09/22/2021] [Indexed: 11/13/2022] Open
Abstract
Hyperactivation of the mTOR pathway during foetal neurodevelopment alters neuron structure and function, leading to focal malformation of cortical development and intractable epilepsy. Recent evidence suggests a role for dysregulated cap-dependent translation downstream of mTOR signalling in the formation of focal malformation of cortical development and seizures. However, it is unknown whether modifying translation once the developmental pathologies are established can reverse neuronal abnormalities and seizures. Addressing these issues is crucial with regards to therapeutics because these neurodevelopmental disorders are predominantly diagnosed during childhood, when patients present with symptoms. Here, we report increased phosphorylation of the mTOR effector and translational repressor, 4E-BP1, in patient focal malformation of cortical development tissue and in a mouse model of focal malformation of cortical development. Using temporally regulated conditional gene expression systems, we found that expression of a constitutively active form of 4E-BP1 that resists phosphorylation by focal malformation of cortical development in juvenile mice reduced neuronal cytomegaly and corrected several neuronal electrophysiological alterations, including depolarized resting membrane potential, irregular firing pattern and aberrant expression of HCN4 ion channels. Further, 4E-BP1 expression in juvenile focal malformation of cortical development mice after epilepsy onset resulted in improved cortical spectral activity and decreased spontaneous seizure frequency in adults. Overall, our study uncovered a remarkable plasticity of the juvenile brain that facilitates novel therapeutic opportunities to treat focal malformation of cortical development-related epilepsy during childhood with potentially long-lasting effects in adults.
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Affiliation(s)
- Lena H Nguyen
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Youfen Xu
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Travorn Mahadeo
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Longbo Zhang
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Tiffany V Lin
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Heather A Born
- Cain Foundation Laboratories, Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Anne E Anderson
- Cain Foundation Laboratories, Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, TX 77030, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA
| | - Angélique Bordey
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA
- Department of Cellular and Molecular Physiology, Yale University School of Medicine, New Haven, CT 06510, USA
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6
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Kinugawa K, Mano T, Takatani T, Kido A, Sugie K. Electroencephalographic-Based Functional Connectivity Networks of Visual Hallucinations and Visuospatial Dysfunctions in Parkinson's Disease. Eur Neurol 2022; 85:404-409. [PMID: 35483334 DOI: 10.1159/000524365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 03/28/2022] [Indexed: 11/19/2022]
Abstract
Visual dysfunction is an important nonmotor symptom of Parkinson's disease (PD). Visual hallucinations (VHs) and visuospatial dysfunctions (VSDs) are common visual dysfunctions in PD; however, the underlying mechanisms remain unclear. Our study aimed to evaluate neuronal synchronization between patients with PD with and without VH or VSD using electroencephalographic (EEG) coherence analysis. Twenty-four patients with sporadic PD were evaluated for the presence of VH and VSD, and were divided into VH-negative and VH-positive groups, and these groups were further subdivided by VSD status. Coherence analysis was performed on EEG data. Whole-brain and regional coherences were calculated and compared between the groups. There was a significant difference in frontal-frontal coherence between the VH+ VSD- and VH+ VSD+ groups (p = 0.026). Our findings suggest that reduced EEG coherence in frontal regions might be involved in VSD in patients with PD. Reduced neuronal synchronization between the frontal lobes may contribute to the disruption of visual processing in PD.
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Affiliation(s)
- Kaoru Kinugawa
- Department of Neurology, Nara Medical University, Kashihara, Japan,
| | - Tomoo Mano
- Department of Neurology, Nara Medical University, Kashihara, Japan.,Department of Rehabilitation Medicine, Nara Medical University, Kashihara, Japan
| | - Tsunenori Takatani
- Division of Central Clinical Laboratory, Nara Medical University, Kashihara, Japan
| | - Akira Kido
- Department of Rehabilitation Medicine, Nara Medical University, Kashihara, Japan
| | - Kazuma Sugie
- Department of Neurology, Nara Medical University, Kashihara, Japan
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7
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Mano T, Kinugawa K, Ozaki M, Kataoka H, Sugie K. Neural synchronization analysis of electroencephalography coherence in patients with Parkinson's disease-related mild cognitive impairment. Clin Park Relat Disord 2022; 6:100140. [PMID: 35308256 PMCID: PMC8928128 DOI: 10.1016/j.prdoa.2022.100140] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 02/13/2022] [Accepted: 03/02/2022] [Indexed: 11/28/2022] Open
Abstract
We studied brain functional connectivity in 20 patients with PD-MCI and 10 MCI patients without Parkinsonism. Cognitive impairment was related to decreased coherence in the alpha range [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]. Regional coherence in left FP had a higher correlation with cognitive function. Differences in EEG coherence may reflect a compensatory response to PD-MCI.
Introduction The underlying pathophysiology of slight cognitive dysfunction in Parkinson’s disease-related mild cognitive impairment (PD-MCI) is yet to be elucidated. Our study aimed to evaluate the association between cognitive function and brain functional connectivity (FC) in patients with PD-MCI. Methods Twenty patients with sporadic PD-MCI were evaluated for FC in the brain network. Further, electroencephalography (EEG) coherence analysis in the whole-brain and quantified regional coherence using phase coupling were performed for each frequency, and motor and cognitive function were assessed in the whole-brain. Results The degree of cognitive impairment was related to a decrease in the coherence in the alpha ranges. The regional coherence in the left frontal-left parietal region rather than the right frontal-right parietal region showed a higher correlation with the cognitive function scores. Conclusion The differences in EEG coherence across different types of cognitive dysfunction reflect a compensatory response to the heterogeneous and complex clinical presentation of PD-MCI. Our findings indicate decreased brain efficiency and impaired neural synchronization in PD-MCI; these results may be crucial in elucidating the pathological exacerbation of PD-MCI.
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Key Words
- Coherence analysis
- EEG, electroencephalography
- Electroencephalography
- FAB, Frontal Assessment Battery
- FC, functional connectivity
- FF, frontal-frontal
- FP, frontal-parietal
- FPL, left frontal-left parietal
- FPR, right frontal-right parietal
- FT, frontal-temporal
- HDS-R, Revised Hasegawa Dementia Score
- LEDD, levodopa-equivalent daily dose
- MCI, Mild Cognitive Impairment
- MCI, mild cognitive impairment
- MDS-UPDRS, Movement Disorder Society Unified Parkinson's Disease Rating Scale
- MMSE, Mini-Mental State Examination
- Mild cognitive impairment
- PD, Parkinson’s disease
- PO, parietal-occipital
- PT, parietal-temporal
- Parkinson's disease
- RBD, rapid eye movement sleep behavior disorder
- TT, temporal-temporal
- Time–frequency analysis
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Affiliation(s)
- Tomoo Mano
- Department of Neurology, Nara Medical University, 840 Shijo-cho, Kashihara, Nara 634-8521, Japan.,Department of Rehabilitation Medicine, Nara Medical University, 840 Shijo-cho, Kashihara, Nara 634-8521, Japan
| | - Kaoru Kinugawa
- Department of Neurology, Nara Medical University, 840 Shijo-cho, Kashihara, Nara 634-8521, Japan
| | - Maki Ozaki
- Department of Neurology, Nara Medical University, 840 Shijo-cho, Kashihara, Nara 634-8521, Japan
| | - Hiroshi Kataoka
- Department of Neurology, Nara Medical University, 840 Shijo-cho, Kashihara, Nara 634-8521, Japan
| | - Kazuma Sugie
- Department of Neurology, Nara Medical University, 840 Shijo-cho, Kashihara, Nara 634-8521, Japan
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Vogel S, Kaltenhäuser M, Kim C, Müller-Voggel N, Rössler K, Dörfler A, Schwab S, Hamer H, Buchfelder M, Rampp S. MEG Node Degree Differences in Patients with Focal Epilepsy vs. Controls-Influence of Experimental Conditions. Brain Sci 2021; 11:1590. [PMID: 34942895 PMCID: PMC8699109 DOI: 10.3390/brainsci11121590] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 11/25/2021] [Accepted: 11/27/2021] [Indexed: 11/16/2022] Open
Abstract
Drug-resistant epilepsy can be most limiting for patients, and surgery represents a viable therapy option. With the growing research on the human connectome and the evidence of epilepsy being a network disorder, connectivity analysis may be able to contribute to our understanding of epilepsy and may be potentially developed into clinical applications. In this magnetoencephalographic study, we determined the whole-brain node degree of connectivity levels in patients and controls. Resting-state activity was measured at five frequency bands in 15 healthy controls and 15 patients with focal epilepsy of different etiologies. The whole-brain all-to-all imaginary part of coherence in source space was then calculated. Node degree was determined and parcellated and was used for further statistical evaluation. In comparison to controls, we found a significantly higher overall node degree in patients with lesional and non-lesional epilepsy. Furthermore, we examined the conditions of high/reduced vigilance and open/closed eyes in controls, to analyze whether patient node degree levels can be achieved. We evaluated intraclass-correlation statistics (ICC) to evaluate the reproducibility. Connectivity and specifically node degree analysis could present new tools for one of the most common neurological diseases, with potential applications in epilepsy diagnostics.
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Affiliation(s)
- Stephan Vogel
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
- Friedrich Alexander University Erlangen Nürnberg (FAU), 91054 Erlangen, Germany
| | - Martin Kaltenhäuser
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Cora Kim
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Nadia Müller-Voggel
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Karl Rössler
- Department of Neurosurgery, Medical University Vienna, 1090 Vienna, Austria;
| | - Arnd Dörfler
- Department of Neuroradiology, University Hospital Erlangen, 91054 Erlangen, Germany;
| | - Stefan Schwab
- Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany; (S.S.); (H.H.)
| | - Hajo Hamer
- Department of Neurology, University Hospital Erlangen, 91054 Erlangen, Germany; (S.S.); (H.H.)
| | - Michael Buchfelder
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, 91054 Erlangen, Germany; (M.K.); (C.K.); (N.M.-V.); (M.B.); (S.R.)
- Department of Neurosurgery, University Hospital Halle (Saale), 06120 Halle (Saale), Germany
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9
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Slinger G, Otte WM, Braun KPJ, van Diessen E. An updated systematic review and meta-analysis of brain network organization in focal epilepsy: Looking back and forth. Neurosci Biobehav Rev 2021; 132:211-223. [PMID: 34813826 DOI: 10.1016/j.neubiorev.2021.11.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 06/23/2021] [Accepted: 11/17/2021] [Indexed: 01/10/2023]
Abstract
Abnormalities of the brain network organization in focal epilepsy have been extensively quantified. However, the extent and directionality of abnormalities are highly variable and subtype insensitive. We conducted meta-analyses to obtain a more accurate and epilepsy type-specific quantification of the interictal global brain network organization in focal epilepsy. By using random-effects models, we estimated differences in average clustering coefficient, average path length, and modularity between patients with focal epilepsy and controls, based on 45 studies with a total sample size of 1,468 patients and 1,021 controls. Structural networks had a significant lower level of integration in patients with epilepsy as compared to controls, with a standardized mean difference of -0.334 (95 % confidence interval -0.631 to -0.038; p-value 0.027). Functional networks did not differ between patients and controls, except for the beta band clustering coefficient. Our meta-analyses show that differences in the brain network organization are not as well defined as individual studies often propose. We discuss potential pitfalls and suggestions to enhance the yield and clinical value of network studies.
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Affiliation(s)
- Geertruida Slinger
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands.
| | - Willem M Otte
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Kees P J Braun
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
| | - Eric van Diessen
- Department of Child Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands
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10
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Resting-State MEG Source Space Network Metrics Associated with the Duration of Temporal Lobe Epilepsy. Brain Topogr 2021; 34:731-744. [PMID: 34652579 DOI: 10.1007/s10548-021-00875-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Accepted: 09/28/2021] [Indexed: 10/20/2022]
Abstract
To evaluate the relationship between the network metrics of 68 brain regions and duration of temporal lobe epilepsy (TLE). Magnetoencephalography (MEG) data from 53 patients with TLE (28 left TLE, 25 right TLE) were recorded between seizures at resting state and analyzed in six frequency bands: delta (0.1-4 Hz), theta (4-8 Hz), lower alpha (8-10 Hz), upper alpha (10-13 Hz), beta (13-30 Hz), and lower gamma (30-48 Hz). Three local network metrics, betweenness centrality, nodal degree, and nodal efficiency, were chosen to analyze the functional brain network. In Left, Right, and All (Left + Right) TLE groups, different metrics provide significant positive or negative correlations with the duration of TLE, in different frequency bands, and in different brain regions. In the Left TLE group, significant correlation between TLE duration and metric exists in the delta, beta, or lower gamma band, with network betweenness centrality, nodal degree, or nodal efficiency, in left caudal middle frontal, left middle temporal, or left supramarginal. In the Right TLE group, significant correlation exists in lower gamma or delta band, with nodal degree, or nodal efficiency, in left precuneus or right temporal pole. In the All TLE group, the significant correlation exists in delta, theta, beta, or lower gamma band, with nodal degree, or betweenness centrality, in either left or right hemisphere. Network metrics for some specific brain regions changed in patients with TLE as the duration of their TLE increased. Further researching these changes may be important for studying the pathogenesis, presurgical evaluation, and clinical treatment of long-term TLE.
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11
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Kinugawa K, Mano T, Sugie K. Neuronal Dynamics of Pain in Parkinson's Disease. Brain Sci 2021; 11:brainsci11091224. [PMID: 34573244 PMCID: PMC8468705 DOI: 10.3390/brainsci11091224] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 09/05/2021] [Accepted: 09/14/2021] [Indexed: 11/16/2022] Open
Abstract
Pain is an important non-motor symptom of Parkinson’s disease (PD). It negatively impacts the quality of life. However, the pathophysiological mechanisms underlying pain in PD remain to be elucidated. This study sought to use electroencephalographic (EEG) coherence analysis to compare neuronal synchronization in neuronal networks between patients with PD, with and without pain. Twenty-four patients with sporadic PD were evaluated for the presence of pain. Time-frequency and coherence analyses were performed on their EEG data. Whole-brain and regional coherence were calculated and compared between pain-positive and pain-negative patients. There was no significant difference in the whole-brain coherence between the pain-positive and pain-negative groups. However, temporal–temporal coherence differed significantly between the two groups (p = 0.031). Our findings indicate that aberrant synchronization of inter-temporal regions is involved in PD-related pain. This will further our understanding of the mechanisms underlying pain in PD.
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12
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Lee DA, Lee HJ, Kim HC, Park KM. Alterations of structural connectivity and structural co-variance network in focal cortical dysplasia. BMC Neurol 2021; 21:330. [PMID: 34452597 PMCID: PMC8394627 DOI: 10.1186/s12883-021-02358-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2021] [Accepted: 08/17/2021] [Indexed: 12/04/2022] Open
Abstract
Background The aim of this study was to investigate alterations in structural connectivity and structural co-variance network in patients with focal cortical dysplasia (FCD). Methods We enrolled 37 patients with FCD and 35 healthy controls. All subjects underwent brain MRI with the same scanner and with the same protocol, which included diffusion tensor imaging (DTI) and T1-weighted imaging. We analyzed the structural connectivity based on DTI, and structural co-variance network based on the structural volume with T1-weighted imaging. We created a connectivity matrix and obtained network measures from the matrix using the graph theory. We tested the difference in network measure between patients with FCD and healthy controls. Results In the structural connectivity analysis, we found that the local efficiency in patients with FCD was significantly lower than in healthy controls (2.390 vs. 2.578, p = 0.031). Structural co-variance network analysis revealed that the mean clustering coefficient, global efficiency, local efficiency, and transitivity were significantly decreased in patients with FCD compared to those in healthy controls (0.527 vs. 0.635, p = 0.036; 0.545 vs. 0.648, p = 0.026; 2.699 vs. 3.801, p = 0.019; 0.791 vs. 0.954, p = 0.026, respectively). Conclusions We demonstrate that there are significant alterations in structural connectivity, based on DTI, and structural co-variance network, based on the structural volume, in patients with FCD compared to healthy controls. These findings suggest that focal lesions with FCD could affect the whole-brain network and that FCD is a network disease.
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Affiliation(s)
- Dong Ah Lee
- Neurology Department, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea
| | - Ho-Joon Lee
- Radiology Department, Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Hyung Chan Kim
- Neurology Department, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea
| | - Kang Min Park
- Neurology Department, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, 48108, Busan, Korea.
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13
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Xu N, Shan W, Qi J, Wu J, Wang Q. Presurgical Evaluation of Epilepsy Using Resting-State MEG Functional Connectivity. Front Hum Neurosci 2021; 15:649074. [PMID: 34276321 PMCID: PMC8283278 DOI: 10.3389/fnhum.2021.649074] [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: 01/03/2021] [Accepted: 06/07/2021] [Indexed: 11/21/2022] Open
Abstract
Epilepsy is caused by abnormal electrical discharges (clinically identified by electrophysiological recording) in a specific part of the brain [originating in only one part of the brain, namely, the epileptogenic zone (EZ)]. Epilepsy is now defined as an archetypical hyperexcited neural network disorder. It can be investigated through the network analysis of interictal discharges, ictal discharges, and resting-state functional connectivity. Currently, there is an increasing interest in embedding resting-state connectivity analysis into the preoperative evaluation of epilepsy. Among the various neuroimaging technologies employed to achieve brain functional networks, magnetoencephalography (MEG) with the excellent temporal resolution is an ideal tool for estimating the resting-state connectivity between brain regions, which can reveal network abnormalities in epilepsy. What value does MEG resting-state functional connectivity offer for epileptic presurgical evaluation? Regarding this topic, this paper introduced the origin of MEG and the workflow of constructing source-space functional connectivity based on MEG signals. Resting-state functional connectivity abnormalities correlate with epileptogenic networks, which are defined by the brain regions involved in the production and propagation of epileptic activities. This paper reviewed the evidence of altered epileptic connectivity based on low- or high-frequency oscillations (HFOs) and the evidence of the advantage of using simultaneous MEG and intracranial electroencephalography (iEEG) recordings. More importantly, this review highlighted that MEG-based resting-state functional connectivity has the potential to predict postsurgical outcomes. In conclusion, resting-state MEG functional connectivity has made a substantial progress toward serving as a candidate biomarker included in epileptic presurgical evaluations.
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Affiliation(s)
- Na Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wei Shan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jing Qi
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jianping Wu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- National Clinical Research Center for Neurological Diseases, Beijing, China
- Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
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14
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Ueda R, Iwasaki M, Kita Y, Takeichi H, Saito T, Nakagawa E, Sugai K, Okada T, Sasaki M. Improvement of brain function after surgery in infants with posterior quadrant cortical dysplasia. Clin Neurophysiol 2020; 132:332-337. [PMID: 33450555 DOI: 10.1016/j.clinph.2020.11.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 10/02/2020] [Accepted: 11/10/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVE To reveal whether neurodevelopmental outcome of infants after epilepsy surgery can be quantitatively assessed by electroencephalography (EEG) functional connectivity analysis. METHODS We enrolled 13 infants with posterior quadrant dysplasia aged <2 years who were treated using posterior quadrantectomy and 21 age-matched infants. EEG was performed both before and one year after surgery. Developmental quotient (DQ) was assessed both before and 3 years after surgery. The phase lag index (PLI) of three different pairs of electrodes in the nonsurgical hemisphere, i.e., the anterior short distance (ASD), posterior short distance (PSD), and long distance (LD) pairs, were calculated as indices of brain connectivity. The relationship between the PLI and DQ was evaluated. RESULTS Overall, 77% infants experienced seizure freedom after surgery. The beta- and gamma- range PLI of PSD pairs increased preoperatively. All these pairs normalized postoperatively. Simple linear regression analysis revealed a significant relationship between the postoperative DQ and the postoperative beta-band PLI of ASD pairs. CONCLUSION Preoperative abnormal hyper-connectivity was normalized to the control level after surgery. The postoperative hyperconnectivity was associated with long-term neurodevelopmental improvement. SIGNIFICANCE PLI quantifies neurodevelopmental improvements after posterior quadrantectomy.
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Affiliation(s)
- Riyo Ueda
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan; Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Masaki Iwasaki
- Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
| | - Yosuke Kita
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan; Cognitive Brain Research Unit (CBRU), Faculty of Medicine, University of Helsinki, Haartmaninkatu 3, FI-00290 Helsinki, Finland; Mori Arinori Center for Higher Education and Global Mobility, Hitotsubashi University, 2-1, Kunitachi, Tokyo 186-8601, Japan.
| | - Hiroshige Takeichi
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Takashi Saito
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
| | - Eiji Nakagawa
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
| | - Kenji Sugai
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
| | - Takashi Okada
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Masayuki Sasaki
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
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15
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Ueda R, Kaga Y, Takeichi H, Iwasaki M, Takeshita E, Shimizu-Motohashi Y, Ishiyama A, Saito T, Nakagawa E, Sugai K, Sasaki M, Inagaki M. Association between lack of functional connectivity of the frontal brain region and poor response inhibition in children with frontal lobe epilepsy. Epilepsy Behav 2020; 113:107561. [PMID: 33232894 DOI: 10.1016/j.yebeh.2020.107561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 10/07/2020] [Accepted: 10/07/2020] [Indexed: 11/19/2022]
Abstract
PURPOSE We investigated the relationship between electroencephalographic (EEG) functional connectivity and executive function in children with frontal lobe epilepsy (FLE). METHODS We enrolled 24 children with FLE (mean age, 11.0 years; 13 boys) and 22 sex-, age-, and intelligence-matched typically developing children (TDC) to undergo 19-channel EEG during light sleep. We estimated functional connectivity using the phase lag index (PLI) that captures the synchronization of EEG. We also performed continuous performance tests (CPTs) on the children and obtained questionnaire responses on attention deficit hyperactivity disorder and oppositional defiant disorder (ODD). RESULTS The average gamma PLI was lower in the FLE group than in the TDC group, especially between long-distance frontoparietal pairs, between interhemispheric frontal pairs, and between interhemispheric parietotemporal pairs. Gamma PLIs with long-distance frontoparietal and interhemispheric frontal pairs were positively associated with inattention, ODD scores, omission error, and reaction time in the FLE group but not in the TDC group. Conversely, they were negatively associated with age, hyperactivity score, and commission error. CONCLUSIONS A lack of functional connectivity of the frontal brain regions in children with FLE was associated with poor response inhibition.
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Affiliation(s)
- Riyo Ueda
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Yoshimi Kaga
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Hiroshige Takeichi
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
| | - Masaki Iwasaki
- Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8551, Japan.
| | - Eri Takeshita
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Yuko Shimizu-Motohashi
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Akihiko Ishiyama
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Takashi Saito
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Eiji Nakagawa
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Kenji Sugai
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Masayuki Sasaki
- Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira 187-8551, Tokyo, Japan.
| | - Masumi Inagaki
- Department of Developmental Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1 Ogawahigashi-cho, Kodaira, Tokyo 187-8553, Japan.
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16
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Ramaraju S, Wang Y, Sinha N, McEvoy AW, Miserocchi A, de Tisi J, Duncan JS, Rugg-Gunn F, Taylor PN. Removal of Interictal MEG-Derived Network Hubs Is Associated With Postoperative Seizure Freedom. Front Neurol 2020; 11:563847. [PMID: 33071948 PMCID: PMC7543719 DOI: 10.3389/fneur.2020.563847] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Accepted: 08/20/2020] [Indexed: 01/21/2023] Open
Abstract
Objective: To investigate whether MEG network connectivity was associated with epilepsy duration, to identify functional brain network hubs in patients with refractory focal epilepsy, and assess if their surgical removal was associated with post-operative seizure freedom. Methods: We studied 31 patients with drug refractory focal epilepsy who underwent resting state magnetoencephalography (MEG), and structural magnetic resonance imaging (MRI) as part of pre-surgical evaluation. Using the structural MRI, we generated 114 cortical regions of interest, performed surface reconstruction and MEG source localization. Representative source localized signals for each region were correlated with each other to generate a functional brain network. We repeated this procedure across three randomly chosen one-minute epochs. Network hubs were defined as those with the highest intra-hemispheric mean correlations. Post-operative MRI identified regions that were surgically removed. Results: Greater mean MEG network connectivity was associated with a longer duration of epilepsy. Patients who were seizure free after surgery had more hubs surgically removed than patients who were not seizure free (AUC = 0.76, p = 0.01) consistently across three randomly chosen time segments. Conclusion: Our results support a growing literature implicating network hub involvement in focal epilepsy, the removal of which by surgery is associated with greater chance of post-operative seizure freedom.
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Affiliation(s)
- Sriharsha Ramaraju
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Yujiang Wang
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Faculty of Medical Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Nishant Sinha
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Faculty of Medical Science, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Andrew W McEvoy
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Anna Miserocchi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jane de Tisi
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - John S Duncan
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Fergus Rugg-Gunn
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Peter N Taylor
- Interdisciplinary Computing and Complex BioSystems Group, CNNP Lab, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.,Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, United Kingdom.,Faculty of Medical Science, Newcastle University, Newcastle upon Tyne, United Kingdom
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17
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Yu H, Zhu L, Cai L, Wang J, Liu C, Shi N, Liu J. Variation of functional brain connectivity in epileptic seizures: an EEG analysis with cross-frequency phase synchronization. Cogn Neurodyn 2020; 14:35-49. [PMID: 32015766 PMCID: PMC6973936 DOI: 10.1007/s11571-019-09551-y] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 07/22/2019] [Accepted: 08/02/2019] [Indexed: 11/26/2022] Open
Abstract
Frequency coupling in nervous system is believed to be associated with normal and impaired brain functions. However, most of the existing experiments have been concentrated on the coupling strength within frequency bands, while the coupling strength between different bands is ignored. In this work, we apply phase synchronization index (PSI) to investigate the cross-frequency coupling (CFC) of Electroencephalogram (EEG) signals. The PSI matrixes for the multi-channel EEG signals are calculated from interictal to ictal period in each sliding time window. The results show that CFC changes obviously once seizure occurs between the different bands, and such alteration is earlier than the appearance of clinical symptoms in seizure. Considering the similar role of the within-frequency coupling (WFC), we further reconstruct multi-layered brain networks, including CFC networks and WFC networks. The graph metrics are applied to investigate the variation of network structure of the epileptic brain. Significant decreases/increases of the local/global efficiency are found in δ-β, δ-α, θ-α and δ-θ bands from the CFC network, while WFC network shows a significant decline in the local efficiency in θ and α bands. These findings suggest that CFC may provide a new perspective to observe the alteration of brain structure when seizure occurs, and the investigation of functional connectivity across the full frequency spectrum can give us a deeper understanding of epileptic brains.
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Affiliation(s)
- Haitao Yu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Lin Zhu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Lihui Cai
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Chen Liu
- School of Electrical and Information Engineering, Tianjin University, Tianjin, China
| | - Nan Shi
- Department of Neurology, Tangshan Gongren Hospital, Tangshan, 063000 Hebei China
| | - Jing Liu
- Department of Neurology, Tangshan Gongren Hospital, Tangshan, 063000 Hebei China
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18
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Subramanian L, Calcagnotto ME, Paredes MF. Cortical Malformations: Lessons in Human Brain Development. Front Cell Neurosci 2020; 13:576. [PMID: 32038172 PMCID: PMC6993122 DOI: 10.3389/fncel.2019.00576] [Citation(s) in RCA: 60] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Accepted: 12/16/2019] [Indexed: 12/11/2022] Open
Abstract
Creating a functional cerebral cortex requires a series of complex and well-coordinated developmental steps. These steps have evolved across species with the emergence of cortical gyrification and coincided with more complex behaviors. The presence of diverse progenitor cells, a protracted timeline for neuronal migration and maturation, and diverse neuronal types are developmental features that have emerged in the gyrated cortex. These factors could explain how the human brain has expanded in size and complexity. However, their complex nature also renders new avenues of vulnerability by providing additional cell types that could contribute to disease and longer time windows that could impact the composition and organization of the cortical circuit. We aim to discuss the unique developmental steps observed in human corticogenesis and propose how disruption of these species-unique processes could lead to malformations of cortical development.
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Affiliation(s)
- Lakshmi Subramanian
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, United States
| | - Maria Elisa Calcagnotto
- Neurophysiology and Neurochemistry of Neuronal Excitability and Synaptic Plasticity Laboratory, Department of Biochemistry, ICBS, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,Graduate Program in Neuroscience, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Mercedes F Paredes
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, United States.,Department of Neurology, University of California, San Francisco, San Francisco, CA, United States.,Neuroscience Graduate Division, University of California, San Francisco, San Francisco, CA, United States
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19
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Chang Q, Liu M, Tian Q, Wang H, Luo Y, Zhang J, Wang C. EEG-Based Brain Functional Connectivity in First-Episode Schizophrenia Patients, Ultra-High-Risk Individuals, and Healthy Controls During P50 Suppression. Front Hum Neurosci 2019; 13:379. [PMID: 31803031 PMCID: PMC6870009 DOI: 10.3389/fnhum.2019.00379] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 10/10/2019] [Indexed: 01/29/2023] Open
Abstract
Dysfunctional processing of auditory sensory gating has generally been found in schizophrenic patients and ultra-high-risk (UHR) individuals. The aim of the study was to investigate the differences of functional interaction between brain regions and performance during the P50 sensory gating in UHR group compared with those in first-episode schizophrenia patients (FESZ) and healthy controls (HC) groups. The study included 128-channel scalp Electroencephalogram (EEG) recordings during the P50 auditory paradigm for 35 unmedicated FESZ, 30 drug-free UHR, and 40 HC. Cortical sources of scalp electrical activity were recomputed using exact low-resolution electromagnetic tomography (eLORETA), and functional brain networks were built at the source level and compared between the groups (FESZ, UHR, HC). A classifier using decision tree was designed for differentiating the three groups, which uses demographic characteristics, MATRICS Consensus Cognitive Battery parameters, behavioral features in P50 paradigm, and the measures of functional brain networks based on graph theory during P50 sensory gating. The results showed that very few brain connectivities were significantly different between FESZ and UHR groups during P50 sensory gating, and that a large number of brain connectivities were significantly different between FESZ and HC groups and between UHR and HC groups. Furthermore, the FESZ group had a stronger connection in the right superior frontal gyrus and right insula than the HC group. And the UHR group had an enhanced connection in the paracentral lobule and the middle temporal gyrus compared with the HC group. Moreover, comparison of classification analysis results showed that brain network metrics during P50 sensory gating can improve the accuracy of the classification for FESZ, UHR and HC groups. Our findings provide insight into the mechanisms of P50 suppression in schizophrenia and could potentially improve the performance of early identification and diagnosis of schizophrenia for the earliest intervention.
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Affiliation(s)
- Qi Chang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China
| | - Meijun Liu
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China
| | - Qing Tian
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Hua Wang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.,Hefei Innovation Research Institute, Beihang University, Hefei, China.,School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Yu Luo
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China
| | - Jicong Zhang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Hefei Innovation Research Institute, Beihang University, Hefei, China.,School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Chuanyue Wang
- The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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20
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Meng L. A Magnetoencephalography Study of Pediatric Interictal Neuromagnetic Activity Changes and Brain Network Alterations Caused by Epilepsy in the High Frequency (80-1000 Hz). IEEE Trans Neural Syst Rehabil Eng 2019; 27:389-399. [PMID: 30762563 DOI: 10.1109/tnsre.2019.2898683] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
More and more studies propose that high frequency brain signals are promising biomarkers of epileptogenic zone. In this paper, our aim is to investigate the neuromagnetic changes and brain network topological alterations during an interictal period at high frequency ranges (80-1000 Hz) between healthy controls and epileptic patients with Magnetoencephalography. We analyzed neuromagnetic activities with accumulated source imaging, and constructed brain network based on graph theory. Neuromagnetic activity changes and brain network alterations between two groups were analyzed in three frequency bands: ripple (80-250 Hz), fast ripples (FRs, 250-500 Hz), and very high frequency oscillations (VHFO, 500-1000 Hz). We found that epileptic patients showed significantly altered patterns of neuromagnetic source localization and altered brain network patterns. And, we also found that mean functional connectivity and the number of modules from epileptic patients significantly increased in the ripple and FRs bands, and mean clustering coefficient from epileptic patients significantly decreased in the ripple and FRs bands. We also found that the mean functional connectivity was positively correlated with duration of epilepsy in the ripple and VHFO bands, and the number of modules was positively correlated with the duration of epilepsy in the ripple, FRs, and VHFO bands. Our results indicate that epilepsy can alter patients' neuromagnetic activities and brain networks in the high-frequency ranges, and these alterations become more pathological as the duration of epilepsy grows longer.
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21
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Li Hegner Y, Marquetand J, Elshahabi A, Klamer S, Lerche H, Braun C, Focke NK. Increased Functional MEG Connectivity as a Hallmark of MRI-Negative Focal and Generalized Epilepsy. Brain Topogr 2018; 31:863-874. [PMID: 29766384 DOI: 10.1007/s10548-018-0649-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 05/08/2018] [Indexed: 01/13/2023]
Abstract
Epilepsy is one of the most prevalent neurological diseases with a high morbidity. Accumulating evidence has shown that epilepsy is an archetypical neural network disorder. Here we developed a non-invasive cortical functional connectivity analysis based on magnetoencephalography (MEG) to assess commonalities and differences in the network phenotype in different epilepsy syndromes (non-lesional/cryptogenic focal and idiopathic/genetic generalized epilepsy). Thirty-seven epilepsy patients with normal structural brain anatomy underwent a 30-min resting state MEG measurement with eyes closed. We only analyzed interictal epochs without epileptiform discharges. The imaginary part of coherency was calculated as an indicator of cortical functional connectivity in five classical frequency bands. This connectivity measure was computed between all sources on individually reconstructed cortical surfaces that were surface-aligned to a common template. In comparison to healthy controls, both focal and generalized epilepsy patients showed widespread increased functional connectivity in several frequency bands, demonstrating the potential of elevated functional connectivity as a common pathophysiological hallmark in different epilepsy types. Furthermore, the comparison between focal and generalized epilepsies revealed increased network connectivity in bilateral mesio-frontal and motor regions specifically for the generalized epilepsy patients. Our study indicated that the surface-based normalization of MEG sources of individual brains enables the comparison of imaging findings across subjects and groups on a united platform, which leads to a straightforward and effective disclosure of pathological network characteristics in epilepsy. This approach may allow for the definition of more specific markers of different epilepsy syndromes, and increased MEG-based resting-state functional connectivity seems to be a common feature in MRI-negative epilepsy syndromes.
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Affiliation(s)
- Yiwen Li Hegner
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.
| | - Justus Marquetand
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany
| | - Adham Elshahabi
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.,Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany
| | - Silke Klamer
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany
| | - Holger Lerche
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.,Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany
| | - Christoph Braun
- Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany.,MEG Center, University of Tübingen, Tübingen, Germany.,CIMeC, Center for Mind/Brain Sciences, University of Trento, Trento, Italy
| | - Niels K Focke
- Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Hope-Seyler-Straße 3, 72076, Tübingen, Germany.,Werner Reichardt Centre for Integrative Neuroscience, Tübingen, Germany.,Clinical Neurophysiology, University of Göttingen, Göttingen, Germany
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22
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Grobelny BT, London D, Hill TC, North E, Dugan P, Doyle WK. Betweenness centrality of intracranial electroencephalography networks and surgical epilepsy outcome. Clin Neurophysiol 2018; 129:1804-1812. [PMID: 29981955 DOI: 10.1016/j.clinph.2018.02.135] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 01/29/2018] [Accepted: 02/27/2018] [Indexed: 11/27/2022]
Abstract
OBJECTIVE We sought to determine whether the presence or surgical removal of certain nodes in a connectivity network constructed from intracranial electroencephalography recordings determines postoperative seizure freedom in surgical epilepsy patients. METHODS We analyzed connectivity networks constructed from peri-ictal intracranial electroencephalography of surgical epilepsy patients before a tailored resection. Thirty-six patients and 123 seizures were analyzed. Their Engel class postsurgical seizure outcome was determined at least one year after surgery. Betweenness centrality, a measure of a node's importance as a hub in the network, was used to compare nodes. RESULTS The presence of larger quantities of high-betweenness nodes in interictal and postictal networks was associated with failure to achieve seizure freedom from the surgery (p < 0.001), as was resection of high-betweenness nodes in three successive frequency groups in mid-seizure networks (p < 0.001). CONCLUSIONS Betweenness centrality is a biomarker for postsurgical seizure outcomes. The presence of high-betweenness nodes in interictal and postictal networks can predict patient outcome independent of resection. Additionally, since their resection is associated with worse seizure outcomes, the mid-seizure network high-betweenness centrality nodes may represent hubs in self-regulatory networks that inhibit or help terminate seizures. SIGNIFICANCE This is the first study to identify network nodes that are possibly protective in epilepsy.
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Affiliation(s)
- Bartosz T Grobelny
- Department of Neurosurgery, New York University Langone Medical Center, New York, NY 10016, USA
| | - Dennis London
- Department of Neurosurgery, New York University Langone Medical Center, New York, NY 10016, USA
| | - Travis C Hill
- Department of Neurosurgery, New York University Langone Medical Center, New York, NY 10016, USA
| | - Emily North
- Department of Neurosurgery, New York University Langone Medical Center, New York, NY 10016, USA
| | - Patricia Dugan
- Comprehensive Epilepsy Center, New York University Langone Medical Center, New York, NY 10016, USA
| | - Werner K Doyle
- Department of Neurosurgery, New York University Langone Medical Center, New York, NY 10016, USA.
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24
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Li YH, Ye XL, Liu QQ, Mao JW, Liang PJ, Xu JW, Zhang PM. Localization of epileptogenic zone based on graph analysis of stereo-EEG. Epilepsy Res 2016; 128:149-157. [DOI: 10.1016/j.eplepsyres.2016.10.021] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 10/10/2016] [Accepted: 10/25/2016] [Indexed: 11/27/2022]
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25
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Interaction between Thalamus and Hippocampus in Termination of Amygdala-Kindled Seizures in Mice. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2016; 2016:9580724. [PMID: 27829869 PMCID: PMC5086540 DOI: 10.1155/2016/9580724] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2016] [Accepted: 09/20/2016] [Indexed: 12/20/2022]
Abstract
The thalamus and hippocampus have been found both involved in the initiation, propagation, and termination of temporal lobe epilepsy. However, the interaction of these regions during seizures is not clear. The present study is to explore whether some regular patterns exist in their interaction during the termination of seizures. Multichannel in vivo recording techniques were used to record the neural activities from the cornu ammonis 1 (CA1) of hippocampus and mediodorsal thalamus (MDT) in mice. The mice were kindled by electrically stimulating basolateral amygdala neurons, and Racine's rank standard was employed to classify the stage of behavioral responses (stage 1~5). The coupling index and directionality index were used to investigate the synchronization and information flow direction between CA1 and MDT. Two main results were found in this study. (1) High levels of synchronization between the thalamus and hippocampus were observed before the termination of seizures at stage 4~5 but after the termination of seizures at stage 1~2. (2) In the end of seizures at stage 4~5, the information tended to flow from MDT to CA1. Those results indicate that the synchronization and information flow direction between the thalamus and the hippocampus may participate in the termination of seizures.
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26
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Pang EW, Snead III OC. From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery. Front Neuroanat 2016; 10:67. [PMID: 27445705 PMCID: PMC4914570 DOI: 10.3389/fnana.2016.00067] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2016] [Accepted: 06/07/2016] [Indexed: 11/14/2022] Open
Abstract
New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.
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Affiliation(s)
- Elizabeth W. Pang
- Division of Neurology, Hospital for Sick ChildrenToronto, ON, Canada
- Neurosciences and Mental Health, SickKids Research InstituteToronto, ON, Canada
- Department of Paediatrics, Faculty of Medicine, University of TorontoToronto, ON, Canada
| | - O. C. Snead III
- Division of Neurology, Hospital for Sick ChildrenToronto, ON, Canada
- Neurosciences and Mental Health, SickKids Research InstituteToronto, ON, Canada
- Department of Paediatrics, Faculty of Medicine, University of TorontoToronto, ON, Canada
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27
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Computational analysis in epilepsy neuroimaging: A survey of features and methods. NEUROIMAGE-CLINICAL 2016; 11:515-529. [PMID: 27114900 PMCID: PMC4833048 DOI: 10.1016/j.nicl.2016.02.013] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Revised: 02/11/2016] [Accepted: 02/22/2016] [Indexed: 12/15/2022]
Abstract
Epilepsy affects 65 million people worldwide, a third of whom have seizures that are resistant to anti-epileptic medications. Some of these patients may be amenable to surgical therapy or treatment with implantable devices, but this usually requires delineation of discrete structural or functional lesion(s), which is challenging in a large percentage of these patients. Advances in neuroimaging and machine learning allow semi-automated detection of malformations of cortical development (MCDs), a common cause of drug resistant epilepsy. A frequently asked question in the field is what techniques currently exist to assist radiologists in identifying these lesions, especially subtle forms of MCDs such as focal cortical dysplasia (FCD) Type I and low grade glial tumors. Below we introduce some of the common lesions encountered in patients with epilepsy and the common imaging findings that radiologists look for in these patients. We then review and discuss the computational techniques introduced over the past 10 years for quantifying and automatically detecting these imaging findings. Due to large variations in the accuracy and implementation of these studies, specific techniques are traditionally used at individual centers, often guided by local expertise, as well as selection bias introduced by the varying prevalence of specific patient populations in different epilepsy centers. We discuss the need for a multi-institutional study that combines features from different imaging modalities as well as computational techniques to definitively assess the utility of specific automated approaches to epilepsy imaging. We conclude that sharing and comparing these different computational techniques through a common data platform provides an opportunity to rigorously test and compare the accuracy of these tools across different patient populations and geographical locations. We propose that these kinds of tools, quantitative imaging analysis methods and open data platforms for aggregating and sharing data and algorithms, can play a vital role in reducing the cost of care, the risks of invasive treatments, and improve overall outcomes for patients with epilepsy. We introduce common epileptogenic lesions encountered in patients with drug resistant epilepsy. We discuss state of the art computational techniques used to detect lesions. There is a need for multi-institutional studies that combine these techniques. Clinically validated pipelines alongside the advances in imaging and electrophysiology will improve outcomes.
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Key Words
- DRE, drug resistant epilepsy
- DTI, diffusion tensor imaging
- DWI, diffusion weighted imaging
- Drug resistant epilepsy
- Epilepsy
- FCD, focal cortical dysplasia
- FLAIR, fluid-attenuated inversion recovery
- Focal cortical dysplasia
- GM, gray matter
- GW, gray-white junction
- HARDI, high angular resolution diffusion imaging
- MEG, magnetoencephalography
- MRS, magnetic resonance spectroscopy imaging
- Machine learning
- Malformations of cortical development
- Multimodal neuroimaging
- PET, positron emission tomography
- PNH, periventricular nodular heterotopia
- SBM, surface-based morphometry
- T1W, T1-weighted MRI
- T2W, T2-weighted MRI
- VBM, voxel-based morphometry
- WM, white matter
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28
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Englot DJ, Hinkley LB, Kort NS, Imber BS, Mizuiri D, Honma SM, Findlay AM, Garrett C, Cheung PL, Mantle M, Tarapore PE, Knowlton RC, Chang EF, Kirsch HE, Nagarajan SS. Global and regional functional connectivity maps of neural oscillations in focal epilepsy. Brain 2015; 138:2249-62. [PMID: 25981965 DOI: 10.1093/brain/awv130] [Citation(s) in RCA: 168] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Accepted: 03/19/2015] [Indexed: 01/27/2023] Open
Abstract
Intractable focal epilepsy is a devastating disorder with profound effects on cognition and quality of life. Epilepsy surgery can lead to seizure freedom in patients with focal epilepsy; however, sometimes it fails due to an incomplete delineation of the epileptogenic zone. Brain networks in epilepsy can be studied with resting-state functional connectivity analysis, yet previous investigations using functional magnetic resonance imaging or electrocorticography have produced inconsistent results. Magnetoencephalography allows non-invasive whole-brain recordings, and can be used to study both long-range network disturbances in focal epilepsy and regional connectivity at the epileptogenic zone. In magnetoencephalography recordings from presurgical epilepsy patients, we examined: (i) global functional connectivity maps in patients versus controls; and (ii) regional functional connectivity maps at the region of resection, compared to the homotopic non-epileptogenic region in the contralateral hemisphere. Sixty-one patients were studied, including 30 with mesial temporal lobe epilepsy and 31 with focal neocortical epilepsy. Compared with a group of 31 controls, patients with epilepsy had decreased resting-state functional connectivity in widespread regions, including perisylvian, posterior temporo-parietal, and orbitofrontal cortices (P < 0.01, t-test). Decreased mean global connectivity was related to longer duration of epilepsy and higher frequency of consciousness-impairing seizures (P < 0.01, linear regression). Furthermore, patients with increased regional connectivity within the resection site (n = 24) were more likely to achieve seizure postoperative seizure freedom (87.5% with Engel I outcome) than those with neutral (n = 15, 64.3% seizure free) or decreased (n = 23, 47.8% seizure free) regional connectivity (P < 0.02, chi-square). Widespread global decreases in functional connectivity are observed in patients with focal epilepsy, and may reflect deleterious long-term effects of recurrent seizures. Furthermore, enhanced regional functional connectivity at the area of resection may help predict seizure outcome and aid surgical planning.
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Affiliation(s)
- Dario J Englot
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 2 Department of Neurological Surgery, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Leighton B Hinkley
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Naomi S Kort
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Brandon S Imber
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 2 Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - Danielle Mizuiri
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Susanne M Honma
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Anne M Findlay
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Coleman Garrett
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Paige L Cheung
- 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Mary Mantle
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Phiroz E Tarapore
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 2 Department of Neurological Surgery, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Robert C Knowlton
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA 4 Department of Neurology, University of California, San Francisco, California, USA
| | - Edward F Chang
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 2 Department of Neurological Surgery, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Heidi E Kirsch
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA 4 Department of Neurology, University of California, San Francisco, California, USA
| | - Srikantan S Nagarajan
- 1 UCSF Comprehensive Epilepsy Centre, University of California, San Francisco, California, USA 3 Biomagnetic Imaging Lab, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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