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      Transfer Function Models for the Localization of Seizure Onset Zone From Cortico-Cortical Evoked Potentials

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          Abstract

          Surgical resection of the seizure onset zone (SOZ) could potentially lead to seizure-freedom in medically refractory epilepsy patients. However, localizing the SOZ can be a time consuming and tedious process involving visual inspection of intracranial electroencephalographic (iEEG) recordings captured during passive patient monitoring. Cortical stimulation is currently performed on patients undergoing invasive EEG monitoring for the main purpose of mapping functional brain networks such as language and motor networks. We hypothesized that evoked responses from single pulse electrical stimulation (SPES) can also be used to localize the SOZ as they may express the natural frequencies and connectivity of the iEEG network. To test our hypothesis, we constructed patient specific transfer function models from the evoked responses recorded from 22 epilepsy patients that underwent SPES evaluation and iEEG monitoring. We then computed the frequency and connectivity dependent “peak gain” of the system as measured by the H    norm from systems theory. We found that in cases for which clinicians had high confidence in localizing the SOZ, the highest peak gain transfer functions with the smallest “floor gain” (gain at which the dipped H    3dB below DC gain) corresponded to when the clinically annotated SOZ and early spread regions were stimulated. In more complex cases, there was a large spread of the peak-to-floor (PF) ratios when the clinically annotated SOZ was stimulated. Interestingly for patients who had successful surgeries, our ratio of gains, agreed with clinical localization, no matter the complexity of the case. For patients with failed surgeries, the PF ratio did not match clinical annotations. Our findings suggest that transfer function gains and their corresponding frequency responses computed from SPES evoked responses may improve SOZ localization and thus surgical outcomes.

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          Functional connectivity in the human language system: a cortico-cortical evoked potential study.

          A better understanding of the mechanisms involved in human higher cortical functions requires a detailed knowledge of neuronal connectivity between functional cortical regions. Currently no good method for tracking in vivo neuronal connectivity exists. We investigated the inter-areal connections in vivo in the human language system using a new method, which we termed 'cortico-cortical evoked potentials' (CCEPs). Eight patients with epilepsy (age 13-42 years) underwent invasive monitoring with subdural electrodes for epilepsy surgery. Six patients had language dominance on the side of grid implantation and two had bilateral language representation by the intracarotid amobarbital test. Conventional cortical electrical stimulation was performed to identify the anterior and posterior language areas. Single pulse electrical stimuli were delivered to the anterior language (eight patients), posterior language (four patients) or face motor (two patients) area, and CCEPs were obtained by averaging electrocorticograms (ECoGs) recorded from the perisylvian and extrasylvian basal temporal language areas time-locked to the stimulus. The subjects were not asked to perform any tasks during the study. Stimulation at the anterior language area elicited CCEPs in the lateral temporo-parietal area (seven of eight patients) in the middle and posterior part of the superior temporal gyrus, the adjacent part of the middle temporal gyrus and the supramarginal gyrus. CCEPs were recorded in 3-21 electrodes per patient. CCEPs occurred at or around the particular electrodes in the posterior language area which, when stimulated, produced speech arrest. Similar early and late CCEPs were obtained from the basal temporal area by stimulating the anterior language area (three of three patients). In contrast, stimulation of the adjacent face motor area did not elicit CCEPs in language areas but rather in the postcentral gyrus. Stimulation of the posterior language area produced CCEPs in the anterior language (three of four patients) as well as in the basal temporal area (one of two patients). These CCEPs were less well defined. These findings suggest that perisylvian and extrasylvian language areas participate in the language system as components of a network by means of feed-forward and feed-back projections. Different from the classical Wernicke-Geschwind model, the present study revealed a bidirectional connection between Broca's and Wernicke's areas probably through the arcuate fasciculus and/or the cortico-subcortico-cortical pathway. CCEPs were recorded from a larger area than the posterior language area identified by electrical stimulation. This suggests the existence of a rather broad neuronal network surrounding the previously recognized core region of this area.
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            Application of Graph Theory for Identifying Connectivity Patterns in Human Brain Networks: A Systematic Review

            Background: Analysis of the human connectome using functional magnetic resonance imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to discover the neural underpinnings of human cognition and neurological disorders. In general, brain connectivity patterns from fMRI data are classified as statistical dependencies (functional connectivity) or causal interactions (effective connectivity) among various neural units. Computational methods, especially graph theory-based methods, have recently played a significant role in understanding brain connectivity architecture. Objectives: Thanks to the emergence of graph theoretical analysis, the main purpose of the current paper is to systematically review how brain properties can emerge through the interactions of distinct neuronal units in various cognitive and neurological applications using fMRI. Moreover, this article provides an overview of the existing functional and effective connectivity methods used to construct the brain network, along with their advantages and pitfalls. Methods: In this systematic review, the databases Science Direct, Scopus, arXiv, Google Scholar, IEEE Xplore, PsycINFO, PubMed, and SpringerLink are employed for exploring the evolution of computational methods in human brain connectivity from 1990 to the present, focusing on graph theory. The Cochrane Collaboration's tool was used to assess the risk of bias in individual studies. Results: Our results show that graph theory and its implications in cognitive neuroscience have attracted the attention of researchers since 2009 (as the Human Connectome Project launched), because of their prominent capability in characterizing the behavior of complex brain systems. Although graph theoretical approach can be generally applied to either functional or effective connectivity patterns during rest or task performance, to date, most articles have focused on the resting-state functional connectivity. Conclusions: This review provides an insight into how to utilize graph theoretical measures to make neurobiological inferences regarding the mechanisms underlying human cognition and behavior as well as different brain disorders.
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              The Epidemiology of Global Epilepsy.

              The International League Against Epilepsy defines epilepsy as at least 2 unprovoked seizures more than 24 hours apart. It is a wide-reaching and complex illness affecting more than 70 million people worldwide and can take on a variety of forms, patterns, and severities. Geographic differences in the illness are often related to its etiology. A host of endemic illnesses and parasitic infections can lead to epilepsy syndromes. Management varies by region due to the availability of diagnostic modalities and medications. Treatment gaps in epilepsy care often are related to social and cultural factors that must also be understood.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                10 December 2020
                2020
                : 11
                : 579961
                Affiliations
                [1] 1Neuromedical Control Systems Laboratory, Department of Electrical and Computer Engineering, Institute of Computational Medicine, Johns Hopkins University , Baltimore, MD, United States
                [2] 2Neuromedical Control Systems Laboratory, Department of Biomedical Engineering, Institute of Computational Medicine, Johns Hopkins University , Baltimore, MD, United States
                [3] 3Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Biomedical Engineering, Johns Hopkins University , Baltimore, MD, United States
                [4] 4Cognitive Research, Online Neuroengineering and Electrophysiology Laboratory, Department of Neurology-Epilepsy, Johns Hopkins School of Medicine , Baltimore, MD, United States
                [5] 5Department of Neurology-Epilepsy, Johns Hopkins School of Medicine , Baltimore, MD, United States
                Author notes

                Edited by: Jorge Alvaro Gonzalez-Martinez, University of Pittsburgh, United States

                Reviewed by: Umit Aydin, King's College London, United Kingdom; Rudá Alessi, Faculdade de Medicina do ABC, Brazil

                *Correspondence: Sridevi V. Sarma ssarma2@ 123456jhmi.edu

                This article was submitted to Epilepsy, a section of the journal Frontiers in Neurology

                †These authors share senior authorship

                Article
                10.3389/fneur.2020.579961
                7758451
                33362689
                f5b01166-8cef-47a9-a8d6-b5549b440639
                Copyright © 2020 Kamali, Smith, Hays, Coogan, Crone, Kang and Sarma.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 03 July 2020
                : 12 October 2020
                Page count
                Figures: 10, Tables: 1, Equations: 7, References: 60, Pages: 15, Words: 9276
                Funding
                Funded by: National Institute of Neurological Disorders and Stroke 10.13039/100000065
                Funded by: National Center for Complementary and Integrative Health 10.13039/100008460
                Categories
                Neurology
                Original Research

                Neurology
                epilepsy,cceps,stimulation,spes,seizure
                Neurology
                epilepsy, cceps, stimulation, spes, seizure

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