Low-to-High Cross-Frequency Coupling in the Electrical Rhythms as Biomarker for Hyperexcitable Neuroglial Networks of the Brain

Abstract

Publisher's Statement © 2017 IEEE. Personal use of this material is permitted.Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. How to cite TSpace itemsAlways cite the published version, so the author(s) will receive recognition through services that track citation counts, e.g. Scopus. If you need to cite the page number of the author manuscript from TSpace because you cannot access the published version, then cite the TSpace version in addition to the published version using the permanent URI (handle) found on the record page.This article was made openly accessible by U of T Faculty. Please tell us how this access benefits you. Your story matters.0018-9294 (c) 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TBME. Abstract-Objective: One of the features used in the study of hyperexcitablility are high frequency oscillations (HFOs, >80Hz). HFOs have been reported in the electrical rhythms of the brain's neuro-glial networks under physiological and pathological conditions. Cross-frequency coupling (CFC) of HFOs with low frequency rhythms was used to identify pathologic HFOs (pHFOs) (i) in the epileptogenic zones of epileptic patients, and (ii) as a biomarker for the severity of seizure-like events in genetically modified rodent models. We describe a model to replicate reported CFC features extracted from recorded local field potentials (LFPs) representing network properties. Methods: This study deals with a 4-unit neuro-glial cellular network model where each unit incorporates pyramidal cells, interneurons and astrocytes. Three different pathways of hyperexcitability generation -Na + -K + ATPase pump, glial potassium clearance, and potassium afterhyperpolarization channel -were used to generate LFPs. Changes in excitability, average spontaneous electrical discharge (SED) duration and CFC were then measured and analyzed. Results: Each parameter caused an increase in network excitability and the consequent lengthening of the SED duration. Short SEDs showed CFC between HFOs and theta oscillations (4-8 Hz), but in longer SEDs the low frequency changed to the delta range (1-4 Hz). Conclusion: Longer duration SEDs exhibit CFC features similar to those reported by our team. Significance: (i) Identifying the exponential relationship between network excitability and SED durations, (ii) highlighting the importance of glia in hyperexcitability (as they relate to extracellular potassium), and (iii) elucidation of the ...

Multiple Oscillatory Push–Pull Antagonisms Constrain Seizure Propagation

“…It has been suggested that CFC is a key mechanism in maintaining the inhibitionexcitation interaction balance and facilitating cerebral information flow. 36,37 In the classical CFC theory, it has been proposed that pulse of inhibition paced at LFA and targeted at the generators of HFA [38][39][40] : when LFA paced inhibition starts to ramp down, the fastspiking interneurons would start firing. 36 However, CFC is an undirected metric and can only assess the coupling strength, so the directional communication between LFA and HFA is still unknown.…”

“…33 In epilepsy patients, elevated CFC had been found within SOZ during the ictal period but not the nonictal periods, 34,35 probably indicating a hyperexcitable ictal state. 36 However, CFC is an undirected metric and can only assess the coupling strength, so the directional communication between LFA and HFA is still unknown. Here, we utilized CFD 17 to investigate the directional interactions between LFA and HFA in the epileptic network with a specific focus on focal seizure evolution.…”

“…At the cellular level, CFD might be associated with the level of pyramidal cell excitatory drive into the pyramidal-interneuron network. 36,37 In the classical CFC theory, it has been proposed that pulse of inhibition paced at LFA and targeted at the generators of HFA [38][39][40] : when LFA paced inhibition starts to ramp down, the fastspiking interneurons would start firing. In this case, the information flow is from LFA to HFA (positive CFD).…”

“…It has been suggested that CFC is a key mechanism in maintaining the inhibition‐excitation interaction balance and facilitating cerebral information flow . In epilepsy patients, elevated CFC had been found within SOZ during the ictal period but not the nonictal periods, probably indicating a hyperexcitable ictal state . However, CFC is an undirected metric and can only assess the coupling strength, so the directional communication between LFA and HFA is still unknown.…”

“…Here, we utilized CFD to investigate the directional interactions between LFA and HFA in the epileptic network with a specific focus on focal seizure evolution. At the cellular level, CFD might be associated with the level of pyramidal cell excitatory drive into the pyramidal‐interneuron network . In the classical CFC theory, it has been proposed that pulse of inhibition paced at LFA and targeted at the generators of HFA: when LFA paced inhibition starts to ramp down, the fast‐spiking interneurons would start firing.…”