Literature DB >> 22389141

Synchrony dynamics across brain structures in limbic epilepsy vary between initiation and termination phases of seizures.

Tiwalade Sobayo1, Ananda S Fine, Elizabeth Gunnar, Christine Kazlauskas, David Nicholls, David J Mogul.   

Abstract

Neuronal populations in the brain achieve levels of synchronous electrophysiological activity during both normal brain function and pathological states such as epileptic seizures. Understanding how the dynamics of neuronal oscillators in the brain evolve from normal to diseased states is a critical component toward decoding such complex behaviors. In this study, we sought to develop a more in-depth understanding of multisite dynamics underlying seizure evolution in limbic epilepsy by analyzing oscillators in recordings of local field potentials from three brain structures (bilateral hippocampi and anteromedial thalamus) in a kainic acid in vivo rat model of temporal lobe epilepsy extracted using the empirical mode decomposition (EMD) technique. EMD provides an adaptive nonlinear decomposition into a set of finite oscillatory components. Oscillator frequencies, power, and phase synchrony were assessed within and between sites as seizures evolved. Consistent patterns of low-frequency (~35 Hz) synchrony occurred transiently during early-stage ictogenesis between thalamus and both hippocampi; in contrast, higher frequency (~120 Hz) synchrony appeared between thalamus and focal hippocampus as seizures naturally terminated. These multi-site synchrony events may provide a key insight into how synchrony disruption via stimulation could be targeted as well as contribute to a better understanding of how brain synchrony evolves in epilepsy.

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Year:  2012        PMID: 22389141     DOI: 10.1109/TBME.2012.2189113

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  9 in total

1.  Using Interictal HFOs to Improve the Identification of Epileptogenic Zones in Preparation for Epilepsy Surgery.

Authors:  Sina Farahmand; Tiwalade Sobayo; David J Mogul
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07

2.  Neural mass models as a tool to investigate neural dynamics during seizures.

Authors:  Tatiana Kameneva; Tianlin Ying; Ben Guo; Dean R Freestone
Journal:  J Comput Neurosci       Date:  2017-01-19       Impact factor: 1.621

3.  Noise-Assisted Multivariate EMD-Based Mean-Phase Coherence Analysis to Evaluate Phase-Synchrony Dynamics in Epilepsy Patients.

Authors:  Sina Farahmand; Tiwalade Sobayo; David J Mogul
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-11-15       Impact factor: 3.802

4.  Should stimulation parameters be individualized to stop seizures: Evidence in support of this approach.

Authors:  Tiwalade Sobayo; David J Mogul
Journal:  Epilepsia       Date:  2015-12-09       Impact factor: 5.864

5.  The Spatiotemporal Dynamics of Phase Synchronization during Epileptogenesis in Amygdala-Kindling Mice.

Authors:  Jia-Jia Li; Yong-Hua Li; Hai-Qing Gong; Pei-Ji Liang; Pu-Ming Zhang; Qin-Chi Lu
Journal:  PLoS One       Date:  2016-04-21       Impact factor: 3.240

6.  What is orgasm? A model of sexual trance and climax via rhythmic entrainment.

Authors:  Adam Safron
Journal:  Socioaffect Neurosci Psychol       Date:  2016-10-25

7.  Interaction between Thalamus and Hippocampus in Termination of Amygdala-Kindled Seizures in Mice.

Authors:  Zhen Zhang; Jia-Jia Li; Qin-Chi Lu; Hai-Qing Gong; Pei-Ji Liang; Pu-Ming Zhang
Journal:  Comput Math Methods Med       Date:  2016-10-17       Impact factor: 2.238

8.  A Computational Model of Deep-Brain Stimulation for Acquired Dystonia in Children.

Authors:  Terence D Sanger
Journal:  Front Comput Neurosci       Date:  2018-09-20       Impact factor: 2.380

9.  Stimulating Solutions for Intractable Epilepsy.

Authors:  Timothy Denison; Mohamad Koubeissi; Esther Krook-Magnuson; David Mogul; Gregory Worrell; Catherine Schevon
Journal:  Epilepsy Curr       Date:  2021-04-30       Impact factor: 7.500

  9 in total

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