Literature DB >> 21076325

Interictal EEG discoordination in a rat seizure model.

Samuel A Neymotin1, Heekyung Lee, André A Fenton, William W Lytton.   

Abstract

Cognitive and psychiatric comorbidities are common and clinically important in medial temporal lobe epilepsy and are likely caused by ongoing abnormalities in brain activity. In addition, it is unclear how the dynamics of interictal brain activity in medial temporal lobe epilepsy contributes to the generation of seizures. To investigate these issues, the authors evaluated multisite interictal EEG from a perinatal excitotoxic, hippocampal lesion rat model of medial temporal lobe epilepsy. Sample entropy, an information theoretical measure, demonstrated decreased complexity at different time scales and across all channels in epileptic animals. However, higher-order multiarea measures showed evidence of increased variability in population correlation measures. This apparent paradox was resolved by noting that although the EEG from epileptic animals was overall more stereotyped, there were frequent periods where two or more brain areas "broke off" from ongoing brain activity in epileptic animals, producing decorrelations between areas. These decorrelations were particularly apparent across the midline, suggesting impairments of interhemispheric coordination, a form of interhemispheric diaschisis. Both the observed alterations could contribute to a reduction in brain functionality: an overall reduction in complexity and a failure of interhemispheric brain coordination, suggesting a breakdown in communication between hemispheres. The authors speculate that any tendency of areas to lose communication or break away from coordinated brain activity might predispose to seizures in these areas.

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Year:  2010        PMID: 21076325     DOI: 10.1097/WNP.0b013e3181fe059e

Source DB:  PubMed          Journal:  J Clin Neurophysiol        ISSN: 0736-0258            Impact factor:   2.177


  6 in total

1.  Entropy analysis of tri-axial leg acceleration signal waveforms for measurement of decrease of physiological variability in human gait.

Authors:  Yuki Tochigi; Neil A Segal; Tanawat Vaseenon; Thomas D Brown
Journal:  J Orthop Res       Date:  2011-12-05       Impact factor: 3.494

2.  Tracking recurrence of correlation structure in neuronal recordings.

Authors:  Samuel A Neymotin; Zoe N Talbot; Jeeyune Q Jung; André A Fenton; William W Lytton
Journal:  J Neurosci Methods       Date:  2016-10-13       Impact factor: 2.390

3.  Calcium regulation of HCN channels supports persistent activity in a multiscale model of neocortex.

Authors:  S A Neymotin; R A McDougal; A S Bulanova; M Zeki; P Lakatos; D Terman; M L Hines; W W Lytton
Journal:  Neuroscience       Date:  2015-12-31       Impact factor: 3.590

4.  Computer modeling for pharmacological treatments for dystonia.

Authors:  Samuel A Neymotin; Salvador Dura-Bernal; Herman Moreno; William W Lytton
Journal:  Drug Discov Today Dis Models       Date:  2017-03-31

5.  Emergence of physiological oscillation frequencies in a computer model of neocortex.

Authors:  Samuel A Neymotin; Heekyung Lee; Eunhye Park; André A Fenton; William W Lytton
Journal:  Front Comput Neurosci       Date:  2011-04-19       Impact factor: 2.380

6.  Targeting Neural Synchrony Deficits is Sufficient to Improve Cognition in a Schizophrenia-Related Neurodevelopmental Model.

Authors:  Heekyung Lee; Dino Dvorak; André A Fenton
Journal:  Front Psychiatry       Date:  2014-02-14       Impact factor: 4.157

  6 in total

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