Literature DB >> 17295624

Cortical activation mapping of epileptiform activity derived from interictal ECoG spikes.

Yuan Lai1, Wim van Drongelen, Kurt Hecox, David Frim, Michael Kohrman, Bin He.   

Abstract

PURPOSE: To develop and evaluate a new cortical activation mapping (CAM) method to obtain the neuronal activation sequences from the cortical potential distributions.
METHODS: Interictal electrocorticogram (ECoG) recordings were analyzed for eight pediatric epilepsy patients to find the cortical activation maps, which were compared with the patients' seizure-onset zones identified from ictal ECoG recordings. Various relations between the local activation time and cortical potential were assumed. The most effective relation was determined by accessing their capability to predict the seizure-onset zone. Computer simulations using a moving dipole source model were also conducted to test the present approach in imaging the propagated cortical activity.
RESULTS: In both clinical data analysis and computer simulations, the maximal amplitude proved to be the most effective criterion with which to determine the local cortical activation time. The present method successfully predicted the seizure-onset zone in seven of eight patients by the CAM analysis of ECoG-recorded interictal spikes (IISs). For patients with multiple seizure foci, each focus can be revealed by analyzing IISs with different spatial patterns.
CONCLUSIONS: The time difference between spike peaks of the interictal events in the leading channel and other channels can be effectively defined as the local cortical activation time. The cortical activation mapping method based on this time latency can be used to predict the seizure-onset zones, suggesting that the present CAM method is useful to assist the presurgical evaluation for the epilepsy patients.

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Year:  2007        PMID: 17295624     DOI: 10.1111/j.1528-1167.2006.00936.x

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  9 in total

1.  Comparison of five directed graph measures for identification of leading interictal epileptic regions.

Authors:  L Amini; C Jutten; S Achard; O David; P Kahane; L Vercueil; L Minotti; G A Hossein-Zadeh; H Soltanian-Zadeh
Journal:  Physiol Meas       Date:  2010-10-15       Impact factor: 2.833

2.  Noninvasive cortical imaging of epileptiform activities from interictal spikes in pediatric patients.

Authors:  Yuan Lai; Xin Zhang; Wim van Drongelen; Michael Korhman; Kurt Hecox; Ying Ni; Bin He
Journal:  Neuroimage       Date:  2010-07-17       Impact factor: 6.556

3.  Dynamic imaging of seizure activity in pediatric epilepsy patients.

Authors:  Yunfeng Lu; Lin Yang; Gregory A Worrell; Benjamin Brinkmann; Cindy Nelson; Bin He
Journal:  Clin Neurophysiol       Date:  2012-05-18       Impact factor: 3.708

4.  Source connectivity analysis from MEG and its application to epilepsy source localization.

Authors:  Yakang Dai; Wenbo Zhang; Deanna L Dickens; Bin He
Journal:  Brain Topogr       Date:  2011-11-19       Impact factor: 3.020

5.  Identification of epileptogenic foci from causal analysis of ECoG interictal spike activity.

Authors:  C Wilke; W van Drongelen; M Kohrman; B He
Journal:  Clin Neurophysiol       Date:  2009-07-17       Impact factor: 3.708

6.  Automatic detection of prominent interictal spikes in intracranial EEG: validation of an algorithm and relationsip to the seizure onset zone.

Authors:  Nicolas Gaspard; Rafeed Alkawadri; Pue Farooque; Irina I Goncharova; Hitten P Zaveri
Journal:  Clin Neurophysiol       Date:  2013-11-05       Impact factor: 3.708

7.  Reproducibility of interictal spike propagation in children with refractory epilepsy.

Authors:  Samuel B Tomlinson; Jeremy N Wong; Erin C Conrad; Benjamin C Kennedy; Eric D Marsh
Journal:  Epilepsia       Date:  2019-04-21       Impact factor: 5.864

8.  Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings.

Authors:  Samuel B Tomlinson; Camilo Bermudez; Chiara Conley; Merritt W Brown; Brenda E Porter; Eric D Marsh
Journal:  Front Neurol       Date:  2016-12-19       Impact factor: 4.003

9.  Recurring Functional Interactions Predict Network Architecture of Interictal and Ictal States in Neocortical Epilepsy.

Authors:  Ankit N Khambhati; Danielle S Bassett; Brian S Oommen; Stephanie H Chen; Timothy H Lucas; Kathryn A Davis; Brian Litt
Journal:  eNeuro       Date:  2017-03-08
  9 in total

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