The FAST graph: A novel framework for the anatomically-guided visualization and analysis of cortico-cortical evoked potentials

Taylor, Kenneth N. ✉; Joshi, Anand A.; Li, Jian; Gonzalez-Martinez, Jorge A.; Wang, Xiaofeng; Leahy, Richard M.; Nair, Dileep R.; Mosher, John C.

Angol nyelvű Tudományos Szakcikk (Folyóiratcikk)
Megjelent: EPILEPSY RESEARCH 0920-1211 1872-6844 161 Paper: 106264 , 12 p. 2020
  • SJR Scopus - Neurology (clinical): Q2
    Background: Intracerebral electroencephalography (iEEG) using stereoelectroencephalography (SEEG) methodology for epilepsy surgery gives rise to complex data sets. The neurophysiological data obtained during the inpatient period includes categorization of the evoked potentials resulting from direct electrical cortical stimulation such as cortico-cortical evoked potentials (CCEPs). These potentials are recorded by hundreds of contacts, making these waveforms difficult to quickly interpret over such high-density arrays that are organized in three dimensional fashion.New Method: The challenge in analyzing CCEPs data arises not just from the density of the array, but also from the stimulation of a number of different intracerebral sites. A systematic methodology for visualization and analysis of these evoked data is lacking. We describe the process of incorporating anatomical information into the visualizations, which are then compared to more traditional plotting techniques to highlight the usefulness of the new framework.Results: We describe here an innovative framework for sorting, registering, labeling, ordering, and quantifying the functional CCEPs data, using the anatomical labelling of the brain, to provide an informative visualization and summary statistics which we call the "FAST graph" (Functional-Anatomical STacked area graphs). The FAST graph analysis is used to depict the significant CCEPs responses in patient with focal epilepsy.Conclusions: The novel plotting approach shown here allows us to visualize high-density stimulation data in a single summary plot for subsequent detailed analyses. Improving the visual presentation of complex data sets aides in enhancing the clinical utility of the data.
    Hivatkozás stílusok: IEEEACMAPAChicagoHarvardCSLMásolásNyomtatás
    2021-05-10 04:15