Grouped Cognitive Subtraction Using Intracranial EEGChristopher Richard Conner1, Gang Chen, PhD1, Thomas Pieters1, Nitin Tandon, MD11Houston, TX United States Keywords: cognition, Neuropsychological Testing, language, electroencephalography, electrocorticography
Many studies have explored cognitive processes using invasive electrophysiology. However, no approaches extend this technique to population level analysis.
Here we apply an innovative neuroimaging method to electro-corticographic (ECoG) data for meaningful and statistically valid group analyses.
ECoG data were collected at 1kHz after subdural electrode (SDE) placement in 17 patients, during three language tasks – visually cued naming of nouns, of verbs, and of scrambled images.
ECoG data were spectrally decomposed and power in each band was integrated from stimulus onset to articulation. Activity in each band was transformed into volumetric data using 3D Gaussians around each SDE localized onto the brain surface. Each patient’s data was transformed into standardized image space and grouped analysis was performed using 3D mixed-effects modeling.
Contrasts of nouns and verbs with scrambled images showed significant (p<0.01) increases in gamma (60-120Hz) and decreases in beta (13-30Hz) over IFG, MFG and MTG. When noun and verb generation were contrasted with each other, greater gamma power in IFG, IPL, ITG and posterior MTG were seen during verb generation, while larger gamma responses in fusiform and para-hippocampal gyrii were seen with nouns. Significant differences in activity ranged from 3-40%.
This is a retrospective study.
This method of grouped cognitive subtraction for ECoG data makes accommodation for variation in individual coverage and responses, and corrects for the sparse sampling problem inherent to this methodology.
Neural activity mapped in this way will yield maps of language function that can inform optimal surgical strategies to prevent post-operative dysnomia, and will aid in validating existent theories of language. Project Roles:
C. Conner (), G. Chen (), T. Pieters (), N. Tandon ()