The Use of High-Density ECoG for Functional Mapping and Neural Decoding

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dc.contributor.advisorInce, Nuri F.
dc.contributor.committeeMemberZhang, Yingchun
dc.contributor.committeeMemberSheth, Bhavin R.
dc.contributor.committeeMemberFrancis, Joseph T.
dc.contributor.committeeMemberPrabhu, Sujit S.
dc.creatorJiang, Tianxiao
dc.date.accessioned2019-05-23T15:59:37Z
dc.date.createdAugust 2018
dc.date.issued2018-08
dc.date.submittedAugust 2018
dc.date.updated2019-05-23T15:59:37Z
dc.description.abstractFunctional mapping of eloquent cortex during the resective brain surgeries, especially brain tumor surgeries, is a critical procedure for optimizing survival and quality of life. Electrocorticography (ECoG) can map functional areas without delivering electrical current to the cortex by placing electrodes directly onto the cortex. Traditional clinical grid electrodes generally have large inter-electrode distance of 1 cm. The customized high-density grids we designed have 100-200 channels with 3-4 mm spacing. In order to locate the hand area of the motor cortex in patients underwent brain surgery, we recorded ECoG from customized high-density grids while they executed various hand movements during awake surgeries. A dedicated system was designed to perform reliable data acquisitions and online/offline analysis. The hand movements were consistently associated with a wide spread power decrease in the low frequency band (LFB: 8–32 Hz), a more localized power increase in the high frequency band (HFB: 60–280 Hz) and ultra-high frequency band (UFB: 300–800 Hz) within the sensorimotor region. The temporal spatial spectral characteristics of the modulations were fully explored for the study of functional mapping. The newly discovered UFB modulation were proposed as a promising biomarker to complement the traditional HFB based mapping. Common spatial pattern (CSP) algorithm fused with linear discriminant analysis (LDA) was used to distinguish between hand extension and flexion. HFB yielded almost 100% classification accuracy within 150–250 ms after the movement onset. These results suggest that spatial patterns of motor cortex captured with high-density ECoG in HFB can effectively drive a neural prosthetic to perform hand flexion/extension. Isometric hand squeezing was also studied. Strong correlations between the squeezing force and HFB modulations were discovered. However, subband power modulations were discovered to be only related to the movement onset/offset. Our result suggests that holding phase decoding is a big challenge for the future development of neural prosthetics. Lastly, a novel real-time functional mapping algorithm was proposed. The algorithm is based on the co-existence of HFB-ERS and LFB-ERD within functional area. It has been tested to yield a real-time map in 30 seconds. The strong correlation between online and offline maps indicates a great potential of using high-density ECoG for real-time intraoperative functional mapping.
dc.description.departmentBiomedical Engineering, Department of
dc.format.digitalOriginborn digital
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10657/4030
dc.language.isoeng
dc.rightsThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectHigh-density ECoG
dc.subjectFunctional Mapping
dc.subjectNeural Decoding
dc.titleThe Use of High-Density ECoG for Functional Mapping and Neural Decoding
dc.type.dcmiText
dc.type.genreThesis
local.embargo.lift2020-08-01
local.embargo.terms2020-08-01
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentBiomedical Engineering, Department of
thesis.degree.disciplineBiomedical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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