Investigation of the Clinical Utility of the Spatio-Spectral Dynamics of Sensorimotor ECoG in Response to Different Somatosensory Stimulation Modalities in Human Subjects

dc.contributor.advisorInce, Nuri F.
dc.contributor.committeeMemberFrancis, Joseph T.
dc.contributor.committeeMemberPellizzer, Guiseppe
dc.contributor.committeeMemberRoh, Jinsook
dc.contributor.committeeMemberPrabhu, Sujit S.
dc.contributor.committeeMemberZhang, Yingchun
dc.creatorAsman, Priscella
dc.creator.orcid0000-0002-0089-4396 2022
dc.description.abstractNeurosurgeons during eloquent brain surgery conduct vital functional mapping to ensure proper brain function. Usually, following the electrical stimulation of the peripheral nerves, visual assessment of the phase reversal of the somatosensory evoked potentials (SSEPs) is employed to delineate the central sulcus (CS). However, proper assessment of the phase reversal in the SSEP waveform is challenging due to the variations in the waveform morphology across subjects and the localized nature of the hand area, which usually requires multiple electrode placements or electrode relocation. On the other side, Direct Cortical Electrical Stimulation (DCS) is also used in clinical practice for cortical mapping, which might elicit seizures. We hypothesized that automated mapping of the sensorimotor cortex could be achieved with high-density electrocorticogram (ECoG) grids. The recorded neural data interpretation can be achieved with machine learning algorithms. Additionally, we used the unique opportunity to assess sensorimotor rhythms intraoperatively during awake surgery with ECoG. We also investigated power modulations in ECoG sub-bands in response to mechanical tactile stimulation at the periphery during anesthetized (unconscious) and awake(conscious) states. Firstly, we show that by investigating the Spatio-temporal characteristics of the SSEP waveforms through an unsupervised machine learning approach, we can identify sensory and motor areas with high accuracy. Our results suggest that the unsupervised clustering of the SSEP trace based on spectral clustering can delineate the CS automatically with high precision (>90%) without the need for peak and latency interpretation. Secondly, to the best of our knowledge, we characterize a late gamma band modulation in SSEP trace in the somatosensory cortex, which consistently distinguishes the anesthetized state from conscious, awake states in all eight human subjects we studied. Finally, we characterized the modulations in beta and gamma bands in the sensorimotor cortex in response to tactile stimulation in the form of vibration and pressure. We show that induced gamma modulations are highly specific to the somatosensory cortex. More importantly, despite delivering a steady/consistent pressure stimulus to the hand, we observed phasic gamma and beta band modulations somatosensory area. These phasic responses might be critical in designing future neuroprosthetic and restoring sensory function through closed-loop cortical stimulation.
dc.description.departmentBiomedical Engineering, Department of
dc.format.digitalOriginborn digital
dc.identifier.citationPortions of this document appear in: Asman, Priscella, Sujit Prabhu, Dhiego Bastos, Sudhakar Tummala, Shreyas Bhavsar, Thomas Michael McHugh, and Nuri Firat Ince. "Unsupervised machine learning can delineate central sulcus by using the spatiotemporal characteristic of somatosensory evoked potentials." Journal of neural engineering 18, no. 4 (2021): 046038; and in: Asman, Priscella, Tianxiao Jiang, Musa Ozturk, Juan Reyna, and Nuri F. Ince. "A Low-Cost Microcontroller Based Stimulation System to Study Sensory Processing." In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER), pp. 883-886. IEEE, 2019.
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. UH Libraries has secured permission to reproduce any and all previously published materials contained in the work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).
dc.subjectFunctional Mapping
dc.subjectSomatosensory evoked potentials
dc.subjectTactile st
dc.titleInvestigation of the Clinical Utility of the Spatio-Spectral Dynamics of Sensorimotor ECoG in Response to Different Somatosensory Stimulation Modalities in Human Subjects
dc.type.genreThesis College of Engineering Engineering, Department of Engineering of Houston of Philosophy
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