Noninvasive Electrical Neuroimaging of the Human Brain during Mobile Tasks including Walking and Running
Abstract
Noninvasive brain imaging during mobile activities could have far-reaching scientific, clinical, and technological benefits. Electroencephalography (EEG) is the only mobile noninvasive sensing modality with sufficient temporal resolution to record brain activity on the time scale of natural motor behavior. In the past, EEG has been limited to stationary settings to prevent contamination by electromyographic and movement artifacts. I overcame this limitation by using Independent Component Analysis (ICA) to parse electrocortical processes from artifact-contaminated EEG. Chapters 2 through 4 demonstrate the feasibility of measuring electrocortical activity during human locomotion. In Chapter 2, subjects performed a visual target discrimination and response task while standing, walking, and running. Cognitive event-related cortical potentials during walking and running were nearly identical to those during standing. Chapter 3 provided the first intra-stride measurements of brain activity during walking. Electrocortical sources in the anterior cingulate, posterior parietal, and sensorimotor cortex exhibited significant intra-stride changes in spectral power. A 264-channel electrode array was used in Chapters 2 and 3. By systematically reducing the number of channels used, Chapter 4 demonstrated that 35 channels were sufficient to record the most dominate electrocortical sources. In Chapters 5 and 6, I studied healthy subjects performing isometric and isotonic lower-limb muscle contractions while seated to better understand the relationship between electrocortical dynamics and lower limb muscle activity. This dissertation demonstrated that EEG-based brain imaging in dynamic environments is possible, and it expanded our understanding of cortical involvement in voluntary lower limb movement. It also provided direction for future developments of clinical neuro-monitoring, neuro-assessment, and neuro-rehabilitation technologies.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2012
- Accession Number
- ADA569717
Entities
People
- Joseph T. Gwin
Organizations
- University of Michigan