Multimodal Imaging of Cortical Networks Controlling Lower Limb Locomotion: Towards the Development of Brain-Computer Interfaces
| dc.contributor.advisor | Ronsky, Janet L. | |
| dc.contributor.advisor | Goodyear, Bradley G. | |
| dc.contributor.author | Kline, Adrienne | |
| dc.contributor.committeemember | Forkert, Nils Daniel | |
| dc.contributor.committeemember | Syed, Naweed L. | |
| dc.date | 2018-11 | |
| dc.date.accessioned | 2018-07-12T17:30:00Z | |
| dc.date.available | 2018-07-12T17:30:00Z | |
| dc.date.issued | 2018-07-11 | |
| dc.description.abstract | In 2015 the National Spinal Cord Injury Association of Canada reported that 30,000 Canadians suffer from paralysis in two or more limbs. In many cases this takes away the fundamental ability to walk. Walking, an intricate sensorimotor task, involves the interactions of both dynamic and balancing neurological processes. Brain computer interfaces (BCIs) are attempting to bridge the gap that will allow persons with compromised mobility to interact with the world via control of prosthetic devices that can ‘act’ by using solely neural input (i.e. thoughts). The goal of this thesis was to aid in the development of a BCI for lower limb locomotion by identifying similarities and differences between cortical activity associated with executed and imagined left and right lower limb movements using electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI). Data from 16 participants showed that it was possible to differentiate between right versus left executed and imagined thought processes for lower limb locomotion using solely information from an EEG, and that these patterns of brain activity were generalizable across time points and trials. It was also found, through the use of fMRI, that areas of brain activation in executed and imagined conditions were similar for some areas but showed unique activation areas as well. A novel paradigm to co-register EEG and fMRI data was developed that can easily be utilized in other contexts. Finally, using EEG and fMRI data allowed for an efficient model to use in a machine learning paradigm that successfully predicted left versus right lower limb movement. This research adds to the existing body of knowledge in understanding psychomotor brain activity associated with thought coordination processes involved in the task of walking in normal persons represented by algorithmic patterns. | en_US |
| dc.identifier.citation | Kline, A. (2018). Multimodal Imaging of Cortical Networks Controlling Lower Limb Locomotion: Towards the Development of Brain-Computer Interfaces (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/32360 | en_US |
| dc.identifier.doi | http://dx.doi.org/10.11575/PRISM/32360 | |
| dc.identifier.uri | http://hdl.handle.net/1880/107138 | |
| dc.language.iso | eng | |
| dc.publisher.faculty | Graduate Studies | |
| dc.publisher.faculty | Schulich School of Engineering | |
| dc.publisher.institution | University of Calgary | en |
| dc.publisher.place | Calgary | en |
| dc.rights | University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. | |
| dc.subject | Magnetic resonance imaging (MRI) | |
| dc.subject | Electroencephalography (EEG) | |
| dc.subject | image processing | |
| dc.subject | kinematics | |
| dc.subject.classification | Neuroscience | en_US |
| dc.subject.classification | Physics--Nuclear | en_US |
| dc.subject.classification | Statistics | en_US |
| dc.subject.classification | Artificial Intelligence | en_US |
| dc.subject.classification | Engineering--Biomedical | en_US |
| dc.subject.classification | Engineering--Mechanical | en_US |
| dc.subject.classification | Robotics | en_US |
| dc.title | Multimodal Imaging of Cortical Networks Controlling Lower Limb Locomotion: Towards the Development of Brain-Computer Interfaces | |
| dc.type | doctoral thesis | |
| thesis.degree.discipline | Biomedical Engineering | |
| thesis.degree.grantor | University of Calgary | |
| thesis.degree.name | Doctor of Philosophy (PhD) | |
| ucalgary.item.requestcopy | true |