Graduate Students
Linda Ko
M.A.Sc. Candidate
Clinical Biomedical Engineering
University of Toronto
Advisor: Dr. Tom Chau
E-mail: lindako[at]gmail[dot]com
Education & Training:
Linda Ko graduated with a Bachelor of Science in Computer Engineering and a Bachelor of Science in Psychology from the University of Calgary in 2006. During the course of her undergraduate degrees, she learned about how computers and people “work.” This lead her to become increasingly interested in how technology and engineering principles can be applied to helping people feel and function better, which is one of the aims of biomedical engineering. As part of her undergraduate experience, Linda was involved in researching algorithms and approaches to measuring cerebral blood flow through the use of magnetic resonance imaging, focusing on ischemic stroke diagnosis. For her graduate studies, Linda is currently enrolled in the Master of Health Science in Clinical Biomedical Engineering program at the University of Toronto, and is currently a recipient of an Ontario Graduate Scholarship for 2007-2008.
Research title:
Near-infrared Spectroscopy as an Access Channel: Prefrontal Cortex Inhibition During an Auditory Go-No-Go Task
Research abstract:
The purpose of this project is to explore the potential of near-infrared spectroscopy (NIRS) as an access channel for individuals with severe motor impairments. Examples of such individuals are those with locked-in syndrome, in which the individuals are awake and aware, but have lost all or nearly all voluntary muscle control. Near-infrared spectroscopy is an attractive communications avenue to explore because it is more portable, less artifact-prone, and more cost-effective than some other measures of brain “activity” (for instance, EEG and fMRI). Additionally, NIRS is safe and non-invasive, which increases its appeal as a potential assistive communication device.
When assessing NIRS as an access channel, it is important to be able to establish signals that are reliably detected and where different values in the signal can be used to distinguish between baseline (resting signal values) and activity. Ideally, users of a NIRS assistive device will be given a mental task that is easy to learn and execute that will also evoke signals that can be reliably identified through NIRS. This project focuses on using NIRS to measure brain activity from the prefrontal cortex (the surface of the brain under the forehead area). The prefrontal cortex area is being investigated partly because there is no interference due to hair when using NIRS to measure activity in this region. Furthermore, the prefrontal cortex is associated with cognitive control, which is a useful domain to explore when dealing with assistive communication technologies. More specifically, the prefrontal cortex has been known to demonstrate increased activity during inhibition tasks. Thus, this project will measure prefrontal cortex activity using NIRS during an auditory Go-No-Go task. The first part of the project will test healthy, able-bodied participants to determine the nature of the signals during the Go-No-Go task, and the second part will test a participant with motor impairments. In the study, participants are instructed that whenever they hear a “Go” stimulus (for example, the letters H, T, or Z), they are to make a response by pressing a button. When they hear a “No-Go” stimulus (for example, the letter X), they have to inhibit their response and refrain from pressing the button.
It is hypothesized that an increase in brain activity in the prefrontal cortex during the No-Go inhibition portions of the task should be observable via a peak in decreased in deoxygenated haemoglobin levels in the blood approximately 5 s after stimulus presentation. The delay of the onset of this response after stimulus presentation has important implications for the speed of any future NIRS assistive communication device developed. This study will also attempt to determine whether the controversial fast neuronal response (also known as the event related optical signal) can be detected using NIRS during a Go-No-Go task. If so, the fast response, which occurs on the order of hundreds of milliseconds, can significantly speed up the capabilities of any future NIRS assistive devices.
