dc.contributor.advisor |
Swann, Nicole |
en_US |
dc.contributor.author |
Leriche, Ryan |
en_US |
dc.date.accessioned |
2020-06-04T21:38:11Z |
|
dc.date.available |
2020-06-04T21:38:11Z |
|
dc.identifier.uri |
https://scholarsbank.uoregon.edu/xmlui/handle/1794/25363 |
|
dc.description |
Project files are comprised of 19 page pdf and presentation recording in mp4 format. |
en_US |
dc.description.abstract |
With no previous signal processing background, I began to study how electrical brain waves vary with movement speed and uncertainty. I learned when fleshing out the details or just seeing the big picture made sense for the techniques I used.
My lab uses scalp-electroencephalography (EEG) to record brain activity. EEG data can be noisy, but there are methods see through this notice. After some pre-processing, I ran an independent component analysis to decompose a complex signal into its sub-signals. I removed the eye movement sub-signals as I just was interested in brain activity. With kurtosis values—the sharpness of a signal—I could remove artifactual trials.
I was uncomfortable using ICA and kurtosis measures without knowing exactly how they worked. Learning every nuance would have halted my analysis progression. So, with a conceptual understanding, I used these tools to generate a cleaner EEG signal.
With a clean signal, I began my time-frequency analysis. This would describe how well a sine wave at a given frequency represents my signal. I could not get a conceptual hold on this topic. After pausing my analysis and taking an online course—at my PI’s suggestion—my progress accelerated.
I now could examine how electrical brain activity changes with movement uncertainty and speed. My analysis suggests that brain activity increases with slower movements; however, now I need to learn how to statistically verify this result. |
|
dc.rights |
Creative Commons BY-NC-ND 4.0-US |
en_US |
dc.subject |
2020 URS Data Stories |
|
dc.title |
Learning to learn: Making sense of electrophysiology data |
en_US |
dc.identifier.orcid |
https://orcid.org/0000-0003-1477-4982 |
|