Complexity-modulated tasks elicit differential hemodynamic activations in the primary
motor cortex for upper limb motor representations. However, much is yet to be learned regarding lower limb complexity modulation, as most fNIRS complexity modulation studies focus on the upper limb. It is currently unknown whether hemodynamic activations from single-joint lower limb motor tasks are detectable by fNIRS, and further, if fNIRS can detect differences between activations from simple and complex lower limb motor tasks. An fNIRS study was conducted to investigate the effects of an unpredictable, complex force-tracking task vs. a predictable, simple force-tracking task on hemodynamic activations in the TA motor representation. No significant TA motor cortex activations were found for 4/5 participants, with one participant showing a significant activation in one channel. Lack of activation in the TA motor representation was attributed to the depth of the area within the central sulcus. Significant hemodynamic activations were also found in areas assumed to overly STG/SII, and pre-SMA/SMA. These activations were attributed to sensory integration and motor learning, respectively. An fNIRS processing review was also conducted to inform processing decisions in the first experiment and to further fNIRS usage in our lab. Common techniques were identified as low-pass, band-pass, and high-pass filters, smoothing filters, wavelet filters, and the GLM. More appropriate alternative techniques were provided, including short-separation regression, pre-whitening, and spline interpolation with a Savitsky-Golay filter. Future studies may elucidate the lack of activity in the TA motor representation, and will further basic neuroscience regarding fNIRS. / Thesis / Master of Science in Kinesiology
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/26228 |
| Date | January 2021 |
| Creators | Dans, Patrick W |
| Contributors | Nelson, Aimee J, Kinesiology |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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