Author: Rajani Khanal
Khanal, Rajani, 2019 Brain connectivity during different sleep stages using EEG and NIRS, Flinders University, College of Science and Engineering
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Brain connectivity is gaining significant attention at present given its scope to unveil brain mechanisms and functions. Sleep, where brain undergoes cycles of distinct behaviours, is one of the complexities in neuroscience where several brain processes occur together. EEG is a commonly used modality in measuring brain electrophysiological signals and is known for a good temporal resolution. Near Infrared Spectroscopy (NIRS), however, is an emerging modality in neuroscience providing a good deal of information about cerebral hemodynamic with better spatial resolution than EEG. A combination of these two modalities can help reveal underlying neurophysiological and hemodynamic activities in complex brain behaviour such as sleep. The present study aims to measure brain connectivity during whole night sleep based on combined hemodynamic and electrophysiological signals and see if the measure can aid in differentiating sleep stages. In doing so, whole night sleep and NIRS data were obtained form 5 healthy volunteers and two common measures of connectivity: transfer entropy and cross-correlation were applied. The focus of the study is particularly on effective connectivity, in terms of prefrontal hemodynamic, and EEG covering frontal, central and occipital brain regions. Statistical validity and reproducibility of the findings were analysed with ANOVA and permutation test. Connectivity measures revealed causal influence to be directed from prefrontal to posterior brain regions. Also, the highest brain connectivity was found during NREM1 sleep with a fair decrease in the measure as sleep progresses to further stages. Significant difference in connectivity was found in the prefrontal region between wake and NREM1, NMREM2 and REM sleep stages. Hemodynamic changes during the different sleep stages could be better understood with these findings. Our findings suggest that brain connectivity measure using NIRS and EEG carry the potential to aid in sleep staging along with information about hemodynamic changes throughout sleep that can help better understand the regulation and functions of sleep. Nevertheless, further research with similar approaches, could help accurately estimate sleep stage and understand full picture of brain mechanisms for sleep regulation.
Keywords: connectivity, sleep stages, hemodynamic, EEG, NIRS, oxyhemoglobin, de-oxyhemoglobin
Subject: Neuroscience thesis
Thesis type: Masters
Completed: 2019
School: College of Science and Engineering
Supervisor: Sherry Randhawa