The two cerebral hemispheres of the brain alternate in dominance with an “ hourly-like” ultradian periodicity and some frequency bands are tightly coupled to the REM-NREM sleep cycle. This is an ongoing project to help elucidate the ultradian rhythm of alternating cerebral hemispheric activity during sleep using whole-head magnetoencephalography (MEG) and electroencephalography (EEG). Four to six hour records of sleep data were collected from four normal healthy subjects using the Elekta Neuromag system with 306 MEG channels and 60 EEG channels collected at 603 Hz that has resulted in a large amount of data to explore and analyze. Much progress has been made to date and we have generated the left minus right (L-R) signals for homologous paired channels across the brain for 6 discrete frequency bands [low-delta (0.1-2 Hz), delta (2-4Hz), theta (4-8 Hz), alpha (8-16 Hz), beta (16-30 Hz, and gamma (30-50 Hz) frequencies].
In addition, the unfiltered signal of 0-80 Hz remains, yielding 7 discrete bands. L-R signals exhibit with the expected ultradian rhythms observed that we demonstrated in one of our earlier studies and that was also found by others. We continue to work on these data sets and much work remains to classify the dynamical patterns and their relationship to the sleep hypnogram. REHS students will use data visualization tools and methods to help identify better workflows and, if needed, write custom code using Matlab and Python to help optimize the workflows. Students will be introduced to the process involved in running jobs on SDSC’s Expanse supercomputer. Students will use Github, Slack, and Google Drive to maintain and track project development and they will be required to submit weekly reports summarizing their progress. REHS Students will gain valuable experience with a wide range of computational science research processes and should be well-prepared to pursue a future in computational science and engineering research.