Robert Thomas, MD, Chair
This course will introduce attendees to new concepts and methods of sleep state analysis. Starting with a discussion of sleep as a multi-level and multi-component network state (health and disease), presentations will address machine learning approaches including estimating brain age from the sleep EEG; deep analysis of continuous EEG; and sleep state as amplifier and biomarker of Alzheimer’s disease.
Psychologist Level of Content: Advanced
- 1:00 PM – 1:15 PM
- 1:15 PM – 2:00 PM
Sleep as a Network State | Robert Thomas, MD
- 2:00 PM – 2:45 PM
Machine Learning, Sleep and Brain Aging | Michael Westover, MD, PhD
- 2:45 PM – 3:00 PM
- 3:00 PM – 3:45 PM
Using Continuous EEG Analysis for Sleep Physiology and Pathology | Magdy Younes, MD
- 3:45 PM – 4:30 PM
Sleep and Alzheimer’s Disease: Biomarker and Pathology Driver | Andrew Varga, MD, PhD
- 4:30 PM – 5:00 PM
Q&A | Faculty
Upon completion of this activity, participants should be able to:
- Encourage thinking of sleep as a complex networks state in multiple dimensions, including cross-system, spatial and time.
- Learn the basic concepts of machine learning of sleep signals and application to sleep staging and brain aging.
- Understand how deep information can be extracted from continuous EEG signals.
- Recognize the value of sleep as a biomarker state for Alzheimer pathology, and in turn, how sleep pathology may amplify such pathology.
Please note, general registration does not include postgraduate courses.
Learn more about ticketed sessions here.
Basic and Translational Sleep Science Postgraduate Courses Ticketed Sessions