Introduction to Spectral Analysis for Sleep Research: From Fourier to Multitaper: Dr. Michael Prerau

Virtual Seminar Series: Computational Approaches to Signal Processing
for Sleep Research
sleepeeg.org/se...
Introduction to Spectral Analysis for Sleep Research
Dr. Michael Prerau
In this seminar, Dr. Prerau will provide an overview of the basics of
spectral analysis, starting with Fourier analysis and leading up to the
understanding of multitaper spectral estimation. We will show how
time-frequency analysis can be used to characterize EEG activity during
sleep and show several applications of this approach to real
experimental data. The goal of this seminar is to provide an
appreciation for the concepts underlying spectral analysis, rather than
in in-depth discussion of the mathematics.
Suggested Reading:
Prerau MJ, Bianchi MT, Brown RE, Ellenbogen JM, Patrick PL. Sleep
Neurophysiological Dynamics Through the Lens of Multitaper Spectral
Analysis. Physiology (Bethesda). 2017 Jan;32(1):60-92. Review. PubMed
PMID: 27927806.
Spectral Scoring Manual:
prerau.bwh.har...
Tutorials:
prerau.bwh.har...
About the Series:
This series is part of the Program in Sleep Epidemiology at Brigham and
Women’s Hospital and organized by the Sleep Neurophysiology Signal
Processing Core, directed by Dr. Michael Prerau. The goal of this
series will be to provide an improved understanding of signal processing
basics and best practices to sleep researchers and clinicians, with a
long term aim of bringing new methods of signal processing to the
regular attention of field. No prior mathematical or signal processing
knowledge is required.
While numerous exciting developments in signal processing and
computational modeling have rapidly been adopted as the standard across
numerous diverse fields, these approaches remain uncommon within the
study of sleep. One of the main reasons for this is that there have been
few resources that cross the divide between the math/engineering
literature and sleep science. This seminar series aims to fill that gap.
These seminars are designed to be accessible to all without the need for
a strong mathematical background. Each talk will have a didactic
component, which will describe the methods or practices in question, and
an application component, which will show ways of applying these
techniques to sleep or related data. By the end of each seminar, you
should understand a new set of concepts and have the ability to think of
ways of applying those concepts to your own research.