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Alain de Cheveigne on cleaning up brain data for analysis and decoding

Date: 
Fri, 10/04/2019 - 10:30am - 12:00pm
Location: 
CCRMA Seminar Room
Event Type: 
Hearing Seminar
Brain signals as measured by EEG, MEG or even ECoG are inherently noisy.  Not only are there only a few dozen sensors to measure billions of different neural sources, the electrical environment can change during an experiment. One would like techniques that can pull the signal out of the noise.  This can be done with smart forms of noise control, de-trending and signal averaging.
 
Alain de Cheveigne will be at CCRMA on Friday to discuss a panoply of techniques to enable you to find the signals you care about. This seminar will be of interest to those that work with EEG, as well as (non-stationary) signal processing folks. 
 
Who: Alain de Cheveigne (CNRS in Paris)
What: Cleaning up brain data for analysis and decoding
When: Friday October 4th at 10:30AM
Where: CCRMA Seminar Room
Why:        We all want more signal and less noise
 
EEG signals might be noisy, but not Alain’s work. Come find out more.

Abstract:
Techniques to measure brain activity (EEG, MEG, ECoG, etc.) all share a similar set of issues: high levels of noise, mixing between sources and observations, and limited dimensionality relative to the billions of sources active within the brain.  I will discuss approaches to address these issues. Source to sensor mixing is highly linear, and thus linear analysis methods are prominent, aiming to attempt to reverse the mixing or factor out major sources of noise and artifact. A wide range of techniques is available, including PCA, ICA, joint decorrelation, CCA, and others.  I will discuss my favorite methods, explain how they work and what they can do, and look at how we might overcome present-day limitations, to dig deeper into the haystack in search of the needle.

Bio: Alain de Cheveigné’s initial training was in Maths, Physics and EE.  He has worked on speech signal processing (pitch and spectral estimation), auditory modeling and psychophysics (pitch perception and sound segregation), and more recently, brain data analysis. He recently coordinated the European project COCOHA (cocoha.org) that aimed to develop a brain-controlled hearing aid. He works for CNRS and is affiliated with the Ecole Normale Superieure and University College London.
FREE
Open to the Public
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