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New methods for MEG, EEG and multichannel physiological data analysis and denoising| old_uid | 4119 |
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| title | New methods for MEG, EEG and multichannel physiological data analysis and denoising |
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| start_date | 2008/02/18 |
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| schedule | 16h15 |
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| online | no |
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| summary | The level of noise in physiological recordings such as MEG and EEG (magneto- and encephalography) sets a limit to what can be learned with these techniques. Noise also reduces the feasablity of applications such as brain-machine interfaces, in which select cortical activity is used to control external systems. Progress in noise reduction translates into a cleaner picture of brain processes. I will present three new methods for data analysis that target the three main sources of noise
observed in electrophysiology: environmental noise from power lines and machinery, sensor noise, and physiological noise (e.g. heartbeat or ongoing brain processes). The methods are based on standard signal processing techniques (PCA, subspace projection, and an ICA-related method called DSS) that are combined in new ways to greatly enhance the level of brain signals relative to noise. The methods have so far been applied to EEG, MEG and intrinsic optical imaging data. Time permitting, I'll also discuss the perspective of applying similar
techniques to the joint analysis of databases of stimuli and responses. |
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| responsibles | van Vreeswijk, Hansel |
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