Download Independent Component Analysis (ICA)

An overview of applications of ICA
to biological data and general data mining,
Computational Neurobiology Laboratory
Salk Institute, La Jolla CA (April, 1999).
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Independent Component Analysis
 Perform “blind separation” of
signals recorded at multiple sensors
Use minimal assumptions about the
characteristics of the signal sources.
Principle: Maximize Information
• Q: How to extract maximum
information from multiple visual
channels?
• A: ICA does this -- it maximizes
joint entropy & minimizes
mutual information between output
channels (Bell & Sejnowski, 1995).
• ICA produces brain-like visual
filters for natural images.
Set of 144 ICA filters
ICA versus PCA
• Independent
Principal Component
Component
Analysis (PCA)
(ICA) finds
finds
directions of maximal
independence
variance
in Gaussian
in non-data
Gaussian data statistics).
(second-order
(higher-order
statistics).
Example: Audio decomposition
Perform ICA
Mic 1
Mic 2
Mic 3
Mic 4
Terry
Te-Won
Play Mixtures
Scott
Tzyy-Ping
Play Components
Electroencephalography (EEG)
Artifacts
Brain
signals
• ICA separates
brain signals from
artifacts.
• Permits study of
brain activity in
noisy conditions.
• Allows monitoring
of multiple brain
processes.
Functional Brain Imaging
• Functional magnetic
resonance imaging (fMRI)
data are noisy and
complex.
ICA Component Types
(b)
(a)
Sustained
task-related
(c)
• ICA identifies concurrent
hemodynamic processes.
• Does not require a priori
knowledge of time courses
or spatial distributions.
Transiently
task-related
(d)
Quasi-periodic
Slowly-varying
(e)
(f)
Abrupt head
movement
Slow head
movement
Activated
Suppressed
Data Mining
• ICA was applied to Armed
Forces Vocation Aptitude
Battery (ASVAB) test
scores and Navy Fire
Control School grades.
• Two ICA components
contributed to final school
grade.
• ICA may suggest more
efficient and balanced
selection criteria.
This presentation by
• Scott Makeig, Naval Health Research Center, San Diego
• Tzyy-Ping Jung, Institute for Neural Computation,
UCSD, La Jolla CA
• Te-Won Lee, Salk Institute, La Jolla CA
• Sigurd Enghoff, Salk Institute
• Terrence J. Sejnowski, Salk Institute & UCSD