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Abstract
Near infrared spectroscopy (NIRS) is a promising technology for functional brain imaging
which measures hemodynamic signals from the cortex, similar to functional magnetic
resonance imaging (fMRI), but does not require the participant to lie motionless in
a confined space. NIRS can therefore be used for more naturalistic experiments, including
face to face communication, or natural body movements, and is well suited for real-time
applications that may require lengthy training. However, improving signal quality
and reducing noise, especially noise induced by head motion, is challenging, particularly
for real time applications. Here we study the properties of head motion induced noise,
and find that motion noise causes the measured oxygenated and deoxygenated hemoglobin
signals, which are typically strongly negatively correlated, to become more positively
correlated. Next, we develop a method to reduce noise based on the principle that
the concentration changes of oxygenated and deoxygenated hemoglobin should be negatively
correlated. We show that despite its simplicity, this method is effective in reducing
noise and improving signal quality, for both online and offline noise reduction.
Copyright 2009 Elsevier Inc. All rights reserved.