Improving the resolution of functional brain imaging: analyzing functional data in anatomical space.
The accurate mapping of functional magnetic resonance imaging (fMRI) activations to anatomical structures is critical for fMRI studies of brain organization. In the commonly used functional space analysis method, functional images are realigned to a functional reference image and processed in low-resolution functional space. The average functional activations are then projected into high-resolution anatomical space for visualization. Here, we describe a new technique, anatomical space analysis (ASA), whereby low-resolution functional images are first coregistered and resampled directly into high-resolution anatomical space with all subsequent data processing performed in high-resolution space. A major advantage of ASA is that minor scanner sampling instabilities and small head movements can increase spatial resolution by providing multiple samples of the relationship between functional and anatomical space. Both simulations and analyses of real fMRI data show that ASA improves the precision, objectivity and reproducibility of functional brain mapping.
Kang
Xiaojian
X
Human Cognitive Neurophysiology Lab, VA Research Service, VA-NCHCS, 150 Muir Road, Martinez, CA 94553, USA. xkang@ucdavis.edu
Yund
E William
EW
Herron
Timothy J
TJ
Woods
David L
DL
D001303:Auditory Cortex / Q000033:anatomy & histology* / Q000502:physiology; D001931:Brain Mapping / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015203:Reproducibility of Results