Adaptive Kalman filtering for real-time mapping of the visual field. Neuroimage 2012 Feb 15;59(4):3533-47
Date
11/22/2011Pubmed ID
22100663Pubmed Central ID
PMC3862081DOI
10.1016/j.neuroimage.2011.11.003Scopus ID
2-s2.0-84855167460 (requires institutional sign-in at Scopus site) 4 CitationsAbstract
This paper demonstrates the feasibility of real-time mapping of the visual field for clinical applications. Specifically, three aspects of this problem were considered: (1) experimental design, (2) statistical analysis, and (3) display of results. Proper experimental design is essential to achieving a successful outcome, particularly for real-time applications. A random-block experimental design was shown to have less sensitivity to measurement noise, as well as greater robustness to error in modeling of the hemodynamic impulse response function (IRF) and greater flexibility than common alternatives. In addition, random encoding of the visual field allows for the detection of voxels that are responsive to multiple, not necessarily contiguous, regions of the visual field. Due to its recursive nature, the Kalman filter is ideally suited for real-time statistical analysis of visual field mapping data. An important feature of the Kalman filter is that it can be used for nonstationary time series analysis. The capability of the Kalman filter to adapt, in real time, to abrupt changes in the baseline arising from subject motion inside the scanner and other external system disturbances is important for the success of clinical applications. The clinician needs real-time information to evaluate the success or failure of the imaging run and to decide whether to extend, modify, or terminate the run. Accordingly, the analytical software provides real-time displays of (1) brain activation maps for each stimulus segment, (2) voxel-wise spatial tuning profiles, (3) time plots of the variability of response parameters, and (4) time plots of activated volume.
Author List
Ward BD, Janik J, Mazaheri Y, Ma Y, DeYoe EAAuthor
Edgar A. DeYoe PhD Adjunct Professor in the Radiology department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
Brain MappingComputer Systems
Humans
Magnetic Resonance Imaging
Visual Cortex
Visual Fields