The goal of this program is development of signal processing methods that will expand the role MEG/EEG functional brain imaging as a clinical tool for diagnosis of brain dysfunction and as a scientific tool for the study of brain development and function. The research program introduces a new approach in which both the measured data and underlying cortical surface are represented using multiresolution basis function expansions. Improved performance is obtained by developing signal processing, source localization, and imaging algorithms that exploit the basis function expansion.
The specific aims of the proposed studies are: 1) To develop basis function expansions that jointly represent the spatio-temporal distribution of brain activity at the sensors and on the cortical surface. Our proposed multiresolution approach employs a parsimonious representation for brain activity at different temporal and spatial scales, a critical property for effective solution of various aspects of the inverse problem. 2) To develop robust signal processing algorithms that exploit the basis function representation to perform detection, localization and monitoring of multiple sources, and imaging of the activity on the cortical surface. The proposed algorithms will have reduced complexity and improved performance relative to existing methods. 3) To characterize the performance of the algorithms developed under Aims 1 and 2 using nonparametric statistical analysis and computer simulation. 4) To obtain human subject pilot data demonstrating the effectiveness of the algorithms developed under Aims 1 and 2. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21EB005473-02
Application #
7230170
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Mclaughlin, Alan Charles
Project Start
2006-03-15
Project End
2009-02-28
Budget Start
2007-03-01
Budget End
2009-02-28
Support Year
2
Fiscal Year
2007
Total Cost
$208,709
Indirect Cost
Name
University of Wisconsin Madison
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
161202122
City
Madison
State
WI
Country
United States
Zip Code
53715
Kundu, Bornali; Chang, Jui-Yang; Postle, Bradley R et al. (2015) Context-specific differences in fronto-parieto-occipital effective connectivity during short-term memory maintenance. Neuroimage 114:320-7
Bolstad, Andrew; Van Veen, Barry D; Nowak, Robert (2011) Causal Network Inference Via Group Sparse Regularization. IEEE Trans Signal Process 59:2628-2641
Limpiti, Tulaya; Van Veen, Barry D; Wakai, Ronald T (2010) A spatiotemporal framework for MEG/EEG evoked response amplitude and latency variability estimation. IEEE Trans Biomed Eng 57:616-25
Cheung, Bing Leung Patrick; Riedner, Brady Alexander; Tononi, Giulio et al. (2010) Estimation of cortical connectivity from EEG using state-space models. IEEE Trans Biomed Eng 57:2122-34
Bolstad, Andrew; Van Veen, Barry; Nowak, Robert (2009) Space-time event sparse penalization for magneto-/electroencephalography. Neuroimage 46:1066-81
Limpiti, Tulaya; Van Veen, Barry D; Attias, Hagai T et al. (2009) A spatiotemporal framework for estimating trial-to-trial amplitude variation in event-related MEG/EEG. IEEE Trans Biomed Eng 56:633-45
Cheung, B L Patrick; Riedner, Brady; Tononi, Giulio et al. (2009) State-space multivariate autoregressive models for estimation of cortical connectivity from EEG. Conf Proc IEEE Eng Med Biol Soc 2009:61-4