Paper Info
Title
Identifying group-wise consistent sub-networks via spatial sparse representation of natural stimulus FMRI data
Abstract
Natural stimulus fMRI has been increasingly used in the brain imaging and brain mapping fields thanks to its more realistic stimulation of the brain's perceptive and cognitive systems. However, identifying consistent functional networks across different brains in natural stimulus fMRI data has been challenging due to the intrinsic variability of individual brain's responses and a variety of sources of noises. Inspired by recent promising results of sparse representation of whole-brain fMRI data, in this paper, we present a novel hybrid temporal and spatial sparse representation of whole-brain natural stimulus fMRI data for the inference of common functional networks across fMRI sessions and individual brains. Experimental results on natural stimulus fMRI dataset demonstrated the effectiveness of this framework.
Year
DOI
Venue
2016
10.1109/ISBI.2016.7493211
2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
Keywords
Field
DocType
consistent brain network,natural stimulus,sparse coding,fMRI
Brain mapping,Computer vision,Pattern recognition,Computer science,Neural coding,Inference,Cognitive systems,Sparse approximation,Resting state fMRI,Artificial intelligence,Stimulus (physiology),Neuroimaging
Conference
ISSN
Citations 
PageRank 
1945-7928
1
0.37
References 
Authors
9
7
Name
Order
Citations
PageRank
Cheng Lyu110.37
Xiang Li212615.50
Jinglei Lv320526.70
Xintao Hu411813.53
Junwei Han53501194.57
Lei Quo611.05
Tianming Liu71033112.95