Large-scale sparse functional networks from resting state fMRI
Delineation of large-scale functional networks (FNs) from resting state functional MRI data
has become a standard tool to explore the functional brain organization in neuroscience …
has become a standard tool to explore the functional brain organization in neuroscience …
Identification of multi-scale hierarchical brain functional networks using deep matrix factorization
We present a deep semi-nonnegative matrix factorization method for identifying subject-
specific functional networks (FNs) at multiple spatial scales with a hierarchical organization …
specific functional networks (FNs) at multiple spatial scales with a hierarchical organization …
Sparse representation of whole-brain fMRI signals for identification of functional networks
There have been several recent studies that used sparse representation for fMRI signal
analysis and activation detection based on the assumption that each voxel's fMRI signal is …
analysis and activation detection based on the assumption that each voxel's fMRI signal is …
Hierarchical extraction of functional connectivity components in human brain using resting-state fMRI
D Sahoo, TD Satterthwaite… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The study of functional networks of the human brain has been of significant interest in
cognitive neuroscience for over two decades, albeit they are typically extracted at a single …
cognitive neuroscience for over two decades, albeit they are typically extracted at a single …
Graph-theory based parcellation of functional subunits in the brain from resting-state fMRI data
Resting-state fMRI provides a method to examine the functional network of the brain under
spontaneous fluctuations. A number of studies have proposed using resting-state BOLD …
spontaneous fluctuations. A number of studies have proposed using resting-state BOLD …
Collective sparse symmetric non-negative matrix factorization for identifying overlapping communities in resting-state brain functional networks
Resting-state functional magnetic resonance imaging (rs-fMRI) provides a valuable tool to
study spontaneous brain activity. Using rs-fMRI, researchers have extensively studied the …
study spontaneous brain activity. Using rs-fMRI, researchers have extensively studied the …
[HTML][HTML] Identification of functional networks in resting state fMRI data using adaptive sparse representation and affinity propagation clustering
Human brain functional system has been viewed as a complex network. To accurately
characterize this brain network, it is important to estimate the functional connectivity between …
characterize this brain network, it is important to estimate the functional connectivity between …
Identifying sparse connectivity patterns in the brain using resting-state fMRI
The human brain processes information via multiple distributed networks. An accurate
model of the brain's functional connectome is critical for understanding both normal brain …
model of the brain's functional connectome is critical for understanding both normal brain …
[HTML][HTML] Individualized functional networks reconfigure with cognitive state
There is extensive evidence that functional organization of the human brain varies
dynamically as the brain switches between task demands, or cognitive states. This functional …
dynamically as the brain switches between task demands, or cognitive states. This functional …
[HTML][HTML] Identifying basal ganglia divisions in individuals using resting-state functional connectivity MRI
Studies in non-human primates and humans reveal that discrete regions
(henceforth,“divisions”) in the basal ganglia are intricately interconnected with regions in the …
(henceforth,“divisions”) in the basal ganglia are intricately interconnected with regions in the …