… A standard oddball paradigm, including a 4-min eyes-closed before-task resting state, 3
runs of P300 tasks, and a 4-min eyes-closed after-task resting state was applied to our exper…

… sparse brain network and weakened functional … fMRI to provide reliable evidence for
ADHD brain dysfunction from the perspective of whole organization and to probe large-scale …

… the sparse identification of nonlinear dynamics (SINDy) method, which uses sparse regression
… 1) We wish to operate within the framework of network-based models of large-scale brain …

… Conclusion: Our longitudinal study observed the large-scale brain network reconfiguration
from the dynamic perspective in HUs after prolonged abstinence and improved the …

… Here we comprehensively investigated the extent at which EEG can be used as a tool to
identify large-scale functional networks, which are typically detected on fMRI. Importantly, this is …

… 20) are used when the aim is to identify functional large-scale networks, as in the present
study, while … between deaf and hearing individuals, sparse imaging procedures could be used. …

… is associated with large-scale functional networks, rather than … brain functional connectivity,
which several distinct resting state … In this paper, we apply sparse representation method to …

… brain and is used to assess the function of large-scale brain networks [13]. Converging
evidence … global efficiency, local efficiency, and strength, were also estimated for each sparse …

… resting state, helping reveal how different subregions of large-scale distributed neural networks
… within each community are dense while connections between communities are sparse. …

… problems encountered in large-scale univariate significance tests in graph or network analysis.
… -functional network is relatively sparse. Lp and λ reflect the minimum cost of a node in the …