Comparison of different methods of extracting large-scale networks from fMRI data, when the number of repeated measurements/volumes is smaller than the number of network nodes
Cognition is thought to result from interactions within large-scale networks of brain regions. Here,...
In functional magnetic resonance imaging (fMRI), cerebral activity has been increasingly considered ...
<p>We here consider five different costs . The dashed lines represents the cost-specific global effi...
Comparison of different methods of extracting large-scale networks from fMRI data, when the number o...
Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) f...
Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) f...
There is great interest in estimating brain “networks” from FMRI data. This is often attempted by id...
There is a growing interest in the neuroscience community on the advantages of multilayer functional...
The raw fMRI data are too large, over 100G. Therefore, we upload the contrast maps of each individua...
A large-scale brain network can be defined as a set of segregated and integrated regions, that is, d...
MEG and fMRI offer complementary insights into connected human brain function. Evidence from the use...
The dataset includes 15 subjects x 5 steady state conditions. Connectivity data has been computed u...
To spatially cluster resting state-functional magnetic resonance imaging (rs-fMRI) data into potenti...
We develop a method for estimating brain networks from fMRI datasets that have not all been measured...
There is great interest in estimating brain "networks" from FMRI data. This is often attempted by id...
Cognition is thought to result from interactions within large-scale networks of brain regions. Here,...
In functional magnetic resonance imaging (fMRI), cerebral activity has been increasingly considered ...
<p>We here consider five different costs . The dashed lines represents the cost-specific global effi...
Comparison of different methods of extracting large-scale networks from fMRI data, when the number o...
Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) f...
Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) f...
There is great interest in estimating brain “networks” from FMRI data. This is often attempted by id...
There is a growing interest in the neuroscience community on the advantages of multilayer functional...
The raw fMRI data are too large, over 100G. Therefore, we upload the contrast maps of each individua...
A large-scale brain network can be defined as a set of segregated and integrated regions, that is, d...
MEG and fMRI offer complementary insights into connected human brain function. Evidence from the use...
The dataset includes 15 subjects x 5 steady state conditions. Connectivity data has been computed u...
To spatially cluster resting state-functional magnetic resonance imaging (rs-fMRI) data into potenti...
We develop a method for estimating brain networks from fMRI datasets that have not all been measured...
There is great interest in estimating brain "networks" from FMRI data. This is often attempted by id...
Cognition is thought to result from interactions within large-scale networks of brain regions. Here,...
In functional magnetic resonance imaging (fMRI), cerebral activity has been increasingly considered ...
<p>We here consider five different costs . The dashed lines represents the cost-specific global effi...
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