Benchmarking functional connectome-based predictive models for resting-state fMRI
Functional connectomes reveal biomarkers of individual psychological or clinical traits.
However, there is great variability in the analytic pipelines typically used to derive them from …
However, there is great variability in the analytic pipelines typically used to derive them from …
The connectivity domain: Analyzing resting state fMRI data using feature-based data-driven and model-based methods
Spontaneous fluctuations of resting state functional MRI (rsfMRI) have been widely used to
understand the macro-connectome of the human brain. However, these fluctuations are not …
understand the macro-connectome of the human brain. However, these fluctuations are not …
Boost in test–retest reliability in resting state fMRI with predictive modeling
Recent studies found low test–retest reliability in functional magnetic resonance imaging
(fMRI), raising serious concerns among researchers, but these studies mostly focused on the …
(fMRI), raising serious concerns among researchers, but these studies mostly focused on the …
Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction
The specificity and sensitivity of resting state functional MRI (rs-fMRI) measurements depend
on preprocessing choices, such as the parcellation scheme used to define regions of …
on preprocessing choices, such as the parcellation scheme used to define regions of …
Resting-state fMRI in the human connectome project
Resting-state functional magnetic resonance imaging (rfMRI) allows one to study functional
connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI …
connectivity in the brain by acquiring fMRI data while subjects lie inactive in the MRI …
Clinical applications of the functional connectome
Central to the development of clinical applications of functional connectomics for neurology
and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is …
and psychiatry is the discovery and validation of biomarkers. Resting state fMRI (R-fMRI) is …
Connectotyping: model based fingerprinting of the functional connectome
O Miranda-Dominguez, BD Mills, SD Carpenter… - PloS one, 2014 - journals.plos.org
A better characterization of how an individual's brain is functionally organized will likely
bring dramatic advances to many fields of study. Here we show a model-based approach …
bring dramatic advances to many fields of study. Here we show a model-based approach …
[HTML][HTML] Advances in resting state fMRI acquisitions for functional connectomics
Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous
fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously …
fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously …
Regression dynamic causal modeling for resting‐state fMRI
Abstract “Resting‐state” functional magnetic resonance imaging (rs‐fMRI) is widely used to
study brain connectivity. So far, researchers have been restricted to measures of functional …
study brain connectivity. So far, researchers have been restricted to measures of functional …
[HTML][HTML] Representation learning of resting state fMRI with variational autoencoder
Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but
structured patterns. However, the underlying origins are unclear and entangled in rsfMRI …
structured patterns. However, the underlying origins are unclear and entangled in rsfMRI …