[HTML][HTML] ConnSearch: A framework for functional connectivity analysis designed for interpretability and effectiveness at limited sample sizes
Functional connectivity studies increasingly turn to machine learning methods, which
typically involve fitting a connectome-wide classifier, then conducting post hoc interpretation …
typically involve fitting a connectome-wide classifier, then conducting post hoc interpretation …
[HTML][HTML] Identifying sex-specific risk architectures for predicting amyloid deposition using neural networks
In older adults without dementia, White Matter Hyperintensities (WMH) in MRI have been
shown to be highly associated with cerebral amyloid deposition, measured by the Pittsburgh …
shown to be highly associated with cerebral amyloid deposition, measured by the Pittsburgh …
Using graph theory as a common language to combine neural structure and function in models of healthy cognitive performance
MC Litwińczuk, N Muhlert… - Human Brain …, 2023 - Wiley Online Library
Graph theory has been used in cognitive neuroscience to understand how organisational
properties of structural and functional brain networks relate to cognitive function. Graph …
properties of structural and functional brain networks relate to cognitive function. Graph …
[HTML][HTML] Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study
To learn multiscale functional connectivity patterns of the aging brain, we built a brain age
prediction model of functional connectivity measures at seven scales on a large fMRI …
prediction model of functional connectivity measures at seven scales on a large fMRI …
Test–retest reliability and predictive utility of a macroscale principal functional connectivity gradient
AR Knodt, ML Elliott, ET Whitman, A Winn… - Human Brain …, 2023 - Wiley Online Library
Mapping individual differences in brain function has been hampered by poor reliability as
well as limited interpretability. Leveraging patterns of brain‐wide functional connectivity (FC) …
well as limited interpretability. Leveraging patterns of brain‐wide functional connectivity (FC) …
Accounting for temporal variability in functional magnetic resonance imaging improves prediction of intelligence
Neuroimaging‐based prediction methods for intelligence have seen a rapid development.
Among different neuroimaging modalities, prediction using functional connectivity (FC) has …
Among different neuroimaging modalities, prediction using functional connectivity (FC) has …
Machine learning applied to fMRI patterns of brain activation in response to mutilation pictures predicts PTSD symptoms
Background The present study aimed to apply multivariate pattern recognition methods to
predict posttraumatic stress symptoms from whole-brain activation patterns during two …
predict posttraumatic stress symptoms from whole-brain activation patterns during two …
[HTML][HTML] A topography-based predictive framework for naturalistic viewing fMRI
Functional magnetic resonance imaging (fMRI) during naturalistic viewing (NV) provides
exciting opportunities for studying brain functions in more ecologically valid settings …
exciting opportunities for studying brain functions in more ecologically valid settings …
[HTML][HTML] Individual-level functional connectivity predicts cognitive control efficiency
Cognitive control (CC) is essential for problem-solving in everyday life, and CC-related
deficits occur alongside costly and debilitating disorders. The tri-partite model suggests that …
deficits occur alongside costly and debilitating disorders. The tri-partite model suggests that …