Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: methods and promises
The neuroimaging community has witnessed a paradigm shift in biomarker discovery from
using traditional univariate brain mapping approaches to multivariate predictive models …
using traditional univariate brain mapping approaches to multivariate predictive models …
The challenges and prospects of brain-based prediction of behaviour
Relating individual brain patterns to behaviour is fundamental in system neuroscience.
Recently, the predictive modelling approach has become increasingly popular, largely due …
Recently, the predictive modelling approach has become increasingly popular, largely due …
[HTML][HTML] Shared and unique brain network features predict cognitive, personality, and mental health scores in the ABCD study
How individual differences in brain network organization track behavioral variability is a
fundamental question in systems neuroscience. Recent work suggests that resting-state and …
fundamental question in systems neuroscience. Recent work suggests that resting-state and …
Spatial topography of individual-specific cortical networks predicts human cognition, personality, and emotion
Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to
delineate individual-specific brain networks. A major question is whether individual-specific …
delineate individual-specific brain networks. A major question is whether individual-specific …
Global signal regression strengthens association between resting-state functional connectivity and behavior
Global signal regression (GSR) is one of the most debated preprocessing strategies for
resting-state functional MRI. GSR effectively removes global artifacts driven by motion and …
resting-state functional MRI. GSR effectively removes global artifacts driven by motion and …
Machine learning in resting-state fMRI analysis
Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …
[HTML][HTML] Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics
There is significant interest in the development and application of deep neural networks
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …
[HTML][HTML] Beyond fingerprinting: Choosing predictive connectomes over reliable connectomes
ES Finn, MD Rosenberg - NeuroImage, 2021 - Elsevier
Recent years have seen a surge of research on variability in functional brain connectivity
within and between individuals, with encouraging progress toward understanding the …
within and between individuals, with encouraging progress toward understanding the …
[HTML][HTML] One size does not fit all: methodological considerations for brain-based predictive modeling in psychiatry
Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way
across individuals, and no two patients with a shared diagnosis exhibit identical symptom …
across individuals, and no two patients with a shared diagnosis exhibit identical symptom …
[HTML][HTML] Towards clinical applications of movie fMRI
As evidenced by the present special issue, movie fMRI is emerging as a powerful tool for
exploring brain function and characterizing its variation across individuals. Here, we provide …
exploring brain function and characterizing its variation across individuals. Here, we provide …