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 map** approaches to multivariate predictive models …
using traditional univariate brain map** approaches to multivariate predictive models …
Towards a brain‐based predictome of mental illness
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …
recent years and have deepened our understanding of both cognitively healthy and …
Tools of the trade: estimating time-varying connectivity patterns from fMRI data
Given the dynamic nature of the brain, there has always been a motivation to move beyond
'static'functional connectivity, which characterizes functional interactions over an extended …
'static'functional connectivity, which characterizes functional interactions over an extended …
Derivation and utility of schizophrenia polygenic risk associated multimodal MRI frontotemporal network
Schizophrenia is a highly heritable psychiatric disorder characterized by widespread
functional and structural brain abnormalities. However, previous association studies …
functional and structural brain abnormalities. However, previous association studies …
Common and unique multimodal covarying patterns in autism spectrum disorder subtypes
Background The heterogeneity inherent in autism spectrum disorder (ASD) presents a
substantial challenge to diagnosis and precision treatment. Heterogeneity across biological …
substantial challenge to diagnosis and precision treatment. Heterogeneity across biological …
Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup
Multi‐institutional brain imaging studies have emerged to resolve conflicting results among
individual studies. However, adjusting multiple variables at the technical and cohort levels is …
individual studies. However, adjusting multiple variables at the technical and cohort levels is …
SMART (splitting-merging assisted reliable) Independent Component Analysis for Extracting Accurate Brain Functional Networks
Functional networks (FNs) hold significant promise in understanding brain function.
Independent component analysis (ICA) has been applied in estimating FNs from functional …
Independent component analysis (ICA) has been applied in estimating FNs from functional …
HybraPD atlas: Towards precise subcortical nuclei segmentation using multimodality medical images in patients with Parkinson disease
Human brain atlases are essential for research and surgical treatment of Parkinson's
disease (PD). For example, deep brain stimulation for PD often requires human brain …
disease (PD). For example, deep brain stimulation for PD often requires human brain …
Three‐way parallel group independent component analysis: Fusion of spatial and spatiotemporal magnetic resonance imaging data
Advances in imaging acquisition techniques allow multiple imaging modalities to be
collected from the same subject. Each individual modality offers limited yet unique views of …
collected from the same subject. Each individual modality offers limited yet unique views of …
Data-driven multimodal fusion: approaches and applications in psychiatric research
In the era of big data, where vast amounts of information are being generated and collected
at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal …
at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal …