Data-driven approaches to neuroimaging biomarkers for neurological and psychiatric disorders: emerging approaches and examples

VD Calhoun, GD Pearlson, J Sui - Current opinion in neurology, 2021 - journals.lww.com
The search for clinically relevant neuroimaging biomarkers for neurological and psychiatric
disorders is rapidly accelerating. Here, we highlight some of these aspects, provide recent …

A survey of brain functional network extraction methods using fMRI data

Y Du, S Fang, X He, VD Calhoun - Trends in Neurosciences, 2024 - Elsevier
Functional network (FN) analyses play a pivotal role in uncovering insights into brain
function and understanding the pathophysiology of various brain disorders. This paper …

Widespread cortical functional disconnection in gliomas: an individual network mapping approach

E Silvestri, M Moretto, S Facchini… - Brain …, 2022 - academic.oup.com
Assessment of impaired/preserved cortical regions in brain tumours is typically performed
via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI …

A method for estimating and characterizing explicitly nonlinear dynamic functional network connectivity in resting-state fMRI data

SM Motlaghian, V Vahidi, B Baker, A Belger… - Journal of neuroscience …, 2023 - Elsevier
The past 10 years have seen an explosion of approaches that focus on the study of time-
resolved change in functional connectivity (FC). FC characterization among networks at a …

[HTML][HTML] Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI …

X Meng, A Iraji, Z Fu, P Kochunov, A Belger, JM Ford… - NeuroImage: Clinical, 2023 - Elsevier
Brain functional networks identified from resting functional magnetic resonance imaging
(fMRI) data have the potential to reveal biomarkers for brain disorders, but studies of …

A deep learning model for data-driven discovery of functional connectivity

U Mahmood, Z Fu, VD Calhoun, S Plis - Algorithms, 2021 - mdpi.com
Functional connectivity (FC) studies have demonstrated the overarching value of studying
the brain and its disorders through the undirected weighted graph of functional magnetic …

A method to estimate longitudinal change patterns in functional network connectivity of the developing brain relevant to psychiatric problems, cognition, and age

R Saha, DK Saha, MA Rahaman, Z Fu, J Liu… - Brain …, 2024 - liebertpub.com
Aim: To develop an approach to evaluate multiple overlapping brain functional change
patterns (FCPs) in functional network connectivity (FNC) and apply to study developmental …

Two-step clustering-based pipeline for big dynamic functional network connectivity data

MSE Sendi, DH Salat, RL Miller… - Frontiers in …, 2022 - frontiersin.org
Background Dynamic functional network connectivity (dFNC) estimated from resting-state
functional magnetic imaging (rs-fMRI) studies the temporally varying functional integration …

Tri-clustering dynamic functional network connectivity identifies significant schizophrenia effects across multiple states in distinct subgroups of individuals

MA Rahaman, E Damaraju, JA Turner… - Brain …, 2022 - liebertpub.com
Background: Brain imaging data collected from individuals are highly complex with unique
variation; however, such variation is typically ignored in approaches that focus on group …

Multimodel order independent component analysis: a data-driven method for evaluating brain functional network connectivity within and between multiple spatial …

X Meng, A Iraji, Z Fu, P Kochunov, A Belger… - Brain …, 2022 - liebertpub.com
Background: While functional connectivity is widely studied, there has been little work
studying functional connectivity at different spatial scales. Likewise, the relationship of …