[HTML][HTML] One size does not fit all: methodological considerations for brain-based predictive modeling in psychiatry

E Dhamala, BTT Yeo, AJ Holmes - Biological Psychiatry, 2023 - Elsevier
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 …

Predicting attention across time and contexts with functional brain connectivity

H Song, MD Rosenberg - Current Opinion in Behavioral Sciences, 2021 - Elsevier
Highlights•Functional connectivity-based models predict individual differences in attentional
abilities.•Time-varying functional connectivity predicts changes in attentional states during …

Sex differences in default mode network connectivity in healthy aging adults

B Ficek-Tani, C Horien, S Ju, W Xu, N Li… - Cerebral …, 2023 - academic.oup.com
Women show an increased lifetime risk of Alzheimer's disease (AD) compared with men.
Characteristic brain connectivity changes, particularly within the default mode network …

[HTML][HTML] Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol

C Horien, S Fontenelle IV, K Joseph, N Powell… - Scientific reports, 2020 - nature.com
Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult
task, as participants tend to move while being scanned. Head motion represents a …

Association of neural reward circuitry function with response to psychotherapy in youths with anxiety disorders

SL Sequeira, JS Silk, CD Ladouceur… - American Journal of …, 2021 - Am Psychiatric Assoc
Objective: Identifying neural correlates of response to psychological treatment may inform
targets for interventions designed to treat psychiatric disorders. This study examined the …

Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder

Y Ju, M Wang, J Liu, B Liu, D Yan, X Lu, J Sun… - Psychological …, 2023 - cambridge.org
BackgroundTreatment non-response and recurrence are the main sources of disease
burden in major depressive disorder (MDD). However, little is known about its …

Interpreting Brain Biomarkers: Challenges and solutions in interpreting machine learning-based predictive neuroimaging

R Jiang, CW Woo, S Qi, J Wu… - IEEE Signal Processing …, 2022 - ieeexplore.ieee.org
Predictive modeling of neuroimaging data (predictive neuroimaging) for evaluating
individual differences in various behavioral phenotypes and clinical outcomes is of growing …

Connectome-based prediction of eating disorder-associated symptomatology

X Chen, D Dong, F Zhou, X Gao, Y Liu… - Psychological …, 2023 - cambridge.org
BackgroundDespite increasing knowledge on the neuroimaging patterns of eating disorder
(ED) symptoms in non-clinical populations, studies using whole-brain machine learning to …

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth

C Horien, AS Greene, X Shen, D Fortes… - Cerebral …, 2023 - academic.oup.com
Difficulty with attention is an important symptom in many conditions in psychiatry, including
neurodiverse conditions such as autism. There is a need to better understand the …

[HTML][HTML] Brain connectivity in major depressive disorder: a precision component of treatment modalities?

A Tura, R Goya-Maldonado - Translational Psychiatry, 2023 - nature.com
Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an
enormous burden on individuals, society, and health care systems. Most patients benefit …