Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

MR Arbabshirani, S Plis, J Sui, VD Calhoun - Neuroimage, 2017 - Elsevier
Neuroimaging-based single subject prediction of brain disorders has gained increasing
attention in recent years. Using a variety of neuroimaging modalities such as structural …

Machine learning in major depression: From classification to treatment outcome prediction

S Gao, VD Calhoun, J Sui - CNS neuroscience & therapeutics, 2018 - Wiley Online Library
Aims Major depression disorder (MDD) is the single greatest cause of disability and
morbidity, and affects about 10% of the population worldwide. Currently, there are no …

Resting-state connectivity biomarkers define neurophysiological subtypes of depression

AT Drysdale, L Grosenick, J Downar, K Dunlop… - Nature medicine, 2017 - nature.com
Biomarkers have transformed modern medicine but remain largely elusive in psychiatry,
partly because there is a weak correspondence between diagnostic labels and their …

Evidence for embracing normative modeling

S Rutherford, P Barkema, IF Tso, C Sripada… - Elife, 2023 - elifesciences.org
In this work, we expand the normative model repository introduced in Rutherford et al.,
2022a to include normative models charting lifespan trajectories of structural surface area …

Benchmarking functional connectome-based predictive models for resting-state fMRI

K Dadi, M Rahim, A Abraham, D Chyzhyk, M Milham… - NeuroImage, 2019 - Elsevier
Functional connectomes reveal biomarkers of individual psychological or clinical traits.
However, there is great variability in the analytic pipelines typically used to derive them from …

The relation between statistical power and inference in fMRI

HR Cremers, TD Wager, T Yarkoni - PloS one, 2017 - journals.plos.org
Statistically underpowered studies can result in experimental failure even when all other
experimental considerations have been addressed impeccably. In fMRI the combination of a …

Classification and prediction of brain disorders using functional connectivity: promising but challenging

Y Du, Z Fu, VD Calhoun - Frontiers in neuroscience, 2018 - frontiersin.org
Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …

Alzheimer's disease detection using depthwise separable convolutional neural networks

J Liu, M Li, Y Luo, S Yang, W Li, Y Bi - Computer Methods and Programs in …, 2021 - Elsevier
To diagnose Alzheimer's disease (AD), neuroimaging methods such as magnetic resonance
imaging have been employed. Recent progress in computer vision with deep learning (DL) …

Towards a brain‐based predictome of mental illness

B Rashid, V Calhoun - Human brain mapping, 2020 - Wiley Online Library
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …

[HTML][HTML] From estimating activation locality to predicting disorder: a review of pattern recognition for neuroimaging-based psychiatric diagnostics

T Wolfers, JK Buitelaar, CF Beckmann, B Franke… - Neuroscience & …, 2015 - Elsevier
Psychiatric disorders are increasingly being recognised as having a biological basis, but
their diagnosis is made exclusively behaviourally. A promising approach for …