Linking interindividual variability in brain structure to behaviour

S Genon, SB Eickhoff, S Kharabian - Nature Reviews Neuroscience, 2022 - nature.com
What are the brain structural correlates of interindividual differences in behaviour? More
than a decade ago, advances in structural MRI opened promising new avenues to address …

[HTML][HTML] Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

F Zhang, A Daducci, Y He, S Schiavi, C Seguin… - Neuroimage, 2022 - Elsevier
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging
technique that enables in vivo reconstruction of the brain's white matter connections at …

Trusted multi-view classification with dynamic evidential fusion

Z Han, C Zhang, H Fu, JT Zhou - IEEE transactions on pattern …, 2022 - ieeexplore.ieee.org
Existing multi-view classification algorithms focus on promoting accuracy by exploiting
different views, typically integrating them into common representations for follow-up tasks …

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 …

Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: methods and promises

J Sui, R Jiang, J Bustillo, V Calhoun - Biological psychiatry, 2020 - Elsevier
The neuroimaging community has witnessed a paradigm shift in biomarker discovery from
using traditional univariate brain mapping approaches to multivariate predictive models …

A technical review of canonical correlation analysis for neuroscience applications

X Zhuang, Z Yang, D Cordes - Human brain mapping, 2020 - Wiley Online Library
Collecting comprehensive data sets of the same subject has become a standard in
neuroscience research and uncovering multivariate relationships among collected data sets …

[HTML][HTML] Cognitive dysfunction in schizophrenia: an expert group paper on the current state of the art

PD Harvey, M Bosia, R Cavallaro, OD Howes… - Schizophrenia Research …, 2022 - Elsevier
Cognitive impairment in schizophrenia represents one of the main obstacles to clinical and
functional recovery. This expert group paper brings together experts in schizophrenia …

[HTML][HTML] Deep neural networks in psychiatry

D Durstewitz, G Koppe, A Meyer-Lindenberg - Molecular psychiatry, 2019 - nature.com
Abstract Machine and deep learning methods, today's core of artificial intelligence, have
been applied with increasing success and impact in many commercial and research …

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] Discriminating schizophrenia using recurrent neural network applied on time courses of multi-site FMRI data

W Yan, V Calhoun, M Song, Y Cui, H Yan, S Liu… - …, 2019 - thelancet.com
Background Current fMRI-based classification approaches mostly use functional
connectivity or spatial maps as input, instead of exploring the dynamic time courses directly …