Interpreting and validating complexity and causality in lesion-symptom prognoses

ML Seghier, CJ Price - Brain Communications, 2023 - academic.oup.com
This paper considers the steps needed to generate pragmatic and interpretable lesion-
symptom map**s that can be used for clinically reliable prognoses. The novel …

Application of deep learning in fMRI-based human brain parcellation: a review

Y Li, X Chen, Q Ling, Z He, A Liu - Measurement Science and …, 2023 - iopscience.iop.org
Functional magnetic resonance imaging (fMRI)-based human brain parcellation reveals
brain fundamental organizational principles noninvasively, providing prior guidance for …

Lack of reproducibility of resting-state functional MRI findings in migraine with aura

A Hougaard, D Gaist, E Garde, P Iversen… - …, 2023 - journals.sagepub.com
Background Several studies have applied resting-state functional MRI to examine whether
functional brain connectivity is altered in migraine with aura patients. These studies had …

Beyond Increasing Sample Sizes: Optimizing Effect Sizes in Neuroimaging Research on Individual Differences

CG DeYoung, K Hilger, JL Hanson, R Abend… - Journal of Cognitive …, 2025 - direct.mit.edu
Linking neurobiology to relatively stable individual differences in cognition, emotion,
motivation, and behavior can require large sample sizes to yield replicable results. Given the …

[HTML][HTML] Consistent frontal-limbic-occipital connections in distinguishing treatment-resistant and non-treatment-resistant schizophrenia

Y Zhang, S Gao, C Liang, J Bustillo, P Kochunov… - NeuroImage: Clinical, 2025 - Elsevier
Background and hypothesis Treatment-resistant schizophrenia (TR-SZ) and non-treatment-
resistant schizophrenia (NTR-SZ) lack specific biomarkers to distinguish from each other …

A Statistical Characterization of Dynamic Brain Functional Connectivity

WW Chow, AK Seghouane… - Human Brain Map**, 2025 - Wiley Online Library
This study examined the statistical underpinnings of dynamic functional connectivity in
mental disorders, using resting‐state fMRI signals. Notably, there has been an absence of …

Identifying ADHD‐Related Abnormal Functional Connectivity with a Graph Convolutional Neural Network

Y Hu, J Ran, R Qiao, J Xu, C Tan, L Hu… - Neural Plasticity, 2024 - Wiley Online Library
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder
that is characterized by inattention, hyperactivity, and impulsivity. The neural mechanisms …

fMRI-based spatio-temporal parcellations of the human brain

Q Ling, A Liu, Y Li, MJ McKeown… - Current Opinion in …, 2024 - journals.lww.com
While recent methodological advancements have significantly enhanced our grasp of the
brain's spatial and temporal dynamics, challenges persist in advancing fMRI-based spatio …

The elusive metric of lesion load

ML Seghier - Brain Structure and Function, 2023 - Springer
One of the widely used metrics in lesion-symptom map** is lesion load that codes the
amount of damage to a given brain region of interest. Lesion load aims to reduce the …

Hexa-Net framework: A fresh ADHD-specific model for identifying ADHD based on integrating brain atlases

DA Al-Ubaidi, AA Samah, M Jasim - International Conference on …, 2023 - Springer
Abstract Attention Deficit Hyperactivity Disorder (ADHD) is a frequent neurodevelopmental
disorder affecting children and adults, which is routinely diagnosed based on subjective …