Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review

M Khodatars, A Shoeibi, D Sadeghi… - Computers in biology …, 2021 - Elsevier
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …

Imaging-based parcellations of the human brain

SB Eickhoff, BTT Yeo, S Genon - Nature Reviews Neuroscience, 2018 - nature.com
A defining aspect of brain organization is its spatial heterogeneity, which gives rise to
multiple topographies at different scales. Brain parcellation—defining distinct partitions in …

Standardizing workflows in imaging transcriptomics with the abagen toolbox

RD Markello, A Arnatkeviciute, JB Poline, BD Fulcher… - elife, 2021 - elifesciences.org
Gene expression fundamentally shapes the structural and functional architecture of the
human brain. Open-access transcriptomic datasets like the Allen Human Brain Atlas provide …

Molecular and network-level mechanisms explaining individual differences in autism spectrum disorder

AM Buch, PE Vértes, J Seidlitz, SH Kim… - Nature …, 2023 - nature.com
The mechanisms underlying phenotypic heterogeneity in autism spectrum disorder (ASD)
are not well understood. Using a large neuroimaging dataset, we identified three latent …

Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI

A Schaefer, R Kong, EM Gordon, TO Laumann… - Cerebral …, 2018 - academic.oup.com
A central goal in systems neuroscience is the parcellation of the cerebral cortex into discrete
neurobiological “atoms”. Resting-state functional magnetic resonance imaging (rs-fMRI) …

Explanations based on the missing: Towards contrastive explanations with pertinent negatives

A Dhurandhar, PY Chen, R Luss… - Advances in neural …, 2018 - proceedings.neurips.cc
In this paper we propose a novel method that provides contrastive explanations justifying the
classification of an input by a black box classifier such as a deep neural network. Given an …

Lead-DBS v2: Towards a comprehensive pipeline for deep brain stimulation imaging

A Horn, N Li, TA Dembek, A Kappel, C Boulay, S Ewert… - Neuroimage, 2019 - Elsevier
Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders
and a growing number of other indications are investigated in clinical trials. To ensure …

Disrupted intrinsic functional brain topology in patients with major depressive disorder

H Yang, X Chen, ZB Chen, L Li, XY Li… - Molecular …, 2021 - nature.com
Aberrant topological organization of whole-brain networks has been inconsistently reported
in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes …

MVS-GCN: A prior brain structure learning-guided multi-view graph convolution network for autism spectrum disorder diagnosis

G Wen, P Cao, H Bao, W Yang, T Zheng… - Computers in biology and …, 2022 - Elsevier
Purpose Recently, functional brain networks (FBN) have been used for the classification of
neurological disorders, such as Autism Spectrum Disorders (ASD). Neurological disorder …

Reduced default mode network functional connectivity in patients with recurrent major depressive disorder

CG Yan, X Chen, L Li, FX Castellanos… - Proceedings of the …, 2019 - National Acad Sciences
Major depressive disorder (MDD) is common and disabling, but its neuropathophysiology
remains unclear. Most studies of functional brain networks in MDD have had limited …