Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Graph Autoencoders for Embedding Learning in Brain Networks and Major
  Depressive Disorder Identification   Brain functional connectivity (FC) reveals biomarkers for identification of
various neuropsychiatric disorders. Recent application of deep neural networks
(DNNs) to connectome-based classification mostly relies on traditional
convolutional neural networks using input connectivity matrices on a regular
Euclidean grid. We propose a graph deep learning framework to incorporate the
non-Euclidean information about graph structure for classifying functional
magnetic resonance imaging (fMRI)- derived brain networks in major depressive
disorder (MDD). We design a novel graph autoencoder (GAE) architecture based on
the graph convolutional networks (GCNs) to embed the topological structure and
node content of large-sized fMRI networks into low-dimensional latent
representations. In network construction, we employ the Ledoit-Wolf (LDW)
shrinkage method to estimate the high-dimensional FC metrics efficiently from
fMRI data. We consider both supervised and unsupervised approaches for the
graph embedded learning. The learned embeddings are then used as feature inputs
for a deep fully-connected neural network (FCNN) to discriminate MDD from
healthy controls. Evaluated on a resting-state fMRI MDD dataset with 43
subjects, results show that the proposed GAE-FCNN model significantly
outperforms several state-of-the-art DNN methods for brain connectome
classification, achieving accuracy of 72.50% using the LDW-FC metrics as node
features. The graph embeddings of fMRI FC networks learned by the GAE also
reveal apparent group differences between MDD and HC. Our new framework
demonstrates feasibility of learning graph embeddings on brain networks to
provide discriminative information for diagnosis of brain disorders.

9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
24
The categories of this paper are: dg-ga
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat