Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: FMRI data augmentation via synthesis   We present an empirical evaluation of fMRI data augmentation via synthesis.
For synthesis we use generative mod-els trained on real neuroimaging data to
produce novel task-dependent functional brain images. Analyzed generative
mod-els include classic approaches such as the Gaussian mixture model (GMM),
and modern implicit generative models such as the generative adversarial
network (GAN) and the variational auto-encoder (VAE). In particular, the
proposed GAN and VAE models utilize 3-dimensional convolutions, which enables
modeling of high-dimensional brain image tensors with structured spatial
correlations. The synthesized datasets are then used to augment classifiers
designed to predict cognitive and behavioural outcomes. Our results suggest
that the proposed models are able to generate high-quality synthetic brain
images which are diverse and task-dependent. Perhaps most importantly, the
performance improvements of data aug-mentation via synthesis are shown to be
complementary to the choice of the predictive model. Thus, our results suggest
that data augmentation via synthesis is a promising approach to address the
limited availability of fMRI data, and to improve the quality of predictive
fMRI models.

12
The categories of this paper are: nucl-th
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
10
The categories of this paper are: q-bio
34
The categories of this paper are: chem-ph
31
The categories of this paper are: ao-sci
30
The categories of this paper are: q-alg
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys