Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Modeling Dynamic Functional Connectivity with Latent Factor Gaussian
  Processes   Dynamic functional connectivity, as measured by the time-varying covariance
of neurological signals, is believed to play an important role in many aspects
of cognition. While many methods have been proposed, reliably establishing the
presence and characteristics of brain connectivity is challenging due to the
high dimensionality and noisiness of neuroimaging data. We present a latent
factor Gaussian process model which addresses these challenges by learning a
parsimonious representation of connectivity dynamics. The proposed model
naturally allows for inference and visualization of time-varying connectivity.
As an illustration of the scientific utility of the model, application to a
data set of rat local field potential activity recorded during a complex
non-spatial memory task provides evidence of stimuli differentiation.

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The categories of this paper are: hep-ph
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
19
The categories of this paper are: eess
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
1
The categories of this paper are: cs
22
The categories of this paper are: chao-dyn
27
The categories of this paper are: comp-gas