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Toward a multisubject analysis of neural connectivity
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Oates, Chris J., Costa, Liliana M. and Nichols, Thomas E. (2015) Toward a multisubject analysis of neural connectivity. Neural Computation, 27 (1). pp. 151-170. doi:10.1162/NECO_a_00690 ISSN 0899-7667.
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Official URL: http://dx.doi.org/10.1162/NECO_a_00690
Abstract
Directed acyclic graphs (DAGs) and associated probability models are widely used to model neural connectivity and communication channels. In many experiments, data are collected from multiple subjects whose connectivities may differ but are likely to share many features. In such circumstances it is natural to leverage similarity between subjects to improve statistical efficiency. The first exact algorithm for estimation of multiple related DAGs was recently proposed by Oates et al. 2014; in this letter we present examples and discuss implications of the methodology as applied to the analysis of fMRI data from a multi-subject experiment. Elicitation of tuning parameters requires care and we illustrate how this may proceed retrospectively based on technical replicate data. In addition to joint learning of subject-specific connectivity, we allow for heterogeneous collections of subjects and simultaneously estimate relationships between the subjects themselves. This letter aims to highlight the potential for exact estimation in the multi-subject setting.
| Item Type: | Journal Article | ||||||||
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
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| Journal or Publication Title: | Neural Computation | ||||||||
| Publisher: | MIT Press | ||||||||
| ISSN: | 0899-7667 | ||||||||
| Official Date: | January 2015 | ||||||||
| Dates: |
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| Volume: | 27 | ||||||||
| Number: | 1 | ||||||||
| Page Range: | pp. 151-170 | ||||||||
| DOI: | 10.1162/NECO_a_00690 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access |
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