Estimating cortical feature maps with dependent gaussian processes

Hughes, Nicholas J. and Goodhill, Geoffrey J. (2016) Estimating cortical feature maps with dependent gaussian processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, PP 99: . doi:10.1109/TPAMI.2016.2624295


Author Hughes, Nicholas J.
Goodhill, Geoffrey J.
Title Estimating cortical feature maps with dependent gaussian processes
Journal name IEEE Transactions on Pattern Analysis and Machine Intelligence   Check publisher's open access policy
ISSN 0162-8828
1939-3539
Publication date 2016-11-02
Sub-type Article (original research)
DOI 10.1109/TPAMI.2016.2624295
Open Access Status Not yet assessed
Volume PP
Issue 99
Total pages 11
Place of publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Collection year 2017
Language eng
Abstract A striking example of brain organisation is the stereotyped arrangement of cell preferences in the visual cortex for edges of particular orientations in the visual image. These “orientation preference maps” appear to have remarkably consistent statistical properties across many species. However fine scale analysis of these properties requires the accurate reconstruction of maps from imaging data which is highly noisy. A new approach for solving this reconstruction problem is to use Bayesian Gaussian process methods, which produce more accurate results than classical techniques. However, so far this work has not considered the fact that maps for several other features of visual input coexist with the orientation preference map and that these maps have mutually dependent spatial arrangements. Here we extend the Gaussian process framework to the multiple output case, so that we can consider multiple maps simultaneously. We demonstrate that this improves reconstruction of multiple maps compared to both classical techniques and the single output approach, can encode the empirically observed relationships, and is easily extendible. This provides the first principled approach for studying the spatial relationships between feature maps in visual cortex.
Keyword Gaussian processes
Multitask learning
Neuroimaging
Visual cortical maps
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Brain Institute Publications
 
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Created: Wed, 01 Mar 2017, 12:25:20 EST by Kirstie Asmussen on behalf of School of Music