Ge, Tian, Luo, Qiang, Grabenhorst, Fabian, Feng, Jianfeng and Rolls, Edmund T. (2013) Attention-dependent modulation of cortical taste circuits revealed by granger causality with signal-dependent noise. PLoS Computational Biology, 9 (10). . e1003265. doi:10.1371/journal.pcbi.1003265 ISSN 1553-7358.

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Abstract

We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention.

Item Type:	Journal Article
Subjects:	R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Library of Congress Subject Headings (LCSH):	Neurosciences -- Research, Cerebral cortex -- Research
Journal or Publication Title:	PLoS Computational Biology
Publisher:	Public Library of Science
ISSN:	1553-7358
Official Date:	24 October 2013
Dates:	Date Event 24 October 2013 Published
Volume:	9
Number:	10
Page Range:
Article Number:	e1003265
DOI:	10.1371/journal.pcbi.1003265
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)
Date of first compliant deposit:	25 December 2015
Date of first compliant Open Access:	25 December 2015
Funder:	Guo jia zi ran ke xue ji jin wei yuan hui (China) [National Natural Science Foundation of China] (NSFC), China. Jiao yu bu [Ministry of Education], China. Guo jia ke xue ji shu bu [Ministry of Science and Technology] (CMST), Gottlieb Daimler- und Karl Benz-Stiftung, Royal Society (Great Britain). Wolfson Research Merit Award (RSWRMA), Zhongguo ke xue yuan [Chinese Academy of Sciences] (CAS), University of Oxford. McDonnell Centre for Cognitive Neuroscience, Oxford Centre for Computational Neuroscience
Grant number:	No. 11101429, No. 11271121, No. 71171195, 91230201 (NSFC) ; No. 20114307120019 (MOE) ; 2011CB707802 (CMST)

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