MEG and fMRI fusion for non-linear estimation of neural and BOLD signal changes
- 1 The Mind Research Network, Albuquerque, NM, USA
- 2 Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- 3 Computer Science Department, University of New Mexico, Albuquerque, NM, USA
The combined analysis of magnetoencephalography (MEG)/electroencephalography and functional magnetic resonance imaging (fMRI) measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the blood oxygenation level dependent (BOLD) response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater signal-to-noise ratio, that confirms the expectation arising from the nature of the experiment. The highly non-linear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system’s behavior by stabilizing the differential equations system and by requiring fewer computational resources.
Keywords: dynamic Bayesian networks, latent variable inference, multimodal data fusion, particle filtering
Citation: Plis SM, Calhoun VD, Weisend MP, Eichele T and Lane T (2010) MEG and fMRI fusion for non-linear estimation of neural and BOLD signal changes. Front. Neuroinform. 4:114. doi: 10.3389/fninf.2010.00114
Received: 25 February 2010;
Accepted: 26 September 2010;
Published online: 11 November 2010.
Copyright: © 2010 Plis, Calhoun, Weisend, Eichele and Lane. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
*Correspondence: Sergey M. Plis, The Mind Research Network, 1101 Yale Boulevard, NE, Albuquerque, NM 87106, USA. e-mail: firstname.lastname@example.org