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This article is part of the supplement: Eighteenth Annual Computational Neuroscience Meeting: CNS*2009

Open Access Poster presentation

Directed information structure in inter-regional cortical interactions in a visuomotor tracking task

Joseph T Lizier14*, John-Dylan Haynes23, Jakob Heinzle2 and Mikhail Prokopenko1

Author Affiliations

1 School of Information Technologies, The University of Sydney, NSW 2006, Australia

2 Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin Berlin, Philippstrasse 13, Haus 6, 10115 Berlin, Germany

3 Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstrasse 1A, 04103 Leipzig, Germany

4 School of Computer Science and Engineering, The University of New South Wales, NSW 2052, Australia

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BMC Neuroscience 2009, 10(Suppl 1):P117  doi:10.1186/1471-2202-10-S1-P117


The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/10/S1/P117


Published:13 July 2009

© 2009 Lizier et al; licensee BioMed Central Ltd.

Poster presentation

Distributed computation in the brain is a complex process, involving interactions between many regions in order to achieve a particular task. We present an analysis of functional Magnetic Resonance Imaging (fMRI) measurements of brain activity in 16 localized regions recorded while eight subjects (who gave informed written consent) control a mouse with their right hand to track a moving target on a computer screen. We examine the underlying interaction structure between region pairs and the changes in that structure as a function of the difficulty of the tracking task. Our approach is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only non-linear relationships, but also collective interactions arising from groups of up to seven voxels in each region, and the direction of these relationships.

The statistical significance of the average transfer entropy [1,2] (a directed measure of information transfer) yields a distinct 3-tier directed interaction structure that underlies all task difficulties (see Figure 1). Importantly, this structure connects movement planning to visual and motor control regions. Random-effects statistical parametric maps (SPM) analysis is then used to determine which pairs of regions have a) more in common (using the mutual information), or b) a more pronounced directional relationship (using the transfer entropy) as the task difficulty increases. Most significantly (see Figure 2), we identify an increased coupling between regions involved in movement planning (left SMA and left PMd) and execution (right cerebellum for right hand and right SC for eye movements) with task difficulty. It is likely these methods and extensions to them can be used to identify inter-regional structural changes due to other tasks and coherent information transfer structures in the cortex [3].

thumbnailFigure 1. Directed relationships between selected regions.

thumbnailFigure 2. The changes in the relationships (dashed green line = more in common, directed red line = a less directional relationship) as task difficulty increases.

Acknowledgements

JL thanks CSIRO and the Australian Research Council Complex Open Systems Research Network (COSNet) for their partial support of this work.

References

  1. Schreiber T: Measuring information transfer.

    Phys Rev Lett 2000, 85:461-464. PubMed Abstract | Publisher Full Text OpenURL

  2. Chávez M, Jacques M, Le Van Quyen M: Statistical assessment of nonlinear causality: application to epileptic EEG signals.

    J Neuroscience Methods 2003, 124:113-128. Publisher Full Text OpenURL

  3. Lizier JT, Prokopenko M, Zomaya AY: Local transfer entropy as a spatiotemporal filter for complex systems.

    Phys Rev E 2008, 77:0261101-0261104. Publisher Full Text OpenURL