Constrain your data: relating detailed animal studies to spatial templates in neuroimaging

Abstract

Event Abstract Back to Event Constrain your data: relating detailed animal studies to spatial templates in neuroimaging Gleb Bezgin1* and Rembrandt Bakker2 1 Baycrest, Rotman Research Institute, Canada 2 Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behavior, Netherlands Techniques such as EEG, fMRI, PET and DTI are widely utilized to extract information on functional and anatomical connectivity in the human brain. For each analyzed brain, these methods provide a complete picture of the measured quantity at a limited resolution. This is in sharp contrast with invasive animal studies, carried out primarily in non-human primates. In particular, the most unambiguous information on long-range interareal connectivity is provided by axonal fibre tract tracing studies. Obtained data are precise up to axonal level, albeit typically apply only to a particular part of the analyzed brain. Hence, linking these two kinds of resources is mutually beneficial. We describe an approach for spatially registering all cortical brain regions from the textual database CoCoMac (K?tter, 2004). Currently, it contains 458 studies, mainly tract tracing experiments, many of which define their own cortical (sub)parcellation. Direct registration to a surface-based Macaque cortex is applied to 9 core parcellations using the tool Caret (Van Essen and Dierker, 2007). The rest of the database is semantically linked to these core parcellations using previously developed algebraic and machine learning techniques (Stephan et al., 2000; Bezgin et al., 2008; Bakker et al., ongoing work). For the translation to the human cortex we rely on Van Essen's landmark-based macaque to human warpings. As a result, one can query CoCoMac for a given spatial coordinate in any of the Caret-supported macaque and human cortical templates. Connectivity was analyzed using multiple graph-theoretical measures to capture global properties of the derived network using the new brain network visualization and analysis tool ConJUNGtion developed on the basis of JUNG software (Madadhain et al., 2005). As a next step, the spatial connectivity maps can be used either as a direct validation of neuroimaging data, or indirectly by constraining generative models of brain activity with a plausible anatomical connectivity assignment. References Bezgin G., Wanke E., Krumnack A., Kötter R. (2008) Deducing logical relationships between spatially registered cortical parcellations under conditions of uncertainty. Neural Networks 21(8): 1132-1145. K?tter R. (2004) Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac database. Neuroinformatics 2(2), 127-44. Madadhain J., Fisher D., Smyth P., White S., Boey Y.B. (2005) Analysis and visualization of network data using JUNG. Journal of Statistical Software, Vol. 10, p. 1--35. Paxinos G., Huang X.-F., Petrides M. and Toga A.W. (2009) The Rhesus Monkey Brain in Stereotaxic Coordinates, 2nd Edition. Amsterdam: Elsevier Science. Stephan K.E., Zilles K., Kötter R. (2000) Coordinate-independent mapping of structural and functional data by objective relational transformation (ORT). Phil. Trans. R. Soc. Lond. B 355, 37-54. Van Essen D. C., Dierker D. L. (2007) Surface-based and probabilistic atlases of primate cerebral cortex. Neuron 56, 209–225. Figure 1 Keywords: digital atlasing Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: Digital atlasing Citation: Bezgin G and Bakker R (2011). Constrain your data: relating detailed animal studies to spatial templates in neuroimaging. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00070 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Gleb Bezgin, Baycrest, Rotman Research Institute, Toronto, Canada, gbezgin@rotman-baycrest.on.ca Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Gleb Bezgin Rembrandt Bakker Google Gleb Bezgin Rembrandt Bakker Google Scholar Gleb Bezgin Rembrandt Bakker PubMed Gleb Bezgin Rembrandt Bakker Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.