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Presentation Abstract Program#/Poster#: 840.04/ZZ56 Presentation Title: What structure underlies the human brain function? Combining human DTI data with axonal tract tracing animal studies. Location:
Hall AC
Presentation time: Wednesday, Nov 16, 2011, 11:00 AM 12:00 PM Authors:
*G. Y. BEZGIN1, E. GIBSON1, R. BAKKER2, A. R. MCINTOSH1; 1Rotman Res. Institute, Baycrest Ctr., Toronto, ON, Canada; 2Donders Institute, UMC Radboud, Nijmegen, Netherlands
Abstract:
Introduction Modern functional neuroimaging studies of the human brain currently attempt to find statistical relationships between voxels or brain regions, and interpret them in the context of underlying brain structure. For example, effective connectivity models often utilize structural connectivity for constraining simulated brain activity. However, our current understanding of anatomical connectivity in the human brain remains limited as DTI, one of the most promising noninvasive techniques to see white matter fiber tracts, 1) can only see bundles of axons, 2) is nondirectional and 3) does not distinguish crossing fibers from connecting fibers. Evidence from invasive animal studies and homologies between human and nonhuman primate brains allowed us to combine human DTI data with evidence derived from primate axonal tract tracing studies into a single structural connectivity model. Methods Axonal tract tracing data from the CoCoMac database (http://cocomac.org) were registered to the human MNI template using the tool Caret (http://www.nitrc.org/projects/caret). The initial connectivity matrix was derived from CoCoMac using algebraic and machine learning techniques. The cortical ROI map, suitable for various primate species (“Regional Map”), was adapted from Kotter & Wanke, (2005). Subsequently, basal ganglia and thalamic (Behrens et al., 2003) ROIs were included. These ROIs were used for seeding the DTI data, and fiber
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tracking was performed using the technique by Zalesky & Fornito (2009). Results and Conclusions The resulting nonsymmetric structural connectivity matrix includes 96 regions in both hemispheres (41+41 cortical regions, 3+3 thalamic subdivisions and 4+4 basal ganglia). The average matrix density is 0.24 (0.34 within each hemisphere and 0.13 between hemispheres). For each matrix entry, the average fiber length and capacity values are specified, which can be used as biologically plausible structural constraints for effective connectivity models. The resulting model takes advantage of both datasets: tracing data provide finedetailed directed axonal connectivity, whereas DTI informs the model about the actual fiber trajectories. References Behrens TEJ, et al. (2003) Noninvasive mapping of connections between human thalamus and cortex using diffusion imaging. Nature Neuroscience, 6: 75057. Kotter R, Wanke E (2005) Mapping brains without coordinates. Philos Trans R Soc Lond B Biol Sci 360: 75166. Zalesky A, Fornito A (2009) A DTIderived measure of corticocortical connectivity. IEEE Trans Med Imaging 28: 102336. Disclosures:
G.Y. Bezgin: None. E. Gibson: None. R. Bakker: None. A.R. McIntosh: None.
Keyword(s):
CONNECTION MODEL DATABASING
Support:
JS McDonnell Foundation 701 800 476 [Authors]. [Abstract Title]. Program No. XXX.XX. 2011 Neuroscience Meeting Planner. Washington, DC: Society for Neuroscience, 2011. Online. 2011 Copyright by the Society for Neuroscience all rights reserved. Permission to republish any abstract or part of any abstract in any form must be obtained in writing by SfN office prior to publication.
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