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Fractality in the neuron axonal topography of the human brain based on 3-D diffusion MRI


In this work the fractal architecture of the neuron axonal topography of the human brain is evaluated, as derived from 3-D diffusion MRI (dMRI) acquisitions. This is a 3D extension of work performed previously in 2D regions of interest (ROIs), where the fractal dimension of the neuron axonal topography was computed from dMRI data. A group study with 18 subjects is here conducted and the fractal dimensions D f of the entire 3-D volume of the brains is estimated via the box counting, the correlation dimension and the fractal mass dimension methods. The neuron axon data is obtained using tractography algorithms on diffusion tensor imaging of the brain. We find that all three calculations of D f give consistent results across subjects, namely, they demonstrate fractal characteristics in the short and medium length scales: different fractal exponents prevail at different length scales, an indication of multifractality. We surmise that this complexity stems as a collective property emerging when many local brain units, performing different functional tasks and having different local topologies, are recorded together.

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Correspondence to A. Provata.

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Katsaloulis, P., Ghosh, A., Philippe, A. et al. Fractality in the neuron axonal topography of the human brain based on 3-D diffusion MRI. Eur. Phys. J. B 85, 150 (2012).

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  • Statistical and Nonlinear Physics