Integration of fMRI and probabilistic tractography for cerebral network analysis

We present a data acquisition and analysis methodology for generating anatomical connectivity matrices using fMRI and diffusion MRI tractography. We describe a protocol for distortion-free, high spatial resolution diffusion MRI suitable for probabilistic tractography in the presence of complex fibre architecture and distortion-free, geometrically-matched fMRI. We then demonstrate that probabilistic tractography may be initiated from a set of functionally-defined regions to generate a matrix representation of the anatomical substrate of functional networks

[1]  Karl J. Friston,et al.  Extracting brain connectivity , 2001 .

[2]  John S. Duncan,et al.  Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo , 2003, NeuroImage.

[3]  D. Tuch Q‐ball imaging , 2004, Magnetic resonance in medicine.

[4]  Matthew H. Davis,et al.  Susceptibility-Induced Loss of Signal: Comparing PET and fMRI on a Semantic Task , 2000, NeuroImage.

[5]  V. Wedeen,et al.  Measuring Cortico-Cortical Connectivity Matrices with Diffusion Spectrum Imaging , 2001 .

[6]  J. Lewin Functional MRI: An introduction to methods , 2003 .

[7]  Kalvis M. Jansons,et al.  Persistent angular structure: new insights from diffusion magnetic resonance imaging data , 2003 .

[8]  Timothy Edward John Behrens,et al.  Characterization and propagation of uncertainty in diffusion‐weighted MR imaging , 2003, Magnetic resonance in medicine.

[9]  Kaleem Siddiqi,et al.  Full-brain Q-Ball Imaging in a Clinically Acceptable Time : Application to White Matter Fibre Tractography , .

[10]  R. Bowtell,et al.  Correction of spatial distortion in EPI due to inhomogeneous static magnetic fields using the reversed gradient method , 2004, Journal of magnetic resonance imaging : JMRI.

[11]  James L. McClelland,et al.  No Right to Speak? The Relationship between Object Naming and Semantic Impairment:Neuropsychological Evidence and a Computational Model , 2001, Journal of Cognitive Neuroscience.

[12]  Daniel C. Alexander,et al.  Probabilistic Monte Carlo Based Mapping of Cerebral Connections Utilising Whole-Brain Crossing Fibre Information , 2003, IPMI.

[13]  Daniel C Alexander,et al.  Probabilistic anatomical connectivity derived from the microscopic persistent angular structure of cerebral tissue , 2005, Philosophical Transactions of the Royal Society B: Biological Sciences.

[14]  Geoffrey J M Parker,et al.  A framework for a streamline‐based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements , 2003, Journal of magnetic resonance imaging : JMRI.

[15]  Peter A. Bandettini,et al.  Selection of the optimal pulse sequence for functional MRI , 2001 .

[16]  Timothy Edward John Behrens,et al.  Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging , 2003, Nature Neuroscience.