Characterizing function–structure relationships in the human visual system with functional MRI and diffusion tensor imaging

A key objective in neuroscience is to improve our understanding of the relationship between brain function and structure. We investigated this in the posterior visual pathways of healthy volunteers by applying functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) with tractography. The optic radiations were segmented using the Probabilistic Index of Connectivity (PICo) tractography algorithm and extracted at several thresholds of connection confidence. The mean fractional anisotropy (FA) of the estimated tracts was found to correlate significantly with fMRI measures of visual cortex activity (induced by a photic stimulation paradigm). The results support the hypothesis that the visual cortical fMRI response is constrained by the external anatomical connections of the subserving optic radiations.

[1]  T Nakada.  [Functionality and connectivity analysis by magnetic resonance imaging]. , 1997, Rinsho shinkeigaku = Clinical neurology.

[2]  P. Basser,et al.  In vivo fiber tractography using DT‐MRI data , 2000, Magnetic resonance in medicine.

[3]  P. Basser,et al.  Water Diffusion Changes in Wallerian Degeneration and Their Dependence on White Matter Architecture , 2000 .

[4]  Susumu Mori,et al.  Fiber tracking: principles and strategies – a technical review , 2002, NMR in biomedicine.

[5]  Gareth J. Barker,et al.  Diffusion tractography based group mapping of major white-matter pathways in the human brain , 2003, NeuroImage.

[6]  M. Jenkinson,et al.  In vivo identification of human cortical areas using high-resolution MRI: An approach to cerebral structure–function correlation , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Karl J. Friston,et al.  Analysis of fMRI Time-Series Revisited , 1995, NeuroImage.

[8]  Neil A. Thacker,et al.  A Framework for a Streamline-Based Probabilistic Index of Connectivity (PICo) Using a Structural Interpretation of Anisotropic Diffusion. , 2002 .

[9]  Robert Costalat,et al.  A Model of the Coupling between Brain Electrical Activity, Metabolism, and Hemodynamics: Application to the Interpretation of Functional Neuroimaging , 2002, NeuroImage.

[10]  Olaf Sporns,et al.  Networks analysis, complexity, and brain function , 2002 .

[11]  P. Basser,et al.  Estimation of the effective self-diffusion tensor from the NMR spin echo. , 1994, Journal of magnetic resonance. Series B.

[12]  Gareth J. Barker,et al.  From diffusion tractography to quantitative white matter tract measures: a reproducibility study , 2003, NeuroImage.

[13]  S C Williams,et al.  Non‐invasive assessment of axonal fiber connectivity in the human brain via diffusion tensor MRI , 1999, Magnetic resonance in medicine.

[14]  Karl J. Friston,et al.  Cerebral Asymmetry and the Effects of Sex and Handedness on Brain Structure: A Voxel-Based Morphometric Analysis of 465 Normal Adult Human Brains , 2001, NeuroImage.

[15]  R E Snyder,et al.  Changes in water diffusion due to Wallerian degeneration in peripheral nerve , 1996, Magnetic resonance in medicine.

[16]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[17]  David H. Miller,et al.  Diffusion tensor imaging can detect and quantify corticospinal tract degeneration after stroke , 2000, Journal of neurology, neurosurgery, and psychiatry.

[18]  Frederik Barkhof,et al.  The functional basis of ocular dominance: functional MRI (fMRI) findings , 1996, Neuroscience Letters.

[19]  E. Bullmore,et al.  The structural and functional mechanisms of motor recovery: complementary use of diffusion tensor and functional magnetic resonance imaging in a traumatic injury of the internal capsule , 1998, Journal of neurology, neurosurgery, and psychiatry.

[20]  Karl J. Friston,et al.  A direct quantitative relationship between the functional properties of human and macaque V5 , 2000, Nature Neuroscience.

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

[22]  G J Barker,et al.  Recovery from optic neuritis is associated with a change in the distribution of cerebral response to visual stimulation: a functional magnetic resonance imaging study , 2000, Journal of neurology, neurosurgery, and psychiatry.

[23]  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.

[24]  P. Basser,et al.  Diffusion tensor MR imaging of the human brain. , 1996, Radiology.

[25]  Guillermo Sapiro,et al.  Creating connected representations of cortical gray matter for functional MRI visualization , 1997, IEEE Transactions on Medical Imaging.

[26]  Christos Davatzikos,et al.  A Framework for Callosal Fiber Distribution Analysis , 2002, NeuroImage.

[27]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[28]  M. Raichle,et al.  Tracking neuronal fiber pathways in the living human brain. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[29]  C. Beaulieu,et al.  The basis of anisotropic water diffusion in the nervous system – a technical review , 2002, NMR in biomedicine.

[30]  R Stokking,et al.  Integration of functional and anatomical brain images. , 1997, Biophysical chemistry.

[31]  P. Lauterbur,et al.  Apparent diffusion tensor measurements in myelin‐deficient rat spinal cords , 2001, Magnetic resonance in medicine.

[32]  M. Horsfield,et al.  Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging , 1999, Magnetic resonance in medicine.

[33]  D B Hackney,et al.  MRI characterization of diffusion coefficients in a rat spinal cord injury model , 1994, Magnetic resonance in medicine.

[34]  D. Tank,et al.  Brain magnetic resonance imaging with contrast dependent on blood oxygenation. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[35]  D. Heeger,et al.  Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1 , 1996, The Journal of Neuroscience.

[36]  Karl J. Friston,et al.  Statistical parametric maps in functional imaging: A general linear approach , 1994 .

[37]  Martin I Sereno,et al.  Brain mapping in animals and humans , 1998, Current Opinion in Neurobiology.

[38]  D. J. Werring,et al.  A Direct Demonstration of both Structure and Function in the Visual System: Combining Diffusion Tensor Imaging with Functional Magnetic Resonance Imaging , 1999, NeuroImage.

[39]  C. Beaulieu,et al.  Determinants of anisotropic water diffusion in nerves , 1994, Magnetic resonance in medicine.

[40]  Lars Olson,et al.  High-Resolution MRI of Intact and Transected Rat Spinal Cord , 1998, Experimental Neurology.

[41]  Gareth J. Barker,et al.  Estimating distributed anatomical connectivity using fast marching methods and diffusion tensor imaging , 2002, IEEE Transactions on Medical Imaging.

[42]  G. Crelier,et al.  Linear coupling between cerebral blood flow and oxygen consumption in activated human cortex. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[43]  Klaas E. Stephan,et al.  The anatomical basis of functional localization in the cortex , 2002, Nature Reviews Neuroscience.

[44]  A L Alexander,et al.  Analytical computation of the eigenvalues and eigenvectors in DT-MRI. , 2001, Journal of magnetic resonance.

[45]  R. Turner,et al.  Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[46]  R. Buxton,et al.  A Model for the Coupling between Cerebral Blood Flow and Oxygen Metabolism during Neural Stimulation , 1997, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[47]  D. Heeger,et al.  In this issue , 2002, Nature Reviews Drug Discovery.

[48]  Antígona Martínez,et al.  Nonlinear temporal dynamics of the cerebral blood flow response , 2001, Human brain mapping.

[49]  Ravi S. Menon,et al.  Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[50]  P. V. van Zijl,et al.  Three‐dimensional tracking of axonal projections in the brain by magnetic resonance imaging , 1999, Annals of neurology.

[51]  R. Passingham,et al.  Initial Demonstration of in Vivo Tracing of Axonal Projections in the Macaque Brain and Comparison with the Human Brain Using Diffusion Tensor Imaging and Fast Marching Tractography , 2002, NeuroImage.