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Diffusion tensor imaging detects early cerebral cortex abnormalities in neuronal architecture induced by bilateral neonatal enucleation: an experimental model in the ferret.

Frontiers in systems neuroscience | 2010

Diffusion tensor imaging (DTI) is a technique that non-invasively provides quantitative measures of water translational diffusion, including fractional anisotropy (FA), that are sensitive to the shape and orientation of cellular elements, such as axons, dendrites and cell somas. For several neurodevelopmental disorders, histopathological investigations have identified abnormalities in the architecture of pyramidal neurons at early stages of cerebral cortex development. To assess the potential capability of DTI to detect neuromorphological abnormalities within the developing cerebral cortex, we compare changes in cortical FA with changes in neuronal architecture and connectivity induced by bilateral enucleation at postnatal day 7 (BEP7) in ferrets. We show here that the visual callosal pattern in BEP7 ferrets is more irregular and occupies a significantly greater cortical area compared to controls at adulthood. To determine whether development of the cerebral cortex is altered in BEP7 ferrets in a manner detectable by DTI, cortical FA was compared in control and BEP7 animals on postnatal day 31. Visual cortex, but not rostrally adjacent non-visual cortex, exhibits higher FA than control animals, consistent with BEP7 animals possessing axonal and dendritic arbors of reduced complexity than age-matched controls. Subsequent to DTI, Golgi-staining and analysis methods were used to identify regions, restricted to visual areas, in which the orientation distribution of neuronal processes is significantly more concentrated than in control ferrets. Together, these findings suggest that DTI can be of utility for detecting abnormalities associated with neurodevelopmental disorders at early stages of cerebral cortical development, and that the neonatally enucleated ferret is a useful animal model system for systematically assessing the potential of this new diagnostic strategy.

Pubmed ID: 21048904 RIS Download

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Associated grants

  • Agency: NCRR NIH HHS, United States
    Id: P51 RR000163
  • Agency: NIAAA NIH HHS, United States
    Id: T32 AA007468
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS070022-01
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS070022
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS070022-02

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Open source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.

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