2. The structural organization of the Brain Gray matter: nerve cell bodies (neurons), glial cells, capillaries, and short nerve cell extensions (axons and dendrites). Information processing White matter: bundles of myelinated nerve cell axons, which connect various gray matter areas of the brain to each other, and carry nerve impulses between neurons. Information transmission

3. Development of morphometric „in vivo“ techniques volumetric analysis of Regions of Interest (ROIs) Voxel-Based Morphometry Cortical Thickness Diffusion Tensor Imaging

4. Volumetric analysis of ROIs/VOIs Lenroot et al., 2007 Brain developmental trajectories

5. Volumetric analysis cons: Require a priori assumptions about ROIs Detect only gross structural changes in GM, WM Manual segmentation of brain tissue (Gray- White matter) and definition of ROIs is time consuming and subject to errors

6. VBM is a voxel-based comparison of local tissue volumes within or across groups Whole-brain analysis, does not require a priori assumptions about ROIs; unbiased way of localising structural changes Can be automated, requires little user intervention  compare to manual ROI tracing Voxel-Based Morphometry

7. GREY MATTER WHITE MATTER CSF SPATIALLY NORMALISED IMAGE Voxel Based Morphometry Aims to classify image as GM, WM or CSF Two sources of information a) Spatial prior probability maps b) Intensity information in the image itself

9. Comparison of local tissue volumes: false positives due to misregistration of the images Lack of accuracy: differences detected only at macroscopic scale Poor understanding of the nature of GM/WM changing VBM Cons E.g. Increased gray matter volume could result from more folding as well as thicker gray matter

10. Cortical Thickness It allows not only to determine significant difference between groups but also to measure this difference (in mm) Changes across the axes of the cortical columns.

11. Cortical Thickness Measures the distance between outer and inner surfaces.

12. Cortical Thickness (Fischl and Dale, 2000 )

13. Shaw, P. et al. J. Neurosci. 2008 Complexity of developmental trajectories throughout the cerebral cortex Lu, L. et al. Cereb. Cortex 2007 Improvement in motor skills or phonological processing results in thinning or thickening of dedicated brain regions

14. Cortical Thickness cons Uncorrected measurements due to mis-registration of the two surfaces (outer and inner) Possible misclassification of GM/WM tissue (Partial volume effects) due to the low resolution of MRI Cortical thinning could be not entirely due to reduction in size or number of neuronal cell bodies or their synaptic processes, but also in part due to an increase in the myelin coating of fibers (Sowell et al. 2007) i.e. axons look like gray matter until they are myelinated, so measured gray matter decreases are observed in part as a result of myelination

15. Diffusion Tensor Imaging by tracking the motion of water along the white matter fibers, gives a measure of the structural connectivity between brain regions

16. Diffusion Tensor Imaging isotropic anisotropic Shows the path of less resistance of water diffusion. This allows to reconstruct the pathway of the underlying fibre Change in Fractional Anysotropy (FA - directionality of the water) or Mean diffusion (MD) are indicator of funcionally relevant variation in the pathway

17. Diffusion Tensor Imaging Cohen et al. 2008, Nature Connectivity-based segregation of the human striatum predicts personality characteristics

18. DTI cons Due to the low resolution of MRI images, the method is not efficient in region were there is high complexity or fibre crossing Not possible to differentiate anterograde or retrogade connections Inference only at macroscopic level The presence or absence of any pathway should be interpreted with care