The structural organization of the Brain Gray matter: nerve cell bodies (neurons), glial cells,...

The structural organizationof 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

Development of morphometric „in vivo“ techniques

volumetric analysis of Regions of Interest (ROIs)

Voxel-Based Morphometry

Cortical Thickness

Diffusion Tensor Imaging

Volumetric analysis of ROIs/VOIs

Lenroot et al., 2007

Brain developmental trajectories

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

• 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

GREY MATTERGREY MATTER WHITE MATTERWHITE MATTER CSF CSF

SPATIALLY SPATIALLY NORMALISED NORMALISED

IMAGE IMAGE

Voxel Based MorphometryAims to classify image as GM, WM or CSF

Two sources of information

a) Spatial prior probability maps

b) Intensity information in the image itself

• 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

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.

Cortical Thickness Measures the distance between outer and inner surfaces.

Cortical Thickness

(Fischl and Dale, 2000 )

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

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

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

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

Diffusion Tensor Imaging

Cohen et al. 2008, Nature

Connectivity-based segregation of the human striatum predicts personality characteristics

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