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Transcript
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
Development of morphometric
„in vivo“ techniques
Voxel-Based
Morphometry
volumetric analysis
of Regions of
Interest (ROIs)
Diffusion
Tensor Imaging
Cortical
Thickness
Volumetric analysis
of ROIs/VOIs
Brain developmental trajectories
Lenroot et al., 2007
Volumetric analysis
cons:
• Require a priori assumptions about ROIs
• Detect only gross structural changes in
GM, WM
• Manual segmentation of brain tissue (GrayWhite matter) and definition of ROIs is
time consuming and subject to errors
Voxel-Based Morphometry
• 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
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
SPATIALLY
NORMALISED
IMAGE
GREY MATTER
WHITE MATTER
CSF
VBM Cons
•
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
E.g. Increased gray matter
volume could result from
more folding as well as
thicker gray matter
Cortical Thickness
Changes across the axes of the cortical columns.
It allows not only to determine significant
difference between groups but also to measure this
difference (in mm)
Cortical Thickness
Measures the distance between outer and inner surfaces.
Cortical Thickness
(Fischl and Dale, 2000 )
Complexity of developmental
trajectories throughout the
cerebral cortex
Shaw, P. et al. J. Neurosci. 2008
Improvement in motor skills or
phonological processing results
in thinning or thickening of
dedicated brain regions
Lu, L. et al. Cereb. Cortex 2007
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
Connectivity-based segregation of the human
striatum predicts personality characteristics
Cohen et al. 2008, Nature
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