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Contribution of Structural Brain Imaging to Our Understanding of the Cortical Development Process
However, 3D stereotactic approaches such as VBM are based on Figure 3: 3D Cortical Reconstructions
Euclidian distances. As a result, stererotactic methods consider the two
banks of the sylvian fissure as nearby (and thus highly connected)
Raw images White matter White surface Pial surface Cortical mesh model
cortical regions, whereas these two cortical areas are separated by the
entire extent of the insular cortex, are connected by long-distance axons
and encode for completely different functional processes. To overcome
such issues, a variety of algorithms have been developed to obtain
accurate 3D representations of the cortical sheet.
matter (basal ganglia) is often automatically excluded using atlas-based
Cortical thickness Gyrification
masking, and constraints on the planar structure of the cortical sheet
are typically used to include buried sulci (see Figure 3). Nowadays,
completely automated methods providing precise cortical surface
models are freely available through various platforms (e.g. FreeSurfer,
BrainVoyager, BrainVisa). Point-by-point comparisons between the
cortical surface of different participants are achieved through optimal
alignment of sulcal patterns.
Aside from being the starting point to
Vertex-wise statistical analyses
measure cortical thickness of folding, 3D mesh models and precise
registration anchored on the main sulci are also increasingly used in
functional neuroimaging studies.
Cortical thickness is computed at each vertex as the distance between
the white–grey and CSF–grey matter interfaces.
With thousands of The upper row details the successive processes used by FreeSurfer software
measurements over the hemisphere, the cortical thickness technique
(www.surfer.nmr.mgh.harvard.edu) to create 3D cortical mesh models. After intensity
correction and skull stripping procedure, a unitary binary white-matter volume is created for
represents the most exquisite spatial resolution available to date in each hemisphere, which serves as a starting point to tessellate the initial white surface. The
structural neuroimaging and has thus received increasing interest.
arrangement of the white surface is then optimised to accurately follow the grey–white-matter
interface. Finally, the pial surface is computed by deforming the white surface towards the grey
Similar to volumetric observations by Giedd et al.,
large-scale cortical matter–cerebrospinal fluid (CSF) interface. The resulting cortical mesh models typically
thickness studies conducted with healthy participants have reported a
encompass 80,000–150,000 vertices for each hemisphere. On the left, cortical thickness values
overlaid with a colour-coded scale on the pial surface are depicted. Alternatively, the 3D mesh
progressive and regressive profile of trajectories in most cortical models can be used to measure cortical folding; an example of local gyrification index overlaid
Indeed, the largest normative cortical thickness study
on the pial surface is shown on the right. For both cortical thickness and local gyrification,
statistical analyses are usually computed at each vertex to quantify the influences of diagnosis,
published to date
revealed that solely cortical regions with simple age, gender and other variables of interest on the cortical structure.
laminar architecture follow linear trajectories. All other cortical regions
demonstrate curvilinear patterns of growth, and the age of attaining the two hemispheres. Being condensed in an average intracranial volume
thickness peak is commonly considered to be an index of cortical of 1,500cm
, human cortical surface is highly folded. Despite the large
development. Primary sensory and motor areas are consistently the first body of literature on the topic, the processes leading to the
to attain their peak, before adjacent secondary cortical areas and before creation of the folds in humans, as well as the functional significance
high-order association areas. While the cellular mechanisms underlying of the number, length, depth and orientation of sulci, remain
the quadratic trajectories of thickness change with age have not yet largely unexplained. The tension-based model of convolutional
been formally verified, there is increasing evidence that the curvilinear development
postulates that strongly interconnected cortical
growths parallel the refining of the neural circuitry that serves cognitive regions are pulled towards one another to result in a compact wiring
acquisitions during the child’s development. In that direction, another of the nervous system. According to this model, disturbed gyrification
study by the same authors reported that children with a superior in the adult human brain reflects an abnormal pattern of connectivity.
intelligence quotient (IQ) showed a particularly plastic cortex with faster Another model proposes that convolutional development is driven by
and more important rates of cortical thickness change with age than mechanical forces intrinsic to the cortex, for instance differential
children with average intelligence. Finally, the utility of cortical thickness proliferative rates between gyri and sulci.
The more recent theory,
as a dynamic measure of cortical maturation is also supported by a the sulcal root hypothesis,
proposes that different recombinations of
growing amount of studies in patients with neurodevelopmental highly stable sulcal subunits can explain inter-individual differences in
conditions, such as attention-deficit–hyperactivity disorder (ADHD),
sulcal patterns. Overall, all of the theories point to early determinants
In particular, children with ADHD of cortical folding and support the view that cortical morphology at
showed a marked delay in cortical maturation. While the sequential any age can represent a window to early brain development.
order of maturing cortical areas were similar in children with ADHD and
in typically developing children, trajectories of cortical changes had an Whereas there is only one definition of cortical thickness, many
average two-year delay in children with ADHD, which was most different methods have been proposed to measure cortical folding.
prominent in the frontal regions.
As discussed by Rubia,
this Fractal dimension condenses information about the frequency and
maturational delay corroborates recent clinical description of ADHD as depth of sulci over the entire brain or in the four main lobes.
an age-inappropriate deficit in attention or self-control. morphometry
is a method that relies on the identification of a set of
sulci and compares some of their features such as sulcal width or
Cortical Folding (Gyrification) depth, position or asymmetry indices. Finally, other approaches
After thickness, the second intrinsic characteristic of cortical surface measure cortical surface area as a direct correlate of cortical folding.
is its considerable area, extending over 3,000cm
on average for the The gyrification index was first defined on coronal sections of the
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