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Growth patterns in the developing brain detected by using continuum mechanical tensor maps


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The dynamic nature of growth and degenerative disease processes requires the design of sensitive strategies to detect, track and quantify structural change in the brain in its full spatial and temporal complexity. Although volumes of brain substructures are known to change during development, detailed maps of these dynamic growth processes have been unavailable. Here we report the creation of spatially complex, four-dimensional quantitative maps of growth patterns in the developing human brain, detected using a tensor mapping strategy with greater spatial detail and sensitivity than previously obtainable. By repeatedly scanning children (aged 3-15 years) across time spans of up to four years, a rostro-caudal wave of growth was detected at the corpus callosum, a fibre system that relays information between brain hemispheres. Peak growth rates, in fibres innervating association and language cortices, were attenuated after puberty, and contrasted sharply with a severe, spatially localized loss of subcortical grey matter. Conversely, at ages 3-6 years, the fastest growth rates occurred in frontal networks that regulate the planning of new actions. Local rates, profiles, and principal directions of growth were visualized in each individual child.
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19. Decharms, R. C. & Merzenich, M. M. Primary cortical representation of sounds by the coordination of
action potential timing. Nature 381, 610±613 (1996).
20. Roy, S. & Calloway, K. D. Synchronization of Local Neural Networks in the Somatosensory Cortex. A
Comparison of Stationary and Moving Stimuli. J. Neurophysiol. 81, 999±1013 (1999).
21. Crick, F. & Koch, C. Towards a neurobiological theory of consciousness. Sem. Neurosci. 2, 263±275
22. DiCarlo, J. J., Lane, J. W., Hsiao, S. S. & Johnson, K. O. Marking microelectrode penetrations with
¯uorescent dyes. J. Neurosci. Methods 54, 75±81 (1996).
23. Brody, C. D. Slow covariations in neuronal resting potentials can lead to artefactually fast cross-
correlations in their spike trains. J. Neurophysiol. 80, 3345±3351 (1998).
24. Efron, B. & Tibshirani, R. J. An Introduction to the Bootstrap (Chapman and Hall, New York, 1993).
25. Roy, A., Steinmetz, P. N., Johnson, K. O. & Niebur, E. Model-free detection of synchrony in neuronal
spike trains, with an application to primate somatosensory cortex. Neurocomputing (in the press).
This work was supported by the NIH, the NSF and the Alfred P. Sloan Foundation. We
thank J. DiCarlo, M. Usher and S. Yantis for discussions and J. Lane for technical support.
Correspondence and requests for materials should be addressed to E.N.
letters to nature
VOL 404
9 MARCH 2000
Growth patterns in the developing
brain detected by using
continuum mechanical tensor maps
Paul M. Thompson*, Jay N. Giedd
, Roger P. Woods*, David MacDonald
Alan C. Evans
& Arthur W. Toga*
*Laboratory of Neuro Imaging, Department of Neurology, Division of Brain
Mapping, UCLA School of Medicine, 710 Westwood Plaza, Los Angeles,
California 90095-1769, USA
Child Psychiatry Branch, National Institute of Mental Health, NIH,
10 Center Drive, MSC 1600, Bethesda 20982-1600, Maryland, USA
Montreal Neurological Institute, McGill University, 3801 University Street,
Montreal, Que
bec, Canada H3A 2B4
The dynamic nature of growth and degenerative disease processes
requires the design of sensitive strategies to detect, track and
quantify structural change in the brain in its full spatial and
temporal complexity
. Although volumes of brain substructures
are known to change during development
, detailed maps of these
dynamic growth processes have been unavailable. Here we report
the creation of spatially complex, four-dimensional quantitative
maps of growth patterns in the developing human brain, detected
using a tensor mapping strategy with greater spatial detail and
sensitivity than previously obtainable. By repeatedly scanning
children (aged 3±15 years) across time spans of up to four years, a
rostro-caudal wave of growth was detected at the corpus callosum,
a ®bre system that relays information between brain hemispheres.
Peak growth rates, in ®bres innervating association and language
cortices, were attenuated after puberty, and contrasted sharply
with a severe, spatially localized loss of subcortical grey matter.
Conversely, at ages 3±6 years, the fastest growth rates occurred in
frontal networks that regulate the planning of new actions. Local
rates, pro®les, and principal directions of growth were visualized
in each individual child.
Time series of high-resolution three-dimensional magnetic reso-
nance imaging (MRI) scans were acquired across large time spans
from young normal subjects (aged 3±6, 6±7, 7±11, 8±12, 9±13 and
11±15 years) at intervals ranging from two weeks to four years.
Growth patterns were recovered by computing a three-dimensional
elastic deformation ®eld, which recon®gures the anatomy at the
earlier time point into the shape of the anatomy of the later scan.
Maps of local growth rates (Figs 1±4) revealed the complexity and
regional heterogeneity of the tissue growth, pruning and maturation
processes of late brain development. In subjects aged 6±15 years, the
Figure 1 Growth patterns in the developing human brain detected at ages 3±15 years.
A rostro-caudal wave of peak growth rates is detected in young normal subjects scanned
repeatedly across time spans of up to four years. Between ages 3 and 6 years, peak
growth rates (red colours; 60±80% locally) were detected in the frontal circuits of the
corpus callosum, which sustain mental vigilance and regulate the planning of new actions.
Older children displayed fastest growth at the callosal isthmus, which innervates temporo-
parietal systems supporting spatial association and language function. Between ages
11±15 years, growth rates still peak at the isthmus, but are attenuated.
Figure 2 Mapping dynamic patterns of brain development: four-dimensional growth
maps. Strikingly similar growth rates were detected in the corpus callosum of ®ve young
normal subjects scanned repeatedly aged 6±13 years. Peak values throughout the
posterior midbody (red colours) were attenuated after puberty (11±15 years). By contrast,
near-zero maps of change were observed between scans acquired over a two-week
interval. Between ages 3±6 years, extreme growth rates were found in the anterior
interhemispheric ®bre systems that transfer information to sustain mental vigilance and
organize new actions. Tensor maps identify the principal directions of growth rates,
revealing an outward radial tissue expansion in frontal regions.
© 2000 Macmillan Magazines Ltd
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VOL 404
9 MARCH 2000
| 191
highest growth rates were consistently attained in temporo-parietal
systems which are functionally specialized for language, and for
understanding spatial relations (Fig. 2). In contrast to the near-zero
maps of change recovered at short time intervals (`Two-week
interval' in Fig. 2), growth maps spanning large time intervals
showed complex and heterogeneous patterns of change. Between
ages 7 and 11 years (Fig. 2), comparative stability of the splenial and
rostral ®bre systems of the corpus callosum contrasted sharply with
rapid focal growth at the callosal isthmus (up to 80%). Although
global measurements indicated an overall 22.4% increase in mid-
sagittal callosal area during the four-year time span (from
527.6 mm
to 645.6 mm
), these global values disguise the complex-
ity of local growth patterns. Local growth is as high as 80% (Fig. 2), a
feature which may not be apparent with conventional volumetric
Although some individual variation was expected, this focus of
extreme growth at the callosal isthmus was detected consistently in
all subjects tracked between 6 and 15 years (Fig. 2), suggesting that
cortico-cortical networks supporting rapid associative relay and
language functions may myelinate more extensively
and over
longer periods than rostral ®bre systems. In a girl scanned twice
exactly one year apart at ages 6 and 7 years, extreme growth (up to
85%) at the callosal isthmus contrasted with a comparatively
quiescent region in the more rostral systems that innervate frontal
and pre-frontal cortices. When a four-year growth map was gener-
ated for a slightly older child (11±15 years, Fig. 2), growth rates were
correspondingly reduced in every region. Nonetheless, growth
patterns at the isthmus and splenium (commonly de®ned as the
posterior ®fth of the callosum) were still more rapid (20±25%
locally) than in the more anterior rostrum and genu (near-zero
change). In an analysis of grey matter at the cortex
, we recently
observed a localized grey matter loss in frontal cortex that persists in
normal subjects throughout adolescence even into adulthood. The
gradual quiescence of growth at the rostral callosum around pub-
erty may therefore be a precursor to a prolonged regressive process
of grey matter loss through adolescence into adulthood in the
frontal circuits it innervates.
Several near-zero maps of change were recovered at short time
intervals. Figure 2 shows a typical map from a subject scanned at age
8 years, exactly four years later at age 12 years, and again two weeks
later. Negligible change at short time intervals (`Two-week interval'
in Fig. 2) contrasted with a highly heterogeneous map of growth
across the four-year time span. Growth rates again achieved their
highest rates in the associative and linguistic networks that cross at
the callosal isthmus.
Figure 3 Patterns of cerebral growth. a, In a subject scanned at age 7 years and again
exactly four years later at age 11 years, dramatic growth is found in temporo-parietal
regions (red colours). b, All brain regions are stable in a control experiment (blue colours)
analysing scans acquired two weeks apart. c, Between ages 9±13 years, growth is also
most pronounced in temporo-parietal regions. d, This was con®rmed by digitally
overlaying models of the cerebral cortex at each time point (arrows 9 and 13). Growth at
the callosal isthmus in subjects aged 7±11 and 9±13 years (Fig. 2) is therefore
accompanied by diffuse growth in its (temporo-parietal) lobar projection zones.
Figure 4 Detecting three-dimensional patterns of deep nuclear tissue loss. a, b, Tensor
maps distinguish local growth or brain tissue loss from global displacements (b) of the
adjacent ventricular anatomy, modelled here (a) at ages 7 years (red) and 11 years
(yellow). c, d, Between ages 7 and 11 years, three-dimensional displacement vector
maps show the deformation required to recon®gure earlier models of the caudate head
into their later shape. The caudate tail is stable (blue colours, d). e, f, Local growth (e) and
anatomical displacement (d) of the caudate head are independently recovered, with 50%
tissue loss detected locally (e, f), adjacent to a region of 20±30% growth throughout the
internal capsule.
© 2000 Macmillan Magazines Ltd
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VOL 404
9 MARCH 2000
A subject scanned at ages 3 and 6 years exhibited a focus of peak
growth rates (60±80% locally) throughout the anterior corpus
callosum, in frontal circuits that help to sustain a vigilant mental
state and regulate the organization and planning of new actions. The
extremely rapid rates of local growth are consistent with metabolic
studies using positron emission tomography
, which show an
extraordinary doubling of the rates of glucose metabolism in the
frontal cortex between ages 2 and 4 years, with frontal metabolic
rates remaining at 199% of their adult values throughout the age
range of 3±8 years. Between ages 3 and 6 years, when language
function and associative thinking are not yet fully developed,
growth rates at the isthmus were more quiescent (Fig. 2; 0±20%
growth). Later growth foci in the isthmus, found consistently in all
subjects aged 6±15 years, may re¯ect ®ne tuning of language
functions known to occur late in childhood.
Regressive processes (tissue loss) were also detected at the same
time as rapid growth. In the 7±11 and 9±13 year old subjects (Fig.
3), maps of lobar growth revealed pronounced (2±6 mm) temporo-
parietal and pre-frontal enlargement. Somatosensory, motor and
occipital brain regions were comparatively stable, with near-zero
change in all brain regions at short time intervals (Fig. 3b). Up to
50% loss of tissue volume was detected at the caudate head (Fig. 4e
and f). This tissue loss was highly localized, and contrasted with a
20±30% growth of the adjacent internal capsule (for which a
separate surface model was made) and a 5±10% dilation of the
superior ventricular horn (Fig. 4a). Gross volumetric measures
con®rmed an overall 60 mm
tissue loss at the caudate head,
although these global measures disguise the regional complexity
of the change. This example helps illustrate how tensor maps
distinguish local growth patterns (Fig. 4e) from bulk shifts, such
as global displacements of the adjacent cerebral ventricles (Fig. 4a
and b). Three-dimensional vector displacement maps (Fig. 4b and
d) emphasize that both global and local displacements are required
to match modelled anatomical elements across time. The three-
dimensional deformation ®eld, however, encodes the patterns of
local anatomical dilation and contraction, and its values are
unaffected by global displacements. Maps of local three-dimen-
sional growth are therefore not critically dependent on how well
scans are initially aligned, and can de®ne growth at arbitrary three-
dimensional points in the local anatomy (Fig. 4e). Figure 4f
indicates the anatomical context and regional complexity of these
growth and regressive processes. The foci of tissue loss corroborate
the hypothesis that pruning processes occur during this develop-
mental stage
, suggesting that these processes can be tracked in an
individual child.
We detected striking, spatially complex patterns of growth and
tissue loss in the developing human brain. A rostro-caudal wave of
peak growth rates (Fig. 1) was identi®ed in the corpus callosum.
Fibre systems that mediate language function and associative
thinking grew more rapidly than surrounding regions across time
spans before and during puberty (6±13 years), with growth attenu-
ated shortly afterwards (11±15 years). This temporal pattern coin-
cides with the ending of a well-known critical period for learning
language, consistently noted in studies of second-language acquisi-
tion, including sign language, and in isolated children not exposed
to language during early development
. The ability to learn new
languages declines rapidly after the age of 12 years, as does the
ability to recover language function if linguistic areas in one brain
hemisphere are surgically resected. Peak growth rates in linguistic
callosal regions, as well as their attenuation around puberty, may
re¯ect the conclusion of the critical period for learning language and
for accelerating signal transduction in networks that support both
associative reasoning and language function. We recently found that
the same temporo-parietal ®bre system, crossing at the callosal
isthmus, degenerates fastest in early Alzheimer's disease
, when
progressive neuronal loss and perfusion de®cits begin to occur in
temporo-parietal association cortices and their commissural pro-
jection systems. The sensitivity of the approach may therefore offer
advantages in tracking ®ne-scale effects of therapeutic interventions
in dementia and oncology, mapping the local complexities of
disease processes using dynamic rather than static criteria.
Magnetic resonance imaging and pre-processing
Three-dimensional (256
´ 124 ´ 0.97 mm ´ 0.97 mm ´ 1.5 mm resolution) T
fast SPGR (spoiled GRASS (gradient-recalled acquisition in the steady state)) MRI
volumes were acquired from young normal subjects (mean age 8.6 6 3.1 years) at intervals
ranging from two weeks to four years. For each scan pair, a radio-frequency bias ®eld
correction algorithm
was applied to both scans to eliminate intensity drifts caused by
scanner ®eld inhomogeneity. The initial scan was then rigidly registered to the target using
automated image registration software
and resampled using chirp-Z (in-plane) and linear
(out-of-plane) interpolation. Registered scans were histogram-matched (that is, their
intensity distributions were equalized) and a preliminary map of differences in MRI signal
intensities between the two scans was constructed
. Tensor models of structural change
were then used to calculate rates of tissue dilation, contraction and shearing, mapping
local patterns of change in three dimensions.
Image analysis
A high-resolution surface model of the cortex was automatically extracted
from each
scan pair, and three-dimensional digital anatomical models, based on parametric surface
, were generated to represent a comprehensive set of deep sulcal, callosal,
caudate and ventricular surfaces at each time point
. Surface models based on manually
digitized data were averaged across multiple trials (N = 6) to minimize error
. These
model surfaces provided anatomic constraints for an elastic image registration
. For each subject, this algorithm calculated a three-dimensional elastic
deformation vector ®eld, with 384
´ 256 ´ 3 < 0.1 billion degrees of freedom,
recon®guring the anatomy at the earlier time point into the shape of the anatomy of the
later scan. Surface deformations were used to derive a volumetric deformation ®eld from
which local measures of three-dimensional tissue dilation or contraction were quanti®ed.
Landmark points, surfaces, and curved anatomic interfaces were matched up in the pair of
three-dimensional image sets, and the biological validity of the resulting anatomical
transformation was guaranteed by forcing a large system of anatomical surface boundaries
to match exactly. These included multiple structural, functional, and tissue type bound-
aries in three dimensions, including the callosum, caudate, cortex and ventricles. The
deformation ®eld driving the earlier onto the later anatomy was extended to the full
volume using a continuum-mechanical model based on the Cauchy±Navier operator of
linear elasticity
. The resulting system of 0.1 billion second-order elliptic partial
differential equations was solved by successive over-relaxation methods, with multi-grid
, on a standard radiologic workstation. Potential artefactual differences due
to differences in how surfaces were parametrized in each scan were compensated for, using
a ®eld of Christoffel symbols to modify the surface differential operators during the
anatomical transformation
Tensor map computation
From this transformation, local rates of tissue dilation, contraction and shearing were
calculated. Deformation processes recovered by the image-matching algorithm were
analysed mathematically with vector ®eld operators
to produce a variety of tensor maps.
These maps re¯ect the magnitude and principal directions of tissue dilation or contrac-
tion, and the local rates, divergence and gradients of the growth processes detected in the
dynamically changing brain.
Received 27 August 1999; accepted 21 January 2000.
1. Fox, N. C., Freeborough, P. A. & Rossor, M. N. Visualisation and quanti®cation of rates of atrophy in
Alzheimer's disease. Lancet 348, 94±97 (1996).
2. Giedd, J. N. et al. Quantitative magnetic resonance imaging of human brain development: ages 4±18.
Cereb. Cortex 6, 551±560 (1996).
3. Yakovlev, P. I. & Lecours, A. R. in Regional Development of the Brain in Early Life (ed. Minkowski, A.)
3±70 (Davis, Philadelphia, 1967).
4. Sowell, E. R., Thompson, P. M., Holmes, C. J., Jernigan, T. L. & Toga, A. W. In vivo evidence for post-
adolescent brain maturation frontal and striatal regions. Nature Neurosci. 2, 859±861 (1999).
5. Chugani, H. T., Phelps, M. E. & Mazziotta, J. C. Positron emission tomography study of human brain
functional development. Ann. Neurol. 22, 487±497 (1987).
6. Grimshaw, G. M., Adelstein, A., Bryden, M. P. & MacKinnon, G. E. First-language acquisition in
adolescence: evidence for a critical period for verbal language development. Brain Lang. 63, 237±255
7. Thompson, P. M. et al. Cortical variability and asymmetry in normal aging and Alzheimer's disease.
Cereb. Cortex 8, 492±509 (1998).
8. Zijdenbos, A. P. & Dawant, B. M. Brain segmentation and white matter lesion detection in MR images.
Crit. Rev. Biomed. Eng. 22, 401±465 (1994).
9. Woods, R. P., Cherry, S. R. & Mazziotta, J. C. Rapid automated algorithm for aligning and reslicing
PET images. J. Comp. Assist. Tomogr. 16, 620±633 (1992).
10. Freeborough, P. A., Woods, R. P. & Fox, N. C. Accurate registration of serial 3D MR brain images and
its application to visualizing change in neurodegenerative disorders. J. Comp. Assist. Tomogr. 20,
1012±1022 (1996).
11. MacDonald, D., Avis, D. & Evans, A. C. in Proc. SPIE Conf. Visualization in Biomedical Computing (ed.
Robb, R. A.) 2359, 160±169 (1994).
© 2000 Macmillan Magazines Ltd
letters to nature
VOL 404
9 MARCH 2000
| 193
12. Thompson, P. M. & Toga, A. W. A surface-based technique for warping 3-dimensional images of the
brain. IEEE Trans. Med. Imag. 15, 471±489 (1996).
13. Thompson, P. M. & Toga, A. W. Detection, visualization and animation of abnormal anatomic
structure with a deformable probabilistic brain atlas based on random vector ®eld transformations.
Med. Image Anal. 1, 271±294 (1997).
14. Thompson, P. M. & Toga, A. W. in Brain Warping (ed. Toga, A. W.) 311±336 (Academic, San Diego,
15. Thompson, P. M., Schwartz, C., Lin, R. T., Khan, A. A. & Toga, A. W. 3D statistical analysis of sulcal
variability in the human brain. J. Neurosci. 16, 4261±4274 (1996).
16. Thompson, P. M. et al. Detection and mapping of abnormal brain structure with a probabilistic atlas
of cortical surfaces. J. Comp. Assist. Tomogr. 21, 567±581 (1997).
17. Davatzikos, C. Spatial normalization of 3D brain images using deformable models. J. Comp. Assist.
Tomogr. 20, 656±665 (1996).
18. Miller, M. I. & Grenander, U. Computational anatomy: an emerging discipline. Q. Appl. Math. 56,
617±694 (1998).
Correspondence and requests for materials should be addressed to P.M.T. (e-mail:
We thank E. Sowell, M. Mega and J. Mazziotta for their advice and support. P.M.T. was
supported by the Howard Hughes Medical Institute, the US Information Agency, and the
US±UK Fulbright Commission. Additional research support was provided by a Human
Brain Project grant to the International Consortium for Brain Mapping, funded jointly by
NIMH and NIDA, by National Institutes of Health intramural funding (J.N.G.), and by
the National Library of Medicine, National Science Foundation, and the NCRR.
A clonogenic common myeloid
progenitor that gives rise
to all myeloid lineages
Koichi Akashi*
, David Traver*, Toshihiro Miyamoto
& Irving L. Weissman
Departments of Pathology and Developmental Biology, Stanford University School
of Medicine, Stanford, California 94305, USA
* These authors contributed equally to this work
Haematopoietic stem cells give rise to progeny that progressively
lose self-renewal capacity and become restricted to one lineage
The points at which haematopoietic stem cell-derived progenitors
commit to each of the various lineages remain mostly unknown.
We have identi®ed a clonogenic common lymphoid progenitor
that can differentiate into T, B and natural killer cells but not
myeloid cells
. Here we report the prospective identi®cation,
puri®cation and characterization, using cell-surface markers
and ¯ow cytometry, of a complementary clonogenic common
myeloid progenitor that gives rise to all myeloid lineages.
Common myeloid progenitors give rise to either megakaryo-
cyte/erythrocyte or granulocyte/macrophage progenitors. Puri-
®ed progenitors were used to provide a ®rst-pass expression
pro®le of various haematopoiesis-related genes. We propose
that the common lymphoid progenitor and common myeloid
progenitor populations re¯ect the earliest branch points between
the lymphoid and myeloid lineages, and that the commitment of
common myeloid progenitors to either the megakaryocyte/
erythrocyte or the granulocyte/macrophage lineages are mutually
exclusive events.
The existence of clonal common lymphoid progenitors (CLPs)
suggests that complementary progenitors common to all myeloid
cells may also exist. Because the expression of the interleukin-7
receptor a-chain (IL-7Ra) marks the CLPs and other downstream
lymphoid progenitors
, we searched the IL-7Ra
fraction of
Present address: Department of Cancer Immunology and AIDS, Dana-Farber Cancer Institute,
44 Binney Street, Boston, Massachusetts 02115, USA.
murine bone marrow for primitive myeloid progenitor populations.
In steady-state mouse bone marrow, myeloerythroid colony-
forming unit (CFU) activity was found almost exclusively in the
fraction (data not shown). Within this popula-
tion, Sca-1
cells are highly enriched for haematopoietic stem cells
. To remove HSCs, Sca-1
cells were excluded. The
fraction was further divided into three
subpopulations according to the expression pro®les of the Fcg
receptor-II/III (FcgR), an important marker for myelomonocytic
cells and a progenitor marker in fetal liver haematopoiesis
, and
CD34, which marks a fraction of haematopoietic stem cells and
: the FcgR
, and FcgR
populations (Fig. 1a).
Each of the above populations were cleanly isolatable (Fig. 1b)
and gave rise to distinct colony types in methylcellulose CFU
assays (Figs 1c and 2). In the presence of steel factor (Slf), Flt-3
ligand (FL), IL-11, IL-3, granulocyte/macrophage-colony stimulat-
ing factor (GM-CSF), erythropoietin (Epo) and thrombopoietin
(Tpo), ,80% of single multipotent HSCs randomly committed to
myeloid lineages
, giving rise to various types of myeloid colonies
including CFU-Mix
, burst-forming units-erythroid (BFU-E),
Figure 1 Identi®cation of myeloid progenitors in mouse bone marrow. a, The IL-7Ra
fraction was subdivided into FcgR
, and FcgR
populations (a, b, c respectively as indicated in the right-hand panel). Percentages of each
population relative to whole bone marrow are shown next to each sort gate. b, Re-analysis
of the sorted FcgR
and FcgR
populations. c, Clonogenic
myeloid colony formation in methylcellulose. From each sorted progenitor population, 288
wells receiving a single cell each were scored. FcgR
cells and HSCs formed various
myeloid colonies including CFU-Mix, whereas the FcgR
and FcgR
gave rise only to MegE and GM colonies, respectively (left). Megakaryocyte/erythroid colony
formation from the FcgR
fractions was dependent upon Epo and/or Tpo (right).
© 2000 Macmillan Magazines Ltd
... However, humans appear to have the greatest prolonged myelination 20 and show atrophy of the CC in later life 7,15 . Studies in humans have reported greater age-related changes in the midsagittal CC area of posterior regions than in anterior regions during late childhood and early adolescence [42][43][44] . However, when exploring early ...
... However, when exploring early childhood development, it appears anterior growth may be more prominent 44 . Taken together, it has been hypothesized that there is likely an anterior-to-posterior maturation gradient in humans, with posterior maturation taking place later than anterior growth 45 . ...
Full-text available
The midsagittal area of the corpus callosum (CC) is frequently studied in relation to brain development, connectivity, and function. Here we quantify myelin characteristics from electron microscopy to understand more fully differential patterns of white matter development occurring within the CC. We subdivided midsagittal regions of the CC into: I—rostrum and genu, II—rostral body, III—anterior midbody, IV—posterior midbody, and V—isthmus and splenium. The sample represented capuchin monkeys ranging in age from 2 weeks to 35 years (Sapajus [Cebus] apella, n = 8). Measurements of myelin thickness, myelin fraction, and g-ratio were obtained in a systematic random fashion. We hypothesized there would be a period of rapid myelin growth within the CC in early development. Using a locally weighted regression analysis (LOESS), we found regional differences in myelin characteristics, with posterior regions showing more rapid increases in myelin thickness and sharper decreases in g-ratio in early development. The most anterior region showed the most sustained growth in myelin thickness. For all regions over the lifespan, myelin fraction increased, plateaued, and decreased. These results suggest differential patterns of nonlinear myelin growth occur early in development and well into adulthood in the CC of capuchin monkeys.
... In this study, we reconstructed a 4D continuum of the developing embryonic brain of the CD1 mouse based on dMRM data at a ultra high resolution of 30 to 45 μm isotropic. We quantitatively examined microstructural and morphological changes in the developing continuum, based on which, regional clusters with distinct developmental trajectories were identified using computational anatomy approaches (28,29). We further demonstrated the feasibility of integrating 4D gene-expression data into the developmental continuum to allow direct visualization of their interactions in both normal and abnormal developing mouse brains. ...
... Techniques used here to characterize the dynamic processes occurring in brain development, including diffeomorphic mapping and quantification of volumetric deformation, have been developed under the framework of computational anatomy (19,20). Applying these techniques to MRI data of developing human and animal brains have revealed whole-brain growth patterns and contributed to defining the growth trajectories of major brain structures (27,28,64,65). The reconstruction of the 4D GVF by concatenating diffeomorphic mappings among consecutive developmental stages from E11.5 to E15.5 enables us to visualize the spatiotemporal changes of the embryonic mouse brain assembled in a common coordinate system. ...
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The embryonic mouse brain undergoes drastic changes in establishing basic anatomical compartments and laying out major axonal connections of the developing brain. Correlating anatomical changes with gene-expression patterns is an essential step toward understanding the mechanisms regulating brain development. Traditionally, this is done in a cross-sectional manner, but the dynamic nature of development calls for probing gene–neuroanatomy interactions in a combined spatiotemporal domain. Here, we present a four-dimensional (4D) spatiotemporal continuum of the embryonic mouse brain from E10.5 to E15.5 reconstructed from diffusion magnetic resonance microscopy (dMRM) data. This study achieved unprecedented high-definition dMRM at 30- to 35-µm isotropic resolution, and together with computational neuroanatomy techniques, we revealed both morphological and microscopic changes in the developing brain. We transformed selected gene-expression data to this continuum and correlated them with the dMRM-based neuroanatomical changes in embryonic brains. Within the continuum, we identified distinct developmental modes comprising regional clusters that shared developmental trajectories and similar gene-expression profiles. Our results demonstrate how this 4D continuum can be used to examine spatiotemporal gene–neuroanatomical interactions by connecting upstream genetic events with anatomical changes that emerge later in development. This approach would be useful for large-scale analysis of the cooperative roles of key genes in shaping the developing brain.
... It is The copyright holder for this preprint this version posted April 24, 2022. ; 1999; Thompson et al., 2004) and the multivariate tensor-based morphometry (mTBM) (Davatzikos, 1996;Thompson et al., 2000;Wang et al., 2010). The RD (a scalar) represents the thickness of the shape at each vertex to the medial axis, which reflects the surface differences along the surface normal directions (Wang et al., 2011). ...
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Mentalising ability, indexed as the ability to understand others' beliefs, feelings, intentions, thoughts, and traits, is a pivotal and fundamental component of human social cognition. However , considering the multifaceted nature of mentalising ability, little research has focused on characterising individual differences in different mentalising components. And even less research has been devoted to investigating how the variance in the structural and functional patterns of the amygdala and hippocampus, two vital subcortical regions of the 'social brain', are related to inter-individual variability in mentalising ability. Here, as a first step toward filling these gaps, we exploited inter-subject representational similarity analysis (IS-RSA) to assess relationships between amygdala and hippocampal morphometry (surface-based mul-tivariate morphometry statistics, MMS), connectivity (resting-state functional connectivity, rs-FC) and mentalising ability (interactive mentalisation questionnaire (IMQ) scores) across the participants (N = 24). In IS-RSA, we proposed a novel pipeline, i.e., computing patching and pooling operations-based surface distance (CPP-SD), to obtain a decent representation for high-dimensional MMS data. On this basis, We found significant correlations (i.e., second-order isomorphisms) between these three distinct modalities, indicating that a trinity existed in idiosyncratic patterns of brain morphometry, connectivity and mentalising ability. Notably, a region-related mentalising specificity emerged from these associations: self-self and self-other mentalisation are more related to the hippocampus, while other-self mentalisation shows a closer link with the amygdala. Furthermore, by utilising the dyadic regression analysis, we observed significant interactions such that subject pairs with similar morphometry had even greater mentalising similarity if they were also similar in rs-FC. Altogether, we demonstrated the feasibility and illustrated the promise in using IS-RSA to study individual differences, deepening our understanding of how individual brains give rise to their mentalising abilities.
... The accurate registration and alignment of two images has been a challenging problem in a wide variety of applications such as medical image processing [1,2], remote sensing [3], biology [4][5][6], and computer vision [7,8]. Particularly, the registration of the medical images has been widely used in tumor localization and targeting [9], organ growth studies [10] and brain atlas reconstruction [11]. ...
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Spatially-varying intensity noise is a common source of distortion in medical images and is often associated with reduced accuracy in medical image registration. In this paper, we propose two multi-resolution image registration algorithms based on Empirical Mode Decomposition (EMD) that are robust against additive spatially-varying noise. EMD is a multi-resolution tool that decomposes a signal into several principle patterns and residual components. Our first proposed algorithm (LR-EMD) is based on the registration of EMD feature maps from both floating and reference images in various resolutions. In the second algorithm (AFR-EMD), we first extract a single average feature map based on EMD and then use a simple hierarchical multi-resolution algorithm to register the average feature maps. We then showcase the superior performance of both algorithms in the registration of brain MRIs as well as retina images. For the registration of brain MR images, using mutual information as the similarity measure, both AFR-EMD and LR-EMD achieve a lower error rate in intensity (42% and 32%, respectively) and lower error rate in transformation (52% and 41%, respectively) compared to intensity-based hierarchical registration. Our results suggest that the two proposed algorithms offer robust registration solutions in the presence of spatially-varying noise.
... Each surface has the same number of vertices (150 × 100). As illustrated in Figure 1D, the intersection of the red curve and the blue curve is a surface vertex, and at each vertex, we adopt two kinds of morphometry features, the RD (Pizer et al., 1999;Thompson et al., 2004) and measures derived from surface TBM (Davatzikos, 1996;Thompson et al., 2000;Woods, 2003;Chung et al., 2008). The RD (a scalar at each vertex) represents the thickness of the shape at each vertex relative to the medial axis; this primarily reflects surface differences along the surface normal directions. ...
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Amyloid-β (Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. One of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research focuses in the AD pathophysiological progress. This work proposes a novel framework, Federated Morphometry Feature Selection (FMFS) model, to examine subtle aspects of hippocampal morphometry that are associated with Aβ/tau burden in the brain, measured using positron emission tomography (PET). FMFS is comprised of hippocampal surface-based feature calculation, patch-based feature selection, federated group LASSO regression, federated screening rule-based stability selection, and region of interest (ROI) identification. FMFS was tested on two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts to understand hippocampal alterations that relate to Aβ/tau depositions. Each cohort included pairs of MRI and PET for AD, mild cognitive impairment (MCI), and cognitively unimpaired (CU) subjects. Experimental results demonstrated that FMFS achieves an 89× speedup compared to other published state-of-the-art methods under five independent hypothetical institutions. In addition, the subiculum and cornu ammonis 1 (CA1 subfield) were identified as hippocampal subregions where atrophy is strongly associated with abnormal Aβ/tau. As potential biomarkers for Aβ/tau pathology, the features from the identified ROIs had greater power for predicting cognitive assessment and for survival analysis than five other imaging biomarkers. All the results indicate that FMFS is an efficient and effective tool to reveal associations between Aβ/tau burden and hippocampal morphometry.
... Developmental changes (maturation) of brain architecture Modern methods to analyse and visualise anatomical peculiarities of the human brain have changed our view about brains in different stages of development (Luders et al. 2005;Sowell et al. 2004;Sowell et al. 2003;Thompson et al. 2004;Thompson et al. 2000;Jancke 2002;Steinberg 2005;Paus 2005;Casey et al. 2005). First, we have learned from these modern methods that the human brain and especially the frontal cortex matures and thus changes it architecture up into the late teens. ...
Background Shape analyses of patients with schizophrenia have revealed bilateral deformations of the anterolateral hippocampus, primarily localized to the CA1 subfield. Incomplete hippocampal inversion (IHI), an anatomical variant of the human hippocampus resulting from an arrest during neurodevelopment, is more prevalent and severe in patients with schizophrenia. We hypothesized that IHI would affect the shape of the hippocampus and contribute to hippocampal shape differences in schizophrenia. Methods We studied 199 schizophrenia patients and 161 healthy control participants with structural-MRI to measure the prevalence and severity of IHI. High-fidelity hippocampal surface reconstructions were generated with the SPHARM-PDM toolkit. We utilized general linear models in SurfStat to test for group shape differences, the impact of IHI on hippocampal shape variation, and whether IHI contributes to hippocampal shape abnormalities in schizophrenia. Results Not including IHI as a main effect in our between-group comparison replicated well-established hippocampal shape differences in schizophrenia patients localized to the CA1 subfield in the anterolateral hippocampus. Shape differences were also observed near the uncus and hippocampal tail. IHI was associated with outward displacements of the dorsal and ventral surfaces of the hippocampus and inward displacements of the medial and lateral surfaces. Including IHI as a main effect in our between-group comparison eliminated the bilateral shape differences in the CA1 subfield. Shape differences in the uncus persisted after including IHI. Conclusions IHI impacts hippocampal shape. Our results suggest IHI as a neurodevelopmental mechanism for the well-known shape differences, particularly in the CA1 subfield, in schizophrenia.
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Education in the 21st century is called upon to prepare students with disabilities to enter a high-consciousness society where people can learn, think and react fast. The current review paper aims at investigating the role of fast learning in special education. We trace the essential indicators of speed learning with a special focus on those factors that are most relevant to learning disabilities. Afterward, we present evidence-based training techniques and strategies that rapidly rewire the brain and speed up learning. In addition, we examine the role of ICTs as essential training tools in speed learning. Finally, we discuss the role of metacognition in training fast and conscious learners. The results of this review showed that speed learning training techniques improve all those factors that accelerate learning such as spatial attention, visual span, processing speed, speed reaction, executive functions, metacognition, and consciousness. Most important, fast learning strategies meliorate control processes and spatial intelligence which is extremely fast and powerful. Metacognition provides learners with all those meta-abilites needed to enter a state of peak performance. This study also points to the option of including speed training strategies in schools to create inclusive learning environments and help students with or without disabilities to transcend their limitations and become conscious and high-capacity learners.
Conference Paper
Biomarker-assisted diagnosis and intervention in Alzheimer's disease (AD) may be the key to prevention breakthroughs. One of the hallmarks of AD is the accumulation of tau plaques in the human brain. However, current methods to detect tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (Tau PET). In our previous work, structural MRI-based hippocampal multivariate morphometry statistics (MMS) showed superior performance as an effective neurodegenerative biomarker for preclinical AD and Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) has excellent ability to generate low-dimensional representations with strong statistical power for brain amyloid prediction. In this work, we apply this framework together with ridge regression models to predict Tau deposition in Braak12 and Braak34 brain regions separately. We evaluate our framework on 925 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject has one pair consisting of a PET image and MRI scan which were collected at about the same times. Experimental results suggest that the representations from our MMS and PASCS-MP have stronger predictive power and their predicted Braak12 and Braak34 are closer to the real values compared to the measures derived from other approaches such as hippocampal surface area and volume, and shape morphometry features based on spherical harmonics (SPHARM).
Visual awareness is a favorable form of consciousness to study neurobiologically. We propose that it takes two forms: a very fast form, linked to iconic memory, that may be difficult to study; and a somewhat slower one involving visual attention and short-term memory. In the slower form an attentional mechanism transiently binds together all those neurons whose activity relates to the relevant features of a single visual object. We suggest this is done by generating coherent semi-synchronous oscillations, probably in the 40-70 Hz range. These oscillations then activate a transient short-term (working) memory. We outfit several lines of experimental work that might advance the understanding of the neural mechanisms involved. The neural basis of very short-term memory especially needs more experimental study.
An iterative algorithm is presented for simultaneous deformation of multiple curves and surfaces to an MRI, with inter-surface constraints and self-intersection avoidance. The resulting robust segmentation, combined with local curvature matching, automatically creates surfaces of MRI datasets with a common mapping to surface parametric space.
This chapter reviews various methods for elastic matching of brain images, and discusses some of their applications, focusing on pathology detection. It emphasizes the advantages and limitations of each approach, while realizing that hybrid strategies will be developed in the future which capitalize on the merits of each. The complexity of anatomic variations, especially at the cortex, mandates the design of specialized approaches to handle neuroanatomic data. Recent years have seen considerable advances in the ability to extract models of neuroanatomic structures in their full spatial complexity. Models which are conveniently parameterized can provide a valuable information source to guide mathematical algorithms which analyze future neuroanatomic data of the same type. One of the most promising applications of warping algorithms is their use as a virtual sensor, creating exquisitely detailed maps of anatomic differences. Maps of anatomical change can also be generated by warping scans acquired from the same subject over time. In many ways, static representations of structure are ill-suited to determine the dynamic effects of disease. Serial scanning of human subjects, however, when combined with a powerful set of registration and modeling algorithms, enables disease and growth processes to be tracked in their full spatial and temporal complexity.
This paper studies mathematical methods in the emerging new discipline of Computational Anatomy. Herein we formalize the Brown/Washington University model of anatomyfollowing the global pattern theory introduced in [1, 2], in which anatomies are represented as deformable templates, collections of 0 � 1 � 2 � 3;dimensional manifolds. Typical structure is carried by the template with the variabilities accommodated via the application of random transformations to the background manifolds. The anatomical model is a quadruple ( � H � I � P), the background space = [ M of 0 � 1 � 2 � 3;dimensional manifolds, the set of di eomorphic transformations on the background space H: $ , the space of idealized medical imagery I, and P the family of probability measures on H. The group of di eomorphic transformations H is chosen to be rich enough so that a large family of shapes may be generated with the topologies of the template maintained. For normal anatomy one deformable template is studied, with ( � H � I) corresponding to a homogeneous space [3], in that it can be completely generated from one of its elements, I = HItemp�Itemp 2I. For disease, a family of templates [ Itemp are introduced of perhaps varying dimensional transformation classes. The complete anatomy is is a collection of homogeneous spaces Itotal = [ (I � H). There are three principal components to computational anatomy studied herein.
From over 100 children studied with 2-deoxy-2{18F}fluoro-D-glucose and positron emission tomography we selected 29 children (aged 5 days to 15.1 years) who had suffered transient neurological events not significantly affecting normal neurodevelopment. These 29 children were reasonably representative of normal children and provided an otherwise unobtainable population in which to study developmental changes in local cerebral metabolic rates for glucose (lCMRGlc). In infants less than 5 weeks old lCMRGlc was highest in sensorimotor cortex, thalamus, brainstem, and cerebellar vermis. By 3 months, lCMRGlc had increased in parietal, temporal, and occipital cortices; basal ganglia; and cerebellar cortex. Frontal and dorsolateral occipital cortical regions displayed a maturational rise in lCMRGlc by approximately 6 to 8 months. Absolute values of lCMRGlc for various grey matter regions were low at birth (13 to 25 μmol/min/100 gm), and rapidly rose to reach adult values (19 to 33 μmol/min/100 gm) by 2 years. lCMRGlc continued to rise until, by 3 to 4 years, it reached values of 49 to 65 μmol/min/100 gm in most regions. These high rates were maintained until approximately 9 years, when they began to Decemberline, and reached adult rates again by the latter part of the second Decemberade. The highest increases of lCMRGlc over adult values occurred in cerebral cortical structures; lesser increases were seen in subcortical structures and in the cerebellum. This time course of lCMRGlc changes matches that describing the process of initial overproduction and subsequent elimination of excessive neurons, synapses, and dendritic spines known to occur in the developing brain. The determination of changing metabolic patterns accompanying normal brain development is a necessary prelude to the study of abnormal brain development with positron emission tomography.
The sexual dimorphism of the human corpus callosum (CC) is currently controversial, possibly because of difficulties in morphometric analysis. We have reinvestigated the issue by using morphometric techniques specially designed to yield objective measurements of CC size and shape. The development of the CC was studied with similar techniques in order to investigate whether its final shape and size might be influenced by axonal elimination, as could be expected from previous animal studies. We have measured the CCs of 32 men and 26 women; 27 male and 19 female CCs were from brain tissue, the others were from magnetic resonance imaging graphs. Women tended to have (1) a smaller cross-sectional callosal area (CCA); (2) a larger fraction of CCA in the posterior fifth of the CC; (3) more slender CCs; and (4) more bulbous splenia. These differences could not be detected by simple inspection but were demonstrated by measurement and statistical analysis. However, CCA was correlated with the other sexually dimorphic parameters, and the sex-related differences in the latter became nonsignificant when variations in CCA were factored out or when male and female populations with similar CCA were compared. In addition, we analyzed CCs of 16 male and 16 female fetuses and of 13 male and 15 female infants and children. This sample ranged in age between 20 weeks of gestation and 14 years but covered in detail the period up to 14 months after birth. CCA increased throughout the latter period but decreased slightly between about 33 weeks of gestation and the beginning of the second postnatal mouth. This decrease coincided with thinning of the CC and a marked increase in bulbosity of the splenium. No sexual dimorphism could be demonstrated until the beginning of the postnatal period. In the age group between birth (at term) and the 14th month, CCA was, as in the adult, larger in males. Unlike in the adults, the CC was longer in males and the bulbosity index was the same in the two sexes. Axonal elimination may play a role in the perinatal pause in CCA growth and in the concomitant changes in callosal shape.