The
amygdala
is
a
subcortical
region
in
the
mesiotemporal
lobe
that
plays
key
role
emotional
and
sensory
functions.
Conventional
neuroimaging
experiments
treat
this
structure
as
single,
uniform
entity,
but
there
ample
histological
evidence
for
subregional
heterogeneity
microstructure
function.
current
study
characterized
structure-function
coupling
human
amygdala,
integrating
post-mortem
histology
vivo
MRI
at
ultra-high
fields.
Core
to
our
work
was
novel
neuroinformatics
approach
leveraged
multiscale
texture
analysis
well
non-linear
dimensionality
reduction
techniques
identify
salient
dimensions
of
microstructural
variation
3D
reconstruction
amygdala.
We
observed
two
axes
region,
describing
inferior-superior
mediolateral
trends
differentiation
part
recapitulated
established
atlases
subnuclei.
Translating
data
acquired
7
Tesla,
we
could
demonstrate
generalizability
these
spatial
across
10
healthy
adults.
then
cross-referenced
with
functional
blood-oxygen-level
dependent
(BOLD)
signal
obtained
during
task-free
conditions,
revealed
close
association
structural
macroscale
network
embedding,
notably
temporo-limbic,
default
mode,
sensory-motor
networks.
Our
consolidates
descriptions
anatomy
function
from
imaging
techniques.
Molecular Autism,
Journal Year:
2025,
Volume and Issue:
16(1)
Published: March 26, 2025
Abstract
Background
Autism
spectrum
disorder
(ASD)
is
marked
by
disruptions
in
low-level
sensory
processing
and
higher-order
sociocognitive
functions,
suggesting
a
complex
interplay
between
different
brain
regions
across
the
cortical
hierarchy.
However,
developmental
trajectory
of
this
hierarchical
organization
ASD
remains
underexplored.
Herein,
we
investigated
maturational
abnormalities
hierarchy
among
individuals
with
ASD.
Methods
Resting-state
functional
magnetic
resonance
imaging
data
from
three
large-scale
datasets
were
analyzed:
Brain
Imaging
Data
Exchange
I
II
Lifespan
Human
Connectome
Project
Development
(aged
5–22
years).
The
principal
connectivity
gradient
representing
was
estimated
using
diffusion
map
embedding.
By
applying
normative
modeling
generalized
additive
model
for
location,
scale,
shape
(GAMLSS),
captured
nonlinear
trajectories
developing
gradient,
as
well
individual-level
deviations
typical
development
based
on
centile
scores
measured
curves.
A
whole-brain
summary
metric,
score,
derived
to
measure
extent
abnormal
maturation
Finally,
through
series
mediation
analyses,
examined
potential
role
network-level
connectomic
diagnoses
Results
followed
non-linear
trajectory,
showing
delayed
during
childhood
compared
that
typically
individuals,
an
accelerated
“catch-up”
phase
adolescence
subsequent
decline
young
adulthood.
nature
these
varied
networks,
attention
networks
displaying
most
pronounced
childhood,
while
particularly
default
mode
network
(DMN),
remaining
impaired
adolescence.
Mediation
analyses
revealed
persistent
reduction
DMN
segregation
throughout
key
contributor
atypical
Limitations
uneven
distribution
samples
age
groups,
later
stages
development,
limited
our
ability
fully
capture
older
individuals.
Conclusions
These
findings
highlight
importance
understanding
ASD,
collectively
early
interventions
aimed
at
promoting
may
be
critical
improving
outcomes