NeuroImage,
Journal Year:
2023,
Volume and Issue:
283, P. 120403 - 120403
Published: Oct. 20, 2023
The
mechanisms
of
cognitive
decline
and
its
variability
during
healthy
aging
are
not
fully
understood,
but
have
been
associated
with
reorganization
white
matter
tracts
functional
brain
networks.
Here,
we
built
a
network
modeling
framework
to
infer
the
causal
link
between
structural
connectivity
architecture
consequent
in
aging.
By
applying
in-silico
interhemispheric
degradation
connectivity,
reproduced
process
dedifferentiation
Thereby,
found
global
modulation
dynamics
by
increase
age,
which
was
steeper
older
adults
poor
performance.
We
validated
our
hypothesis
via
deep-learning
Bayesian
approach.
Our
results
might
be
first
mechanistic
demonstration
leading
decline.
Nature,
Journal Year:
2023,
Volume and Issue:
618(7965), P. 566 - 574
Published: May 31, 2023
The
anatomy
of
the
brain
necessarily
constrains
its
function,
but
precisely
how
remains
unclear.
classical
and
dominant
paradigm
in
neuroscience
is
that
neuronal
dynamics
are
driven
by
interactions
between
discrete,
functionally
specialized
cell
populations
connected
a
complex
array
axonal
fibres
Gene
expression
fundamentally
shapes
the
structural
and
functional
architecture
of
human
brain.
Open-access
transcriptomic
datasets
like
Allen
Human
Brain
Atlas
provide
an
unprecedented
ability
to
examine
these
mechanisms
in
vivo;
however,
a
lack
standardization
across
research
groups
has
given
rise
myriad
processing
pipelines
for
using
data.
Here,
we
develop
abagen
toolbox,
open-access
software
package
working
with
data,
use
it
how
methodological
variability
influences
outcomes
Atlas.
Applying
three
prototypical
analyses
outputs
750,000
unique
pipelines,
find
that
choice
pipeline
large
impact
on
findings,
parameters
commonly
varied
literature
influencing
correlations
between
derived
gene
other
imaging
phenotypes
by
as
much
ρ
≥
1.0.
Our
results
further
reveal
ordering
parameter
importance,
steps
influence
normalization
yielding
greatest
downstream
statistical
inferences
conclusions.
The
presented
work
development
toolbox
lay
foundation
more
standardized
systematic
transcriptomics,
will
help
advance
future
understanding
Trends in Cognitive Sciences,
Journal Year:
2024,
Volume and Issue:
28(4), P. 352 - 368
Published: Jan. 9, 2024
To
explain
how
the
brain
orchestrates
information-processing
for
cognition,
we
must
understand
information
itself.
Importantly,
is
not
a
monolithic
entity.
Information
decomposition
techniques
provide
way
to
split
into
its
constituent
elements:
unique,
redundant,
and
synergistic
information.
We
review
disentangling
redundant
interactions
redefining
our
understanding
of
integrative
function
neural
organisation.
navigates
trade-offs
between
redundancy
synergy,
converging
evidence
integrating
structural,
molecular,
functional
underpinnings
synergy
redundancy;
their
roles
in
cognition
computation;
they
might
arise
over
evolution
development.
Overall,
provides
guiding
principle
informational
architecture
cognition.
National Science Review,
Journal Year:
2024,
Volume and Issue:
11(5)
Published: Feb. 27, 2024
ABSTRACT
Virtual
brain
twins
are
personalized,
generative
and
adaptive
models
based
on
data
from
an
individual’s
for
scientific
clinical
use.
After
a
description
of
the
key
elements
virtual
twins,
we
present
standard
model
personalized
whole-brain
network
models.
The
personalization
is
accomplished
using
subject’s
imaging
by
three
means:
(1)
assemble
cortical
subcortical
areas
in
subject-specific
space;
(2)
directly
map
connectivity
into
models,
which
can
be
generalized
to
other
parameters;
(3)
estimate
relevant
parameters
through
inversion,
typically
probabilistic
machine
learning.
We
use
healthy
ageing
five
diseases:
epilepsy,
Alzheimer’s
disease,
multiple
sclerosis,
Parkinson’s
disease
psychiatric
disorders.
Specifically,
introduce
spatial
masks
demonstrate
their
physiological
pathophysiological
hypotheses.
Finally,
pinpoint
challenges
future
directions.
The
intrinsic
dynamics
of
neuronal
populations
are
shaped
by
both
microscale
attributes
and
macroscale
connectome
architecture.
Here
we
comprehensively
characterize
the
rich
temporal
patterns
neural
activity
throughout
human
brain.
Applying
massive
feature
extraction
to
regional
haemodynamic
activity,
systematically
estimate
over
6000
statistical
properties
individual
brain
regions'
time-series
across
neocortex.
We
identify
two
robust
spatial
gradients
dynamics,
one
spanning
a
ventromedial-dorsolateral
axis
dominated
measures
signal
autocorrelation,
other
unimodal-transmodal
dynamic
range.
These
reflect
gene
expression,
intracortical
myelin
cortical
thickness,
as
well
structural
functional
network
embedding.
Importantly,
these
correlated
with
meta-analytic
activation,
differentiating
cognitive
versus
affective
processing
sensory
higher-order
processing.
Altogether,
findings
demonstrate
link
between
architecture,
cognition.
Communications Biology,
Journal Year:
2022,
Volume and Issue:
5(1)
Published: June 2, 2022
The
relationship
between
structural
and
functional
connectivity
in
the
brain
is
a
key
question
systems
neuroscience.
Modern
accounts
assume
single
global
structure-function
that
persists
over
time.
Here
we
study
coupling
from
dynamic
perspective,
show
it
regionally
heterogeneous.
We
use
temporal
unwrapping
procedure
to
identify
moment-to-moment
co-fluctuations
neural
activity,
reconstruct
time-resolved
patterns.
find
patterns
of
are
region-specific.
observe
stable
unimodal
transmodal
cortex,
intermediate
regions,
particularly
insular
cortex
(salience
network)
frontal
eye
fields
(dorsal
attention
network).
Finally,
variability
region's
related
distribution
its
connection
lengths.
Collectively,
our
findings
provide
way
relationships
perspective.
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences,
Journal Year:
2022,
Volume and Issue:
380(2227)
Published: May 23, 2022
In
order
to
survive
in
a
complex
environment,
the
human
brain
relies
on
ability
flexibly
adapt
ongoing
behaviour
according
intrinsic
and
extrinsic
signals.
This
capability
has
been
linked
specific
whole-brain
activity
patterns
whose
relative
stability
(order)
allows
for
consistent
functioning,
supported
by
sufficient
instability
needed
optimal
adaptability.
The
emergent,
spontaneous
balance
between
disorder
over
spacetime
underpins
distinct
states.
For
example,
depression
is
characterized
excessively
rigid,
highly
ordered
states,
while
psychedelics
can
bring
about
more
disordered,
sometimes
overly
flexible
Recent
developments
systems,
computational
theoretical
neuroscience
have
started
make
inroads
into
characterization
of
such
dynamics
space
time.
Here,
we
review
recent
insights
drawn
from
neuroimaging
modelling
motivating
using
mechanistic
principles
dynamical
system
theory
study
characterize
We
show
how
different
healthy
altered
states
are
associated
characteristic
which
turn
may
offer
that
time
inspire
new
treatments
rebalancing
disease.
article
part
theme
issue
'Emergent
phenomena
physical
socio-technical
systems:
cells
societies'.
Network Neuroscience,
Journal Year:
2022,
Volume and Issue:
6(4), P. 960 - 979
Published: Jan. 1, 2022
Abstract
Most
human
neuroscience
research
to
date
has
focused
on
statistical
approaches
that
describe
stationary
patterns
of
localized
neural
activity
or
blood
flow.
While
these
are
often
interpreted
in
light
dynamic,
information-processing
concepts,
the
static,
local,
and
inferential
nature
approach
makes
it
challenging
directly
link
neuroimaging
results
plausible
underlying
mechanisms.
Here,
we
argue
dynamical
systems
theory
provides
crucial
mechanistic
framework
for
characterizing
both
brain’s
time-varying
quality
its
partial
stability
face
perturbations,
hence,
this
perspective
can
have
a
profound
impact
interpretation
their
relationship
with
behavior.
After
briefly
reviewing
some
key
terminology,
identify
three
ways
which
analyses
embrace
perspective:
by
shifting
from
local
more
global
perspective,
focusing
dynamics
instead
static
snapshots
activity,
embracing
modeling
map
using
“forward”
models.
Through
approach,
envisage
ample
opportunities
researchers
enrich
understanding
dynamic
mechanisms
support
wide
array
brain
functions,
health
setting
psychopathology.
Science Advances,
Journal Year:
2023,
Volume and Issue:
9(11)
Published: March 17, 2023
Model-based
data
analysis
of
whole-brain
dynamics
links
the
observed
to
model
parameters
in
a
network
neural
masses.
Recently,
studies
focused
on
role
regional
variance
parameters.
Such
analyses
however
necessarily
depend
properties
preselected
mass
model.
We
introduce
method
infer
from
functional
both
representing
and
region-
subject-specific
while
respecting
known
structure.
apply
human
resting-state
fMRI.
find
that
underlying
can
be
described
as
noisy
fluctuations
around
single
fixed
point.
The
reliably
discovers
three
with
clear
distinct
dynamics,
one
which
is
strongly
correlated
first
principal
component
gene
expression
spatial
map.
present
approach
opens
novel
way
fMRI
possible
applications
for
understanding
brain
during
aging
or
neurodegeneration.