Research Square (Research Square),
Год журнала:
2022,
Номер
unknown
Опубликована: Авг. 3, 2022
Abstract
Recent
studies
have
shown
that
functional
connectivity
can
be
decomposed
into
its
exact
framewise
contributions,
revealing
short-lived,
infrequent,
and
high-amplitude
time
points
referred
to
as
``events.''
Although
events
contribute
disproportionately
the
time-averaged
pattern,
improve
identifiability
brain-behavior
associations,
been
linked
endogenous
hormonal
fluctuations
autism,
their
origins
remain
unclear.
Here,
we
address
this
question
using
two
independently-acquired
imaging
datasets
in
which
participants
passively
watched
movies.
We
find
synchronize
across
individuals
based
on
level
of
synchronization,
categorized
three
distinct
classes:
those
at
boundaries
between
movies,
during
do
not
all.
boundary
events,
compared
other
categories,
exhibit
greater
amplitude,
co-fluctuation
patterns,
temporal
propagation.
show
underlying
is
a
specific
mode
involving
activation
control
salience
systems
alongside
deactivation
visual
systems.
Finally,
strong
positive
relationship
similarity
time-locked
patterns
propensity
for
frames
involve
synchronous
events.
Collectively,
our
results
suggest
spatiotemporal
properties
are
non-random
locked
time-varying
stimuli.
medRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Май 14, 2023
Understanding
the
interrelationships
of
brain
function
as
measured
by
resting-state
magnetic
resonance
imaging
and
neuropsychological/behavioral
measures
in
Alzheimer's
disease
is
key
for
advancement
neuroimaging
analysis
methods
clinical
research.
The
edge
time-series
framework
recently
developed
field
network
neuroscience,
combination
with
other
science
methods,
allows
investigations
brain-behavior
relationships
that
are
not
possible
conventional
functional
connectivity
methods.
Data
from
Indiana
Disease
Research
Center
sample
(53
cognitively
normal
control,
47
subjective
cognitive
decline,
32
mild
impairment,
20
participants)
were
used
to
investigate
between
components,
each
derived
a
subset
time
points
based
on
co-fluctuation
regional
signals,
domain-specific
neuropsychological
functions.
Multiple
identified
component
approach
found
connectivity.
These
involved
attentional,
limbic,
frontoparietal,
default
mode
systems
their
interactions,
which
shown
couple
cognitive,
executive,
language,
attention
domains.
Additionally,
overlapping
results
obtained
two
different
statistical
strategies
(network
contingency
correlation
network-based
statistics
correlation).
Results
demonstrate
components
reveal
disease-relevant
observed
static
Brain Imaging and Behavior,
Год журнала:
2023,
Номер
18(1), С. 243 - 255
Опубликована: Ноя. 27, 2023
Understanding
the
interrelationships
of
brain
function
as
measured
by
resting-state
magnetic
resonance
imaging
and
neuropsychological/behavioral
measures
in
Alzheimer's
disease
is
key
for
advancement
neuroimaging
analysis
methods
clinical
research.
The
edge
time-series
framework
recently
developed
field
network
neuroscience,
combination
with
other
science
methods,
allows
investigations
brain-behavior
relationships
that
are
not
possible
conventional
functional
connectivity
methods.
Data
from
Indiana
Disease
Research
Center
sample
(53
cognitively
normal
control,
47
subjective
cognitive
decline,
32
mild
impairment,
20
participants)
were
used
to
investigate
between
components,
each
derived
a
subset
time
points
based
on
co-fluctuation
regional
signals,
domain-specific
neuropsychological
functions.
Multiple
identified
component
approach
found
connectivity.
These
involved
attentional,
limbic,
frontoparietal,
default
mode
systems
their
interactions,
which
shown
couple
cognitive,
executive,
language,
attention
domains.
Additionally,
overlapping
results
obtained
two
different
statistical
strategies
(network
contingency
correlation
network-based
statistics
correlation).
Results
demonstrate
components
reveal
disease-relevant
observed
static
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Фев. 13, 2024
Abstract
Transdiagnostic
factors
are
considered
promising
in
elucidating
the
etiological
underpinnings
of
psychiatric
comorbidities,
especially
anxiety
and
depression.
However,
their
symptom-centered
neurobiological
substrates,
encompassing
genetic
macro-micro-molecular
brain
functional
landscape,
remain
elusive.
Here,
we
develop
edge-centric
connectome-based
predictive
models
for
transdiagnostic
depression
symptoms
(sTDF).
These
estimated
from
nonlinear
Gaussian
topological
schemes
a
nationwide
sample
twin
dataset.
Edge-centric
connectome
was
found
to
be
reproducible
generalizable
neural
signatures
sTDF,
showing
high
sensitivity
neurally
representing
sTDF
similarity
patterns
attention/frontoparietal
networks.
Such
were
moderately
heritable.
Genetic
transcriptional
analyses
further
revealed
biological
enrichment
gene
expression
these
emerging
into
vessel
systems
metabolism
CMRO2
cerebellar
development
late-childhood-to-young-adulthood.
Our
findings
shed
lights
on
architectures
by
clarifying
edge-centeric
connectome-transcriptional
signature.
Brain Communications,
Год журнала:
2024,
Номер
6(6)
Опубликована: Янв. 1, 2024
Agitated
depression
(A-MDD)
is
a
severe
subtype
of
major
depressive
disorder,
with
an
increased
risk
suicidality
and
the
potential
to
evolve
into
bipolar
disorder.
Despite
its
clinical
significance,
neural
basis
remains
unclear.
We
hypothesize
that
psychomotor
agitation,
marked
by
pressured
speech
racing
thoughts,
linked
disruptions
in
brain
dynamics.
To
test
this
hypothesis,
we
examined
dynamics
using
time
delay
estimation
edge-centre
series,
as
well
dynamic
connections
between
somatomotor
network
(SMN)
default
mode
44
patients
A-MDD,
75
non-agitated
MDD
(NA-MDD),
94
healthy
controls.
Our
results
revealed
co-activity
duration
was
shorter
A-MDD
group
compared
both
NA-MDD
controls
(A-MDD
versus
NA-MDD:
Research Square (Research Square),
Год журнала:
2022,
Номер
unknown
Опубликована: Авг. 3, 2022
Abstract
Recent
studies
have
shown
that
functional
connectivity
can
be
decomposed
into
its
exact
framewise
contributions,
revealing
short-lived,
infrequent,
and
high-amplitude
time
points
referred
to
as
``events.''
Although
events
contribute
disproportionately
the
time-averaged
pattern,
improve
identifiability
brain-behavior
associations,
been
linked
endogenous
hormonal
fluctuations
autism,
their
origins
remain
unclear.
Here,
we
address
this
question
using
two
independently-acquired
imaging
datasets
in
which
participants
passively
watched
movies.
We
find
synchronize
across
individuals
based
on
level
of
synchronization,
categorized
three
distinct
classes:
those
at
boundaries
between
movies,
during
do
not
all.
boundary
events,
compared
other
categories,
exhibit
greater
amplitude,
co-fluctuation
patterns,
temporal
propagation.
show
underlying
is
a
specific
mode
involving
activation
control
salience
systems
alongside
deactivation
visual
systems.
Finally,
strong
positive
relationship
similarity
time-locked
patterns
propensity
for
frames
involve
synchronous
events.
Collectively,
our
results
suggest
spatiotemporal
properties
are
non-random
locked
time-varying
stimuli.
