bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 16, 2024
Analyses
of
functional
connectivity
(FC)
in
resting-state
brain
networks
(RSNs)
have
generated
many
insights
into
cognition.
However,
the
mechanistic
underpinnings
FC
and
RSNs
are
still
not
well-understood.
It
remains
debated
whether
resting
state
activity
is
best
characterized
as
noise-driven
fluctuations
around
a
single
stable
state,
or
instead,
nonlinear
dynamical
system
with
nontrivial
attractors
embedded
RSNs.
Here,
we
provide
evidence
for
latter,
by
constructing
whole-brain
systems
models
from
individual
fMRI
(rfMRI)
recordings,
using
Mesoscale
Individualized
NeuroDynamic
(MINDy)
platform.
The
MINDy
consist
hundreds
neural
masses
representing
parcels,
connected
fully
trainable,
individualized
weights.
We
found
that
our
manifested
diverse
taxonomy
attractor
landscapes
including
multiple
equilibria
limit
cycles.
when
projected
anatomical
space,
these
mapped
onto
limited
set
canonical
RSNs,
default
mode
network
(DMN)
frontoparietal
control
(FPN),
which
were
reliable
at
level.
Further,
creating
convex
combinations
models,
bifurcations
induced
recapitulated
full
spectrum
dynamics
via
fitting.
These
findings
suggest
traverses
dynamics,
generates
several
distinct
but
anatomically
overlapping
landscapes.
Treating
rfMRI
unimodal
stationary
process
(i.e.,
conventional
FC)
may
miss
critical
properties
structure
within
brain.
Instead,
be
better
captured
through
modeling
analytic
approaches.
results
new
generative
mechanisms
intrinsic
spatiotemporal
organization
networks.
Journal of Neuroscience,
Год журнала:
2021,
Номер
41(12), С. 2684 - 2702
Опубликована: Фев. 4, 2021
Resting-state
functional
connectivity
has
provided
substantial
insight
into
intrinsic
brain
network
organization,
yet
the
importance
of
task-related
change
from
that
organization
remains
unclear.
Indeed,
such
changes
are
known
to
be
small,
suggesting
they
may
have
only
minimal
relevance.
Alternatively,
despite
their
small
amplitude,
these
essential
for
ability
human
adaptively
alter
its
functionality
via
rapid
in
inter-regional
relationships.
We
used
activity
flow
mapping-an
approach
building
empirically
derived
models-to
quantify
task-state
(above
and
beyond
resting-state
connectivity)
shaping
cognitive
task
activations
(female
male)
brain.
found
could
better
predict
independent
fMRI
across
all
24
conditions
360
cortical
regions
tested.
Further,
we
prediction
accuracy
was
strongly
driven
by
individual-specific
patterns,
while
patterns
other
tasks
(task-general
still
improved
predictions
connectivity.
Additionally,
since
models
simulate
how
task-evoked
(which
underlie
behavior)
generated,
results
provide
mechanistic
why
prior
studies
correlations
between
individual
differences
behavior.
These
findings
suggest
connections
play
an
important
role
dynamically
reshaping
shifting
neural
during
performance.SIGNIFICANCE
STATEMENT
Human
cognition
is
highly
dynamic,
similar
rest
states.
hypothesized
that,
this
overall
stability,
(resting-state)
contribute
performance.
Given
emerge
through
interactions,
leveraged
connectivity-based
using
versus
This
revealed
increased
substantially,
demonstrating
likely
relevance
dynamic
processes
size
changes.
NeuroImage,
Год журнала:
2020,
Номер
221, С. 117141 - 117141
Опубликована: Июль 12, 2020
Many
studies
have
identified
the
role
of
localized
and
distributed
cognitive
functionality
by
mapping
either
local
task-related
activity
or
functional
connectivity
(FC).
However,
few
directly
explored
relationship
between
a
brain
region's
task
its
FC.
Here
we
systematically
evaluated
differential
contributions
FC
changes
to
identify
processes
across
cortical
hierarchy.
We
found
that
multiple
tasks,
magnitude
regional
task-evoked
was
high
in
unimodal
areas,
but
low
transmodal
areas.
In
contrast,
task-state
significantly
reduced
areas
relative
This
revealed
strong
negative
regions
associated
with
previously
reported
principal
gradient
macroscale
organization.
Moreover,
this
dissociation
corresponded
hierarchical
differences
intrinsic
timescale
estimated
from
resting-state
fMRI
region
myelin
content
structural
MRI.
Together,
our
results
contribute
growing
literature
illustrating
representing
processes.
Journal of Neuroscience,
Год журнала:
2020,
Номер
40(36), С. 6949 - 6968
Опубликована: Июль 30, 2020
Functional
connectivity
(FC)
studies
have
identified
at
least
two
large-scale
neural
systems
that
constitute
cognitive
control
networks,
the
frontoparietal
network
(FPN)
and
cingulo-opercular
(CON).
Control
networks
are
thought
to
support
goal-directed
cognition
behavior.
It
was
previously
shown
FPN
flexibly
shifts
its
global
pattern
according
task
goal,
consistent
with
a
"flexible
hub"
mechanism
for
control.
Our
aim
build
on
this
finding
develop
functional
cartography
(a
multimetric
profile)
of
in
terms
dynamic
properties.
We
quantified
properties
(male
female)
humans
using
high-control-demand
paradigm
involving
switching
among
64
sets.
hypothesized
is
enacted
by
CON
via
distinct
but
complementary
roles
reflected
dynamics.
Consistent
flexible
"coordinator"
mechanism,
connections
were
varied
across
tasks,
while
maintaining
within-network
aid
cross-region
coordination.
"switcher"
regions
switched
other
task-dependent
manner,
driven
primarily
reduced
regions.
This
results
suggests
acts
as
dynamic,
coordinator
goal-relevant
information,
transiently
disbands
lend
processing
resources
networks.
dynamics
reveals
dissociation
between
prominent
suggesting
mechanisms
underlying
cognition.SIGNIFICANCE
STATEMENT
Cognitive
supports
variety
behaviors
requiring
cognition,
such
rapidly
tasks.
Furthermore,
negatively
impacted
mental
illnesses.
used
tools
from
science
characterize
implementation
brain
systems.
revealed
systems,
(CON)
controlling
reconfigurations.
The
exhibited
(orchestrating
changes),
acted
switcher
(switching
specific
resources).
These
findings
reveal
an
distinction
processes
may
be
applicable
clinical,
educational,
machine
learning
work
targeting
flexibility.
Communications Biology,
Год журнала:
2021,
Номер
4(1)
Опубликована: Июнь 15, 2021
Spontaneous
neural
activity
fluctuations
have
been
shown
to
influence
trial-by-trial
variation
in
perceptual,
cognitive,
and
behavioral
outcomes.
However,
the
complex
electrophysiological
mechanisms
by
which
these
shape
stimulus-evoked
remain
largely
be
explored.
Employing
a
large-scale
magnetoencephalographic
dataset
an
electroencephalographic
replication
dataset,
we
investigate
relationship
between
spontaneous
evoked
across
range
of
variables.
We
observe
that
for
high-frequency
activity,
high
pre-stimulus
amplitudes
lead
greater
desynchronization,
while
low
frequencies,
induce
larger
degrees
event-related
synchronization.
further
decompose
power
into
oscillatory
scale-free
components,
demonstrating
different
patterns
spontaneous-evoked
correlation
each
component.
Finally,
find
correlations
time-domain
signals.
Overall,
demonstrate
dynamics
multiple
variables
exhibit
distinct
relationships
their
result
carries
implications
experimental
design
analysis
non-invasive
electrophysiology.
Nature Communications,
Год журнала:
2022,
Номер
13(1)
Опубликована: Фев. 3, 2022
Abstract
The
human
ability
to
adaptively
implement
a
wide
variety
of
tasks
is
thought
emerge
from
the
dynamic
transformation
cognitive
information.
We
hypothesized
that
these
transformations
are
implemented
via
conjunctive
activations
in
“conjunction
hubs”—brain
regions
selectively
integrate
sensory,
cognitive,
and
motor
activations.
used
recent
advances
using
functional
connectivity
map
flow
activity
between
brain
construct
task-performing
neural
network
model
fMRI
data
during
control
task.
verified
importance
conjunction
hubs
computations
by
simulating
over
this
empirically-estimated
model.
These
empirically-specified
simulations
produced
above-chance
task
performance
(motor
responses)
integrating
sensory
rule
hubs.
findings
reveal
role
supporting
flexible
computations,
while
demonstrating
feasibility
models
gain
insight
into
brain.
NeuroImage,
Год журнала:
2020,
Номер
226, С. 117549 - 117549
Опубликована: Ноя. 26, 2020
Compelling
evidence
suggests
the
need
for
more
data
per
individual
to
reliably
map
functional
organization
of
human
connectome.
As
notion
that
'more
is
better'
emerges
as
a
golden
rule
connectomics,
researchers
find
themselves
grappling
with
challenges
how
obtain
desired
amounts
participant
in
practical
manner,
particularly
retrospective
aggregation.
Increasingly,
aggregation
across
all
fMRI
scans
available
an
being
viewed
solution,
regardless
scan
condition
(e.g.,
rest,
task,
movie).
A
number
open
questions
exist
regarding
process
and
impact
different
decisions
on
reliability
resultant
aggregate
data.
We
leveraged
availability
highly
sampled
test-retest
datasets
systematically
examine
strategies
cortical
connectomics.
Specifically,
we
compared
connectivity
estimates
derived
after
concatenating
from:
1)
multiple
under
same
state,
2)
states
(i.e.
hybrid
or
general
connectivity),
3)
subsets
one
long
scan.
also
varied
processing
global
signal
regression,
ICA-FIX,
task
regression)
estimation
procedures.
When
total
time
points
equal,
state
held
constant,
shorter
had
clear
advantage
over
single
However,
this
was
not
necessarily
true
when
conditions),
where
from
states.
Concatenating
fewer
numbers
are
reliable
tends
yield
higher
reliability.
Our
findings
provide
overview
dependencies
concatenation
should
be
considered
optimize
analysis