Neuroscience & Biobehavioral Reviews,
Journal Year:
2017,
Volume and Issue:
75, P. 53 - 64
Published: Jan. 16, 2017
Traditional
approaches
to
understanding
the
brain's
resilience
neuropathology
have
identified
neurophysiological
variables,
often
described
as
brain
or
cognitive
"reserve,"
associated
with
better
outcomes.
However,
mechanisms
of
function
and
in
large-scale
networks
remain
poorly
understood.
Dynamic
network
theory
may
provide
a
basis
for
substantive
advances
functional
human
brain.
In
this
perspective,
we
describe
recent
theoretical
from
control
framework
investigating
level
underlying
dynamics
neuroplasticity
We
opportunities
offered
by
application
at
connectome
understand
inform
translational
intervention.
Nature Communications,
Journal Year:
2018,
Volume and Issue:
9(1)
Published: Jan. 18, 2018
The
brain's
functional
diversity
is
reflected
in
the
meso-scale
architecture
of
its
connectome,
i.e.
division
into
clusters
and
communities
topologically-related
brain
regions.
dominant
view,
one
that
reinforced
by
current
analysis
techniques,
are
strictly
assortative
segregated
from
another,
purportedly
for
purpose
carrying
out
specialized
information
processing.
Such
a
however,
precludes
possibility
non-assortative
could
engender
richer
repertoire
allowing
more
complex
set
inter-community
interactions.
Here,
we
use
weighted
stochastic
blockmodels
to
uncover
\emph{Drosophila},
mouse,
rat,
macaque,
human
connectomes.
We
confirm
while
many
assortative,
others
form
core-periphery
disassortative
structures,
which
better
recapitulate
observed
patterns
connectivity
mouse
gene
co-expression
than
other
community
detection
techniques.
define
network
measures
quantifying
types
regions
participate.
Finally,
show
peaked
control
subcortical
systems
humans,
individual
differences
within
those
predicts
cognitive
performance
on
Stroop
Navon
tasks.
In
summary,
our
report
paints
diverse
portrait
connectome
structure
demonstrates
relevance
performance.
Communications Biology,
Journal Year:
2020,
Volume and Issue:
3(1)
Published: May 22, 2020
A
diverse
set
of
white
matter
connections
supports
seamless
transitions
between
cognitive
states.
However,
it
remains
unclear
how
these
guide
the
temporal
progression
large-scale
brain
activity
patterns
in
different
Here,
we
analyze
brain's
trajectories
across
a
single
time
point
from
functional
magnetic
resonance
imaging
data
acquired
during
resting
state
and
an
n-back
working
memory
task.
We
find
that
specific
sequences
are
modulated
by
load,
associated
with
age,
related
to
task
performance.
Using
diffusion-weighted
same
subjects,
apply
tools
network
control
theory
show
linear
spread
along
constrains
probabilities
at
rest,
while
stimulus-driven
visual
inputs
explain
observed
Overall,
results
elucidate
structural
underpinnings
cognitively
developmentally
relevant
spatiotemporal
dynamics.
Cell Reports,
Journal Year:
2019,
Volume and Issue:
28(10), P. 2554 - 2566.e7
Published: Sept. 1, 2019
Optimizing
direct
electrical
stimulation
for
the
treatment
of
neurological
disease
remains
difficult
due
to
an
incomplete
understanding
its
physical
propagation
through
brain
tissue.
Here,
we
use
network
control
theory
predict
how
spreads
white
matter
influence
spatially
distributed
dynamics.
We
test
theory's
predictions
using
a
unique
dataset
comprising
diffusion
weighted
imaging
and
electrocorticography
in
epilepsy
patients
undergoing
grid
stimulation.
find
statistically
significant
shared
variance
between
predicted
activity
state
transitions
observed
transitions.
then
optimal
framework
posit
testable
hypotheses
regarding
which
states
structural
properties
will
efficiently
improve
memory
encoding
when
stimulated.
Our
work
quantifies
role
that
architecture
plays
guiding
dynamics
offers
empirical
support
utility
explaining
brain's
response
Neuroscience & Biobehavioral Reviews,
Journal Year:
2017,
Volume and Issue:
75, P. 53 - 64
Published: Jan. 16, 2017
Traditional
approaches
to
understanding
the
brain's
resilience
neuropathology
have
identified
neurophysiological
variables,
often
described
as
brain
or
cognitive
"reserve,"
associated
with
better
outcomes.
However,
mechanisms
of
function
and
in
large-scale
networks
remain
poorly
understood.
Dynamic
network
theory
may
provide
a
basis
for
substantive
advances
functional
human
brain.
In
this
perspective,
we
describe
recent
theoretical
from
control
framework
investigating
level
underlying
dynamics
neuroplasticity
We
opportunities
offered
by
application
at
connectome
understand
inform
translational
intervention.
