PLoS Computational Biology,
Journal Year:
2025,
Volume and Issue:
21(1), P. e1012691 - e1012691
Published: Jan. 7, 2025
Identifying
the
driver
nodes
of
a
network
has
crucial
implications
in
biological
systems
from
unveiling
causal
interactions
to
informing
effective
intervention
strategies.
Despite
recent
advances
control
theory,
results
remain
inaccurate
as
number
drivers
becomes
too
small
compared
size,
thus
limiting
concrete
usability
many
real-life
applications.
To
overcome
this
issue,
we
introduced
framework
that
integrates
principles
spectral
graph
theory
and
output
controllability
project
state
into
smaller
topological
space
formed
by
Laplacian
structure.
Through
extensive
simulations
on
synthetic
real
networks,
showed
relatively
low
projected
components
can
significantly
improve
accuracy.
By
introducing
new
low-dimensional
metric
experimentally
validated
our
method
N
=
6134
human
connectomes
obtained
UK-biobank
cohort.
Results
revealed
previously
unappreciated
influential
brain
regions,
enabled
draw
directed
maps
between
differently
specialized
cerebral
systems,
yielded
insights
hemispheric
lateralization.
Taken
together,
offered
theoretically
grounded
solution
deal
with
provided
brain.
CPT Pharmacometrics & Systems Pharmacology,
Journal Year:
2019,
Volume and Issue:
9(1), P. 5 - 20
Published: Nov. 1, 2019
The
substantial
progress
made
in
the
basic
sciences
of
brain
has
yet
to
be
adequately
translated
successful
clinical
therapeutics
treat
central
nervous
system
(CNS)
diseases.
Possible
explanations
include
lack
quantitative
and
validated
biomarkers,
subjective
nature
many
endpoints,
complex
pharmacokinetic/pharmacodynamic
relationships,
but
also
possibility
that
highly
selective
drugs
CNS
do
not
reflect
interactions
different
circuits.
Although
computational
systems
pharmacology
modeling
designed
capture
essential
components
biological
been
increasingly
accepted
pharmaceutical
research
development
for
oncology,
inflammation,
metabolic
disorders,
uptake
field
very
modest.
In
this
article,
a
cross‐disciplinary
group
with
representatives
from
academia,
pharma,
regulatory,
funding
agencies
make
case
identification
exploitation
therapeutic
targets
drug
discovery
can
benefit
greatly
network
approach
span
gap
between
molecular
pathways
neuronal
circuits
ultimately
regulate
activity
behavior.
National
Institute
Neurological
Disorders
Stroke
(NINDS),
collaboration
on
Aging
(NIA),
Mental
Health
(NIMH),
Drug
Abuse
(NIDA),
Center
Advancing
Translational
Sciences
(NCATS),
convened
workshop
explore
evaluate
potential
(QSP)
development.
objective
was
identify
challenges
opportunities
QSP
as
an
accelerate
disorders.
particular,
examined
neuroscience
perform
QSP‐based
interrogation
mechanism
action
diseases,
along
more
accurate
comprehensive
method
evaluating
effects
optimizing
design
trials.
Following
up
earlier
white
paper
use
general
disease
discovery,
report
focuses
new
applications,
opportunities,
accompanying
limitations
area
based
discussions
various
stakeholders.
Cognitive Therapy and Research,
Journal Year:
2024,
Volume and Issue:
48(5), P. 791 - 807
Published: June 24, 2024
Abstract
Background
Despite
impressive
dissemination
programs
of
best-practice
therapies,
clinical
psychology
faces
obstacles
in
developing
more
efficacious
treatments
for
mental
disorders.
In
contrast
to
other
medical
disciplines,
psychotherapy
has
made
only
slow
progress
improving
treatment
outcomes.
Improvements
the
classification
disorders
could
enhance
tailoring
improve
effectiveness.
We
introduce
a
multimodal
dynamical
network
approach,
address
some
challenges
faced
by
research.
These
include
absence
comprehensive
meta-theory,
comorbidity,
substantial
diagnostic
heterogeneity,
violations
ergodicity
assumptions,
and
limited
understanding
causal
processes.
Methods
Through
application
analysis,
we
describe
how
advance
research
addressing
central
problems
field.
By
utilizing
dynamic
analysis
techniques
(e.g.,
Group
Iterative
Multiple
Model
Estimation,
multivariate
Granger
causality),
measurements
(i.e.,
psychological,
psychopathological,
neurobiological
data),
intensive
longitudinal
data
collection
Ecological
Momentary
Assessment),
inference
methods
GIMME),
our
approach
comprehension
Under
umbrella
systems
e.g.,
graph
theory
control
theory,
aim
integrate
from
longitudinal,
measurements.
Results
The
enables
as
networks
interconnected
symptoms.
It
dismantles
artificial
boundaries,
facilitating
transdiagnostic
view
psychopathology.
integration
enhances
ability
identify
influential
nodes,
prioritize
interventions,
predict
impact
therapeutic
strategies.
Conclusion
proposed
psychological
providing
individualized
models
psychopathology
suggesting
individual
angles.
Frontiers in Aging Neuroscience,
Journal Year:
2017,
Volume and Issue:
9
Published: Dec. 1, 2017
Cognitive
reserve
(CR)
is
a
protective
mechanism
that
supports
sustained
cognitive
function
following
damage
to
the
physical
brain
associated
with
age,
injury,
or
disease.
The
goal
of
research
was
identify
relationships
between
CR,
and
connectivity.
A
sample
90
cognitively
normal
adults,
ages
45-64
years,
had
their
resting-state
activity
recorded
electroencephalography
(EEG)
completed
series
memory
executive
assessments.
CR
estimated
using
years
education
verbal
IQ
scores.
Participants
were
divided
into
younger
older
age
groups
low-
high-CR
groups.
We
observed
greater
left-
than
right-hemisphere
coherence
in
participants,
right-
left-hemisphere
participants.
In
addition,
under
eyes-closed
eyes-open
recording
conditions
for
both
low-CR
more
substantial
difference
individuals
high
regardless
age.
Finally,
participants
low
exhibited
mean
whereas
opposite
pattern
CR.
Together,
these
findings
suggest
possibility
shift
relationship
connectivity
during
aging.
PLoS Computational Biology,
Journal Year:
2025,
Volume and Issue:
21(1), P. e1012691 - e1012691
Published: Jan. 7, 2025
Identifying
the
driver
nodes
of
a
network
has
crucial
implications
in
biological
systems
from
unveiling
causal
interactions
to
informing
effective
intervention
strategies.
Despite
recent
advances
control
theory,
results
remain
inaccurate
as
number
drivers
becomes
too
small
compared
size,
thus
limiting
concrete
usability
many
real-life
applications.
To
overcome
this
issue,
we
introduced
framework
that
integrates
principles
spectral
graph
theory
and
output
controllability
project
state
into
smaller
topological
space
formed
by
Laplacian
structure.
Through
extensive
simulations
on
synthetic
real
networks,
showed
relatively
low
projected
components
can
significantly
improve
accuracy.
By
introducing
new
low-dimensional
metric
experimentally
validated
our
method
N
=
6134
human
connectomes
obtained
UK-biobank
cohort.
Results
revealed
previously
unappreciated
influential
brain
regions,
enabled
draw
directed
maps
between
differently
specialized
cerebral
systems,
yielded
insights
hemispheric
lateralization.
Taken
together,
offered
theoretically
grounded
solution
deal
with
provided
brain.
