npj Parkinson s Disease,
Год журнала:
2022,
Номер
8(1)
Опубликована: Апрель 19, 2022
Adaptive
deep
brain
stimulation
(aDBS)
is
a
promising
concept
for
feedback-based
neurostimulation,
with
the
potential
of
clinical
implementation
sensing-enabled
Percept
neurostimulator.
We
aim
to
characterize
chronic
electrophysiological
activity
during
and
validate
beta-band
as
biomarker
bradykinesia.
Subthalamic
was
recorded
stepwise
amplitude
increase
OFF
medication
in
10
Parkinson's
patients
rest
finger
tapping.
Offline
analysis
wavelet-transformed
assessment
inter-variable
relationships
linear
mixed
effects
models
were
implemented.
There
suppression
low-beta
increasing
intensity
(p
=
0.002).
Low-beta
power
negatively
correlated
movement
speed
predictive
velocity
improvements
<
0.001),
beta
0.001).
Here,
we
modulation
motor
performance.
Our
investigations
support
use
electrophysiology
therapy
optimization,
providing
evidence
aDBS.
New England Journal of Medicine,
Год журнала:
2018,
Номер
379(23), С. 2237 - 2245
Опубликована: Дек. 5, 2018
Complex
neurologic
and
psychiatric
syndromes
cannot
be
understood
on
the
basis
of
focal
brain
lesions.
Functional
neuroimaging,
maps
interrelated
regions
called
connectome,
combination
lesion
analysis
with
networks
connectome
offer
a
new
way
to
understand
function
disease.
American Journal of Psychiatry,
Год журнала:
2020,
Номер
177(5), С. 435 - 446
Опубликована: Март 12, 2020
Treatment
of
different
depression
symptoms
may
require
brain
stimulation
targets
with
underlying
circuits.
The
authors
sought
to
identify
such
targets,
which
could
improve
the
efficacy
therapeutic
and
facilitate
personalized
therapy.The
retrospectively
analyzed
two
independent
cohorts
patients
who
received
left
prefrontal
transcranial
magnetic
(TMS)
for
treatment
(discovery
sample,
N=30;
active
replication
N=81;
sham
N=87).
Each
patient's
TMS
site
was
mapped
circuits
using
functional
connectivity
MRI
from
a
large
connectome
database
(N=1,000).
Circuits
associated
improvement
in
each
symptom
were
identified
then
clustered
based
on
similarity.
tested
reproducibility
across
data
sets
whether
symptom-specific
derived
one
set
predict
other
cohort.The
distinct
circuit
effective
discrete
clusters
depressive
symptoms.
Dysphoric
symptoms,
as
sadness
anhedonia,
responded
best
circuit,
while
anxiety
somatic
circuit.
These
maps
reproducible,
predicted
patient
cohorts,
specific
compared
stimulation.
an
exploratory
analysis
sites
14
clinical
trials.Distinct
better
retrospective
sets.
can
be
prospectively
randomized
trial.
This
data-driven
approach
identifying
prove
useful
disorders
neuromodulation
therapy.
Nature Communications,
Год журнала:
2020,
Номер
11(1)
Опубликована: Июль 3, 2020
Abstract
Multiple
surgical
targets
for
treating
obsessive-compulsive
disorder
with
deep
brain
stimulation
(DBS)
have
been
proposed.
However,
different
may
modulate
the
same
neural
network
responsible
clinical
improvement.
We
analyzed
data
from
four
cohorts
of
patients
(
N
=
50)
that
underwent
DBS
to
anterior
limb
internal
capsule
(ALIC),
nucleus
accumbens
or
subthalamic
(STN).
The
fiber
bundle
was
associated
optimal
response
in
targeting
either
structure.
This
connected
frontal
regions
STN.
When
informing
tract
target
based
on
first
cohort,
improvements
second
could
be
significantly
predicted,
and
vice
versa.
To
further
confirm
results,
eight
a
third
center
six
fourth
were
predicted
their
overlap
this
tract.
Our
results
show
connectivity-derived
models
inform
across
targets,
surgeons
centers.
identified
is
openly
available
atlas
form.
NeuroImage Clinical,
Год журнала:
2017,
Номер
17, С. 80 - 89
Опубликована: Окт. 12, 2017
Deep
brain
stimulation
(DBS)
is
a
neurosurgical
intervention
where
electrodes
are
permanently
implanted
into
the
in
order
to
modulate
pathologic
neural
activity.
The
post-operative
reconstruction
of
DBS
important
for
an
efficient
parameter
tuning.
A
major
limitation
existing
approaches
electrode
from
imaging
that
prevents
clinical
routine
use
they
manual
or
semi-automatic,
and
thus
both
time-consuming
subjective.
Moreover,
methods
rely
on
simplified
model
straight
line
trajectory,
rather
than
more
realistic
curved
trajectory.
main
contribution
this
paper
first
time
we
present
highly
accurate
fully
automated
method
considers
trajectories.
robustness
our
proposed
demonstrated
using
multi-center
dataset
consisting
N
=
44
electrodes.
In
all
cases
trajectories
were
successfully
identified
reconstructed.
addition,
accuracy
quantitatively
high-accuracy
phantom
with
known
ground
truth.
experiment,
could
detect
individual
contacts
high
trajectory
reached
error
level
below
100
μm
(0.046
±
0.025
mm).
An
implementation
made
publicly
available
such
it
can
directly
be
used
by
researchers
clinicians.
This
constitutes
step
towards
future
integration
lead
standard
care.
