NeuroImage,
Journal Year:
2018,
Volume and Issue:
184, P. 36 - 44
Published: Sept. 8, 2018
There
is
increasing
interest
in
exploring
the
use
of
functional
MRI
neurofeedback
(fMRI-NF)
as
a
therapeutic
technique
for
range
neurological
conditions
such
stroke
and
Parkinson's
disease
(PD).
One
main
potential
fMRI-NF
to
enhance
volitional
control
damaged
or
dysfunctional
neural
nodes
networks
via
closed-loop
feedback
model
using
mental
imagery
catalyst
self-regulation.
The
choice
target
node/network
direction
regulation
(increase
decrease
activity)
are
central
design
considerations
studies.
Whilst
it
remains
unclear
whether
primary
motor
cortex
(M1)
can
be
activated
during
imagery,
supplementary
area
(SMA)
has
been
robustly
imagery.
Such
differences
between
important
because
these
areas
differentially
affected
by
PD,
grade
self-regulation
activity
likely
have
substantial
influence
on
clinical
effects
cost
effectiveness
NF-based
interventions.
In
this
study
we
therefore
investigated
firstly
healthy
subjects
would
able
achieve
hand-representation
M1
SMA
training.
was
significant
fMRI-NF,
whereas
increased,
albeit
not
with
predicated
graded
effect.
This
implications
protocols
that
employ
modulate
specific
regions
brain
determine
how
they
may
tailored
neurorehabilitation.
Brain,
Journal Year:
2020,
Volume and Issue:
143(6), P. 1674 - 1685
Published: Jan. 17, 2020
Abstract
Neurofeedback
has
begun
to
attract
the
attention
and
scrutiny
of
scientific
medical
mainstream.
Here,
neurofeedback
researchers
present
a
consensus-derived
checklist
that
aims
improve
reporting
experimental
design
standards
in
field.
PLoS Biology,
Journal Year:
2019,
Volume and Issue:
17(4), P. e3000042 - e3000042
Published: April 18, 2019
When
collecting
large
amounts
of
neuroimaging
data
associated
with
psychiatric
disorders,
images
must
be
acquired
from
multiple
sites
because
the
limited
capacity
a
single
site.
However,
site
differences
represent
barrier
when
acquiring
multisite
data.
We
utilized
traveling-subject
dataset
in
conjunction
multisite,
multidisorder
to
demonstrate
that
are
composed
biological
sampling
bias
and
engineering
measurement
bias.
The
effects
on
resting-state
functional
MRI
connectivity
based
pairwise
correlations
both
types
were
greater
than
or
equal
disorder
differences.
Furthermore,
our
findings
indicated
each
can
sample
only
subpopulation
participants.
This
result
suggests
it
is
essential
collect
as
many
possible
appropriately
estimate
distribution
grand
population.
Finally,
we
developed
novel
harmonization
method
removed
by
using
achieved
reduction
29%
improvement
signal-to-noise
ratios
40%.
Our
results
provide
fundamental
knowledge
regarding
effects,
which
important
for
future
research
Proceedings of the National Academy of Sciences,
Journal Year:
2018,
Volume and Issue:
115(13), P. 3470 - 3475
Published: March 6, 2018
Significance
Conventional
therapies
for
the
treatment
of
anxiety
disorders
are
aversive,
and
as
a
result,
many
patients
terminate
prematurely.
We
have
developed
an
unconscious
method
to
bypass
unpleasantness
in
conscious
exposure
using
functional
magnetic
resonance
imaging
neural
reinforcement.
Using
this
method,
participants
learn
generate
brain
patterns
similar
multivariate
pattern
feared
animal.
demonstrate
double-blind
placebo-controlled
experiment
that
reinforcement
can
lead
reliable
reductions
physiological
fear
responses.
Crucially,
intervention
be
achieved
completely
unconsciously
without
any
aversive
reaction.
Extending
our
approach
other
forms
psychopathologies,
such
posttraumatic
stress
disorders,
might
eventually
provide
another
means
currently
receiving
insufficient
treatments.
Social Cognitive and Affective Neuroscience,
Journal Year:
2020,
Volume and Issue:
15(4), P. 487 - 509
Published: April 1, 2020
Abstract
The
family
of
neuroimaging
analytical
techniques
known
as
multivoxel
pattern
analysis
(MVPA)
has
dramatically
increased
in
popularity
over
the
past
decade,
particularly
social
and
affective
neuroscience
research
using
functional
magnetic
resonance
imaging
(fMRI).
MVPA
examines
patterns
neural
responses,
rather
than
analyzing
single
voxel-
or
region-based
values,
is
customary
conventional
univariate
analyses.
Here,
we
provide
a
practical
introduction
to
its
most
popular
variants
(namely,
representational
similarity
(RSA)
decoding
analyses,
such
classification
machine
learning)
for
neuroscientists
all
levels,
those
new
methods.
We
discuss
how
differs
from
traditional
mass-univariate
benefits
offers
neuroscientists,
experimental
design
considerations,
step-by-step
instructions
implement
specific
analyses
one’s
own
dataset
issues
that
are
currently
facing
NeuroImage,
Journal Year:
2018,
Volume and Issue:
188, P. 539 - 556
Published: Dec. 17, 2018
Real-time
functional
magnetic
resonance
imaging
(fMRI)
neurofeedback
is
an
experimental
framework
in
which
fMRI
signals
are
presented
to
participants
a
real-time
manner
change
their
behaviors.
Changes
behaviors
after
postulated
be
caused
by
neural
plasticity
driven
the
induction
of
specific
targeted
activities
at
neuronal
level
(targeted
model).
However,
some
research
groups
argued
that
behavioral
changes
conventional
studies
explained
alternative
accounts,
including
placebo
effect
and
physiological
artifacts.
Recently,
decoded
(DecNef)
has
been
developed
as
result
adapting
new
technological
advancements,
implicit
multivariate
analyses.
DecNef
provides
strong
evidence
for
model
while
refuting
abovementioned
accounts.
In
this
review,
we
first
discuss
how
refutes
Second,
propose
shows
occurs
during
training.
Finally,
computational
empirical
supports
model.
Clarification
mechanisms
would
lead
development
more
advanced
methods
may
serve
powerful
tools
both
basic
clinical
research.
Psychotherapy and Psychosomatics,
Journal Year:
2019,
Volume and Issue:
88(1), P. 5 - 15
Published: Jan. 1, 2019
<b><i>Background:</i></b>
Deficient
emotion
regulation
and
exaggerated
anxiety
represent
a
major
transdiagnostic
psychopathological
marker.
On
the
neural
level
these
deficits
have
been
closely
linked
to
impaired,
yet
treatment-sensitive,
prefrontal
regulatory
control
over
amygdala.
Gaining
direct
pathways
could
therefore
provide
an
innovative
promising
intervention
regulate
anxiety.
To
this
end
current
proof-of-concept
study
evaluated
feasibility,
functional
relevance
maintenance
of
novel
connectivity-informed
real-time
fMRI
neurofeedback
training.
<b><i>Methods:</i></b>
In
randomized
crossover
sham-controlled
design,
26
healthy
subjects
with
high
underwent
fMRI-guided
training
enhance
connectivity
between
ventrolateral
cortex
(vlPFC)
amygdala
(target
pathway)
during
threat
exposure.
Maintenance
was
assessed
after
3
days
in
absence
feedback.
Training-induced
changes
target
pathway
ratings
served
as
primary
outcomes.
<b><i>Results:</i></b>
Training
target,
not
sham
control,
significantly
increased
amygdala-vlPFC
decreased
levels
Stronger
increases
were
associated
higher
reduction
on
group
level.
At
follow-up,
volitional
maintained
<b><i>Conclusions:</i></b>
The
present
results
demonstrate
for
first
time
that
successful
self-regulation
amygdala-prefrontal
top-down
circuits
may
As
such,
findings
underscore
both
critical
contribution
therapeutic
potential
neurofeedback.