Journal of Medical Internet Research,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Oct. 30, 2024
There
is
burgeoning
interest
in
the
application
of
neuroscientific
technology
to
facilitate
meditation
and
lead
beneficial
psychological
outcomes.
One
popular
approach
using
consumer-grade
neurofeedback
devices
deliver
feedback
on
brain
targets
during
(mindfulness-based
neurofeedback).
It
hypothesized
that
optimizing
like
alpha
theta
band
activity
may
allow
meditators
experience
deeper
mindfulness
thus
This
study
aimed
systematically
review
meta-analyze
impacts
mindfulness-based
compared
with
control
conditions.
Included
studies
involved
practice
operationalized
as
open
monitoring
or
focused
attention
meditation.
was
preregistered.
A
total
16
randomized
controlled
training
trials,
well
5
within-participant
designs
were
included,
encompassing
763
167
unique
participants,
respectively.
Effects
categorized
outcomes
(ie,
distress,
cognitive
function,
physiological
health)
process
variables
state
measures).
Study
risk
bias,
reporting
publication
bias
assessed.
Samples
typically
small
(n=30-50),
majority
used
apps
controls.
To
neurofeedback,
most
Muse
device
(11/16
trials
[RCTs]).
a
modest
effect
for
decreases
distress
controls
(k=11,
g=-0.16,
P=.03),
heterogeneity
low
(I2<
0.25).
However,
there
no
evidence
improvements
cognition
(k=7,
g=0.07,
P=.48),
(k=9,
g=0.02,
P=.83),
health
g=0.11,
P=.57)
Mechanistic
modulation
not
found
RCTs
designs.
Sex
(male
female),
age,
clinical
status,
quality,
active
passive
controls,
sample
size,
duration
did
moderate
effects.
some
but
bias.
Adverse
effects
assessed
19
out
21
2
them.
Assertions
can
participants
modulate
their
brains
deepen
meditations
are
currently
supported.
possible
rely
"neurosuggestion"
(placebo
neurotechnology).
Future
research
should
examine
more
extensive
calibration
individualization
devices,
larger
sizes,
gold-standard
sham-controlled
RCTs.
Meditation
practices
have
demonstrated
numerous
psychological
and
physiological
benefits,
yet
capturing
the
neural
correlates
of
varying
meditative
depths
remains
challenging.
This
study
aimed
to
decode
self-reported
time-varying
depth
in
expert
practitioners
using
EEG.
Expert
Vipassana
meditators
(n=34)
participated
two
separate
sessions.
Participants
reported
their
on
a
personally
defined
1-5
scale
both
traditional
probing
novel
"spontaneous
emergence"
method.
EEG
activity
effective
connectivity
theta,
alpha,
gamma
bands
was
used
predict
machine/deep
learning,
including
method
that
fused
source
information.
We
achieved
significant
accuracy
decoding
across
unseen
The
yielded
improved
performance
correlated
more
strongly
with
post-session
outcome
measures.
Best
by
machine
learning
which
spatial,
spectral,
Conventional
channel-level
methods
pre-selected
default
mode
network
regions
fell
short
complex
dynamics
associated
meditation
depths.
demonstrates
feasibility
findings
highlight
complex,
multivariate
nature
during
introduce
as
an
ecologically
valid
less
obtrusive
experiential
sampling
These
results
implications
for
advancing
neurofeedback
techniques
enhancing
our
understanding
practices.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 15, 2024
Neurofeedback
concurrent
with
mindfulness
meditation
may
reveal
effects
on
the
brain
and
facilitate
improved
mental
health
outcomes.
Here,
we
systematically
reviewed
EEG
fMRI
studies
of
neurofeedback
(mbNF)
followed
PRISMA
guidelines.
We
identified
10
reports,
consisting
177
unique
participants,
9
242
participants.
Studies
focused
primarily
downregulating
default-mode
network
(DMN).
Although
found
decreases
in
DMN
activations
during
neurofeedback,
there
is
a
lack
evidence
for
transfer
effects,
majority
did
not
employ
adequate
controls,
e.g.
sham
neurofeedback.
Accordingly,
have
been
confounded
by
general
task-related
deactivation.
typically
examined
alpha,
gamma,
theta
frequency
bands,
most
robust
supporting
modulation
band
activity.
Both
mbNF
implemented
high
fidelity
clinical
populations.
However,
benefits
established.
In
general,
would
benefit
from
sham-controlled
RCTs,
as
well
clear
reporting
(e.g.
CRED-NF).
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Oct. 26, 2024
In
this
randomized,
controlled,
and
double-blind
experiment
with
a
relatively
large
sample
(n
=
262),
novel
technique
of
audiovisual
stimulation
(AVS)
was
demonstrated
to
substantially
improve
self-reported
mood
states
by
reducing
several
negative
affects,
including
anxiety
depression,
enhancing
performance
on
mood-sensitive
cognitive
tasks.
Most
the
AVS
effects
were
highly
similar
whether
binaural
beats
present
or
not
regardless
duration
experience.
Remarkably,
benefits
from
closely
aligned
those
achieved
through
breath-focused
meditation
additional
evidence
that
brief
exposure
approximately
five
minutes
may
be
sufficient
even
optimal
for
improving
comparable
greater
degree
than
sessions
equal
longer
durations
(11-22
min).
These
exciting
findings
position
as
promising
avenue
cognition
enhancement
potentially
more
accessible
"plug-and-play"
alternative
meditation,
which
is
especially
relevant
considering
high
attrition
rates
commonly
observed
in
practices.
In
this
randomized,
controlled,
and
double-blind
experiment
with
a
relatively
large
sample
(n=262),
novel
technique
of
audiovisual
stimulation
(AVS)
was
demonstrated
to
substantially
improve
self-reported
mood
states
by
reducing
several
negative
affects,
including
anxiety
depression,
enhancing
performance
on
mood-sensitive
cognitive
tasks.
Most
the
AVS
effects
were
highly
similar
whether
binaural
beats
present
or
not
regardless
duration
experience.
Remarkably,
benefits
from
closely
aligned
those
achieved
through
breath-focused
meditation
additional
evidence
that
brief
exposure
approximately
five
minutes
may
be
sufficient
even
optimal
for
improving
comparable
greater
degree
than
sessions
equal
longer
durations
(11
22
minutes).
These
exciting
findings
position
as
promising
avenue
cognition
enhancement
potentially
more
accessible
“plug-and-play”
alternative
meditation,
which
is
especially
relevant
considering
high
attrition
rates
commonly
observed
in
practices.
Research Square (Research Square),
Journal Year:
2024,
Volume and Issue:
unknown
Published: March 14, 2024
Abstract
In
this
randomized,
controlled,
and
double-blind
experiment
with
a
relatively
large
sample
(n
=
262),
novel
technique
of
audiovisual
stimulation
(AVS)
was
demonstrated
to
substantially
improve
self-reported
mood
states
by
reducing
several
negative
affects,
including
anxiety
depression,
enhancing
performance
on
mood-sensitive
cognitive
tasks.
Most
the
AVS
effects
were
highly
similar
whether
binaural
beats
present
or
not
regardless
duration
experience.
Remarkably,
benefits
from
closely
aligned
those
achieved
through
breath-focused
meditation
additional
evidence
that
brief
exposure
approximately
five
minutes
may
be
sufficient
even
optimal
for
improving
comparable
greater
degree
than
sessions
equal
longer
durations
(11
22
minutes).
These
exciting
findings
position
as
promising
avenue
psychological
enhancement
potentially
more
accessible
“plug-and-play”
alternative
meditation,
which
is
especially
relevant
considering
high
attrition
rates
commonly
observed
in
practices.
Identifying
the
brain
mechanisms
that
underlie
salutary
effects
of
mindfulness,
meditation,
and
related
practices
is
a
critical
goal
contemplative
neuroscience.
Here
we
suggest
use
multivariate
predictive
models
represents
promising
powerful
methodology
could
be
better
leveraged
to
pursue
this
goal.
We
describe
primary
principles
approach,
including
decoding,
classification,
model-based
analyses,
all
which
represent
strong
departure
from
conventional
mapping
approaches.
highlight
two
such
research
strategies
–
state
induction
neuromarker
identification
provide
illustrative
examples
how
these
approaches
have
been
used
examine
central
questions
in
as
distinction
between
internally
directed
focused
attention
mind
wandering,
role
mindfulness
interventions
on
somatic
pain
drug-related
cravings.
conclude
by
discussing
important
issues
addressed
with
future
research,
key
tradeoffs
using
personalized
versus
population-based
approach
modeling.