Science,
Journal Year:
2022,
Volume and Issue:
378(6616), P. 160 - 168
Published: Oct. 13, 2022
There
has
been
a
long-standing
demand
for
noninvasive
neuroimaging
methods
that
can
detect
neuronal
activity
at
both
high
temporal
and
spatial
resolution.
We
present
two-dimensional
fast
line-scan
approach
enables
direct
imaging
of
with
millisecond
precision
while
retaining
the
resolution
magnetic
resonance
(MRI).
This
was
demonstrated
through
in
vivo
mouse
brain
9.4
tesla
during
electrical
whisker-pad
stimulation.
In
spike
recording
optogenetics
confirmed
correlation
observed
MRI
signal
neural
activity.
It
also
captured
sequential
laminar-specific
propagation
along
thalamocortical
pathway.
high-resolution,
will
open
up
new
avenues
science
by
providing
deeper
understanding
brain's
functional
organization,
including
temporospatial
dynamics
networks.
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: Feb. 6, 2023
Abstract
Spontaneous
fluctuations
in
functional
magnetic
resonance
imaging
(fMRI)
signals
correlate
across
distant
brain
areas,
shaping
functionally
relevant
intrinsic
networks.
However,
the
generative
mechanism
of
fMRI
signal
correlations,
and
particular
link
with
locally-detected
ultra-slow
oscillations,
are
not
fully
understood.
To
investigate
this
link,
we
record
ultrafast
ultrahigh
field
(9.4
Tesla,
temporal
resolution
=
38
milliseconds)
from
female
rats
three
anesthesia
conditions.
Power
at
frequencies
extending
up
to
0.3
Hz
is
detected
consistently
rat
brains
modulated
by
level.
Principal
component
analysis
reveals
a
repertoire
modes,
which
transient
oscillations
organize
fixed
phase
relationships
distinct
cortical
subcortical
structures.
Oscillatory
modes
found
vary
between
conditions,
resonating
faster
under
medetomidine
sedation
reducing
both
number,
frequency,
duration
addition
isoflurane.
Peaking
power
within
clear
anatomical
boundaries,
these
oscillatory
point
an
emergent
systemic
property.
This
work
provides
additional
insight
into
origin
organizing
principles
underpinning
spontaneous
long-range
connectivity.
Diagnostics,
Journal Year:
2025,
Volume and Issue:
15(4), P. 456 - 456
Published: Feb. 13, 2025
Background/Objectives:
The
following
systematic
review
integrates
neuroimaging
techniques
with
deep
learning
approaches
concerning
emotion
detection.
It,
therefore,
aims
to
merge
cognitive
neuroscience
insights
advanced
algorithmic
methods
in
pursuit
of
an
enhanced
understanding
and
applications
recognition.
Methods:
study
was
conducted
PRISMA
guidelines,
involving
a
rigorous
selection
process
that
resulted
the
inclusion
64
empirical
studies
explore
modalities
such
as
fMRI,
EEG,
MEG,
discussing
their
capabilities
limitations
It
further
evaluates
architectures,
including
neural
networks,
CNNs,
GANs,
terms
roles
classifying
emotions
from
various
domains:
human-computer
interaction,
mental
health,
marketing,
more.
Ethical
practical
challenges
implementing
these
systems
are
also
analyzed.
Results:
identifies
fMRI
powerful
but
resource-intensive
modality,
while
EEG
MEG
more
accessible
high
temporal
resolution
limited
by
spatial
accuracy.
Deep
models,
especially
CNNs
have
performed
well
emotions,
though
they
do
not
always
require
large
diverse
datasets.
Combining
data
behavioral
features
improves
classification
performance.
However,
ethical
challenges,
privacy
bias,
remain
significant
concerns.
Conclusions:
has
emphasized
efficiencies
detection,
technical
were
highlighted.
Future
research
should
integrate
advances,
establish
innovative
enhance
system
reliability
applicability.
Diagnostic and Interventional Radiology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 16, 2025
Radiography
is
a
field
of
medicine
inherently
intertwined
with
technology.The
dependency
on
technology
very
high
for
obtaining
images
in
ultrasound
(US),
computed
tomography
(CT),
and
magnetic
resonance
imaging
(MRI).Although
the
reduction
radiation
dose
not
applicable
US
MRI,
advancements
have
made
it
possible
CT,
ongoing
studies
aimed
at
further
optimization.The
resolution
diagnostic
quality
obtained
through
each
modality
are
steadily
improving.Additionally,
technological
progress
has
significantly
shortened
acquisition
times
CT
MRI.The
use
artificial
intelligence
(AI),
which
becoming
increasingly
widespread
worldwide,
also
been
incorporated
into
radiography.This
can
produce
more
accurate
reproducible
results
examinations.Machine
learning
offers
great
potential
improving
image
quality,
creating
distinct
useful
images,
even
developing
new
modalities.Furthermore,
AI
technologies
prevalent
MRI
evaluation,
generation,
enhanced
quality.
ACS Nano,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 10, 2025
Interfacing
artificial
devices
with
the
human
brain
is
central
goal
of
neurotechnology.
Yet,
our
imaginations
are
often
limited
by
currently
available
paradigms
and
technologies.
Suggestions
for
brain-machine
interfaces
have
changed
over
time,
along
technology.
Mechanical
levers
cable
winches
were
used
to
move
parts
during
mechanical
age.
Sophisticated
electronic
wiring
remote
control
arisen
age,
ultimately
leading
plug-and-play
computer
interfaces.
Nonetheless,
brains
so
complex
that
these
visions,
until
recently,
largely
remained
unreachable
dreams.
The
general
problem,
thus
far,
most
technology
mechanically
and/or
electrically
engineered,
whereas
a
living,
dynamic
entity.
As
result,
worlds
difficult
interface
one
another.
Nanotechnology,
which
encompasses
engineered
solid-state
objects
integrated
circuits,
excels
at
small
length
scales
single
few
hundred
nanometers
and,
thus,
matches
sizes
biomolecules,
biomolecular
assemblies,
cells.
Consequently,
we
envision
nanomaterials
nanotools
as
opportunities
in
alternative
ways.
Here,
review
existing
literature
on
use
nanotechnology
look
forward
discussing
perspectives
limitations
based
authors'
expertise
across
range
complementary
disciplines─from
neuroscience,
engineering,
physics,
chemistry
biology
medicine,
science
mathematics,
social
jurisprudence.
We
focus
but
also
include
information
from
related
fields
when
useful
complementary.
Imaging Neuroscience,
Journal Year:
2024,
Volume and Issue:
2, P. 1 - 35
Published: April 1, 2024
Abstract
In
recent
years,
brain
research
has
indisputably
entered
a
new
epoch,
driven
by
substantial
methodological
advances
and
digitally
enabled
data
integration
modelling
at
multiple
scales—from
molecules
to
the
whole
brain.
Major
are
emerging
intersection
of
neuroscience
with
technology
computing.
This
science
combines
high-quality
research,
across
scales,
culture
multidisciplinary
large-scale
collaboration,
translation
into
applications.
As
pioneered
in
Europe’s
Human
Brain
Project
(HBP),
systematic
approach
will
be
essential
for
meeting
coming
decade’s
pressing
medical
technological
challenges.
The
aims
this
paper
to:
develop
concept
decade
digital
discuss
community
large,
identify
points
convergence,
derive
therefrom
scientific
common
goals;
provide
framework
current
future
development
EBRAINS,
infrastructure
resulting
from
HBP’s
work;
inform
engage
stakeholders,
funding
organisations
institutions
regarding
research;
address
transformational
potential
comprehensive
models
artificial
intelligence,
including
machine
learning
deep
learning;
outline
collaborative
that
integrates
reflection,
dialogues,
societal
engagement
on
ethical
opportunities
challenges
as
part
research.
Science Advances,
Journal Year:
2024,
Volume and Issue:
10(13)
Published: March 27, 2024
Direct
imaging
of
neuronal
activity
(DIANA)
by
functional
magnetic
resonance
(fMRI)
could
be
a
revolutionary
approach
for
advancing
systems
neuroscience
research.
To
independently
replicate
this
observation,
we
performed
fMRI
experiments
in
anesthetized
mice.
The
blood
oxygenation
level–dependent
(BOLD)
response
to
whisker
stimulation
was
reliably
detected
the
primary
barrel
cortex
before
and
after
DIANA
experiments;
however,
no
DIANA–like
peak
observed
individual
animals’
data
with
50
300
trials.
Extensively
averaged
involving
1050
trials
six
mice
showed
flat
baseline
detectable
activity–like
peak.
However,
spurious,
nonreplicable
peaks
were
found
when
using
small
number
trials,
artifactual
some
outlier-like
excluded.
Further,
BOLD-responding
thalamus
from
selected
reference
function
cortex.
Thus,
unable
previously
reported
results
without
preselection.
Neuroscience Bulletin,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 24, 2025
Epilepsy
affects
over
50
million
people
worldwide.
Drug-resistant
epilepsy
(DRE)
accounts
for
up
to
a
third
of
these
cases,
and
neuro-inflammation
is
thought
play
role
in
such
cases.
Despite
being
long-debated
issue
the
field
DRE,
mechanisms
underlying
neuroinflammation
have
yet
be
fully
elucidated.
The
pro-inflammatory
microenvironment
within
brain
tissue
with
DRE
has
been
probed
using
single-cell
multimodal
transcriptomics.
Evidence
suggests
that
inflammatory
cells
cytokines
nervous
system
can
lead
extensive
biochemical
changes,
as
connexin
hemichannel
excitability
disruption
neurotransmitter
homeostasis.
presence
inflammation
may
give
rise
neuronal
network
abnormalities
suppress
endogenous
antiepileptic
systems.
We
focus
on
anomalies
from
multiple
perspectives
identify
critical
points
clinical
application.
hope
provide
an
insightful
overview
advance
quest
better
treatments.
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: March 24, 2023
Abstract
Sleep
is
ubiquitous
and
essential,
but
its
mechanisms
remain
unclear.
Studies
in
animals
humans
have
provided
insights
of
sleep
at
vastly
different
spatiotemporal
scales.
However,
challenges
to
integrate
local
global
information
sleep.
Therefore,
we
developed
fMRI
based
on
simultaneous
electrophysiology
9.4
T
male
mice.
Optimized
un-anesthetized
mouse
setup
allowed
manifestation
NREM
REM
sleep,
a
large
dataset
was
collected
openly
accessible.
State
dependent
patterns
were
revealed,
state
transitions
found
be
global,
asymmetrical
sequential,
which
can
predicted
up
17.8
s
using
LSTM
models.
Importantly,
with
hippocampal
recording
revealed
potentiated
sharp-wave
ripple
triggered
during
than
awake
state,
potentially
attributable
co-occurrence
spindle
events.
To
conclude,
established
electrophysiology,
demonstrated
capability
by
revealing
dynamics
neural
