2021 IEEE Symposium Series on Computational Intelligence (SSCI),
Journal Year:
2023,
Volume and Issue:
unknown, P. 64 - 68
Published: Dec. 5, 2023
Electroencephalography
(EEG)
is
an
essential
neuromonitoring
modality,
deeply
integrated
across
scientific
disciplines
such
as
psychology,
cognitive
science,
computational
neuroscience,
neurology,
and
psychiatry.
Its
relevance
has
surged
with
the
rise
of
brain-computer
interfaces.
However,
potential
non-invasive
EEG
hindered
by
compromised
signal
quality
compared
to
invasive
methods.
The
distinction
between
modest
source
amplitudes
pronounced
magnitudes
non-EEG
physiological
signals
environmental
interferences
complicates
analysis.
coexistence
subtle
neural
prominent
artifacts,
both
intrinsic
acquired,
characterizes
processing.
Various
artifact
management
techniques
have
been
proposed,
yet
pursuit
assessment
remains
underexplored.
This
mini-review
addresses
this
gap
emphasizing
vital
role
in
recordings.
article
highlights
significance
rigorous
evaluation,
reliable
data.
It
also
encapsulates
evolving
quantitative
methodologies
that
bolster
fidelity
assessment.
By
delving
into
these
aspects,
presents
a
compact
overview
ongoing
advancements
research
field
analysis
applications.
Behavior Research Methods,
Journal Year:
2024,
Volume and Issue:
56(6), P. 6020 - 6050
Published: Feb. 26, 2024
Abstract
We
present
motivation
and
practical
steps
necessary
to
find
parameter
estimates
of
joint
models
behavior
neural
electrophysiological
data.
This
tutorial
is
written
for
researchers
wishing
build
human
scalp
intracranial
electroencephalographic
(EEG)
or
magnetoencephalographic
(MEG)
data,
more
specifically
those
who
seek
understand
cognition.
Although
these
techniques
could
easily
be
applied
animal
models,
the
focus
this
on
participants.
Joint
modeling
M/EEG
requires
some
knowledge
existing
computational
cognitive
theories,
artifact
correction,
analysis
techniques,
modeling,
programming
statistical
implementation.
paper
seeks
give
an
introduction
as
they
apply
estimating
parameters
from
neurocognitive
behavior,
evaluate
model
results
compare
models.
Due
our
research
subject
matter,
examples
in
will
testing
specific
hypotheses
decision-making
theory.
However,
most
discussion
applies
across
many
procedures
applications.
provide
Python
(and
linked
R)
code
appendix.
Readers
are
encouraged
try
exercises
at
end
document.
Frontiers in Psychology,
Journal Year:
2024,
Volume and Issue:
14
Published: Jan. 4, 2024
Electroencephalography
(EEG)
stands
as
a
pioneering
tool
at
the
intersection
of
neuroscience
and
technology,
offering
unprecedented
insights
into
human
emotions.
Through
this
comprehensive
review,
we
explore
challenges
opportunities
associated
with
EEGbased
emotion
recognition.
While
recent
literature
suggests
promising
high
accuracy
rates,
these
claims
necessitate
critical
scrutiny
for
their
authenticity
applicability.
The
article
highlights
significant
in
generalizing
findings
from
multitude
EEG
devices
data
sources,
well
difficulties
collection.
Furthermore,
disparity
between
controlled
laboratory
settings
genuine
emotional
experiences
presents
paradox
within
paradigm
research.
We
advocate
balanced
approach,
emphasizing
importance
evaluation,
methodological
standardization,
acknowledging
dynamism
emotions
more
holistic
understanding
landscape.
Schizophrenia Bulletin,
Journal Year:
2024,
Volume and Issue:
unknown
Published: April 14, 2024
Abstract
Background
and
Hypothesis
The
current
study
investigated
the
extent
to
which
changes
in
attentional
control
contribute
performance
on
a
visual
perceptual
discrimination
task,
trial-by-trial
basis
transdiagnostic
clinical
sample.
Study
Design
Participants
with
schizophrenia
(SZ;
N
=
58),
bipolar
disorder
(N
42),
major
depression
51),
psychiatrically
healthy
controls
92)
completed
perception
task
stimuli
appeared
briefly.
design
allowed
us
estimate
lapse
rate
precision
of
representations
stimuli.
Electroencephalograms
(EEG)
were
recorded
examine
pre-stimulus
activity
alpha
band
(8–13
Hz),
overall
relation
behavior
task.
Results
We
found
that
attention
was
elevated
SZ
group
compared
all
other
groups.
also
observed
differences
activity,
participants
showing
highest
levels
when
averaging
across
trials.
However,
analyses
showed
within-participant
fluctuations
significantly
predicted
likelihood
making
an
error,
Interestingly,
our
analysis
demonstrated
aperiodic
contributions
EEG
signal
(which
affect
power
estimates
frequency
bands)
serve
as
significant
predictor
well.
Conclusions
These
results
confirm
has
been
SZ,
validate
markers
their
use
basis,
suggest
are
important
target
for
further
research
this
area,
addition
alpha-band
activity.
NeuroImage,
Journal Year:
2024,
Volume and Issue:
286, P. 120514 - 120514
Published: Jan. 9, 2024
Visual
attention
can
be
guided
by
statistical
regularities
in
the
environment,
that
people
implicitly
learn
from
past
experiences
(statistical
learning,
SL).
Moreover,
a
perceptually
salient
element
automatically
capture
attention,
gaining
processing
priority
through
bottom-up
attentional
control
mechanism.
The
aim
of
our
study
was
to
investigate
dynamics
SL
and
if
it
shapes
target
selection
additively
with
salience
processing,
or
whether
these
mechanisms
interact,
e.g.
one
gates
other.
In
visual
search
task,
we
therefore
manipulated
frequency
(high
vs.
low)
across
locations
while,
some
trials,
terms
colour.
Additionally,
halfway
experiment,
high-frequency
location
changed
opposite
hemifield.
EEG
activity
simultaneously
recorded,
specific
interest
two
markers
related
post-selection
respectively:
N2pc
SPCN.
Our
results
revealed
both
saliency
significantly
enhanced
behavioural
performance,
but
also
interacted
each
other,
an
attenuated
effect
at
location,
smaller
for
targets.
Concerning
dynamics,
benefit
more
evident
during
early
stage
as
indexed
larger
early-SPCN,
whereas
modulated
underlying
neural
particularly
later
on,
late-SPCN.
Furthermore,
showed
rapidly
acquired
adjusted
when
spatial
imbalance
changed.
Overall,
findings
suggest
is
flexible
changes
and,
combined
jointly
contributes
establishing
priority.
Abstract
The
current
study
tested
the
hypothesis
that
lexical
ambiguity,
a
common
source
of
representational
conflict
during
language
comprehension,
engages
domain-general
cognitive
control
processes
are
reflected
by
theta-band
oscillations
in
scalp-recorded
electroencephalograms
(EEG).
In
Experiment
1,
we
examined
neural
signature
elicited
lexically
ambiguous
compared
to
unambiguous
words
sentence
comprehension.
results
showed
midfrontal
theta
activity
was
increased
response
linguistic
(lexical
ambiguity).
2,
postconflict
adaptation
effects
comparing
temporarily
sentences
followed
previous
instances
(other
sentences)
those
low-conflict
(unambiguous)
sentence.
A
effect
associated
with
again
found
such
for
high-conflict
(temporarily
ambiguous)
sentences.
both
experiments,
facilitated
semantic
processing
also
observed
came
after
point
conflict,
which
may
reflect
downstream
“benefit”
engagement.
Overall,
our
provide
novel
insights
into
neurocognitive
mechanisms
underlying
comprehension
and
suggest
same
computations
involved
nonlinguistic
conflict.
We
present
motivation
and
practical
steps
necessary
to
find
parameter
estimates
of
joint
models
behavior
neural
electrophysiological
data.
This
tutorial
is
written
for
researchers
wishing
build
human
scalp
intracranial
electroencephalographic
(EEG)
or
magnetoencephalographic
(MEG)
data,
more
specifically
those
who
seek
understand
cognition.
Although
these
techniques
could
easily
be
applied
animal
models,
the
focus
this
on
participants.
Joint
modeling
M/EEG
requires
some
knowledge
existing
computational
cognitive
theories,
artifact
correction,
analysis
techniques,
modeling,
programming
statistical
implementation.
paper
seeks
give
an
introduction
as
they
apply
estimating
parameters
from
neurocognitive
behavior,
evaluate
model
results
compare
models.
Due
our
research
subject
matter,
examples
in
will
testing
specific
hypotheses
decision-making
theory.
However
most
discussion
applies
across
many
procedures
applications.
provide
Python
(and
linked
R)
code
appendix.
Readers
are
encouraged
try
exercises
at
end
document.
Frontiers in Psychology,
Journal Year:
2024,
Volume and Issue:
15
Published: March 13, 2024
Citation:
Wang
M-Y,
Zöllner
HJ,
Yücel
MA
and
Specht
K
(2024)
Editorial:
Variability
reproducibility
of
brain
imaging.
Front.
Psychol.
15:1386948.
doi:
10.3389/fpsyg.2024.1386948
The
replication
crisis
in
experimental
psychology
and
neuroscience
has
received
much
attention
recently.
This
led
to
wide
acceptance
of
measures
improve
scientific
practices,
such
as
preregistration
registered
reports.
Less
efforts
have
been
devoted
performing
reporting
the
results
systematic
tests
functioning
setup
itself.
Yet,
inaccuracies
performance
may
affect
a
study,
lead
failures,
importantly,
impede
ability
integrate
across
studies.
Prompted
by
challenges
we
experienced
when
deploying
studies
six
laboratories
collecting
EEG/MEG,
fMRI,
intracranial
EEG
(iEEG),
here
describe
framework
for
both
testing
setup.
In
addition,
100
researchers
were
surveyed
provide
snapshot
current
common
practices
community
standards
concerning
published
experiments’
setups.
Most
reported
their
Almost
none,
however,
performed
test
or
results.
Tests
diverse,
targeting
different
aspects
Through
simulations,
clearly
demonstrate
how
even
slight
can
impact
final
We
end
with
standardized,
open-source,
step-by-step
protocol
(visual)
event-related
experiments,
shared
via
protocols.io.
aims
benchmark
future
replications
insights
into
research
quality
help
reproducibility
results,
accelerate
multi-center
studies,
increase
robustness,
enable
integration
(English)
This
study
delves
deeply
into
the
complex
relationship
between
field
of
architecture
and
human
emotions,
aiming
to
fill
a
significant
gap
in
existing
research.
It
extensively
explores
profound
impact
architectural
design
elements,
such
as
lighting,
colour
schemes,
integration
natural
landscapes,
on
emotional
responses.
research
goes
beyond
traditional
focuses
aesthetics
sustainability,
striving
innovate
methods
for
assessing
spaces.
In
this
study,
we
adopted
technological
pathway
from
laboratory
virtual
reality,
finally
AI,
combining
theoretical
analysis
with
practical
experiments
case
studies.
The
main
includes
examining
effects
lighting
spatial
dimension
variations
people's
well
application
facial
emotion
recognition
technology
reality
environments,
exploring
AI's
perceptual
capabilities
tool
design.
These
studies
aim
narrow
application,
providing
new
perspectives
empirical
data
concludes
reflection
methodologies
used
their
broader
implications
practice.
offers
specific
strategies
architects
designers,
aimed
at
creating
spaces
that
resonate
emotionally
add
substantial
value
experiences.
By
prioritizing
factors
process,
seeks
enhance
overall
quality
life
promote
well-being
thoughtfully
designed
(Català)
Aquest
estudi
aprofundeix
en
la
complexa
relació
entre
el
camp
de
l'arquitectura
i
les
emocions
humanes,
amb
l'objectiu
cobrir
un
buit
significatiu
investigació
existent.
Explora
àmpliament
l'impacte
profund
d'elements
disseny
arquitectònic,
com
ara
il·luminació,
els
esquemes
colors
integració
paisatges
naturals,
respostes
emocionals.
Aquesta
recerca
va
més
enllà
dels
enfocaments
tradicionals
estètica
sostenibilitat,
esforçant-se
per
innovar
mètodes
avaluar
emocional
espais
arquitectònics.
En
aquest
estudi,
s'adopta
una
ruta
tecnològica
que
des
del
laboratori
fins
realitat
i,
finalment,
intel·ligència
artificial,
combinant
anàlisi
teòric
pràctics
estudis
cas.
La
principal
inclou
l'examen
efectes
variacions
il·luminació
dimensions
espacials
persones,
així
l'aplicació
tecnologia
reconeixement
d'emocions
entorns
arquitectònics
virtual,
explorant
capacitats
perceptives
IA
eina
arquitectònic.
Aquests
busquen
reduir
bretxa
teòrica
pràctica,
proporcionant
noves
dades
empíriques
al
L'estudi
conclou
reflexió
sobre
metodologies
utilitzades
seves
implicacions
àmplies
pràctica
Ofereix
estratègies
específiques
arquitectes
dissenyadors,
destinades
crear
ressonin
emocionalment
afegeixin
valor
substancial
experiències
humanes.
prioritzar
emocionals
procés
disseny,
aquesta
busca
millorar
qualitat
general
vida
promoure
benestar
dissenyats
cura.
(Español)
Este
estudio
profundiza
compleja
relación
campo
arquitectura
y
las
emociones
humanas,
con
objetivo
llenar
vacío
significativo
investigación
existente.
extensamente
profundo
impacto
elementos
diseño
arquitectónico,
como
iluminación,
los
esquemas
colores
integración
paisajes
naturales,
respuestas
emocionales.
Esta
más
allá
enfoques
tradicionales
estética
sostenibilidad,
esforzándose
por
métodos
para
evaluar
espacios
arquitectónicos.
este
estudio,
se
adopta
tecnológica
desde
laboratorio
hasta
realidad
y,
finalmente,
inteligencia
combinando
análisis
teórico
experimentos
prácticos
estudios
caso.
incluye
examen
efectos
variaciones
iluminación
dimensiones
espaciales
personas,
así
aplicación
tecnología
reconocimiento
entornos
arquitectónicos
explorando
capacidades
perceptuales
herramienta
arquitectónico.
Estos
buscan
reducir
brecha
teórica
práctica,
proporcionando
nuevas
perspectivas
datos
empíricos
El
concluye
reflexión
metodologías
utilizadas
sus
implicaciones
amplias
práctica
Ofrece
estrategias
específicas
arquitectos
diseñadores,
destinadas
resuenen
emocionalmente
añadan
sustancial
experiencias
humanas.
Al
priorizar
factores
emocionales
proceso
diseño,
esta
mejorar
calidad
promover
bienestar
diseñados
cuidadosamente.