Neural dynamics express syntax in the time domain during natural story listening
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Март 22, 2024
Abstract
Studies
of
perception
have
long
shown
that
the
brain
adds
information
to
its
sensory
analysis
physical
environment.
A
touchstone
example
for
humans
is
language
use:
comprehend
a
signal
like
speech,
must
add
linguistic
knowledge,
including
syntax.
Yet,
syntactic
rules
and
representations
are
atemporal
(i.e.,
abstract
not
bound
by
time),
so
they
be
translated
into
time-varying
signals
speech
comprehension
production.
Here,
we
test
three
different
models
temporal
spell-out
structure
against
activity
people
listening
Dutch
stories:
an
integratory
bottom-up
parser,
predictive
top-down
mildly
left-corner
parser.
These
build
exactly
same
but
differ
in
when
added
–
this
difference
captured
(temporal
distribution
the)
complexity
metric
‘incremental
node
count’.
Using
response
function
with
both
acoustic
information-theoretic
control
predictors,
counts
were
regressed
source-reconstructed
delta-band
acquired
magnetoencephalography.
Neural
dynamics
left
frontal
regions
most
strongly
reflect
derived
method,
which
postulates
syntax
early
time,
suggesting
building
important
component
sentence
comprehension.
The
absence
strong
effects
model
further
suggests
strategy
does
represent
well,
contrast
what
has
been
found
English.
Understanding
projects
knowledge
onto
whether
done
language-specific
ways,
will
inform
constrain
development
mechanistic
syntactic-structure
brain.
Язык: Английский
Electrophysiological responses to syntactic and “morphological” structures: evidence from Mandarin Chinese
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Фев. 1, 2024
Abstract
Although
psycho-/neuro-linguistics
has
assumed
a
distinction
between
morphological
and
syntactic
structure
building
as
in
traditional
theoretical
linguistics,
this
been
increasingly
challenged
by
linguists
recent
years.
Opposing
sharp,
lexicalist
morphology
syntax,
non-lexicalist
theories
propose
common
morpho-syntactic
operations
that
cut
across
the
realms
of
“morphology”
“syntax”,
which
are
considered
distinct
territories
theories.
Taking
advantage
two
pairs
contrasts
Mandarin
Chinese
with
desirable
linguistic
properties,
namely
compound
vs.
simplex
nouns
(the
contrast,
differing
complexity
per
theories)
separable
inseparable
verbs
“syntax”
theories),
we
report
one
first
pieces
evidence
for
shared
neural
responses
language
comprehension,
supporting
view
where
computations
employed
building.
Specifically,
observed
both
modulated
left
anterior
centro-parietal
electrodes
an
priori
275:400
ms
time
window,
corroborated
topographical
similarity
analyses.
These
results
serve
preliminary
yet
prima
facie
towards
comprehension.
Язык: Английский
Neural synchrony is "good enough" for speech comprehension
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 1, 2024
Abstract
Recent
evidence
indicates
that
neural
populations
exhibit
synchronous
firing
at
phrase
boundaries
to
facilitate
the
encoding
of
syntactic
units
during
speech
comprehension.
However,
good-enough
processing
accounts
comprehension
suggest
detailed
analysis
may
not
always
be
necessary
for
successful
interpretation,
especially
when
listeners
can
deduce
meaning
from
lexical-semantic
contexts.
In
this
brief
report,
we
evaluate
notion
and
assess
whether
synchrony
is
modulated
by
local
content.
To
end,
reanalyzed
an
open-source
EEG
dataset,
consisting
brain
recordings
obtained
while
participants
passively
listened
audiobook.
determine
boundaries,
computed
mutual
information
(MI)
between
delta
band
activity
(<
3Hz)
hierarchically
derived
structures
each
sentence
in
We
then
quantified
local-lexical
semantic
contexts
using
dissimilarity
values
were
high-dimensional
vectors
co-occurrence.
regressed
MI
against
sentence’s
values,
linear
mixed-effects
models.
Results
indicated
showed
a
positive
relationship
with
dissimilarity.
interpret
finding
as
listeners’
reliance
on
contexts,
consistent
accounts.
Язык: Английский