bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 14, 2024
Summary
During
speech
listening,
it
has
been
hypothesized
that
the
brain
builds
representations
of
large
linguistic
structures
such
as
sentences,
which
are
captured
by
neural
activity
tracking
rhythm
these
structures.
Nevertheless,
concerned
may
only
encode
words,
and
be
confounded
predictability
or
syntactic
properties
individual
words.
Here,
to
disentangle
responses
sentences
we
design
word
sequences
parsed
into
different
in
contexts.
By
analyzing
recorded
magnetoencephalography,
find
low-frequency
strongly
depends
on
context
–
The
difference
between
MEG
same
sequence
two
contexts
yields
a
signal,
most
generated
superior
temporal
gyrus,
precisely
tracks
sentences.
words
can
partly
explain
response
each
but
cannot
In
summary,
encodes
reliably
reflect
how
is
Synthese,
Journal Year:
2024,
Volume and Issue:
203(5)
Published: May 3, 2024
Abstract
Natural
language
syntax
yields
an
unbounded
array
of
hierarchically
structured
expressions.
We
claim
that
these
are
used
in
the
service
active
inference
accord
with
free-energy
principle
(FEP).
While
conceptual
advances
alongside
modelling
and
simulation
work
have
attempted
to
connect
speech
segmentation
linguistic
communication
FEP,
we
extend
this
program
underlying
computations
responsible
for
generating
syntactic
objects.
argue
recently
proposed
principles
economy
design—such
as
“minimal
search”
criteria
from
theoretical
syntax—adhere
FEP.
This
affords
a
greater
degree
explanatory
power
FEP—with
respect
higher
functions—and
offers
linguistics
grounding
first
computability.
mostly
focus
on
building
new
principled
relations
between
also
show
through
sample
preliminary
examples
how
both
tree-geometric
depth
Kolmogorov
complexity
estimate
(recruiting
Lempel–Ziv
compression
algorithm)
can
be
accurately
predict
legal
operations
workspaces,
directly
line
formulations
variational
free
energy
minimization.
is
motivate
general
design
term
Turing–Chomsky
Compression
(TCC).
use
TCC
align
concerns
linguists
normative
account
self-organization
furnished
by
marshalling
evidence
psycholinguistics
ground
core
efficient
computation
within
inference.
Various
theories
in
neuroscience
maintain
that
brain
oscillations
have
an
important
role
neuronal
computation,
but
opposing
views
claim
these
macroscale
dynamics
are
“exhaust
fumes”
of
more
relevant
processes.
Here,
we
argue
the
question
whether
epiphenomenal
is
ill-defined
and
cannot
be
productively
resolved
without
further
refinement.
Toward
end,
outline
a
conceptual
framework
clarifies
dispute
along
two
axes:
first,
introduce
distinction
between
measurement
process
to
categorize
theoretical
status
electrophysiology
terms
such
as
local
field
potentials
oscillations.
Second,
consider
relationships
disambiguated
terms,
evaluating
based
on
experimental
computational
evidence
there
exist
causal
or
inferentially
useful
links
them.
This
decomposes
epiphenomenalism
into
set
empirically
tractable
alternatives.
Finally,
demarcate
conceptually
distinct
entity
where
either
processes
measurements
exhibit
periodic
behavior,
suggest
oscillatory
orchestrate
neural
computation
by
implementing
temporal,
spatial,
frequency
syntax.
Overall,
our
reframed
evaluation
supports
view
electric
fields—oscillating
not—are
causally
relevant,
their
associated
signals
informative.
More
broadly,
offer
vocabulary
starting
point
for
scientific
exchanges
utility
biological
they
capture.
Nature Communications,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: Oct. 14, 2024
Humans
excel
at
extracting
structurally-determined
meaning
from
speech
despite
inherent
physical
variability.
This
study
explores
the
brain's
ability
to
predict
and
understand
spoken
language
robustly.
It
investigates
relationship
between
structural
statistical
knowledge
in
brain
dynamics,
focusing
on
phase
amplitude
modulation.
Using
syntactic
features
constituent
hierarchies
surface
statistics
a
transformer
model
as
predictors
of
forward
encoding
models,
we
reconstructed
cross-frequency
neural
dynamics
MEG
data
during
audiobook
listening.
Our
findings
challenge
strict
separation
linguistic
structure
brain,
with
both
aiding
signal
reconstruction.
Syntactic
have
more
temporally
spread
impact,
word
entropy
number
closing
constituents
are
linked
phase-amplitude
coupling
implying
role
temporal
prediction
cortical
oscillation
alignment
processing.
results
indicate
that
structured
information
jointly
shape
comprehension
suggest
an
integration
process
via
mechanism.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 16, 2025
Naturalistic
electrocorticography
(ECoG)
data
are
a
rare
but
essential
resource
for
studying
the
brain's
linguistic
capabilities.
ECoG
offers
high
temporal
resolution
suitable
investigating
processes
at
multiple
timescales
and
frequency
bands.
It
also
provides
broad
spatial
coverage,
often
along
critical
language
areas.
Here,
we
share
dataset
of
nine
participants
with
1,330
electrodes
listening
to
30-minute
audio
podcast.
The
richness
this
naturalistic
stimulus
can
be
used
various
research
endeavors,
from
auditory
perception
semantic
integration.
In
addition
neural
data,
extract
features
ranging
phonetic
information
large
model
word
embeddings.
We
use
these
in
encoding
models
that
relate
properties
activity.
Finally,
provide
detailed
tutorials
preprocessing
raw
extracting
features,
running
analyses
serve
as
pedagogical
or
springboard
new
research.
Brain and Language,
Journal Year:
2025,
Volume and Issue:
264, P. 105549 - 105549
Published: Feb. 20, 2025
Although
there
is
a
sizeable
body
of
literature
on
sentence
comprehension
and
processing
both
in
healthy
disordered
language
users,
the
production
remains
much
more
sparse.
Linguistic
computational
descriptions
expressive
syntactic
deficits
aphasia
are
especially
rare.
In
addition,
neuroimaging
(psycho)
linguistic
literatures
operate
largely
separately.
this
paper,
I
will
first
lay
out
theoretical
land
with
regard
to
psycholinguistic
models
production.
then
provide
brief
narrative
overview
large-scale
meta-analysis
as
it
pertains
computation,
followed
by
an
attempt
integrate
findings
from
functional
clinical
neuroimaging.
Finally,
surrounding
propose
path
forward
close
some
existing
gaps.
Trends in Cognitive Sciences,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 1, 2025
Grouping
sensory
events
into
chunks
is
an
efficient
strategy
to
integrate
information
across
long
sequences
such
as
speech,
music,
and
complex
movements.
Although
can
be
constructed
based
on
diverse
cues
(e.g.,
features,
statistical
patterns,
internal
knowledge)
recent
studies
have
consistently
demonstrated
that
the
by
different
are
all
tracked
low-frequency
neural
dynamics.
Here,
I
review
evidence
chunking
drive
activity
in
modality-dependent
networks,
which
interact
generate
chunk-tracking
broad
brain
areas.
Functionally,
this
work
suggests
a
core
computation
underlying
sequence
may
assign
each
event
its
ordinal
position
within
chunk
causally
implemented
during
predictive
chunking.
