NeuroImage,
Journal Year:
2023,
Volume and Issue:
285, P. 120479 - 120479
Published: Nov. 29, 2023
Functional
magnetic
resonance
imaging
(fMRI)
in
behaving
monkeys
has
a
strong
potential
to
bridge
the
gap
between
human
neuroimaging
and
primate
neurophysiology.
In
monkey
fMRI,
restrain
head
movements,
researchers
usually
surgically
implant
plastic
head-post
on
skull.
Although
time-proven
be
effective,
this
technique
could
create
burdens
for
animals,
including
risk
of
infection
discomfort.
Furthermore,
presence
extraneous
objects
skull,
such
as
bone
screws
dental
cement,
adversely
affects
signals
near
cortical
surface.
These
side
effects
are
undesirable
terms
both
practical
aspect
efficient
data
collection
spirit
"refinement"
from
3R's.
Here,
we
demonstrate
that
completely
non-invasive
fMRI
scan
awake
is
possible
by
using
mask
made
fit
skull
individual
animals.
all
three
tested,
longitudinal,
quantitative
assessment
movements
showed
effectively
suppressed
were
able
obtain
reliable
retinotopic
BOLD
standard
mapping
task.
The
present,
easy-to-make
simplify
experiments
monkeys,
while
giving
good
or
even
better
quality
than
obtained
with
conventional
method.
Annual Review of Neuroscience,
Journal Year:
2023,
Volume and Issue:
46(1), P. 233 - 258
Published: March 27, 2023
Flexible
behavior
requires
the
creation,
updating,
and
expression
of
memories
to
depend
on
context.
While
neural
underpinnings
each
these
processes
have
been
intensively
studied,
recent
advances
in
computational
modeling
revealed
a
key
challenge
context-dependent
learning
that
had
largely
ignored
previously:
Under
naturalistic
conditions,
context
is
typically
uncertain,
necessitating
contextual
inference.
We
review
theoretical
approach
formalizing
face
uncertainty
core
computations
it
requires.
show
how
this
begins
organize
large
body
disparate
experimental
observations,
from
multiple
levels
brain
organization
(including
circuits,
systems,
behavior)
regions
(most
prominently
prefrontal
cortex,
hippocampus,
motor
cortices),
into
coherent
framework.
argue
inference
may
also
be
understanding
continual
brain.
This
theory-driven
perspective
places
as
component
learning.
Trends in Cognitive Sciences,
Journal Year:
2024,
Volume and Issue:
28(7), P. 614 - 627
Published: April 4, 2024
Working
memory
(WM)
is
a
fundamental
aspect
of
cognition.
WM
maintenance
classically
thought
to
rely
on
stable
patterns
neural
activities.
However,
recent
evidence
shows
that
population
activities
during
undergo
dynamic
variations
before
settling
into
pattern.
Although
this
has
been
difficult
explain
theoretically,
network
models
optimized
for
typically
also
exhibit
such
dynamics.
Here,
we
examine
versus
coding
in
data,
classical
models,
and
task-optimized
networks.
We
review
principled
mathematical
reasons
why
do
not,
while
naturally
coding.
suggest
an
update
our
understanding
maintenance,
which
computational
feature
rather
than
epiphenomenon.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Feb. 6, 2024
Abstract
Plans
are
formulated
and
refined
over
the
period
leading
to
their
execution,
ensuring
that
appropriate
behavior
is
enacted
at
just
right
time.
While
existing
evidence
suggests
memory
circuits
convey
passage
of
time
through
diverse
neuronal
responses,
it
remains
unclear
whether
neural
involved
in
planning
exhibit
analogous
temporal
dynamics.
Using
publicly
available
data,
we
analyzed
how
activity
frontal
motor
cortex
evolves
during
planning.
Individual
neurons
exhibited
ramping
throughout
a
delay
interval
preceded
planned
movement.
The
collective
these
was
useful
for
making
predictions
became
increasingly
precise
as
movement
approached.
This
diversity
gave
rise
spectrum
encoding
patterns,
ranging
from
stable
dynamic
representations
upcoming
Our
results
indicate
unfolds
multiple
timescales
planning,
suggesting
shared
mechanism
brain
processing
information
related
both
past
memories
future
plans.
International Journal of Neural Systems,
Journal Year:
2025,
Volume and Issue:
35(05)
Published: Feb. 7, 2025
Preparatory
activity
is
crucial
for
voluntary
motor
control,
reducing
reaction
time
and
enhancing
precision.
To
understand
the
neurodynamic
mechanisms
behind
this,
we
construct
a
dynamical
model
within
cortex,
which
comprises
coupled
heterogeneous
attractors
to
simulate
delayed
reaching
tasks.
This
replicates
neural
patterns
observed
in
macaque
distinct
attractor
spaces
preparatory
executive
activities.
It
can
capture
transition
from
preparation
execution
through
shifts
an
orthogonal
subspace
combined
with
thresholding
mechanism.
Results
show
that
duration
modulates
behavioral
accuracy,
optimal
intervals
performance.
External
inputs
primarily
shape
activity,
while
synaptic
connections
dominate
execution.
Our
analysis
of
network’s
multi-stable
dynamics
reveals
external
reshape
stable
points
modules
both
before
after
preparation,
strength
affects
stability
input
sensitivity,
allowing
rapid
precise
actions.
Additionally,
sensitivity
perturbations
decreases
as
increases,
emphasizing
importance
during
preparation.
Overall,
this
study
provides
insights
into
underlying
underscores
significance
accurate
control.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: April 19, 2024
Speech
comprehension
requires
the
human
brain
to
transform
an
acoustic
waveform
into
meaning.
To
do
so,
generates
a
hierarchy
of
features
that
converts
sensory
input
increasingly
abstract
language
properties.
However,
little
is
known
about
how
these
hierarchical
are
generated
and
continuously
coordinated.
Here,
we
propose
each
linguistic
feature
dynamically
represented
in
simultaneously
represent
successive
events.
test
this
'Hierarchical
Dynamic
Coding'
(HDC)
hypothesis,
use
time-resolved
decoding
activity
track
construction,
maintenance,
integration
comprehensive
spanning
acoustic,
phonetic,
sub-lexical,
lexical,
syntactic
semantic
representations.
For
this,
recorded
21
participants
with
magnetoencephalography
(MEG),
while
they
listened
two
hours
short
stories.
Our
analyses
reveal
three
main
findings.
First,
incrementally
represents
maintains
features.
Second,
duration
representations
depend
on
their
level
hierarchy.
Third,
representation
maintained
by
dynamic
neural
code,
which
evolves
at
speed
commensurate
its
corresponding
level.
This
HDC
preserves
maintenance
information
over
time
limiting
interference
between
Overall,
reveals
builds
during
natural
speech
comprehension,
thereby
anchoring
theories
biological
implementations.
