bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: May 12, 2023
Abstract
Understanding
the
variability
of
environment
is
essential
to
function
in
everyday
life.
The
brain
must
hence
take
uncertainty
into
account
when
updating
its
internal
model
world.
basis
for
are
prediction
errors
that
arise
from
a
difference
between
current
and
new
sensory
experiences.
Although
error
neurons
have
been
identified
layer
2/3
diverse
areas,
how
modulates
these
learning
is,
however,
unclear.
Here,
we
use
normative
approach
derive
should
modulate
postulate
represent
uncertainty-modulated
(UPE).
We
further
hypothesise
circuit
calculates
UPE
through
subtractive
divisive
inhibition
by
different
inhibitory
cell
types.
By
implementing
calculation
UPEs
microcircuit
model,
show
types
can
compute
means
variances
stimulus
distribution.
With
local
activity-dependent
plasticity
rules,
computations
be
learned
context-dependently,
allow
upcoming
stimuli
their
Finally,
mechanism
enables
an
organism
optimise
strategy
via
adaptive
rates.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: May 30, 2024
Parvalbumin-expressing
inhibitory
neurons
(PVNs)
stabilize
cortical
network
activity,
generate
gamma
rhythms,
and
regulate
experience-dependent
plasticity.
Here,
we
observed
that
activation
or
inactivation
of
PVNs
functioned
like
a
volume
knob
in
the
mouse
auditory
cortex
(ACtx),
turning
neural
behavioral
classification
sound
level
up
down
over
20dB
range.
PVN
loudness
adjustments
were
"sticky",
such
single
bout
40Hz
stimulation
sustainably
suppressed
ACtx
responsiveness,
potentiated
feedforward
inhibition,
behaviorally
desensitized
mice
to
loudness.
Sensory
sensitivity
is
cardinal
feature
autism,
aging,
peripheral
neuropathy,
prompting
us
ask
whether
can
persistently
desensitize
with
hyperactivity,
hypofunction,
hypersensitivity
triggered
by
cochlear
sensorineural
damage.
We
found
16-minute
session
restored
normal
perception
for
one
week,
showing
perceptual
deficits
irreversible
injuries
be
reversed
through
targeted
circuit
interventions.
Nature Communications,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: July 26, 2024
Abstract
When
preparing
a
movement,
we
often
rely
on
partial
or
incomplete
information,
which
can
decrement
task
performance.
In
behaving
monkeys
show
that
the
degree
of
cued
target
information
is
reflected
in
both,
neural
variability
motor
cortex
and
behavioral
reaction
times.
We
study
underlying
mechanisms
spiking
motor-cortical
attractor
model.
By
introducing
biologically
realistic
network
topology
where
excitatory
neuron
clusters
are
locally
balanced
with
inhibitory
robustly
achieve
metastable
activity
across
wide
range
parameters.
application
to
monkey
task,
model
performs
target-specific
action
selection
accurately
reproduces
task-epoch
dependent
reduction
trial-to-trial
vivo
directly
reflects
amount
processed
while
irregularity
remained
constant
throughout
task.
context
cue
increased
time
explain
conclude
context-dependent
signum
computation
cortex.
Cerebral Cortex,
Journal Year:
2024,
Volume and Issue:
34(11)
Published: Nov. 1, 2024
Neurons
are
thought
to
act
as
parts
of
assemblies
with
strong
internal
excitatory
connectivity.
Conversely,
inhibition
is
often
reduced
blanket
no
targeting
specificity.
We
analyzed
the
structure
excitation
and
in
MICrONS
$mm^{3}$
dataset,
an
electron
microscopic
reconstruction
a
piece
cortical
tissue.
found
that
was
structured
around
feed-forward
flow
large
non-random
neuron
motifs
information
from
small
number
sources
larger
potential
targets.
Inhibitory
neurons
connected
specific
sequential
positions
these
motifs,
implementing
targeted
symmetrical
competition
between
them.
None
trends
detectable
only
pairwise
connectivity,
demonstrating
by
motifs.
While
descriptions
circuits
range
non-specific
blanket-inhibition
targeted,
our
results
describe
form
specificity
existing
higher-order
connectome.
These
findings
have
important
implications
for
role
learning
synaptic
plasticity.
Advanced Science,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 23, 2025
Abstract
The
primate
cerebral
cortex,
the
major
organ
for
cognition,
consists
of
an
immense
number
neurons.
However,
organizational
principles
governing
these
neurons
remain
unclear.
By
accessing
single‐cell
spatial
transcriptome
over
25
million
neuron
cells
across
entire
macaque
it
is
discovered
that
distribution
within
cortical
layers
highly
non‐random.
Strikingly,
three‐quarters
are
located
in
distinct
neuronal
clusters.
Within
clusters,
different
cell
types
tend
to
collaborate
rather
than
function
independently.
Typically,
excitatory
clusters
mainly
consist
excitatory‐excitatory
combinations,
while
inhibitory
primarily
contain
excitatory‐inhibitory
combinations.
Both
cluster
have
roughly
equal
numbers
each
layer.
Importantly,
most
and
form
partnerships,
indicating
a
balanced
local
network
correlating
with
specific
functional
regions.
These
conserved
mouse
findings
suggest
brain
regions
cortex
may
exhibit
similar
mechanisms
at
population
level.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: May 12, 2023
Abstract
Understanding
the
variability
of
environment
is
essential
to
function
in
everyday
life.
The
brain
must
hence
take
uncertainty
into
account
when
updating
its
internal
model
world.
basis
for
are
prediction
errors
that
arise
from
a
difference
between
current
and
new
sensory
experiences.
Although
error
neurons
have
been
identified
layer
2/3
diverse
areas,
how
modulates
these
learning
is,
however,
unclear.
Here,
we
use
normative
approach
derive
should
modulate
postulate
represent
uncertainty-modulated
(UPE).
We
further
hypothesise
circuit
calculates
UPE
through
subtractive
divisive
inhibition
by
different
inhibitory
cell
types.
By
implementing
calculation
UPEs
microcircuit
model,
show
types
can
compute
means
variances
stimulus
distribution.
With
local
activity-dependent
plasticity
rules,
computations
be
learned
context-dependently,
allow
upcoming
stimuli
their
Finally,
mechanism
enables
an
organism
optimise
strategy
via
adaptive
rates.