Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part II: Physiology and Experimentation
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Май 17, 2023
Summary
Cortical
dynamics
underlie
many
cognitive
processes
and
emerge
from
complex
multi-scale
interactions,
which
are
challenging
to
study
in
vivo
.
Large-scale,
biophysically
detailed
models
offer
a
tool
can
complement
laboratory
approaches.
We
present
model
comprising
eight
somatosensory
cortex
subregions,
4.2
million
morphological
electrically-detailed
neurons,
13.2
billion
local
mid-range
synapses.
In
silico
tools
enabled
reproduction
extension
of
experiments
under
single
parameterization,
providing
strong
validation.
The
reproduced
millisecond-precise
stimulus-responses,
stimulus-encoding
targeted
optogenetic
activation,
selective
propagation
stimulus-evoked
activity
downstream
areas.
model’s
direct
correspondence
with
biology
generated
predictions
about
how
multiscale
organization
shapes
activity;
for
example,
cortical
is
shaped
by
high-dimensional
connectivity
motifs
connectivity,
spatial
targeting
rules
inhibitory
subpopulations.
latter
was
facilitated
using
rewired
connectome
included
specific
observed
different
neuron
types
electron
microscopy.
also
predicted
the
role
interneuron
layers
stimulus
encoding.
Simulation
large
subvolume
made
available
enable
further
community-driven
improvement,
validation
investigation.
Язык: Английский
Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons
Journal of Neuroscience,
Год журнала:
2024,
Номер
44(40), С. e1236242024 - e1236242024
Опубликована: Окт. 2, 2024
Understanding
the
brain
requires
studying
its
multiscale
interactions
from
molecules
to
networks.
The
increasing
availability
of
large-scale
datasets
detailing
circuit
composition,
connectivity,
and
activity
is
transforming
neuroscience.
However,
integrating
interpreting
this
data
remains
challenging.
Concurrently,
advances
in
supercomputing
sophisticated
modeling
tools
now
enable
development
highly
detailed,
biophysical
models.
These
mechanistic
models
offer
a
method
systematically
integrate
experimental
data,
facilitating
investigations
into
structure,
function,
disease.
This
review,
based
on
Society
for
Neuroscience
2024
MiniSymposium,
aims
disseminate
recent
broader
community.
It
highlights
(1)
examples
current
various
regions
developed
through
integration;
(2)
their
predictive
capabilities
regarding
cellular
mechanisms
underlying
recordings
(e.g.,
membrane
voltage,
spikes,
local-field
potential,
electroencephalography/magnetoencephalography)
function;
(3)
use
simulating
biomarkers
diseases
like
epilepsy,
depression,
schizophrenia,
Parkinson's,
aiding
understanding
underpinnings
developing
novel
treatments.
review
showcases
state-of-the-art
covering
hippocampus,
somatosensory,
visual,
motor,
auditory
cortical,
thalamic
circuits
across
species.
predict
neural
at
multiple
scales
provide
insights
sensation,
motor
behavior,
signals,
coding,
disease,
pharmacological
interventions,
stimulation.
Collaboration
with
neuroscientists
clinicians
essential
validation
these
models,
particularly
as
grow.
Hence,
foster
interest
detailed
leading
cross-disciplinary
collaborations
that
accelerate
research.
Язык: Английский
A biophysically-detailed model of inter-areal interactions in cortical sensory processing
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Окт. 13, 2024
Abstract
Mechanisms
of
top-down
modulation
in
sensory
perception
and
their
relation
to
underlying
connectivity
are
not
completely
understood.
We
present
here
a
biophysically-detailed
computational
model
two
interconnected
cortical
areas,
representing
the
first
steps
processing
hierarchy,
as
tool
for
potential
discovery.
The
integrates
large
body
data
from
rodent
primary
somatosensory
cortex
reproduces
biological
features
across
multiple
scales:
handful
ion
channels
defining
diversity
electrical
types
hundreds
thousands
morphologically
detailed
neurons,
local
long-range
networks
mediated
by
millions
synapses.
Notably,
incorporates
target
lamination
patterns
associated
with
feed-forward
feedback
pathways.
use
study
impact
inter-areal
interactions
on
processing.
First,
we
exhibit
cortico-cortical
loop
between
areas
(X
Y),
wherein
input
area
X
produces
response
components
time,
driven
stimulus
second
Y.
perform
structural
functional
characterization
this
loop,
finding
differential
layer-specific
pathways
directions.
Second,
explore
discrimination
presenting
four
different
spatially-segregate
patterns.
observe
well-defined
temporal
sequences
cell
assembly
activation,
specificity
early
but
late
assemblies
X,
i.e.,
stimulus-driven
component
feedback-driven
component.
also
find
earliest
Y
be
specific
pairs
patterns,
consistent
topography
connections.
Finally,
examine
integration
bottom-up
signals.
When
coincident
component,
an
approximate
linear
superposition
responses.
implied
lack
interaction
naive
absence
plasticity
mechanisms
that
would
underlie
learning
influences.
This
work
represents
step
simulations.
Язык: Английский
Kernel-based LFP estimation in detailed large-scale spiking network model of mouse visual cortex
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Ноя. 30, 2024
Simulations
of
large-scale
neural
activity
are
powerful
tools
for
investigating
networks.
Calculating
measurable
brain
signals
like
local
field
potentials
(LFPs)
bridges
the
gap
between
model
predictions
and
experimental
observations.
However,
accurately
simulating
LFPs
from
models
has
traditionally
required
highly
detailed
multicompartmental
neuron
models,
posing
significant
computational
challenges.
Here,
we
demonstrate
that
a
kernel-based
method
can
efficiently
estimate
in
state-of-the-art
mouse
primary
visual
cortex
(V1).
Beyond
its
efficiency,
kernel
aids
analysis
by
disentangling
contributions
individual
neuronal
populations
to
LFP.
Using
this
approach,
found
V1
were
dominated
external
synaptic
inputs,
with
playing
minimal
role.
Our
findings
establish
as
tool
LFP
estimation
network
uncovering
mechanisms
underlying
signals.
Язык: Английский
Computational modeling reveals biological mechanisms underlying the whisker-flick EEG
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 17, 2024
Abstract
Whisker
flick
stimulation
is
a
commonly
used
protocol
to
investigate
somatosensory
processing
in
rodents.
Neural
activity
the
brain
evoked
by
whisker
flicks
produces
characteristic
EEG
waveform
recorded
at
skull,
known
as
potential.
In
this
paper,
we
use
silico
modeling
identify
neural
populations
that
serve
sources
and
targets
of
synaptic
currents
contributing
signal
(presynaptic
postsynaptic
populations,
respectively).
The
initial
positive
deflection
driven
largely
direct
thalamic
inputs
Layer
2/3
5
pyramidal
cells,
though
interestingly,
L5-L5
inhibition
plays
modulatory
role,
reducing
amplitude
width
deflection.
This
suggests
increasing
thalamocortical
connectivity
decreasing
may
be
responsible
for
some
changes
observed
over
course
development.
negative
more
complex
mix
sources,
including
both
recurrent
cortical
connectivity.
We
demonstrate
small
local
circuit,
particularly
perisomatic
inhibitory
targeting,
can
have
an
important
impact
on
EEG,
without
substantially
affecting
firing
rates,
suggesting
useful
constraining
models.
Язык: Английский