BlueRecording: A pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: May 14, 2024
Abstract
As
the
size
and
complexity
of
network
simulations
accessible
to
computational
neuroscience
grows,
new
avenues
open
for
research
into
extracellularly
recorded
electric
signals.
Biophysically
detailed
permit
identification
biological
origins
different
components
signals,
evaluation
signal
sensitivity
anatomical,
physiological,
geometric
factors,
selection
recording
parameters
maximize
information
content.
Simultaneously,
virtual
extracellular
signals
produced
by
these
networks
may
become
important
metrics
neuro-simulation
validation.
To
enable
efficient
calculation
from
large
neural
simulations,
we
have
developed
BlueRecording
,
a
pipeline
consisting
standalone
Python
code,
along
with
extensions
Neurodamus
simulation
control
application,
CoreNEURON
computation
engine,
SONATA
data
format,
online
such
In
particular,
implement
general
form
reciprocity
theorem,
which
is
capable
handling
non-dipolar
current
sources,
as
be
found
in
long
axons
recordings
close
source,
well
complex
tissue
anatomy,
dielectric
heterogeneity,
electrode
geometries.
our
knowledge,
this
first
application
generalized
(i.e.,
non-dipolar)
reciprocity-based
approach
simulate
EEG
recordings.
We
use
tools
calculate
an
silico
model
rat
somatosensory
cortex
hippocampus
study
contribution
differences
between
regions
cell
types.
Language: Английский
Modeling and Simulation of Neocortical Micro- and Mesocircuitry. Part I: Anatomy
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2022,
Volume and Issue:
unknown
Published: Aug. 15, 2022
Abstract
The
function
of
the
neocortex
is
fundamentally
determined
by
its
repeating
microcircuit
motif,
but
also
rich,
interregional
connectivity.
We
present
a
data-driven
computational
model
anatomy
non-barrel
primary
somatosensory
cortex
juvenile
rat,
integrating
whole-brain
scale
data
while
providing
cellular
and
subcellular
specificity.
consists
4.2
million
morphologically
detailed
neurons,
placed
in
digital
brain
atlas.
They
are
connected
14.2
billion
synapses,
comprising
local,
mid-range
extrinsic
delineated
limits
determining
connectivity
from
neuron
morphology
placement,
finding
that
it
reproduces
targeting
Sst+
requires
additional
specificity
to
reproduce
PV+
VIP+
interneurons.
Globally,
was
characterized
local
clusters
tied
together
through
hub
neurons
layer
5,
demonstrating
how
interegional
complicit,
inseparable
networks.
suitable
for
simulation-based
studies,
211,712
subvolume
made
openly
available
community.
Language: Английский
Large-Scale Mechanistic Models of Brain Circuits with Biophysically and Morphologically Detailed Neurons
Journal of Neuroscience,
Journal Year:
2024,
Volume and Issue:
44(40), P. e1236242024 - e1236242024
Published: Oct. 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.
Language: Английский
Assemblies, synapse clustering and network topology interact with plasticity to explain structure-function relationships of the cortical connectome
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Aug. 7, 2023
Synaptic
plasticity
underlies
the
brain's
ability
to
learn
and
adapt.
While
experiments
in
brain
slices
have
revealed
mechanisms
protocols
for
induction
of
between
pairs
neurons,
how
these
synaptic
changes
are
coordinated
biological
neuronal
networks
ensure
emergence
learning
remains
poorly
understood.
Simulation
modeling
emerged
as
important
tools
study
plastic
networks,
but
yet
achieve
a
scale
that
incorporates
realistic
network
structure,
active
dendrites,
multi-synapse
interactions,
key
determinants
plasticity.
To
rise
this
challenge,
we
endowed
an
existing
large-scale
cortical
model,
incorporating
data-constrained
dendritic
processing
multi-synaptic
connections,
with
calcium-based
model
functional
captures
diversity
excitatory
connections
extrapolated
vivo-like
conditions.
This
allowed
us
dendrites
structure
interact
shape
stimulus
representations
at
microcircuit
level.
In
our
exploratory
simulations,
acted
sparsely
specifically,
firing
rates
weight
distributions
remained
stable
without
additional
homeostatic
mechanisms.
At
circuit
level,
found
was
driven
by
co-firing
stimulus-evoked
assemblies,
spatial
clustering
synapses
on
topology
connectivity.
As
result
changes,
became
more
reliable
stimulus-specific
responses.
We
confirmed
testable
predictions
MICrONS
datasets,
openly
available
electron
microscopic
reconstruction
large
volume
tissue.
Our
results
quantify
architecture
higher-order
microcircuits
play
central
role
provide
foundation
elucidating
their
learning.
Language: Английский
An extended and improved CCFv3 annotation and Nissl atlas of the entire mouse brain
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 8, 2024
ABSTRACT
Brain
atlases
are
essential
for
quantifying
cellular
composition
in
mouse
brain
regions.
The
Allen
Institute’s
Common
Coordinate
Framework
version
3
(CCFv3)
is
widely
used,
delineating
over
600
anatomical
regions,
but
it
lacks
coverage
the
most
rostral
and
caudal
parts,
including
main
olfactory
bulb,
cerebellum,
medulla.
Additionally,
CCFv3
omits
key
cerebellar
layers,
its
corresponding
Nissl-stained
reference
volume
not
precisely
aligned,
limiting
utilisability.
To
address
these
issues,
we
developed
an
extended
atlas,
Blue
Project
augmented
(CCFv3aBBP),
which
includes
a
fully
annotated
improved
Nissl
aligned
CCFv3.
This
enhanced
atlas
also
features
central
nervous
system
annotation
(CCFv3cBBP).
Using
this
resource,
734
brains
to
produce
average
template,
enabling
updated
distribution
of
neuronal
soma
positions.
These
data
available
as
open-source
broadening
applications
such
alignment
precision,
cell
type
mapping,
multimodal
integration.
Language: Английский