bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Июль 28, 2023
Abstract
Advances
in
Electron
Microscopy,
image
segmentation
and
computational
infrastructure
have
given
rise
to
large-scale
richly
annotated
connectomic
datasets
which
are
increasingly
shared
across
communities.
To
enable
collaboration,
users
need
be
able
concurrently
create
new
annotations
correct
errors
the
automated
by
proofreading.
In
large
datasets,
every
proofreading
edit
relabels
cell
identities
of
millions
voxels
thousands
like
synapses.
For
analysis,
require
immediate
reproducible
access
this
constantly
changing
expanding
data
landscape.
Here,
we
present
Connectome
Annotation
Versioning
Engine
(CAVE),
a
for
connectome
analysis
up-to
petascale
(∼1mm
3
)
while
annotating
is
ongoing.
segmentation,
CAVE
provides
distributed
continuous
versioning
reconstructions.
Annotations
defined
locations
such
that
they
can
quickly
assigned
underlying
segment
enables
fast
queries
CAVE’s
arbitrary
time
points.
supports
schematized,
extensible
annotations,
so
researchers
readily
design
novel
annotation
types.
already
used
many
connectomics
including
largest
available
date.
The
neural
circuits
responsible
for
animal
behavior
remain
largely
unknown.
We
summarize
new
methods
and
present
the
circuitry
of
a
large
fraction
brain
fruit
fly
Drosophila
melanogaster
.
Improved
include
procedures
to
prepare,
image,
align,
segment,
find
synapses
in,
proofread
such
data
sets.
define
cell
types,
refine
computational
compartments,
provide
an
exhaustive
atlas
examples
many
them
novel.
detailed
consisting
neurons
their
chemical
most
central
brain.
make
public
simplify
access,
reducing
effort
needed
answer
circuit
questions,
linking
defined
by
our
analysis
with
genetic
reagents.
Biologically,
we
examine
distributions
connection
strengths,
motifs
on
different
scales,
electrical
consequences
compartmentalization,
evidence
that
maximizing
packing
density
is
important
criterion
in
evolution
fly’s
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Июнь 30, 2023
Abstract
Connections
between
neurons
can
be
mapped
by
acquiring
and
analyzing
electron
microscopic
(EM)
brain
images.
In
recent
years,
this
approach
has
been
applied
to
chunks
of
brains
reconstruct
local
connectivity
maps
that
are
highly
informative,
yet
inadequate
for
understanding
function
more
globally.
Here,
we
present
the
first
neuronal
wiring
diagram
a
whole
adult
brain,
containing
5×10
7
chemical
synapses
∼130,000
reconstructed
from
female
Drosophila
melanogaster
.
The
resource
also
incorporates
annotations
cell
classes
types,
nerves,
hemilineages,
predictions
neurotransmitter
identities.
Data
products
available
download,
programmatic
access,
interactive
browsing
made
interoperable
with
other
fly
data
resources.
We
show
how
derive
projectome,
map
projections
regions,
connectome.
demonstrate
tracing
synaptic
pathways
analysis
information
flow
inputs
(sensory
ascending
neurons)
outputs
(motor,
endocrine,
descending
neurons),
across
both
hemispheres,
central
optic
lobes.
Tracing
subset
photoreceptors
all
way
motor
illustrates
structure
uncover
putative
circuit
mechanisms
underlying
sensorimotor
behaviors.
technologies
open
ecosystem
FlyWire
Consortium
set
stage
future
large-scale
connectome
projects
in
species.
Proceedings of the National Academy of Sciences,
Год журнала:
2022,
Номер
119(48)
Опубликована: Ноя. 23, 2022
Neurons
in
the
developing
brain
undergo
extensive
structural
refinement
as
nascent
circuits
adopt
their
mature
form.
This
physical
transformation
of
neurons
is
facilitated
by
engulfment
and
degradation
axonal
branches
synapses
surrounding
glial
cells,
including
microglia
astrocytes.
However,
small
size
phagocytic
organelles
complex,
highly
ramified
morphology
glia
have
made
it
difficult
to
define
contribution
these
other
cell
types
this
crucial
process.
Here,
we
used
large-scale,
serial
section
transmission
electron
microscopy
(TEM)
with
computational
volume
segmentation
reconstruct
complete
3D
morphologies
distinct
mouse
visual
cortex,
providing
unprecedented
resolution
composition.
Unexpectedly,
discovered
that
fine
processes
oligodendrocyte
precursor
cells
(OPCs),
a
population
abundant,
dynamic
progenitors,
frequently
surrounded
axons.
Numerous
phagosomes
phagolysosomes
(PLs)
containing
fragments
axons
vesicular
structures
were
present
inside
processes,
suggesting
OPCs
engage
axon
pruning.
Single-nucleus
RNA
sequencing
from
cortex
revealed
express
key
genes
at
stage,
well
neuronal
transcripts,
consistent
active
engulfment.
Although
are
thought
be
responsible
for
majority
synaptic
pruning
refinement,
PLs
ten
times
more
abundant
than
markedly
less
newly
generated
oligodendrocytes,
contribute
substantially
during
cortical
development.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Янв. 24, 2023
Mammalian
cortex
features
a
vast
diversity
of
neuronal
cell
types,
each
with
characteristic
anatomical,
molecular
and
functional
properties.
Synaptic
connectivity
powerfully
shapes
how
type
participates
in
the
cortical
circuit,
but
mapping
rules
at
resolution
distinct
types
remains
difficult.
Here,
we
used
millimeter-scale
volumetric
electron
microscopy
1
to
investigate
all
inhibitory
neurons
across
densely-segmented
population
1352
cells
spanning
layers
mouse
visual
cortex,
producing
wiring
diagram
connections
more
than
70,000
synapses.
Taking
data-driven
approach
inspired
by
classical
neuroanatomy,
classified
based
on
relative
targeting
dendritic
compartments
other
developed
novel
classification
excitatory
morphological
synaptic
input
The
between
revealed
class
disinhibitory
specialist
basket
cells,
addition
familiar
subclasses.
Analysis
onto
found
widespread
specificity,
many
interneurons
exhibiting
differential
certain
subpopulations
spatially
intermingled
potential
targets.
Inhibitory
was
organized
into
“motif
groups,”
diverse
sets
that
collectively
target
both
perisomatic
same
Collectively,
our
analysis
identified
new
organizing
principles
for
inhibition
will
serve
as
foundation
linking
modern
multimodal
atlases
diagram.
Nature Methods,
Год журнала:
2024,
Номер
21(5), С. 908 - 913
Опубликована: Март 21, 2024
Mapping
neuronal
networks
from
three-dimensional
electron
microscopy
(3D-EM)
data
still
poses
substantial
reconstruction
challenges,
in
particular
for
thin
axons.
Currently
available
automated
image
segmentation
methods
require
manual
proofreading
many
types
of
connectomic
analysis.
Here
we
introduce
RoboEM,
an
artificial
intelligence-based
self-steering
3D
'flight'
system
trained
to
navigate
along
neurites
using
only
3D-EM
as
input.
Applied
mouse
and
human
cortex,
RoboEM
substantially
improves
state-of-the-art
segmentations
can
replace
more
complex
analysis
problems,
yielding
computational
annotation
cost
cortical
connectomes
about
400-fold
lower
than
the
error
correction.