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.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 6, 2025
How
specification
mechanisms
that
generate
neural
diversity
translate
into
specific
neuronal
targeting,
connectivity,
and
function
in
the
adult
brain
is
not
understood.
In
medulla
region
of
Drosophila
optic
lobe,
progenitors
different
neurons
a
fixed
order
by
sequentially
expressing
series
temporal
transcription
factors
as
they
age.
Then,
Notch
signaling
intermediate
further
diversifies
progeny.
By
establishing
birth
neurons,
we
found
their
identity
correlates
with
depth
neuropil
targeting
brain,
for
both
local
interneurons
projection
neurons.
We
show
this
identity-dependent
unfolds
early
development
genetically
determined.
leveraging
Electron
Microscopy
reconstruction
fly
determined
synapse
location
lobe
neuropils
find
it
significantly
associated
status.
Moreover,
all
putative
same
predicted
share
similar
location,
indicating
ensembles
layers
encode
visual
functions.
conclusion,
status
can
predict
function,
linking
developmental
patterning
connectivity
functional
features
brain.
Neurobiology of Sleep and Circadian Rhythms,
Год журнала:
2025,
Номер
18, С. 100112 - 100112
Опубликована: Янв. 18, 2025
Circadian
master
clocks
in
the
brain
consist
of
multiple
neurons
that
are
organized
into
populations
with
different
morphology,
physiology,
and
neuromessenger
content
presumably
functions.
In
most
animals,
these
distributed
bilaterally,
located
close
proximity
to
visual
system,
synchronized
by
eyes
light-dark
cycles
environment.
mammals
cockroaches,
each
two
consists
a
core
region
receives
information
from
shell
which
output
projections
originate,
whereas
flies
several
other
insects,
lateral
dorsal
regions.
all
cases,
morning
evening
clock
seem
exist,
communication
between
them
neurons,
as
well
connection
across
hemispheres,
is
prerequisite
for
normal
rhythmic
function.
Phenomena
such
rhythm
splitting,
internal
desynchronization
caused
"decoupling"
hemispheres
or
decoupling
certain
within
one
hemisphere.
Since
contain
relatively
few
characterized
at
individual
level,
fly
particularly
suited
study
neurons.
Here,
we
review
organization
bilateral
brain,
focus
on
synaptic
paracrine
connections
comparison
insects
mammals.
Physical Review Research,
Год журнала:
2025,
Номер
7(1)
Опубликована: Фев. 5, 2025
To
determine
the
precise
link
between
anatomical
structure
and
function,
brain
studies
primarily
concentrate
on
wiring
of
its
topological
properties.
In
this
work,
we
investigate
weighted
degree
connection
length
distributions
KKI-113
KKI-18
human
connectomes,
fruit
fly,
mouse
retina.
We
find
that
node
strength
(weighted
degree)
distribution
behavior
differs
depending
considered
scale.
On
global
scale,
are
found
to
follow
a
power-law
behavior,
with
roughly
universal
exponent
close
3.
However,
breaks
at
local
scale
as
stretched
exponential,
fly
retina
log-normal
distribution,
respectively,
which
indicative
underlying
random
multiplicative
processes
underpins
nonlocality
learning
in
critical
state.
for
case
H01
(1mm3)
datasets,
an
exponentially
truncated
power
law,
may
hint
fact
mechanism
have
manifested
level
too.
Published
by
American
Physical
Society
2025
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2023,
Номер
unknown
Опубликована: Июль 29, 2023
Abstract
Brains
comprise
complex
networks
of
neurons
and
connections.
Network
analysis
applied
to
the
wiring
diagrams
brains
can
offer
insights
into
how
support
computations
regulate
information
flow.
The
completion
first
whole-brain
connectome
an
adult
Drosophila
,
largest
date,
containing
130,000
millions
connections,
offers
unprecedented
opportunity
analyze
its
network
properties
topological
features.
To
gain
local
connectivity,
we
computed
prevalence
two-
three-node
motifs,
examined
their
strengths
neurotransmitter
compositions,
compared
these
metrics
with
other
animals.
We
discovered
that
fly
brain
displays
rich
club
organization,
a
large
population
(30%
percent
connectome)
highly
connected
neurons.
identified
subsets
may
serve
as
integrators
or
broadcasters
signals.
Finally,
subnetworks
based
on
78
anatomically
defined
regions
neuropils.
These
data
products
are
shared
within
FlyWire
Codex
will
foundation
for
models
experiments
exploring
relationship
between
neural
activity
anatomical
structure.
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.