Abstract
In
the
last
decade,
researchers
using
Drosophila
melanogaster
have
made
extraordinary
progress
in
uncovering
mysteries
underlying
learning
and
memory.
This
has
been
propelled
by
amazing
toolkit
available
that
affords
combined
behavioral,
molecular,
electrophysiological,
systems
neuroscience
approaches.
The
arduous
reconstruction
of
electron
microscopic
images
resulted
a
first-generation
connectome
adult
larval
brain,
revealing
complex
structural
interconnections
between
memory-related
neurons.
serves
as
substrate
for
future
investigations
on
these
connections
building
complete
circuits
from
sensory
cue
detection
to
changes
motor
behavior.
Mushroom
body
output
neurons
(MBOn)
were
discovered,
which
individually
forward
information
discrete
non-overlapping
compartments
axons
mushroom
(MBn).
These
mirror
previously
discovered
tiling
inputs
dopamine
led
model
ascribes
valence
event,
either
appetitive
or
aversive,
activity
different
populations
balance
MBOn
promoting
avoidance
approach
Studies
calyx,
houses
MBn
dendrites,
revealed
beautiful
microglomeruluar
organization
synapses
occur
with
long-term
memory
(LTM)
formation.
Larval
advanced,
positioning
it
possibly
lead
producing
new
conceptual
insights
due
its
markedly
simpler
structure
over
brain.
Advances
how
cAMP
response
element-binding
protein
interacts
kinases
other
transcription
factors
promote
formation
LTM.
New
Orb2,
prion-like
forms
oligomers
enhance
synaptic
synthesis
required
LTM
Finally,
research
pioneered
our
understanding
mechanisms
mediate
permanent
transient
active
forgetting,
an
important
function
brain
along
acquisition,
consolidation,
retrieval.
was
catalyzed
partly
identification
suppressor
genes—genes
whose
normal
is
limit
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
Making
inferences
about
the
computations
performed
by
neuronal
circuits
from
synapse-level
connectivity
maps
is
an
emerging
opportunity
in
neuroscience.
The
mushroom
body
(MB)
well
positioned
for
developing
and
testing
such
approach
due
to
its
conserved
architecture,
recently
completed
dense
connectome,
extensive
prior
experimental
studies
of
roles
learning,
memory,
activity
regulation.
Here,
we
identify
new
components
MB
circuit
Drosophila,
including
visual
input
output
neurons
(MBONs)
with
direct
connections
descending
neurons.
We
find
unexpected
structure
sensory
inputs,
transfer
information
different
modalities
MBONs,
modulation
that
dopaminergic
(DANs).
provide
insights
into
circuitry
used
integrate
outputs,
between
central
complex
inputs
DANs,
feedback
MBONs.
Our
results
a
foundation
further
theoretical
work.
Flexible
behaviors
over
long
timescales
are
thought
to
engage
recurrent
neural
networks
in
deep
brain
regions,
which
experimentally
challenging
study.
In
insects,
circuit
dynamics
a
region
called
the
central
complex
(CX)
enable
directed
locomotion,
sleep,
and
context-
experience-dependent
spatial
navigation.
We
describe
first
complete
electron
microscopy-based
connectome
of
To
analyse
neuron
data
at
scale,
neuroscientists
expend
substantial
effort
reading
documentation,
installing
dependencies
and
moving
between
analysis
visualisation
environments.
facilitate
this,
we
have
developed
a
suite
of
interoperable
open-source
R
packages
called
the
natverse.
The
natverse
allows
users
to
read
local
remote
data,
perform
popular
analyses
including
clustering
graph-theoretic
neuronal
branching.
Unlike
most
tools,
enables
comparison
across
many
neurons
morphology
connectivity
after
imaging
or
co-registration
within
common
template
space.
also
transformations
different
spaces
modalities.
We
demonstrate
tools
that
integrate
vast
majority
Current Biology,
Год журнала:
2020,
Номер
30(16), С. 3183 - 3199.e6
Опубликована: Июль 2, 2020
Nervous
systems
contain
sensory
neurons,
local
projection
and
motor
neurons.
To
understand
how
these
building
blocks
form
whole
circuits,
we
must
distil
broad
classes
into
neuronal
cell
types
describe
their
network
connectivity.
Using
an
electron
micrograph
dataset
for
entire
Drosophila
melanogaster
brain,
reconstruct
the
first
complete
inventory
of
olfactory
projections
connecting
antennal
lobe,
insect
analog
mammalian
bulb,
to
higher-order
brain
regions
in
adult
animal
brain.
We
then
connect
this
extant
data
literature,
providing
synaptic-resolution
"holotypes"
both
heavily
investigated
previously
unknown
types.
Projection
neurons
are
approximately
twice
as
numerous
reported
by
light
level
studies;
stereotyped,
but
not
identical,
synapse
numbers
between
hemispheres.
The
lateral
horn,
cortical
amygdala,
is
main
target
information
has
been
shown
guide
innate
behavior.
Here,
find
new
connectivity
motifs,
including
axo-axonic
feedback,
inhibition
axons
a
large
population
convergence
different
inputs,
non-olfactory
inputs
memory-related
feedback
onto
third-order
These
features
less
prominent
mushroom
body
calyx,
piriform
cortex
center
associative
memory.
Our
work
provides
neuroanatomical
platform
future
studies
system.
Annual Review of Neuroscience,
Год журнала:
2020,
Номер
43(1), С. 465 - 484
Опубликована: Апрель 14, 2020
The
Drosophila
brain
contains
a
relatively
simple
circuit
for
forming
Pavlovian
associations,
yet
it
achieves
many
operations
common
across
memory
systems.
Recent
advances
have
established
clear
framework
learning
and
revealed
the
following
key
operations:
a)
pattern
separation,
whereby
dense
combinatorial
representations
of
odors
are
preprocessed
to
generate
highly
specific,
nonoverlapping
odor
patterns
used
learning;
b)
convergence,
in
which
sensory
information
is
funneled
small
set
output
neurons
that
guide
behavioral
actions;
c)
plasticity,
where
changing
mapping
input
requires
strong
reinforcement
signal,
also
modulated
by
internal
state
environmental
context;
d)
modularization,
consists
multiple
parallel
traces,
distinct
stability
flexibility
exist
anatomically
well-defined
modules
within
network.
Cross-module
interactions
allow
higher-order
effects
past
experience
influences
future
learning.
Many
these
parallels
with
processes
formation
action
selection
more
complex
brains.
Cell,
Год журнала:
2024,
Номер
187(10), С. 2574 - 2594.e23
Опубликована: Май 1, 2024
High-resolution
electron
microscopy
of
nervous
systems
has
enabled
the
reconstruction
synaptic
connectomes.
However,
we
do
not
know
sign
for
each
connection
(i.e.,
whether
a
is
excitatory
or
inhibitory),
which
implied
by
released
transmitter.
We
demonstrate
that
artificial
neural
networks
can
predict
transmitter
types
presynapses
from
micrographs:
network
trained
to
six
transmitters
(acetylcholine,
glutamate,
GABA,
serotonin,
dopamine,
octopamine)
achieves
an
accuracy
87%
individual
synapses,
94%
neurons,
and
91%
known
cell
across
D.
melanogaster
whole
brain.
visualize
ultrastructural
features
used
prediction,
discovering
subtle
but
significant
differences
between
phenotypes.
also
analyze
distributions
brain
find
neurons
develop
together
largely
express
only
one
fast-acting
GABA).
hope
our
publicly
available
predictions
act
as
accelerant
neuroscientific
hypothesis
generation
fly.
Nature Communications,
Год журнала:
2022,
Номер
13(1)
Опубликована: Авг. 8, 2022
Abstract
To
navigate
towards
a
food
source,
animals
frequently
combine
odor
cues
about
source
identity
with
wind
direction
location.
Where
and
how
these
two
are
integrated
to
support
navigation
is
unclear.
Here
we
describe
pathway
the
Drosophila
fan-shaped
body
that
encodes
attractive
promotes
upwind
navigation.
We
show
neurons
throughout
this
encode
odor,
but
not
direction.
Using
connectomics,
identify
local
called
h∆C
receive
input
from
previously
described
pathway.
exhibit
odor-gated,
direction-tuned
activity,
sparse
activation
of
in
reproducible
direction,
activity
required
for
persistent
orientation
during
odor.
Based
on
connectome
data,
develop
computational
model
showing
can
promote
goal
such
as
an
source.
Our
results
suggest
processed
by
separate
pathways
within
goal-directed