Journal of Neuroscience,
Год журнала:
2018,
Номер
38(37), С. 7976 - 7985
Опубликована: Авг. 6, 2018
Calcium
imaging
is
a
powerful
method
to
record
the
activity
of
neural
populations
in
many
species,
but
inferring
spike
times
from
calcium
signals
challenging
problem.
We
compared
multiple
approaches
using
datasets
with
ground
truth
electrophysiology
and
found
that
simple
non-negative
deconvolution
(NND)
outperformed
all
other
algorithms
on
out-of-sample
test
data.
introduce
novel
benchmark
applicable
recordings
without
electrophysiological
truth,
based
correlation
responses
two
stimulus
repeats,
used
this
show
unconstrained
NND
also
when
run
“zoomed
out”
∼10,000
cell
visual
cortex
mice
either
sex.
Finally,
we
NND-based
methods
match
performance
supervised
convolutional
networks
while
avoiding
some
biases
such
methods,
at
much
faster
running
times.
therefore
recommend
spikes
be
inferred
traces
because
its
simplicity,
efficiency,
accuracy.
SIGNIFICANCE
STATEMENT
The
experimental
currently
allows
for
largest
numbers
cells
simultaneously
two-photon
imaging.
However,
use
requires
neuronal
firing
correctly
large
resulting
datasets.
Previous
studies
have
claimed
complex
learning
outperform
task.
Unfortunately,
these
suffered
several
problems
biases.
When
repeated
analysis,
same
data
correcting
problems,
simpler
inference
perform
better.
Even
more
importantly,
can
artifactual
structure
into
trains,
which
turn
lead
erroneous
scientific
conclusions.
Of
evaluated,
an
extremely
performed
best
circumstances
tested,
was
run,
insensitive
parameter
choices,
making
incorrect
conclusions
less
likely.
NeuroImage,
Год журнала:
2020,
Номер
222, С. 117254 - 117254
Опубликована: Авг. 13, 2020
Naturalistic
experimental
paradigms
in
neuroimaging
arose
from
a
pressure
to
test
the
validity
of
models
we
derive
highly-controlled
experiments
real-world
contexts.
In
many
cases,
however,
such
efforts
led
realization
that
developed
under
particular
manipulations
failed
capture
much
variance
outside
context
manipulation.
The
critique
non-naturalistic
is
not
recent
development;
it
echoes
persistent
and
subversive
thread
history
modern
psychology.
brain
has
evolved
guide
behavior
multidimensional
world
with
interacting
variables.
assumption
artificially
decoupling
manipulating
these
variables
will
lead
satisfactory
understanding
may
be
untenable.
We
develop
an
argument
for
primacy
naturalistic
paradigms,
point
developments
machine
learning
as
example
transformative
power
relinquishing
control.
should
deployed
afterthought
if
hope
build
extend
beyond
laboratory
into
real
world.
Annual Review of Neuroscience,
Год журнала:
2020,
Номер
43(1), С. 391 - 415
Опубликована: Апрель 6, 2020
Neural
activity
and
behavior
are
both
notoriously
variable,
with
responses
differing
widely
between
repeated
presentation
of
identical
stimuli
or
trials.
Recent
results
in
humans
animals
reveal
that
these
variations
not
random
their
nature,
but
may
fact
be
due
large
part
to
rapid
shifts
neural,
cognitive,
behavioral
states.
Here
we
review
recent
advances
the
understanding
waking
state,
how
generated,
they
modulate
neural
mice
humans.
We
propose
brain
has
an
identifiable
set
states
through
which
it
wanders
continuously
a
nonrandom
fashion,
owing
ascending
modulatory
fast-acting
corticocortical
subcortical-cortical
pathways.
These
state
provide
backdrop
upon
operates,
them
is
critical
making
progress
revealing
mechanisms
underlying
cognition
behavior.
Nature Communications,
Год журнала:
2021,
Номер
12(1)
Опубликована: Авг. 31, 2021
Abstract
Studying
naturalistic
animal
behavior
remains
a
difficult
objective.
Recent
machine
learning
advances
have
enabled
limb
localization;
however,
extracting
behaviors
requires
ascertaining
the
spatiotemporal
patterns
of
these
positions.
To
provide
link
from
poses
to
actions
and
their
kinematics,
we
developed
B-SOiD
-
an
open-source,
unsupervised
algorithm
that
identifies
without
user
bias.
By
training
classifier
on
pose
pattern
statistics
clustered
using
new
methods,
our
approach
achieves
greatly
improved
processing
speed
ability
generalize
across
subjects
or
labs.
Using
frameshift
alignment
paradigm,
overcomes
previous
temporal
resolution
barriers.
only
single,
off-the-shelf
camera,
provides
categories
sub-action
for
trained
kinematic
measures
individual
trajectories
in
any
model.
These
behavioral
are
but
critical
obtain,
particularly
study
rodent
other
models
pain,
OCD,
movement
disorders.
