PLoS Biology,
Journal Year:
2019,
Volume and Issue:
17(2), P. e3000021 - e3000021
Published: Feb. 7, 2019
The
ability
to
perceive
and
recognise
a
reflected
mirror
image
as
self
(mirror
self-recognition,
MSR)
is
considered
hallmark
of
cognition
across
species.
Although
MSR
has
been
reported
in
mammals
birds,
it
not
known
occur
any
other
major
taxon.
Potentially
limiting
our
test
for
taxa
that
the
established
assay,
mark
test,
requires
animals
display
contingency
testing
self-directed
behaviour.
These
behaviours
may
be
difficult
humans
interpret
taxonomically
divergent
animals,
especially
those
lack
dexterity
(or
limbs)
required
touch
mark.
Here,
we
show
fish,
cleaner
wrasse
Labroides
dimidiatus,
shows
behaviour
reasonably
interpreted
passing
through
all
phases
test:
(i)
social
reactions
towards
reflection,
(ii)
repeated
idiosyncratic
mirror,
(iii)
frequent
observation
their
reflection.
When
subsequently
provided
with
coloured
tag
modified
fish
attempt
remove
by
scraping
body
presence
but
no
response
transparent
marks
or
absence
mirror.
This
remarkable
finding
presents
challenge
interpretation
test—do
accept
these
behavioural
responses,
which
are
taken
evidence
self-recognition
species
during
lead
conclusion
self-aware?
Or
do
rather
decide
patterns
have
basis
cognitive
process
than
pass
test?
If
former,
what
does
this
mean
understanding
animal
intelligence?
latter,
application
metric
abilities?This
Short
Report
received
both
positive
negative
reviews
experts.
Academic
Editor
written
an
accompanying
Primer
publishing
alongside
article
(https://doi.org/10.1371/journal.pbio.3000112).
linked
complementary
expert
perspective;
discusses
how
current
study
should
context
against
self-awareness
wide
range
animals.
Proceedings of the National Academy of Sciences,
Journal Year:
2015,
Volume and Issue:
112(38)
Published: Sept. 9, 2015
A
lack
of
automated,
quantitative,
and
accurate
assessment
social
behaviors
in
mammalian
animal
models
has
limited
progress
toward
understanding
mechanisms
underlying
interactions
their
disorders
such
as
autism.
Here
we
present
a
new
integrated
hardware
software
system
that
combines
video
tracking,
depth
sensing,
machine
learning
for
automatic
detection
quantification
involving
close
dynamic
between
two
mice
different
coat
colors
home
cage.
We
designed
setup
integrates
traditional
cameras
with
camera,
developed
computer
vision
tools
to
extract
the
body
"pose"
individual
animals
context,
used
supervised
algorithm
classify
several
well-described
behaviors.
validated
robustness
automated
classifiers
various
experimental
settings
them
examine
how
genetic
background,
Black
Tan
Brachyury
(BTBR)
(a
previously
reported
autism
model),
influences
behavior.
Our
approach
allows
rapid,
measurement
across
diverse
designs
also
affords
ability
develop
new,
objective
behavioral
metrics.
Annual Review of Neuroscience,
Journal Year:
2016,
Volume and Issue:
39(1), P. 217 - 236
Published: April 19, 2016
In
this
review,
we
discuss
the
emerging
field
of
computational
behavioral
analysis-the
use
modern
methods
from
computer
science
and
engineering
to
quantitatively
measure
animal
behavior.
We
aspects
experiment
design
important
both
obtaining
biologically
relevant
data
enabling
machine
vision
learning
techniques
for
automation.
These
two
goals
are
often
in
conflict.
Restraining
or
restricting
environment
can
simplify
automatic
behavior
quantification,
but
it
also
degrade
quality
alter
To
enable
biologists
experiments
obtain
better
measurements,
scientists
pinpoint
fruitful
directions
algorithm
improvement,
review
known
effects
artificial
manipulation
on
tracking,
feature
extraction,
automated
classification,
discovery,
assumptions
they
make,
types
work
best
with.