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The dog (Canis familiaris) is a promising non-invasive translational model of human cognitive neuroscience including sleep research. Studies on the relationship between sleep and cognition in dogs and other canines are only just emerging, but still very scarce. Here we provide insight into canine sleep and sleep-related physiological and cognitive/behavioral phenomena. We show that dogs do not only fulfil all behavioral and polygraphic criteria of sleep, but are characterized by sleep homeostasis, diurnal pattern of activity, circadian rhythms, ultradian sleep cycles, socio-ecologically and environmentally shaped wake-sleep structure, sleep-related memory improvement, as well as specific sleep disorders. Developmental patterns of sleep-related physiological indices, as well as parallel trends in age-dependent changes in cognition and sleep were evidenced in dogs.
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Sleep
in
the
dog:
comparative,
behavioral
and
translational
relevance
Ro
´bert
Bo
´dizs
1,2
,
Anna
Kis
3
,
Ma
´rta
Ga
´csi
4,5
and
Jo
´zsef
Topa
´l
3
The
dog
(Canis
familiaris)
is
a
promising
non-invasive
translational
model
of
human
cognitive
neuroscience
including
sleep
research.
Studies
on
the
relationship
between
sleep
and
cognition
in
dogs
and
other
canines
are
only
just
emerging,
but
still
very
scarce.
Here
we
provide
insight
into
canine
sleep
and
sleep-related
physiological
and
cognitive/behavioral
phenomena.
We
show
that
dogs
do
not
only
fulfil
all
behavioral
and
polygraphic
criteria
of
sleep,
but
are
characterized
by
sleep
homeostasis,
diurnal
pattern
of
activity,
circadian
rhythms,
ultradian
sleep
cycles,
socio-ecologically
and
environmentally
shaped
wake-sleep
structure,
sleep-related
memory
improvement,
as
well
as
specific
sleep
disorders.
Developmental
patterns
of
sleep-related
physiological
indices,
as
well
as
parallel
trends
in
age-dependent
changes
in
cognition
and
sleep
were
evidenced
in
dogs.
Addresses
1
Institute
of
Behavioural
Sciences,
Semmelweis
University,
H-1089
Budapest,
Hungary
2
Epilepsy
Center,
National
Institute
of
Clinical
Neurosciences,
H-1145
Budapest,
Hungary
3
Institute
of
Cognitive
Neuroscience
and
Psychology,
Research
Centre
for
Natural
Sciences
H-1117
Budapest,
Hungary
4
Department
of
Ethology,
Institute
of
Biology,
Eo
¨tvo
¨s
Lora
´nd
University,
H-1117
Budapest,
Hungary
5
MTA-ELTE
Comparative
Ethology
Research
Group,
H-1117
Budapest,
Hungary
Corresponding
author:
Bo
´dizs,
Ro
´bert
(bodizs.robert@med.semmelweis-univ.hu)
Current
Opinion
in
Behavioral
Sciences
2019,
33:25–33
This
review
comes
from
a
themed
issue
on
Cognition
and
perception
*sleep
and
cognition*
Edited
by
Michael
Chee
and
Philippe
Peigneux
https://doi.org/10.1016/j.cobeha.2019.12.006
2352-1546/ã
2019
The
Author(s).
Published
by
Elsevier
Ltd.
This
is
an
open
access
article
under
the
CC
BY-NC-ND
license
(http://creative-
commons.org/licenses/by-nc-nd/4.0/).
Introduction:
why
is
dog
sleep
relevant
for
humans?
Behavioral
sleep
is
common
in
the
animal
kingdom,
whereas
polygraphically
defined
sleep
is
best
characterized
in
mammals
[1],
including
the dog (Table 1).
The
dominant
(and
somewhat
implicitly
idealized)
subject
of
sleep
research
is
the
young,
healthy
human
and
the
laboratory
rodent
(most
often
the
rat).
Most
of
our
current
knowledge
on
sleep
comes
from
these
species
(and
age
group),
thus
the
available
knowledge
is
seriously
restricted.
The
non-
human/non-rodent
sleep
studies
are
mainly
performed
on
laboratory
cats
[2].
In
accordance
with
shared
evolutionary
history
(domes-
tication)
and
social
environment
of
family
dogs
and
humans,
the
dog
has
been
successfully
applied
as
a
model
species
for
comparative
investigations
of
several
human
socio-cognitive
skills
[3
].
Considering
estab-
lished
parallels
in
dog
and
human
psychopathology
[4],
research
of
brain
mechanisms
underlying
the
dog’s
cognitive,
behavioral
and
social
dysfunctions,
in
the
long
run,
hold
promise
for
an
improved
understanding
of
human
neuropsychiatric
conditions,
such
as
obsessive-
compulsive
disorder
[5],
autism
[3
],
or
sleep
disorders,
like
narcolepsy,
sleep-disordered
breathing
and
REM
behavior
disorder
(Box
1).
Methodological
issues
in
canine
sleep
studies
Sleep
studies
on
dogs
have
been
carried
out
with
methods
ranging
from
behavioral
observations
to
sur-
gical
procedures,
differing
in
invasiveness,
ecological
validity
and
specificity
(Table
2).
The
advantages
of
the
recently
established
family
dog
sleep
model
[13

]
include
(i)
dogs’
unique
willingness
to
cooperate
during
the
measurements
to
an
extent
comparable
to
or
even
exceeding
children
(thus
allowing
the
use
of
fully
non-invasive
methods),
(ii)
a
relatively
large
sample
size
(availability
of
a
large
number
of
pet
dogs),
(iii)
subjects
that
live
(and
can
be
measured)
in
their
natural
environment,
and
(iv)
significant
inter-breed
and
inter-
individual
variability
in
their
human
analogous
social
behaviors
and
cognitive
performance,
including
natural
extremes
(Figure
1).
Sleep-wake
cycle
basics
in
the
domestic
dog
Overall
sleep
length
in
dogs
Comparative
databases
use
the
value
of
10.1
hours
of
average
daily
sleep
for
the
domestic
dog
[14].
Reported
values
vary
between
7.7
and
16
hours
[15].
Whether
the
21%/day
of
drowsiness
seen
in
dogs
and
several
other
species
but
neither
humans
nor
rodents,
can
be
consid-
ered
‘light
sleep’
[11]
or
a
transitional
state
[16]
is
a
matter
of
debate,
and
alters
the
estimations
of
total
sleep
time
in
this
species
[15].
To
put
in
context,
laboratory
rats
sleep
around
13
hours,
whereas
humans
sleep
7–8
hours
daily
[14].
Available
online
at
www.sciencedirect.com
ScienceDirect
www.sciencedirect.com
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
Sleep
homeostasis
in
dogs
Several
findings
indicate
the
presence
of
sleep
homeo-
stasis
in
dogs.
Lost
sleep
is
recovered
in
terms
of
decreased
motor
activity
[17],
increased
initial
slow
wave
sleep
and
a
later
increase
in
the
percentage
of
REM
sleep
[18],
as
well
as
in
increased
electroencephalogram
(EEG)
slow
wave/delta
activity
during
NREM
sleep
[19].
Growth
hormone
release
is
strongly
associated
with
early
episodes
of
deep
(slow
wave)
sleep
in
humans
[20],
whereas
such
association
is
not
seen
under
baseline
conditions
in
dogs
[21].
However,
canine
growth
hormone
secretion
becomes
associated
with
slow
wave
sleep
during
rebound
sleep
after
sleep
deprivation
(i.e.
during
deeper,
more
intense
sleep
containing
more
slow
waves)
[21].
That
is,
the
unique
neuroendocrine
state
characterized
by
increased
growth
hormone
and
decreased
cortisol
during
early
sleep
and
its
proposed
restorative
and
neurocognitive
functions
[22]
is
not
emerging
during
baseline
conditions
in
dogs,
but
can
be
induced
by
increasing
sleep
pressure.
26
Cognition
and
perception
*sleep
and
cognition*
Table
1
The
criteria
of
sleep
and
theirs
fulfilment
in
dogs
a
Specific
criteria
Presence
in
dogs
Type
of
evidence
(methodology)
NReference(s)
Behavioural
criteria
Motor
rest
.
.
.
is
evidently
associated
with
other
signs
of
sleep
Video
recordings,
polysomnography
(including
EMG)
23
[19,24]
Stereotyped
posture(s)
Lying
with
head
on
or
between
the
forepaws,
or
on
the
side
or
back,
with
neck
muscles
relaxed
Video
recordings
24
[24]
Increased
sensory
thresholds
Slow
wave
sleep:
‘The
dogs
do
not
react
behaviorally
to
external
stimuli,
but
may
show
a
short-lasting
desynchronization
of
the
EEG.’
Invasive
EEG
b
/
polysomnography
7
[16]
Reversibility-
arousability
.
.
.
was
proven
by
auditory
stimulation
Invasive
EEG/
polysomnography
5
[56]
Specific
rest
sites
.
.
.
are
used
for
sleeping
and
are
frequently
provided
by
the
owners
Video
recordings
17
[57]
Homeostatic
regulation
.
.
.
was
reported
in
terms
of
both
motor
and
EEG
activity
Actigraphy,
invasive
EEG/
polysomnography
10
[17,18]
Circadian
organization
Dogs
are
diurnal
in
terms
of
motor
activity,
core
body
temperature,
plasma
melatonin
rhythm
and
EEG/polygraphic
criteria
Actigraphy,
metabolism
kennels,
repeated
blood
sampling,
non-invasive
polysomnography
15
[17,28

,58,59,25

]
Eye
closure
.
.
.
is
present
in
resting/
sleeping
dogs
Video
recordings
24
[24]
Polygraphic
criteria
(mammalian
type)
NREM
c
EEG
slow
waves
and
spindles,
lack
of
rapid
eye
movements;
HR
e
<60
beats/min;
slow,
deep,
and
less
variable
breathing;
reduced
EMG
f
Invasive
and
non-invasive
EEG/polysomnography
14.2
[16,19,32,33
,60]
REM
d
Low
amplitude
high
frequency
EEG
activity
(cortex),
hippocampal
rhythmic
slow
activity,
rapid
eye
movements;
HR
<60
beats/min;
rapid,
shallow,
and
irregular
breathing;
reduced
EMG
with
occasional
phasic
increase
(twitches)
Invasive
and
non-invasive
EEG/polysomnography
a
The
list
of
features
is
based
on
the
criteria
summarized
by
Nicolau
et
al.
[1].
b
EEG
electroencephalography.
c
NREM
non
rapid
eye
movement
sleep.
d
REM
rapid
eye
movement
sleep.
e
HR
heart
rate.
f
EMG
electromyography.
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
www.sciencedirect.com
Circadian
regulation
of
sleep
in
dogs
The
majority
of
motor
inactivity/polygraphic
sleep
of
dogs
occurs
between
21.00
and
6.00
with
a
period
of
rest
during
the
afternoon
[17,23,24].
Night
sleep
was
characterized
by
higher
sleep
efficiency
and
continuity
as
compared
to
afternoon
naps
[25

].
Corroboration
of
these
findings
with
the
reported
core
body
temperature
rhythms
(increasing
temperature
during
most
of
the
light
period
and
decreasing
during
the
dark)
[26,27,28

]
clearly
indicates
a
diurnal
type
of
wake-sleep
pattern
in
dogs.
It
has
to
be
noted
however,
that
unlike
in
humans,
the
circadian
variation
in
cortisol
level
is
not
always
found
in
dogs
[21,26].
In
contrast
to
human
mRNA
levels
of
clock
genes
period1
and
period2
measured
in
peripheral
blood
mononuclear
cells
reflecting
evident
circadian
expression
profiles,
only
period1,
but
not
period2
was
characterized
by
such
profile
in
dogs
[26].
Diurnal
activity
of
domestic
dogs
is
hypothesized
to
reflect
an
adaptation
to
humans,
as
there
is
evidence
for
nocturnal,
crepuscular
or
arrhyth-
mic
activity
pattern
in
most
other
canines,
like
red
and
arctic
foxes,
as
well
as
arctic
and
grey
wolves,
whereas
diurnal
activity
is
a
rare
observation
[15,29].
The
weaker
circadian
regulation
(see
for
example
[30])
might
result
in
greater
flexibility
in
the
timing
of
activity
in
dogs
as
compared
to
humans.
Thus,
patterns
of
video-recorded
sleep-wake
cycles
in
drug
detector
dogs
were
not
altered
when
handler-dog
teams
worked
in
different
day
and
night
shifts.
The
ability
of
dogs
to
cope
with
changing
shifts
may
be
due
to
their
natural
brief
and
frequent
sleep-wake
cycles
which
may
allow
them
sufficient
and
easy
adjustment
to
changing
routines,
which
is
usually
not
the
case
in
humans
[31].
Ultradian
regulation
of
sleep
in
dogs
Ultradian
sleep
cycles
of
about
20-min
length
were
described
in
dogs
(12
min
of
drowsiness/NREM
and
6
min
of
REM
sleep
episodes)
with
well
discernible
EEG,
EOG
(electrooculography),
EMG
(electromyogra-
phy),
ECG
(electrocardiography)
and
respiration-related
features
(Figure
2;
Table
3)
[16,19,23,32,33
].
Rats
and
humans
are
characterized
by
11
and
90
min
cycles,
respec-
tively.
Dog
sleep
was
found
to
be
mainly
polyphasic,
with
an
average
of
polyphasic
wake-sleep
cycle
length
of
83
min
Sleep
in
the
dog
Bo
´dizs
et
al.
27
Box
1
Sleep
disorders
and
behavioral
problems
in
dogs
Canine
narcolepsy
is
characterized
by
fragmented
sleep,
REM
sleep
dysregulation,
frequent
sleep
attacks
(excessive
sleepiness)
and
emotion-induced
losses
in
muscular
tonus
(cataplexy)
during
play,
before
feeding,
and
so
on.
The
condition
is
caused
by
the
mutation
of
the
canine
orexin
receptor
2
gene
or
by
the
loss
of
production
of
the
orexin
peptides
[6,7].
Sleep
disordered
breathing
is
associated
with
episodes
of
O
2
desaturation
and
loud
snoring
during
sleep,
as
well
as
daytime
hypersomnolence,
sluggishness,
and
shortened
sleep
latency.
The
English
bulldog,
the
Cavalier
King
Charles
spaniel,
as
well
as
other
brachycephalic
breeds
are
most
commonly
affected.
The
English
bulldog
has
been
proposed
as
a
natural
model
of
sleep-disordered
breathing
[8,9
].
REM
sleep
behavior
disorder
is
characterized
by
violent
motor
activity
and/or
complex
behavioral
phenomena
emerging
during
REM
sleep.
Clinical
signs
include
episodes
of
violent
limb
move-
ments,
howling,
barking,
growling,
chewing,
or
biting.
Episodes
occur
both
at
night
and
during
daytime
naps
[10].
Behavioral
output
is
clearly
unrelated
to
the
actual
environment
(‘hallucinatory’).
In
some
of
the
dogs,
REM
sleep
behavior
disorder
was
associated
with
other
neurological
conditions,
whereas
congenital
forms
were
also
reported
[11,12].
Table
2
Methodological
approaches
in
studying
dog
sleep
Method
Ethical
consideration
Advantage
Disadvantage
Reference
Invasive
Cisternal
puncture/
cerebrospinal
fluid
extraction
(associated
with
sleep
deprivation)
Extremely
painful
and
distressing,
potentially
lethal
Neurochemical
factors
can
be
measured
Low
ecological
validity,
restricted
subject
pool
and
sample
size
[61]
Surgically
inserted
stimulation/recording
electrodes
Seriously
painful
and
distressing
High
specificity,
good
signal
quality
Low
ecological
validity,
restricted
subject
pool
and
sample
size
[62,32]
Needle
electrodes
introduced
into
the
skin
and
the
cranial
muscles,
contacting
the
skull
Moderately
painful
and
distressing
(semi-invasive)
Trade-off
between
signal
quality
and
invasivity
Somewhat
restricted
subject
pool
and
sample
size,
pharmacologically
altered
sleep
[45]
Non-invasive
Video
recordings
No
distress
is
caused
to
subjects
Highest
ecological
validity
Low
construct
validity
[24]
Actigraphy
Not
painful,
depending
on
subjects’
individual
sensitivity
might
be
moderately
distressing
High
ecological
validity
Low
specificity
in
differentiating
different
sleep
states,
restricted
to
motor
activity
[17]
Polysomnography
Not
painful,
depending
on
subjects’
individual
sensitivity
might
be
moderately
distressing
High
ecological
validity
combined
with
electrophysiology,
potentially
high
sample
size
Lower
signal
quality,
potential
need
for
adaptation
occasion(s)
before
reaching
full
ecological
validity
[19]
www.sciencedirect.com
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
[16,23].
In
dogs,
2.9
hours
is
the
estimated
daily
amount
of
REM
sleep,
whereas
humans
and
rats
are
characterized
by
1.9
and
2.4
hours,
respectively
[14].
Similar
to
some
other
species
like
the
rat,
the
hedgehog
and
the
rabbit,
awakening
after
active
sleep
(assumed
REM
sleep,
based
on
video-recordings)
was
found
to
be
more
common
in
dogs,
than
in
humans,
providing
perhaps
an
opportunity
to
be
more
alert
towards
their
surroundings
after
a
period
of
reduced
responsiveness
[24].
Is
there
an
intraspecies
allometric
scaling
of
sleep
physiology
in
dogs?
An
additional
factor
to
be
considered
is
the
huge
individual
(between-breed)
variation
that
characterizes
dog
morphol-
ogy
[34].
Although
the
effect
of
body
size
on
dogs’
longevity
is
well-documented
[35],
the
hypothesis
of
the
intraspecies
allometric
scaling
of
physiological
measures,
like
heart
rate
is
controversial,
as
both
confirmatory
findings
[36]
and
recent
null-results
on
datasets
containing
rest/sleep
mea-
surements
[33
,37]
were
reported.
Although
intriguing,
the
intraspecies
allometric
modulation
of
sleep
in
dogs
was
not
yet
systematically
investigated,
thus
we
do
not
know
whether
measures
like
total
sleep
time
or
sleep
cycle
length
are
different
among
breeds
with
different
body
weights.
Behavioral
and
learning-related
aspects
of
sleep
in
dogs
Effects
of
sleep
location
and
pre-sleep
experiences
on
sleep
Dogs
sleeping
indoors
were
reported
to
spend
80%
of
the
night
in
behaviorally
defined
sleep,
whereas
this
ratio
was
70%
for
dogs
sleeping
outdoors
in
a
yard,
and
60%
for
dogs
sleeping
outdoors
in
a
non-fenced
area
[24].
A
polysom-
nography
study
demonstrated
a
later
emergence
of
the
first
REM
episode
in
laboratory
conditions
as
compared
to
home
sleep
[25

].
These
findings
cohere
with
the
view
that
active
sleep
(a
behavioral
definition
of
a
REM
sleep-
like
state)
is
emerging
in
safe
sleeping
conditions
mainly
[24].
Following
a
behaviorally
active
day,
dogs,
like
other
mammals,
including
humans
slept
more,
were
more
likely
to
have
an
earlier
drowsiness
and
NREM,
and
spent
less
time
in
drowsiness
and
more
time
in
NREM
and
REM
sleep
[19,25

].
In
addition
to
physical
settings
and
circumstances,
the
social
context
plays
a
decisive
role
in
the
sleep
of
dogs
and
other
canines
as
well
(Supple-
mentary
text).
Pre-sleep
socio-emotional
experiences
with
negative
valence
(separation
from
the
owner,
threat-
ening
approach
by
a
stranger)
were
followed
by
shorter
REM
sleep
latency
and
increased
REM
sleep
time
compared
to
sleep
following
positive
social
interactions
(petting
and
ball
play).
Within-subject
changes
in
sleep
structure
were
associated
with
behavioral
reactions
to
pre-sleep
social
interactions
(e.g.
time
spent
playing
or
looking
at
the
door
[38

]).
Pre-sleep
social
interaction-
dependent
changes
in
cardiac
activity
were
not
seen
during
sleep
in
dogs,
whereas
increased
heart
rate
(HR)
and
decreased
heart
rate
variability
(HRV)
after
positive
as
compared
to
negative
interaction
could
be
observed
during
post-interventional
wakefulness.
This
direction
of
change
is
in
contrast
with
the
expected
findings
and
previous
research
on
humans,
perhaps
28
Cognition
and
perception
*sleep
and
cognition*
Figure
1
(a)
(b)
F8
EOG2 EOG1
EMG
ECG
Rsp
Fz
F7
A1
Cz
Fz
F8
Cz
Gnd
Current Opinion in Behavioral Sciences
Non-invasive
polysomnography
in
the
pet
dog.
(a)
Placement
of
the
recording
electrodes
and
devices
as
follows:
(i)
Electroencephalography
(EEG)
is
performed
by
frontal
midline
(Fz),
central
midline
(Cz),
left
orbitofrontal
(F7)
and
right
orbitofrontal
(F8)
contacts,
with
the
A1
used
as
common
reference
and
Gnd
as
ground
(because
of
lower
artifact
contamination
the
offline
re-referencing
of
Fz-Cz
is
most
frequently
used),
(ii)
Electro-oculography
(EOG)
is
performed
by
the
bipolar
reference
between
F7
and
F8
(which
are
the
same
as
EOG1
and
EOG2),
(iii)
Electromyography
(EMG)
electrodes
assessing
muscular
tonus
were
bilaterally
placed
on
the
musculus
iliocostalis
dorsi,
(iv)
Electrocardiography
(ECG)
is
assessed
over
the
second
rib,
(v)
Respiration
(Rsp)
is
assessed
by
respiratory
inductance
plethysmography
using
a
respiratory
belt.
The
owner
is
present
and
the
dog
is
positively
reinforced
during
the
electrode
attachment
procedure
(technical
details
of
the
attachment
are
equivalent
to
the
ones
used
in
human
studies).
(b)
A
photo
of
a
dog
with
electrodes
attached.
Note
the
close
proximity
of
the
owner.
(Modified
from
Refs.
[33
]
and
[25

]).
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
www.sciencedirect.com
Sleep
in
the
dog
Bo
´dizs
et
al.
29
Figure
2
Fz-Cz
EOG
RSP
ECG
EMG
Fz-Cz
Fz-Cz
Fz-Cz
EOG
EOG
EOG
RSP
RSP
RSP
ECG
ECG
ECG
EMG
EMG
EMG
Current Opinion in Behavioral Sciences
Exemplary
segments
of
a
non-invasive
polysomnography
records
of
night
time
sleep
in
an
adult
dog.
Horizontal
broken
lines
delimit
the
states
of
wakefulness,
drowsiness,
non-rapid
eye
movement
(NREM)
sleep
and
Rapid
eye
movement
(REM)
sleep
(see
notation
on
the
left).
Wakefulness
is
characterized
by
low
amplitude,
high
frequency
electroencephalogram
(EEG)
(frontocentral
midline,
bipolar
derivation
Fz-Cz)
with
occasional
(eye
movement)
artifacts,
clear
eye
movements
and
blinking
as
indicated
by
large
deflections
of
the
electro-ocuologram
(EOG),
a
respiratory
(RSP)
www.sciencedirect.com
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
indicating
that
increased
activation/emotion
intensity
is
a
key
factor,
irrespective
of
emotional
valence
[39
].
Sleep
and
memory
in
the
domestic
dog
Sleep-related
improvement
in
memory
consolidation
of
humans
and
rats
[40]
may
apply
to
dogs’
inter-specific
communication
skills
(learning
new
commands).
A
3-hour-long
post-learning
non-invasive
polysomnogra-
phy
study
[41

]
indicated
increased
NREM
delta
and
REM
theta,
as
well
as
decreased
NREM
alpha
activity
in
post-learning
as
compared
to
baseline
sleep
in
dogs.
Behavioral
performance
significantly
increased
after
the
3-hour-long
rest/sleep
compared
to
the
pre-sleep
baseline,
whereas
the
within-subject
increase
in
perfor-
mance
correlated
with
certain
aspects
of
the
sleep
EEG
spectrum
(REM
beta
and
delta
power).
Besides
sleep,
post
learning
walk
and
play
were
also
associated
with
increasing
performances
approximately
one
week
later,
whereas
learning
of
unrelated
tasks
had
detrimental
effects
on
memory
consolidation
[41

].
A
behavioral
study
[42]
somewhat
contrastingly
found
that
playful
activity
during
retention
enhanced
memory
30
Cognition
and
perception
*sleep
and
cognition*
(Figure
2
Legend
Continued)
frequency
(frequency
range)
of
15/min
as
indicated
by
respiratory
inductance
plethysmography
and
clear
respiratory
sinus
arrhythmia
(the
heart
rate
as
indicated
by
electrocardiography
[ECG]
increases
during
inspiration
and
decreases
during
expiration
as
in
all
further
panels
and
corresponding
states).
Muscular
tonus
is
indicated
by
the
amplitude
of
the
electromyogram
(EMG).
Drowsiness:
slower
theta-alpha
frequency
EEG
components,
slower
eye
movements,
slow
regular
breathing
and
maintained
muscular
tonus.
NREM
sleep:
slow
EEG
waves
of
12
Hz
frequency,
around
12/min
respiratory
frequency,
lowered
heart
rate
and
decreased
muscular
tonus
are
seen.
REM
sleep:
low
amplitude,
high
frequency
EEG,
rapid
eye
movements
(EOG),
relatively
accelerated
respiration
(15/min)
and
a
further
decrease
in
muscular
tonus.
Note
that
the
vertical
scale
refers
to
the
EEG
traces
only.
The
rest
of
the
derivations
are
adapted
for
illustrative
purposes
and
visibility,
but
their
scaling
is
consistent
across
the
panels.
Filter
settings:
EEG:
0.5–50
Hz;
EOG:
0.2–10
Hz;
RSP:
0–1
Hz;
ECG:
0,5–50
Hz;
EMG:
10–50
Hz.
Table
3
Reported
polygraphic
signs
of
different
sleep-waking
states
in
dogs
Ref.
Wakefulness
Drowsiness
NREM
REM
[32]
low
amplitude
and
fast
frequency
pattern
cortical
activity
(desynchronization),
mixture
of
low
voltage
slow
and
fast
waves
in
the
hippocampal
traces
slow
waves
and
spindles
in
the
cortex,
irregular
slow
activity
in
the
hippocampus
neocortical
desynchronization,
3-5
Hz
rhythmic
hippocampal
activity
[23]
low-voltage
(5-10
mV)
fast
frequency
(>
15
Hz)
EEG
from
one
or
both
cortical
areas,
frequent
eye
movements
and
a
tonic
but
irregular
neck
EMG
high
voltage
slow
waves
(up
to
40
mV)
EEG
12-14
Hz
spindle
bursts
(40-50
mV)
against
a
background
of
slower
4-8
Hz
activity
(10-20
mV)
recorded
from
the
sensorimotor
cortex
(light
sleep);
high
amplitude
(up
to
50
mV)
stow
waves
(2-8
Hz)
recorded
from
the
visual
cortex
(slow
wave
sleep)
relatively
low-voltage
(5-10
mV)
fast
frequency
(>15
Hz)
tracing
recorded
from
the
cortical
leads,
frequent
and
characteristic
binocular,
conjugate,
rapid
eye
movements
and
a
suppression
of
the
neck
EMG
[16]
beta
activity
of
<50
mV
in
cortical
derivations
(ratio
alpha/beta
power
1),
no
spindles;
short-lasting
theta
activity
(2-10
s)
in
the
hippocampus
with
higher
frequencies
superimposed;
EMG
is
relatively
great
mixed
and
unstable
frequency
pattern:
9.5-13.5
Hz
waves
vary
with
synchronous
waves
at
4–7
Hz,
50-100
mV
on
a
background
of
low
voltage
fast
activity
(ratio
alpha/beta
power
>1);
spindles
are
lacking;
slow
eye
movements
may
be
present
waves
of
3-4
Hz
become
predominant;
spindles
of
>100
mV,
lasting
0.2-0.5
s,
mainly
in
the
frontal
cortex;
the
EMG
is
small
and
there
are
no
eye
movements
(light
sleep);
slow
waves
(1–4
Hz)
of
100-250
mV,
superimposed
on
waves
of
6-7.5
Hz
of
50-100
mV;
spindling
at
10–14
Hz,
200
mV
or
more;
EMG
is
small
and
there
are
no
eye
movements
(deep
slow
wave
sleep)
beta
activity
of
50-100
mV
(ratio
alpha/beta
power
<1);
hippocampal
theta
activity
(5
Hz);
rapid
eye
movements;
the
EMG
is
small,
but
amplitude
increases
appear
simultaneously
with
facial
or
leg
twitches
or
myoclonic
jerks
[19]
fast
activity
in
the
EEG,
high
amplitude
and
frequency
eye
movements
in
the
EOG,
elevated
muscle
tone
and
frequent
movements
(EMG
channel)
fast
EEG
activity
in
the
EEG
channel,
decreased
amplitude
and
frequency
eye
movements,
lowered
but
observable
muscle
tone,
fairly
regular
respiration
15
mV
delta
(1–4
Hz)
activity,
no
or
low
amplitude
eye
movements,
regular
respiration,
decreased
muscle
tone
rapid
eye
movements,
fast
EEG
activity,
muscular
atonia,
irregular
respiration
and
heart
beat
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
www.sciencedirect.com
performance
in
the
short
run
to
a
greater
extent
com-
pared
to
a
resting
period.
The
effect
of
learning
on
sleep
was
apparent
when
analyz-
ing
the
same
dataset
[41

]
for
sleep
spindles
[43

].
Sleep
spindles
are
major
hallmarks
of
NREM
sleep
in
humans
playing
a
definitive
role
in
offline
neuroplasticity
[44].
Spindle
waves
are
not
easy
to
assess
in
dogs,
as
they
are
both
shorter
in
duration
(0.2–0.5
s)
as
compared
to
humans
(>0.5
s)
and
of
a
very
low
amplitude
(at
least
in
surface/non-
invasive
traces).
Sleep
spindles
have,
however,
been
described
in
dogs
using
both
invasive
[16]
and
semi-
invasive
[45]
sleep/propofol
restraint
EEG
recordings,
whereas
quantitative
EEG
analyses
seem
to
be
effective
in
detecting
spindle-like
activity
in
dogs
even
from
non-
invasive
scalp
recordings
[43

].
The
occurrence
rate
of
such
automatically
measured
sleep
spindles
in
the
surface
(non-invasive)
EEG
records
was
higher
after
learning
compared
to
control
dogs
and
the
same
measure
correlated
with
performance
increase.
Development
and
aging:
changes
in
sleep
and
cognition
Developmental
steps
in
the
sleep
EEG
of
dogs
are
characterized
by
gradual
emergence
of
sleep
slow-wave
activity
transiently
peaking
around
6–8
weeks
of
age
and
thereafter
decreasing
till
at
least
16
weeks
of
age
[46].
Such
transient
peaking
in
the
amplitude
of
NREM
sleep
slow
wave
activity
is
well
known
in
prepubertal
human
subjects
and
laboratory
rats
paralleling
the
age-dependent
trends
in
synaptic
density
and
brain
energy
consumption
[47].
In
addition,
adult-like
sleep
spindles
emerge
around
5
weeks
in
dogs
[46]
and
around
12
weeks
in
humans
[48].
Dogs
have
been
shown
to
manifest
a
cognitive
decline
with
increasing
age
(called
the
Canine
Cognitive
Dysfunction
Syndrome;
[49]),
which
parallels
human
ageing
in
many
aspects.
Cognitive
decline
in
dogs
has
been
associated
with
several
behavioral
signs,
including
owner-reported
sleep-
wake
cycle
alterations
[50].
Furthermore,
lower
amplitude
of
circadian
core
body
temperature
rhythm
was
reported
in
aged
dogs
with
lowest
spatial
memory
ability
[28

].
Aging
was
also
characterized
by
reduced
overall
REM
sleep
amount,
as
well
as
increased
NREM
sleep
during
daytime
and
wakefulness
during
nighttime
[51].
This
type
of
wake
and
sleep
fragmentation
during
day
time
and
night
time,
respectively,
together
with
reduced
REM
sleep
are
well
known
features
of
sleep
in
the
aged
human
subjects
and
were
shown
to
relate
with
cognitive
aspects
of
aging
[52,53].
Older
dogs
(within
an
age
range
of
2–8
years-old)
were
characterized
by
decreased
delta
activity
and
increased
alpha
and
beta
activity
both
during
NREM
and
REM,
but
not
during
drowsiness
[19].
In
addition,
sleep
spindle
analysis
in
over
150
dogs
indicated
that
centrally
measured
(Cz)
slow
(9–13
Hz)
spindle
density
declined
and
fast
(13–16
Hz)
spindle
frequency
increased
with
age,
while
on
the
frontal
electrode
(Fz),
an
age-related
amplitude
decline
in
slow
sleep
spindles
was
observed
[54

].
There
is
also
some
indication
that
contrary
to
the
age-dependent
decline
of
rapid
eye
movement
density
(REMD)
reported
in
humans,
dogs’
age
is
positively
associated
with
REMD.
It
has
to
be
noted
however,
that
the
above
mentioned
effect
seems
to
characterize
male
dogs
with
short
REM
sleep
duration,
but
not
the
whole
population,
indicating
the
need
for
further
studies
clarifying
its
generalizability
[55
].
Conclusion
Like
most
terrestrial
mammals,
the
domestic
dog
is
char-
acterized
by
unequivocal
sleep
in
terms
of
behavioral
and
physiological
criteria.
The
relationship
between
socio-
ecological
and
physical
environmental,
as
well
as
cogni-
tive-behavioral
factors
with
sleep
improves
our
insight
into
the
functional
significance
of
sleep,
as
well
as
into
the
still
unraveled
mysteries
of
dog
behavior.
This
new
emerging
evidence
strongly
suggests
that
dogs
are
valid
and
useful
models
of
sleep-related
cognition.
However,
the
achieve-
ment
of
these
goals
needs
further
research
investment,
some
of
which
could
deepen
our
knowledge
on
both
dog
and
human
behavior
and
physiology.
Research
agenda:
Selective
breeding
for
deeper
(more
intense,
thus
cognitively
more
efficient)
sleep
Investigating
the
parallelism
between
cognitive
devel-
opment
and
sleep
EEG
maturation
in
dogs
by
means
of
non-invasive
methods
Unravelling
the
functions
of
NREM
and
REM
sleep
by
selective
manipulations
(e.g.
deprivation)
of
these
sleep
stages
Integrating
cognitive
and
affective
aspects
of
sleep-
related
memory
consolidation
Depicting
sleep
electrophysiological
profiles
of
natural
dog
models
of
human
psychiatric
conditions
Understanding
the
effects
of
domestication
on
sleep
by
further
comparisons
of
dogs
and
wolves
in
terms
of
sleep
phenotypes
and
physiology
Understanding
the
effects
of
different
lifetime
experi-
ences
(free-ranging
dogs,
pet
dogs,
and
shelter
dogs)
on
sleep
and
sleep-related
cognitive
processes
Conflict
of
interest
statement
Nothing
declared.
CRediT
authorship
contribution
statement
Ro
´bert
Bo
´dizs:
Conceptualization,
Funding
acquisition,
Visualization,
Data
curation,
Writing
-
original
draft,
Writing
-
review
&
editing.
Anna
Kis:
Conceptualization,
Funding
acquisition,
Visualization,
Writing
-
original
draft,
Writing
-
review
&
editing.
Ma
´rta
Ga
´csi:
Concep-
tualization,
Funding
acquisition,
Data
curation,
Writing
-
original
draft,
Writing
-
review
&
editing.
Jo
´zsef
Topa
´l:
Conceptualization,
Funding
acquisition,
Writing
-
origi-
nal
draft,
Writing
-
review
&
editing,
Supervision.
Sleep
in
the
dog
Bo
´dizs
et
al.
31
www.sciencedirect.com
Current
Opinion
in
Behavioral
Sciences
2020,
33:25–33
Appendix
A.
Supplementary
data
Supplementary
material
related
to
this
article
can
be
found,
in
the
online
version,
at
doi:https://doi.org/10.1016/j.
cobeha.2019.12.006.
Acknowledgements
The
writing
of
this
paper
was
supported
by
the
Higher
Education
Institutional
Excellence
Program
of
the
Ministry
of
Human
Capacities
in
Hungary,
within
the
framework
of
the
Neurology
thematic
program
of
the
Semmelweis
University;
the
Bial
Foundation
(grant
no
169/16),
the
National
Research
Development
and
Innovation
Office
(OTKA
FK128242K132372;
K128448;
K115862),
the
Hungarian
Academy
of
Sciences
(F01/031)
and
the
Ja
´nos
Bolyai
Research
Scholarship
of
the
Hungarian
Academy
of
Sciences.
References
and
recommended
reading
Papers
of
particular
interest,
published
within
the
period
of
review,
have
been
highlighted
as:
of
special
interest

of
outstanding
interest
1.
Nicolau
MC,
Akaa
ˆrir
M,
Gamundı
´A,
Gonza
´lez
J,
Rial
RV:
Why
we
sleep:
the
evolutionary
pathway
to
the
mammalian
sleep.
Prog
Neurobiol
2000,
62:379-406.
2.
Castro-Zaballa
S,
Cavelli
ML,
Gonzalez
J,
Nardi
AE,
Machado
S,
Scorza
C,
Torterolo
P:
EEG
40Hz
coherence
decreases
in
REM
sleep
and
ketamine
model
of
psychosis.
Front
Psychiatry
2019,
9:766
http://dx.doi.org/10.3389/fpsyt.2018.00766.
3.
Topa
´l
J,
Roma
´n
V,
Turcsa
´n
B:
The
dog
(Canis
familiaris)
as
a
translational
model
of
autism:
it’s
high
time
we
move
from
promise
to
reality.
WIREs
Cognit
Sci
2019,
10:e1495
http://dx.
doi.org/10.1002/wcs.1495.
Theoretical
and
empirical
evidence
for
the
translational
relevance
of
pet
dog
studies
in
the
research
attempts
revealing
the
unravel
the
factors
involved
in
autism
spectrum
disorder
of
human
subjects
are
presented
in
this
paper.
4.
Overall
KL,
Dunham
AE:
Dogs
as
‘natural’
models
for
human
psychiatric
conditions:
information
gained
from
purely
behavioral
or
physiological
studies,
versus
studies
that
combine
both
approaches.
J
Vet
Behav
Clin
Appl
Res
2013,
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5.
Ledford
H:
Dog
DNA
probed
for
clues
to
human
psychiatric
ills.
Nature
2016,
529:446-447.
6.
Lin
L,
Faraco
J,
Li
R,
Kadotani
H,
Rogers
W,
Lin
X,
Qiu
X,
de
Jong
PJ,
Nishino
S,
Mignot
E:
The
sleep
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canine
narcolepsy
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mutation
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the
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B,
Fujiki
N,
Okura
M,
Mignot
E,
Nishino
S:
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familial
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2001,
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8.
Hendricks
JC,
Kline
LR,
Kovalski
RJ,
O’Brien
JA,
Morrison
AR,
Pack
AI:
The
English
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a
natural
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9.
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TA,
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NC,
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J:
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Charles
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case
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Vet
Surg
2019,
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The
study
is
about
recent
case
series
investigating
one
of
the
most
common
human
sleep
disorders
in
Cavalier
King
Charles
spaniels.
Dog
behavior
is
altered
as
a
result
of
sleep-disordered
breathing
pretty
much
like
human
behavior
is.
10.
Schubert
TA,
Chidester
RM,
Chrisman
CL:
Clinical
characteristics,
management
and
long-term
outcome
of
suspected
rapid
eye
movement
sleep
behaviour
disorder
in
14
dogs.
J
Small
Anim
Pract
2011,
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11.
Mitler
MM,
Dement
WC:
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1977,
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12.
Bush
WW,
Barr
CS,
Stecker
MM,
Overall
KL,
Bernier
NM,
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EW,
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AR:
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sleep
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
Bunford
N,
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A,
Kis
A,
Miklo
´si
A
´,
Ga
´csi
M:
Canis
familiaris
as
a
model
for
non-invasive
comparative
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Trends
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2017,
40:438-452.
Theoretically
and
empirically
based
arguments
are
provided
for
the
usefulness
and
relevance
of
non-invasive
dog
studies
in
a
comparative
neuroscientific
context.
14.
Savage
VM,
West
GB:
A
quantitative,
theoretical
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for
understanding
mammalian
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U
S
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SS,
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I:
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A,
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JL,
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WAE,
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PAJ:
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based
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of
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h
sleep-waking
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1979,
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17.
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I,
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H:
Long-term
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18.
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Y,
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S,
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Y,
Takahashi
K:
Temporal
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wave
sleep
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REM
sleep
during
recovery
sleep
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12-h
forced
wakefulness
in
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A,
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´t
S,
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M,
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P,
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F,
Topa
´l
J,
Miklo
´si
A
´,
Bo
´dizs
R:
Development
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a
non-invasive
polysomnography
technique
for
dogs
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Physiol
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2014,
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20.
Sassin
JF,
Parker
DC,
Mace
JW,
Gotlin
RW,
Johnson
LC,
Rossman
LG:
Human
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relation
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Y,
Ebihara
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Nakamura
Y,
Takahashi
K:
A
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growth
hormone
secretion
in
dogs:
effects
of
3,
6,
and
12
hours
of
forced
wakefulness
on
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hormone,
cortisol,
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22.
Born
J,
Fehm
HL:
Hypothalamus-pituitary-adrenal
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a
coordinating
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the
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23.
Lucas
EA,
Powell
EW,
Murphree
OD:
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patterns
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pointer
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Physiol
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1977,
19:285-291.
24.
Adams
GJ,
Johnson
KG:
Sleep-wake
cycles
and
other
night-
time
behaviours
of
the
domestic
dog
Canis
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Anim
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25.

Bunford
N,
Reicher
V,
Kis
A,
Poga
´ny
A
´,
Gombos
F,
Bo
´dizs
R,
Ga
´csi
M:
Differences
in
pre-sleep
activity
and
sleep
location
are
associated
with
variability
in
daytime/nighttime
sleep
electrophysiology
in
the
domestic
dog.
Sci
Rep
2018,
8:7109.
Time-of-day
as
well
as
activity
and
location-dependency
of
non-invasive
polysomnography
measures
of
dog
sleep
are
provided
in
this
study.
Findings
are
relevant
from
both
a
somnological
and
an
animal
behavioral
point
of
view.
26.
Ohmori
K,
Nishikawa
S,
Oku
K,
Oida
K,
Amagai
Y,
Kajiwara
N,
Jung
K,
Matsuda
A,
Tanaka
A,
Matsuda
H:
Circadian
rhythms
and
the
effect
of
glucocorticoids
on
expression
of
the
clock
gene
period1
in
canine
peripheral
blood
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Vet
J
2013,
196:402-407.
27.
Giannetto
C,
Fazio
F,
Panzera
M,
Alberghina
D,
Piccione
G:
Comparison
of
rectal
and
vaginal
temperature
daily
rhythm
in
dogs
(Canis
familiaris)
under
different
photoperiod.
Biol
Rhythm
Res
2015,
46:113-119.
28.

Zanghi
BM,
Gardner
C,
Araujo
J,
Milgram
NW:
Diurnal
changes
in
core
body
temperature,
day/night
locomotor
activity
patterns,
and
actigraphy-generated
behavioral
sleep
in
aged
canines
32
Cognition
and
perception
*sleep
and
cognition*
Current
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in
Behavioral
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2020,
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www.sciencedirect.com
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varying
levels
of
cognitive
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Neurobiol
Sleep
Circadian
Rhythms
2016,
1:8-18.
Study
reports
that
decreased
amplitude
of
circadian
core
body
tempera-
ture
rhythm
is
a
correlate
of
spatial
memory
impairment
in
aged
dogs.
29.
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JL:
Carnivore
brain
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behavioral
ecology,
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J
Mamm
1986,
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30.
Hawking
F,
Lobban
MC,
Gammage
K,
Worms
MJ:
Circadian
rhythms
(activity,
temperature,
urine
and
microfilariae)
in
dog,
cat,
hen,
duck,
thamnomys
and
gerbillus.
J
Interdisiplinary
Cycle
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1971,
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31.
Adams
GJ,
Johnson
KG:
Sleep,
work,
and
the
effects
of
shift
work
in
drug
detector
dogs
Canis
familiaris.
Appl
Anim
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1994,
41:115-126.
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Shimazono Y, Horie T, Yanagisawa Y, Hori N, Chikazawa S, Shozuka K:
The correlation of the rhythmic waves of the hippocampus with the
behaviors
of
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1960,
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33.
Ba
´lint
A,
EleÅd
H,
Ko
¨rmendi
J,
Bo
´dizs
R,
Reicher
V,
Ga
´csi
M:
Potential
physiological
parameters
to
indicate
inner
states
in
dogs:
the
analysis
of
ECG,
and
respiratory
signal
during
different
sleep
phases.
Front
Behav
Neurosci
2019,
13:207.
Authors
provide
direct
evidence
for
behavioral
state-dependent
heart
rate
(variability)
and
respiratory
measures
in
pet
dogs,
by
using
non-invasive
polysomnography.
The
paper
differentiates
wakefulness,
drowsiness,
NREM
sleep
and
REM
sleep,
and
reports
findings
on
lack
of
allometric
relationship
between
body
size
and
heart
rate
as
well.
34.
Fleischer
S,
Sharkey
M,
Mealey
K,
Ostrander
EA,
Martinez
M:
Pharmacogenetic
and
metabolic
differences
between
dog
breeds:
their
impact
on
canine
medicine
and
the
use
of
the
dog
as
a
preclinical
animal
model.
AAPS
J
2008,
10:110-119.
35.
Galis
F,
Van
der
Sluijs
I,
Van
Dooren
TJ,
Metz
JA,
Nussbaumer
M:
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large
dogs
die
young?
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Mol
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36.
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MJ,
Humm
K,
Dennis
SG,
Agee
L,
Boswood
A:
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between
heart
rate
and
age,
bodyweight
and
breed
in
10,849
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37.
Kortekaas
K,
Kotrschal
K:
Does
socio-ecology
drive
differences
in
alertness
between
wolves
and
dogs
when
resting?
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2019,
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38.

Kis
A,
Gergely
A,
Galambos
A
´,
Abdai
J,
Gombos
F,
Bo
´dizs
R,
Topa
´l
J:
Sleep
macrostructure
is
modulated
by
positive
and
negative
social
experience
in
adult
pet
dogs.
Proc
R
Soc
B
2017,
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This
is
the
very
first
study
providing
evidence
for
the
relationship
between
pre-sleep
socio-emotional
experiences
and
non-invasively
measured
polygraphic
sleep
structure
in
canines.
39.
Varga
B,
Gergely
A,
Galambos
A
´,
Kis
A:
Heart
rate
and
heart
rate
variability
during
sleep
in
family
dogs
(Canis
familiaris).
Moderate
effect
of
pre-sleep
emotions.
Animals
2018,
8:107
http://dx.doi.org/10.3390/ani8070107.
Sleep-related
cardiac
activity
is
only
moderately
influenced
by
pre-sleep
emotional
effects
in
family
dogs,
according
to
this
paper.
40.
Feld
GB,
Born
J:
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during
sleep:
concurrent
consolidation
and
forgetting.
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2017,
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41.

Kis
A,
Szakada
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S,
Ga
´csi
M,
Kova
´cs
E,
Simor
P,
To
¨ro
¨k
C,
Gombos
F,
Bo
´dizs
R,
Topa
´l
J:
The
interrelated
effect
of
sleep
and
learning
in
dogs
(Canis
familiaris);
an
EEG
and
behavioural
study.
Sci
Rep
2017,
7:41873.
Learning-related
changes
in
sleep
structure
and
EEG
power
are
reported
in
this
non-invasive
pet
dog
study.
Findings
are
partially
coherent
with
human
and
rodent
studies.
42.
Affenzeller
N,
Palme
R,
Zulch
H:
Playful
activity
post-learning
improves
training
performance
in
Labrador
retriever
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(Canis
lupus
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Physiol
Behav
2017,
168:62-73.
43.

Iotchev
IB,
Kis
A,
Bo
´dizs
R,
van
Luijtelaar
G,
Kubinyi
E:
EEG
transients
in
the
sigma
range
during
non-REM
sleep
predict
learning
in
dogs.
Sci
Rep
2017,
7:12936.
The
very
first
study
investigating
the
relationship
between
sleep
spindles
and
memory
in
dogs.
Methodology
is
non-invasive,
findings
are
support-
ing
the
role
of
spindle-like
events
in
memory
formation/strengthening.
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A
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Thalhammer
JG,
Leschnik
M,
Hala
´sz
P:
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epileptic
dogs
under
propofol
restraint.
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Vet
Hung
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MX:
Postnatal
development
of
the
EEG
in
the
dog-II:
development
of
electrocortical
activity.
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1967,
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47.
Kurth
S,
Olini
N,
Huber
R,
LeBourgeois
M:
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DR:
EEG
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Ruehl
WW,
Bruyette
DS,
Cotman
ADCW,
Head
E:
Canine
cognitive
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as
a
model
for
human
age-related
cognitive
decline,
dementia
and
Alzheimer’s
disease:
clinical
presentation,
cognitive
testing,
pathology
and
response
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1-deprenyl
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Brain
Res
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50.
Landsberg
G:
Therapeutic
agents
for
the
treatment
of
cognitive
dysfunction
syndrome
in
senior
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Psychopharmacol
Biol
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51.
Takeuchi
T,
Harada
E:
Age-related
changes
in
sleep-wake
rhythm
in
dog.
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Brain
Res
2002,
136:193-199.
52.
Moraes
W,
Piovezan
R,
Poyares
D,
Bittencourt
LR,
Santos-
Silva
R,
Tufik
S:
Effects
of
aging
on
sleep
structure
throughout
adulthood:
a
population-based
study.
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2014,
15:401-409.
53.
Mander
BA,
Winer
JR,
Walker
MP:
Sleep
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2017,
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54.

Iotchev
IB,
Kis
A,
Turcsa
´n
B,
Tejeda
Ferna
´ndez
de
Lara
DR,
Reicher
V,
Kubinyi
E:
Age-related
differences
and
sexual
dimorphism
in
canine
sleep
spindles.
Sci
Rep
2019,
9:10092
http://dx.doi.org/10.1038/s41598-019-46434-y.
Sleep
spindles
in
dogs
are
shown
to
be
sexually
dimorphic
and
age-
dependent.
Correlations
are
echoing
the
findings
of
human
studies
and
are
based
on
the
largest
sample
ever
used
in
dog
sleep
studies.
In
addition,
research
is
solely
based
on
non-invasive
polysomnography.
55.
Kova
´cs
E,
Kosztola
´nyi
A,
Kis
A:
Rapid
eye
movement
density
during
REM
sleep
in
dogs
(Canis
familiaris).
Learn
Behav
2018,
46:554-560
http://dx.doi.org/10.3758/s13420-018-0355-9.
The
very
first
study
reporting
the
factors
determining
the
density
of
rapid
eye
movements
during
REM
sleep
phases
in
non-invasively
measured
pet
dogs.
56.
Bowes
G,
Woolf
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... There is a growing body of evidence that dogs (Canis familiaris) can be a unique translational model for human sleep physiology (Kis et al., 2014;Bunford et al., 2017;Bódizs et al., 2020;Iotchev and Kubinyi, 2021). It has recently been demonstrated that dogs' learning skills, in a social context, are linked to sleep-dependent memory consolidation, as indicated by EEG spectral changes and sleep spindles (Iotchev et al., 2017(Iotchev et al., , 2020b. ...
... Due to their long domestication history (∼18,000-32,000 years; Druzhkova et al., 2013), dogs' sociocognitive skills adapted to the same environmental challenges as humans' (Hare and Tomasello, 2005;Topál et al., 2009;Parker et al., 2010). Using dogs as model animals in neurocognitive research has several advantages considering that (1) dogs are willing to cooperate during the measurement at least to the same extent as children, (2) a relatively large number of subjects are available, (3) subjects have more diverse genotypes and phenotypes than mice or rats, and (4) measurements can be performed in the subjects' natural environment similarly to the methods used in children (Kis et al., 2014;Bunford et al., 2017;Bódizs et al., 2020). ...
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The role of sleep in memory consolidation is a widely discussed but still debated area of research. In light of the fact that memory consolidation during sleep is an evolutionary adaptive function, investigating the same phenomenon in nonhuman model species is highly relevant for its understanding. One such species, which has acquired human-analog sociocognitive skills through convergent evolution, is the domestic dog. Family dogs have surfaced as an outstanding animal model in sleep research, and their learning skills (in a social context) are subject to sleep-dependent memory consolidation. These results, however, are correlational, and the next challenge is to establish causality. In the present study, we aimed to adapt a TMR (targeted memory reactivation) paradigm in dogs and investigate its effect on sleep parameters. Dogs ( N = 16) learned new commands associated with different locations and afterward took part in a sleep polysomnography recording when they were re-exposed to one of the previously learned commands. The results did not indicate a cueing benefit on choice performance. However, there was evidence for a decrease in choice latency after sleep, while the density (occurrence/minute) of fast sleep spindles was also notably higher during TMR recordings than adaptation recordings from the same animals and even compared with a larger reference sample from a previous work. Our study provides empirical evidence that TMR is feasible with family dogs, even during a daytime nap. Furthermore, the present study highlights several methodological and conceptual challenges for future research.
... In the related data analysis, the data were classified and filtered based on veterinary advice [18]. On average, canines sleep between 7.7 and 16.0 h per day [19]. Thus, dementia or dermatitis, which interfere with continuous sleep patterns, and representative diseases, such as digestive system disorders and lethargy, can be inferred through a data analysis of sleep patterns (i.e., waking frequency and excessive sleeping) [20]. ...
... No complete literature review was available as a starting point for this review, although two articles on sleep EEG in dogs [32] and sleep spindles [33] were encountered that provided useful context. To begin, we conducted an informal search using Google Scholar in February 2023, searching for 'EEG in dogs' and read through a number of obvious candidates ( [22,[34][35][36][37][38] [26,30,39,40]) to identify commonalities. ...
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The emerging field of canine cognitive neuroscience uses neuroimaging tools such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to map the cognitive processes of dogs to neural substrates in their brain. Within the past decade, the non-invasive use of EEG has provided real-time, accessible, and portable neuroimaging insight into canine cognitive processes. To promote systematization and create an overview of framings, methods and findings for future work, we provide a systematic review of non-invasive canine EEG studies (N=22), dissecting their study makeup, technical setup, and analysis frameworks and highlighting emerging trends. We further propose new directions of development, such as the standardization of data structures and integrating predictive modeling with descriptive statistical approaches. Our review ends by underscoring the advances and advantages of EEG-based canine cognitive neuroscience and the potential for accessible canine neuroimaging to inform both fundamental sciences as well as practical applications for cognitive neuroscience, working dogs, and human-canine interactions.
... The data collection occurred in three phases. First, Bennett et al., 2021;Bódizs et al., 2020;Carlen et al., 2021;Delon, 2020;Göttert & Perry, 2023;Kalof & Whitley, 2021;Leveau, 2020;Torretta et al., 2021;Wischermann et al., 2019;Yom-Tov, 2003). ...
Article
This study aims to understand urban animal welfare policy development and implementation for four species in public spaces: cats (Felis catus), dogs (Canis familiaris), pigeons (Columbia livia domestica), and foxes (Vulpes vulpes). Our exploratory research offers an overview of the perspectives of all involved municipal and police officers and their challenges in a metropolitan urban context, the Brussels Capital Region in Belgium. We conducted semi-structured interviews with 35 participants from 19 municipalities and six police zones of the region. Additionally, we organized two focus groups consisting of representatives from municipalities, police zones, and nongovernmental organizations. Afterward, we analyzed the data thematically, leading to the identification of six policy and six practice recommendations. These recommendations can help advance the notion of urban animal welfare for the four species from a multispecies perspective.
... Studies aiming to automate the investigation of dog behaviour have relied on wearable technology for pets to measure dog behaviour [52]. While these devices can measure activity and sleeping patterns, scientific validation is often lacking [53,54]. Furthermore, using this technology in clinical or scientific settings is not always appropriate. ...
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Simple Summary Our research team has developed an automated computer system that uses convolutional neural networks (CNNs) to monitor and analyse the sleep patterns of dogs. Traditional methods of recording animal behaviour, such as direct observations (of sleep) of either live behaviour or recorded behaviour, can be time-consuming and error-prone, making it difficult to replicate studies. Sleep may be a crucial indicator of an animal’s well-being, but it has been overlooked in animal welfare research due to the time-consuming nature of measuring sleep. Compared to direct behavioural observations from the same videos, our system achieved an 89% similarity score in automatically detecting and quantifying sleep duration and fragmentation in dogs. Although there were no significant differences in the time percentage of sleep observed, the system recorded more total sleep time than human observers making direct observations on the same data sources. The automated system used could become a valuable tool for animal behaviour and welfare research. Abstract Although direct behavioural observations are widely used, they are time-consuming, prone to error, require knowledge of the observed species, and depend on intra/inter-observer consistency. As a result, they pose challenges to the reliability and repeatability of studies. Automated video analysis is becoming popular for behavioural observations. Sleep is a biological metric that has the potential to become a reliable broad-spectrum metric that can indicate the quality of life and understanding sleep patterns can contribute to identifying and addressing potential welfare concerns, such as stress, discomfort, or health issues, thus promoting the overall welfare of animals; however, due to the laborious process of quantifying sleep patterns, it has been overlooked in animal welfare research. This study presents a system comparing convolutional neural networks (CNNs) with direct behavioural observation methods for the same data to detect and quantify dogs’ sleeping patterns. A total of 13,688 videos were used to develop and train the model to quantify sleep duration and sleep fragmentation in dogs. To evaluate its similarity to the direct behavioural observations made by a single human observer, 6000 previously unseen frames were used. The system successfully classified 5430 frames, scoring a similarity rate of 89% when compared to the manually recorded observations. There was no significant difference in the percentage of time observed between the system and the human observer (p > 0.05). However, a significant difference was found in total sleep time recorded, where the automated system captured more hours than the observer (p < 0.05). This highlights the potential of using a CNN-based system to study animal welfare and behaviour research.
Chapter
In veterinary psychiatry, the process of translating collected signs into symptoms is a key element. The collection of semiological data is a complex technique that requires a meticulous interview with the pet owner. Details of this data collection, behavior by behavior, are provided to underscore the intricate nature of this process and emphasize the critical need for accuracy in the information gathered.
Chapter
In this chapter, we present the influence of hormones, pain, and other major biological functions on behavior. In particular, many links between endocrine systems and neurophysiology are highlighted through the description of the major organic functions. In detail, ► Sect. 3.1 describes the endocrinological functions and their behavioral influences; ► Sect. 3.2 describes the major organic functions common to all mammals, with emphasis on their expression in the canine species; and ► Sect. 3.3 deals with pain and its consequences. In clinical practice, while the veterinary psychiatrist focuses more on brain functions to establish a diagnosis, the study of these major functions remains essential to maintain a comprehensive approach to canine behavior.
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In dogs, as in humans, both emotional and learning pretreatment affect subsequent behaviour and sleep. Although learning often occurs in an emotional-social context, the emotion-learning interplay in such context remain mainly unknown. Aims were to assess the effects of Controlling versus Permissive (emotional factors) training (learning factors) styles on dogs’ behaviour, learning performance, and sleep. Family dogs (N = 24) participated in two command learning sessions employing the two training styles with each session followed by assessment of learning performance, a 2-h-long non-invasive sleep EEG measurement, and a retest of learning performance. Pre- to post-sleep improvement in learning performance was evident in dogs that received the Permissive training during the second learning session, indicating that dogs that experienced a more rewarding situation than expected (positive expectancy violation) during the second training session showed improved learning success after their afternoon sleep. These results possibly indicate an interactive effect of expectancy violation and sleep on enhancing learning.
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The sleeping activity of family dogs has been studied increasingly in the past years. Recently, a validated, non-invasive polysomnographic method has been developed for dogs, enabling the parallel recording of several neurophysiological signals on non-anesthetized family dogs, including brain activity (EEG), eye movements (EOG), cardiac (ECG), and respiratory activity (PNG). In this study, we examined the ECG (N = 30) and respiratory signals (N = 19) of dogs during a 3-h sleep period in the afternoon, under laboratory conditions. We calculated four time-domain heart rate variables [mean heart rate (HR), SDNN, RMSSD, and pNN50] from the ECG and the estimated average respiratory frequency from the respiratory signal. We analyzed how these variables are affected by the different sleep-wake phases (wakefulness, drowsiness, NREM, and REM) as well as the dogs' sex, age and weight. We have found that the sleep-wake phase had a significant effect on all measured cardiac parameters. In the wake phase, the mean HR was higher than in all other phases, while SDNN, RMSSD, and pNN50 were lower than in all other sleep phases. In drowsiness, mean HR was higher compared to NREM and REM phases, while SDNN and RMSSD was lower compared to NREM and REM phases. In REM, SDNN, and RMSSD was higher than in NREM. However, the sleep-wake phase had no effect on the estimated average respiratory frequency of dogs. The dogs' sex, age and weight had no effect on any of the investigated variables. This study represents a detailed analysis of the cardiac and respiratory activity of dogs during sleep. Since variations in these physiological signals reflect the dynamics of autonomic functions, a more detailed understanding of their changes may help us to gain a better understanding of the internal/emotional processes of dogs in response to different conditions of external stimuli. As such, our results are important since they are directly comparable to human findings and may also serve as a potential basis for future studies on dogs.
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Non-REM bursts of activity in the sigma range (9–16 Hz) typical of sleep spindles predict learning in dogs, similar to humans and rats. Little is known, however, about the age-related changes in amplitude, density (spindles/minute) and frequency (waves/second) of canine spindles. We investigated a large sample (N = 155) of intact and neutered pet dogs of both sexes, varying in breed and age, searching for spindles in segments of non-REM sleep. We recorded EEG from both a frontal midline electrode (Fz) and a central midline electrode (Cz) in 55.5% of the dogs, in the remaining animals only the Fz electrode was active (bipolar derivation). A similar topography was observed for fast (≥13 Hz) spindle occurrence as in humans (fast spindle number, density on Cz > Fz). For fast spindles, density was higher in females, and increased with age. These effects were more pronounced among intact animals and on Fz. Slow spindle density declined and fast spindle frequency increased with age on Cz, while on Fz age-related amplitude decline was observed. The frequency of fast spindles on Fz and slow spindles on Cz was linked to both sex and neutering, suggesting modulation by sexual hormones. Intact females displayed higher frequencies than males and neutered females. Our findings support the argument that sigma bursts in the canine non-REM sleep are analogous to human sleep spindles, and suggest that slow and fast spindles display different trajectories related to age, of which an increase in frontal fast spindles is unique to dogs.
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Variation in resting behaviour across animals may be driven by adaptations towards their environment. Wolves and dogs seem promising models to examine this idea as they share a common ancestor, but occupy different socio-ecological niches. While wolves generally avoid humans, hunt, defend their territory, and raise offspring cooperatively, most dogs live in human-shaped environments. Hence, we hypothesized wolves to be more alert towards their environment than dogs, i.e. the degree of activation along the sleep-wake continuum (alertness) should be greater in wolves than in dogs. We estimated alertness via cardiac output. We tested similarly raised and kept pack-living wolves and dogs in two different behavioural conditions: (1) inactive wakefulness: animal is lying, head in an upward position with eyes opened, (2) resting: animal is lying, head in downward position with eyes mainly closed. In contrast to our expectations, we found that in both conditions wolves had a lower heart rate and higher heart rate variability than dogs, i.e. wolves might be less alert/more relaxed than dogs. Although our results are preliminary, we suggest that the higher alertness of dogs compared to wolves is potentially driven by differences in their socio-ecology (i.e. domestication) causing greater attention of dogs to human behaviour.
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Selecting appropriate animal models for a particular human phenomenon is a difficult but important challenge. The difficulty lies in finding animal behaviors that are not only sufficiently relevant and analog to the complex human symptoms (face validity) but also have similar underlying biological and etiological mechanisms (translational or construct validity), and have “human‐like” responses to treatment (predictive validity). Over the past several years, the domestic dog (Canis familiaris) has become increasingly proposed as a model for comparative and translational neuroscience. In parallel to the recent advances in canine behavior research, dogs have also been proposed as a model of many human neuropsychiatric conditions, including autism spectrum disorder (ASD). In this opinion paper we will shortly discuss the challenging nature of autism research then summarize the different neurocognitive frameworks for ASD making the case for a canine model of autism. The translational value of a dog model stems from the recognition that (a) there is a large inter‐individual variability in the manifestation of dogs' social cognitive abilities including both high and low phenotypic extremes; (b) the phenotypic similarity between the dog and human symptoms are much higher than between the rodent and human symptoms; (c) the symptoms are functionally analogous to the human condition; and (d) more likely to have similar etiology. This article is categorized under: • Psychology > Comparative Psychology • Cognitive Biology > Evolutionary Roots of Cognition
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Cognitive processes are carried out during wakefulness by means of extensive interactions between cortical and subcortical areas. In psychiatric conditions, such as psychosis, these processes are altered. Interestingly, REM sleep where most dreams occurs, shares electrophysiological, pharmacological, and neurochemical features with psychosis. Because of this fact, REM sleep is considered a natural model of psychosis. Ketamine is a non-competitive N-methyl-D-aspartate (NMDA) receptor antagonist that at sub-anesthetic dose induces psychotomimetic-like effects in humans and animals, and is employed as a pharmacological model of psychosis. Oscillations in the gamma frequency band of the electroencephalogram (EEG), mainly at about 40 Hz, have been involved in cognitive functions. Hence, the present study was conducted to analyze the EEG low gamma (30–45 Hz) band power and coherence of the cat, in natural (REM sleep) and pharmacological (sub-anesthetic doses of ketamine) models of psychosis. These results were compared with the gamma activity during alert (AW) and quiet wakefulness (QW), as well as during non-REM (NREM) sleep. Five cats were chronically prepared for polysomnographic recordings, with electrodes in different cortical areas. Basal recordings were obtained and ketamine (5, 10, and 15 mg/kg, i.m.) was administrated. Gamma activity (power and coherence) was analyzed in the abovementioned conditions. Compared to wakefulness and NREM sleep, following ketamine administration gamma coherence decreased among all cortical regions studied; the same coherence profile was observed during REM sleep. On the contrary, gamma power was relatively high under ketamine, and similar to QW and REM sleep. We conclude that functional interactions between cortical areas in the gamma frequency band decrease in both experimental models of psychosis. This uncoupling of gamma frequency activity may be involved in the cognitive features shared by dreaming and psychosis.
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Simple Summary It is common knowledge that negative emotions in humans are accompanied by both impaired subjective experience as well as maladaptive changes in behavior and physiology. The present paper investigates heart rate—one of the most commonly used emotion-related physiology measures—in the family dog, with the aim of uncovering its potential relationship with emotions. Sleep recordings were conducted following a positive versus a negative social interaction, as sleep alternations are one of the most conspicuous changes in response to negative affect. We observed differences in heart rate following the positive versus negative interactions, however these were only apparent during wakefulness, but not during sleep. Abstract The domestic dog (Canis familiaris) has been shown to both excel in recognising human emotions and produce emotion-related vocalisations and postures that humans can easily recognise. However, little is known about the effect of emotional experiences on subsequent sleep physiology, a set of phenomena heavily interrelated with emotions in the case of humans. The present paper examines heart rate (HR) and heart rate variability (HRV) during dogs’ sleep, measures that are influenced by both positive and negative emotions in awake dogs. In Study I, descriptive HR and HRV data is provided on N = 12 dogs about the different sleep stages (wake, drowsiness, non-rapid eye movement (non-REM), REM; scoring based on electroencephalogram (EEG) data). We conclude that wakefulness is characterised by higher HR and lower HRV compared to all sleep stages. Furthermore, drowsiness is characterised by higher HR and lower HRV than non-REM and REM, but only if the electrocardiogram (ECG) samples are taken from the first occurrence of a given sleep stage, not when the longest periods of each sleep stage are analysed. Non-REM and REM sleep were not found to be different from each other in either HR or HRV parameters. In Study II, sleep HR and HRV measures are compared in N = 16 dogs after a positive versus negative social interaction (within-subject design). The positive social interaction consisted of petting and ball play, while the negative social interaction was a mixture of separation, threatening approach and still face test. Results are consistent with the two-dimensional emotion hypothesis in that following the intense positive interaction more elevated HR and decreased HRV is found compared to the mildly negative (lower intensity) interaction. However, although this trend can be observed in all sleep stages except for REM, the results only reach significance in the wake stage. In sum, the present findings suggest that HR and HRV are possible to measure during dogs’ sleep, and can potentially be used to study the effect of emotions not only during but also after such interactions.
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The domestic dog (Canis familiaris) is a promising animal model. Yet, the canine neuroscience literature is predominantly comprised of studies wherein (semi-)invasive methods and intensive training are used to study awake dog behavior. Given prior findings with humans and/or dogs, our goal was to assess, in 16 family dogs (1.5–7 years old; 10 males; 10 different breeds) the effects of pre-sleep activity and timing and location of sleep on sleep electrophysiology. All three factors had a main and/or interactive effect on sleep macrostructure. Following an active day, dogs slept more, were more likely to have an earlier drowsiness and NREM, and spent less time in drowsiness and more time in NREM and REM. Activity also had location- and time of day-specific effects. Time of day had main effects; at nighttime, dogs slept more and spent less time in drowsiness and awake after first drowsiness, and more time in NREM and in REM. Location had a main effect; when not at home, REM sleep following a first NREM was less likely. Findings are consistent with and extend prior human and dog data and have implications for the dog as an animal model and for informing future comparative research on sleep.
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The effects of emotionally valenced events on sleep physiology are well studied in humans and laboratory rodents. However, little is known about these effects in other species, despite the fact that several sleep characteristics differ across species and thus limit the generalizability of such findings. Here we studied the effect of positive and negative social experiences on sleep macrostructure in dogs, a species proven to be a good model of human social cognition. A non-invasive polysomnography method was used to collect data from pet dogs (n = 16) participating in 3-hour-long sleep occasions. Before sleep, dogs were exposed to emotionally positive or negative social interactions (PSI or NSI) in a within-subject design. PSI consisted of petting and ball play, while NSI was a mixture of separation, threatening approach and still face test. Sleep macrostructure was markedly different between pre-treatment conditions, with a shorter sleep latency after NSI and a redistribution of the time spent in the different sleep stages. Dogs’ behaviour during pre-treatments was related to the macrostructural difference between the two occasions, and was further modulated by individual variability in personality. This result provides the first direct evidence that emotional stimuli affect subsequent sleep physiology in dogs. © 2017 The Author(s) Published by the Royal Society. All rights reserved.
Article
Objective To describe sleep‐disordered breathing (SDB) in the Cavalier King Charles spaniel (CKCS). Study design Retrospective case series. Animals Five client‐owned dogs referred for SDB. Methods Medical records were reviewed including recheck appointments and routine preoperative and postoperative questionnaires. Whole‐body barometric plethysmography was used to categorize SDB. Results All dogs presented with multiple episodes of stertorous breathing, choking, and apnea during sleep. Severe nasal septal deviation, aberrant nasal turbinates, and soft palate elongation and thickening were noted on computed tomography and rhinoscopy of each dog. Whole‐body barometric plethysmography measurements during sleep (in 3 dogs) documented periods of choking, snoring, and apnea. Treatment combined laser turbinectomy, folding flap palatoplasty, tonsillectomy, laryngeal sacculectomy, and cuneiform process resection. All dogs improved in terms of incidence and severity of sleep apnea within 1 week, with 4 of 5 dogs achieving complete resolution. Conclusion The objective measurements used to characterize SDB in this population of CKCS provided some evidence to support an obstructive cause for this condition, which improved with surgical treatment. Clinical significance Sleep‐disordered breathing in the CKCS is a different clinical presentation of brachycephalic obstructive airway syndrome. Our finding of intranasal abnormalities in these 5 dogs with SDB provides justification for future research into its clinical significance.
Article
Dogs (Canis familiaris) are excellent models of human behavior as during domestication they have adapted to the same environment as humans. There have been many comparative studies on dog behavior; however, several easily measurable and analyzable psychophysiological variables that are widely used in humans are still largely unexplored in dogs. One such measure is rapid eye movement density (REMD) during REM sleep. The aim of this study was to test the viability of measuring REMD in dogs and to explore the relationship between the REMD and different variables (sex, age, body size, and REM sleep duration). Fifty family dogs of different breeds and ages (from 6 months to 15 years old) participated in a 3-h non-invasive polysomnography recording, and the data for 31 of them could be analyzed. The signal of the electro-oculogram (EOG) was used to detect the rapid eye movements during REM sleep, and REMD was calculated based on these data. The duration of REM sleep had a quadratic effect on REMD. Subjects’ REMD increased with age, but only in male dogs with short REM sleep duration. Furthermore, in the case of dogs with short REM sleep, the interaction of body mass and REM sleep duration had a significant effect on REMD. No such effects were found in dogs with long REM duration. These results suggest that relationships may exist between REMD and several different variables.