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Animals may experience positive affective states in response to their own achievements. We investigated emotional responses to problem-solving in dogs, separating these from reactions to rewards per se using a yoked control design. We also questioned whether the intensity of reaction would vary with reward type. We examined the response (behavior and heart rate) of dogs as they learned to gain access to different rewards: (1) food (2) human contact, and (3) dog contact. Twelve beagles were assigned to matched pairs, and each dog served as both an experimental and a control animal during different stages of the experiment. We trained all dogs to perform distinct operant tasks and exposed them to additional devices to which they were not trained. Later, dogs were tested in a new context. When acting as an experimental dog, access to the reward was granted immediately upon completion of trained operant tasks. When acting as a control, access to the reward was independent of the dog's actions and was instead granted after a delay equal to their matched partner's latency to complete their task. Thus, differences between the two situations could be attributed to experimental dogs having the opportunity to learn to control access to the reward. Experimental dogs showed signs of excitement (e.g., increased tail wagging and activity) in response to their achievements, whereas controls showed signs of frustration (e.g., chewing of the operant device) in response to the unpredictability of the situation. The intensity of emotional response in experimental dogs was influenced by the reward type, i.e., greatest response to food and least to another dog. Our results suggest that dogs react emotionally to problem-solving opportunities and that tail wagging may be a useful indicator of positive affective states in dogs.
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Positive affect and learning: exploring
the ‘Eureka Effect’ in dogs
Ragen T. S. McGowan
Therese Rehn
Yezica Norling
Linda J. Keeling
Received: 31 May 2013 / Revised: 24 September 2013 / Accepted: 25 September 2013 / Published online: 6 October 2013
Ó Springer-Verlag Berlin Heidelberg 2013
Abstract Animals may experience positive affective
states in response to their own achievements. We investi-
gated emotional responses to problem-solving in dogs,
separating these from reactions to rewards per se using a
yoked control design. We also questioned whether the
intensity of reaction would vary with reward type. We
examined the response (behavior and heart rate) of dogs as
they learned to gain access to different rewards: (1) food
(2) human contact, and (3) dog contact. Twelve beagles
were assigned to matched pairs, and each dog served as
both an experimental and a control animal during different
stages of the experiment. We trained all dogs to perform
distinct operant tasks and exposed them to additional
devices to which they were not trained. Later, dogs were
tested in a new context. When acting as an experimental
dog, access to the reward was granted immediately upon
completion of trained operant tasks. When acting as a
control, access to the reward was independent of the dog’s
actions and was instead granted after a delay equal to their
matched partner’s latency to complete their task. Thus,
differences between the two situations could be attributed
to experimental dogs having the opportunity to learn to
control access to the reward. Experimental dogs showed
signs of excitement (e.g., increased tail wagging and
activity) in response to their achievements, whereas con-
trols showed signs of frustration (e.g., chewing of the
operant device) in response to the unpredictability of the
situation. The intensity of emotional response in experi-
mental dogs was influenced by the reward type, i.e.,
greatest response to food and least to another dog. Our
results suggest that dogs react emotionally to problem-
solving opportunities and that tail wagging may be a useful
indicator of positive affective states in dogs.
Keywords Canis familiaris Canine
Positive emotions Problem-solving Behavior
Animal welfare
The investigation of emotional states in animals is fast
becoming a key area in animal welfare research (e.g.,
Wemelsfelder 2007; Green and Mellor 2011). Although
experimental studies in this area are still limited, the exact
nature of the emotional experiences of animals remains
poorly understood (Harding et al. 2004; Paul et al. 2005;
Boissy et al. 2007). Affective states are complex, involving
an interplay between behavioral, physiological, and sub-
jective components (Panksepp 1998; Paul et al. 2005;
Panksepp 2011); although the way in which animals
experience emotion is difficult to measure directly,
behavioral and physiological components of affective
responses can serve as useful proxy measures (Burman
et al. 2008; Gygax et al. 2013). From an evolutionary
perspective, there should be positive states associated with
actions where the benefits are in the future (e.g., play).
Problem-solving opportunities should evoke an immediate
positive emotional state in animals, as a means to motivate
the animal to explore and solve problems, even if the true
benefit of the behavior is in the long term. Such a notion is
supported by recent evidence that in order to store
R. T. S. McGowan T. Rehn Y. Norling L. J. Keeling
Department of Animal Environment and Health, Swedish
University of Agricultural Sciences, Box 7068, 750 07 Uppsala,
R. T. S. McGowan (& )
Purina Research, St. Louis, MO, USA
Anim Cogn (2014) 17:577–587
DOI 10.1007/s10071-013-0688-x
experiences permanently, the brain must release dopamine
(e.g., Bethus et al. 2010; Chowdhury et al. 2012).
The idea that providing animals with opportunities for
learning and problem-solving could elicit positive emo-
tions has been the topic of much discussion (Meehan and
Mench 2007; Boissy et al. 2007; McGowan et al. 2010);
however, experimental work focusing on the intrinsic
reinforcing properties of problem-solving and the emo-
tional consequences of responding to challenge is rare
(Langbein et al. 2009; Zebunke et al. 2011). One paper
which has specifically addressed this idea is that of Hagen
and Broom (2004), who designed a study with cattle using
a yoked control design to determine whether cattle respond
emotionally to their own achievements in an operant
learning task. They found that cattle who had mastered an
operant task in order to receive a food reward demonstrated
more behavior indicative of excitement than control ani-
mals that received the same reward without the opportunity
to learn the relationship between the task and the reward. A
finding of this nature deserves replication and investigation
of its generality, as well as further study due to its potential
in the assessment of animal emotion. There has been a call
for additional studies to examine the idea that problem-
solving opportunities are intrinsically rewarding, even if
the experiences are also externally rewarded (e.g., Meehan
and Mench 2007).
Measuring emotion in animals is challenging, and
although most work in the past has focused on negative
affective states, there is an emerging view that good wel-
fare requires the presence of positive affective states such
as pleasure (Fraser and Duncan 1998; Boissy et al. 2007).
There is, however, a lack of research concerning the cir-
cumstances under which such positive emotional states
might occur and also on how these positive states can be
measured. In particular, since most work on emotional
states has involved research on negative affect, finding
biologically based paradigms to put animals into positive
states is key to starting the investigation into positive
emotional states.
In this paper, we took on this challenge in an investi-
gation into the emotional responses to learning in dogs,
Canis familiaris. Utilizing a modified version of the yoked
control design outlined by Hagen and Broom (2004), we
aimed to identify the reactions of dogs to their own
learning and to separate these from reactions to the rewards
themselves. We hypothesized that dogs would react emo-
tionally to their own achievements, predicting that the
development of an understanding of the relationship
between an action and a reward would elicit a positive
affective state in dogs. We also took this idea one step
further hypothesizing that the intensity of such emotional
reactions to learning might vary in response to different
reward types. For example, we questioned whether the
excitement of learning to gain access to food is experienced
the same as the excitement for learning to gain access to a
social companion (as suggested in humans, Sakaki et al.
2012). We therefore investigated the emotional response to
learning in dogs in relation to rewards catering to different
motivational systems.
Individual dogs with different experiences and personali-
ties may be expected to solve problems more or less quickly or
experience learning in different ways (Carere and Locurto
2011). Accordingly, we were interested in teasing out the
individual differences that dogs demonstrated during prob-
lem-solving events and relating this back to their past per-
formances with cognitive tasks. In doing so, we felt that it was
important to look at the heart rate in addition to the behavior as
we know that the heart rate can be a measure of arousal or
excitement, providing insight into the internal state of the
animal. In particular, we were interested in trying to identify
the moment at which dogs might experience the ‘Eureka
Effect’ during a problem-solving event by looking closely at
the behavior and the heart rate before and after the dogs learn
the causal relationship between their actions and gaining
access to a reward. Their behavioral and physiological
responses to this learning may be an indicator of what they
experience at this presumably positive moment in time.
Animals and housing
We conducted trials to investigate emotional responses to
problem-solving with twelve female beagles (age
10–14 months) housed at the Swedish University of Agri-
cultural Sciences in Uppsala. During the day, dogs at this
facility were kept in groups of six in large (145–200 m
outdoor runs constructed from chain-link fencing. This con-
struction allowed for visual, auditory, and olfactory commu-
nication between groups. Each outdoor run was furnished
with multiple shelters, climbing structures, toys, and water
dispensers. Dogs were moved indoors (in groups of three) at
night into rooms (24.3 m
) equipped with blankets, water
dispensers, and toys. Indoor rooms were cleaned each morn-
ing when the dogs were moved to the outdoor runs. Dogs were
fed a maintenance chow diet twice daily (individually in
separate feeding areas) at 08.30 and 15.30 h. Dogs interacted
with human caregivers during routine care, play sessions and
daily walks, and had been used in several behavioral obser-
vation studies exploring the positive affective states.
Training sessions were conducted to familiarize the dogs
with the operant devices and the skills required for
578 Anim Cogn (2014) 17:577–587
manipulating them. Since each dog would serve as both an
experimental and a control animal at different stages of the
experiment, we trained all dogs to perform three distinct
operant tasks (experimental treatment) and exposed all
dogs to an additional three operant devices without training
(control treatment). Training sessions were carried out in a
single indoor room to which dogs were habituated prior to
the initiation of the training sessions. In this room, two
training arenas were constructed (1 m 9 2 m), each
equipped with two different operant devices (Fig. 1). The
dogs were assigned to matched pairs. Both dogs of a
matched pair were present in the training room at the same
time, one in each training arena. Each dog was accompa-
nied by a handler and they could hear what was happening
in the other arena, but they could not see into it.
The dogs were trained to perform three operant tasks
(learning one at a time) by means of shaping with food
rewards and acoustic signaling. Different acoustic signals
(click or beep) were used for each dog of the pair. Shaping
was conducted in three stages where dogs were rewarded
for (1) approaching the operant device, (2) making contact
with the operant device, and then (3) correctly manipulat-
ing the operant device. In each phase, appropriate action by
the dog was immediately rewarded with a click/beep and a
treat. By having two operant devices present in each
training arena and training each dog of the pair on a dif-
ferent device of the pair, and with a different acoustic
signal (Table 1) to confirm that the dog was taking
appropriate action, each dog in the pair could be trained as
an experimental and control animal simultaneously. That is
to say, while dogs were learning to manipulate one device,
they were not receiving any training on their matched
experimental partner’s operant task even though that same
device was in their own training arena. Any manipulation
of the ‘control’ device was ignored by the handler. This
experimental design meant that while learning to be
controls, dogs were exposed to identical circumstances as
their matched experimental dogs (i.e., they heard the same
number of these two acoustic cues, were exposed to the
same two identical operant devices, and received the same
length of ‘training’ session). Once a dog approached and
successfully manipulated the device three times on its own
accord, training ceased. Due to the differences in learning
ability between dogs, the total length of training sessions
for each matched pair varied, being determined by the
slowest learning dog of each pair. The pair of dogs then
proceeded to learn the second and then the third operant
task, in a similar way.
Dogs were removed from their groups just prior to each
training session and returned immediately afterward. The
handlers, operant devices, location of the training arena,
and location of the devices within the arena were balanced
between dogs.
One week after completing their training sessions, the dogs
were tested in a new context where the performance of the
learned task was necessary to gain access to one of the
three rewards. This one-week time gap along with a change
in location between training and testing created a new
situation in which the dogs were required to put together
the pieces of their training to solve a novel problem.
Fig. 1 Diagram of the training arenas. Two dogs of a matched pair
were trained simultaneously: dog I trained as the experimental dog on
device A and exposed to device D as a control; dog II trained as the
experimental dog on device D and exposed to device A as a control
Table 1 List of the operant tasks and corresponding signal signifying
the task was completed successfully
Task Signal Description of device
Press wood
Click Wooden lever attached to a wheel with
spokes that clicked when the lever
was pressed
Press paddle
Bell A canoe paddle attached to a bicycle
bell that rang when the paddle was
Push box off
A stack of four plastic boxes where the
lower three boxes were attached to the
floor and the top box could be pushed
off the stack
Pushover dog
A tall plastic container that was
weighted at the top and hinged so that,
with some force, it could be tipped
Push ball of
A child’s rubber ball placed on top of a
heavy cardboard tube affixed to the
floor so that, with some force, the ball
could be pushed off
Press key on
dog piano
Metal ding A child’s piano with plastic keys that
when manipulated struck a metal
xylophone making a tone
Each dog trained to complete three tasks (one per reward type)
Anim Cogn (2014) 17:577–587 579
Testing took place in a room to which all dogs were
habituated prior to the initiation of the first test session. The
test room was divided into four parts such as (1) start arena,
(2) hide for experimenter, (3) runway, and (4) reward area
(Fig. 2). The start arena had an entrance door, through
which the dogs were led into the test room, and a door into
the runway, through which they could access the reward.
Dogs were accompanied to the test room by a handler who
remained in the start arena with the dog for the duration of
each test run. The handler wore headphones, and after
releasing the dog into the start arena, they stood in the
corner with their back turned toward the dog so as to
prevent providing any cues that might aid the dog in
solving the task at hand (Kupa
n et al. 2011; Lit et al. 2011;
Buttelmann and Tomasello 2012). This procedure was
necessary because if the handler exited the start arena, most
dogs focused on the door the handler left from, instead of
the operant device. An experimenter was present during the
entire test session, but was visually isolated from the dog in
a hide located outside the start arena. From the hide, the
experimenter could manipulate the door to the runway via a
pulley system. Cameras were mounted on both the start
arena and the runway, which allowed the experimenter to
view the dogs’ actions via a monitor located in the hide.
As with the training sessions, dogs were removed from
their groups just prior to each test session and were
returned immediately afterward. Each test session con-
sisted of eight consecutive runs conducted on Day 1.
During the first two runs, the dog was led into an empty
start arena, and upon release of the dog by the handler, the
door to the runway was immediately opened by the
experimenter. This demonstrated to the dog that there was
a way out of the start arena and that there was a reward at
the end of the runway. For these initial two runs, the dogs
were allowed 30 s to interact with the reward once they
reached the end of the runway.
Before the beginning of the third run, the experimenter
placed one of the operant devices into the start arena. This
device was familiar to both dogs in the matched pair;
however, only the dog acting as the experimental dog was
trained to manipulate this device. Although the experi-
mental dogs were trained on how to manipulate the device
in general, here the device was presented in a new context
where appropriate manipulation led to the door to the
runway being opened. This provided the opportunity for
experimental dogs to learn the causal relationship between
performing the task and the door opening. If successful, the
door to the runway was immediately opened providing
access to the runway and the dogs were allowed 30 s to
interact with the reward once they reached the end of the
runway. The door to the start arena was closed after the dog
exited into the runway, preventing the reentrance into the
start arena. Experimental dogs were allowed 5 min per test
run to explore the start arena and perform the operant task.
If a dog did not complete the task during the 5-min
exploration period in the start arena, she was collected by
the handler and led out of the room for a 5-min rest period
before being brought in for the next test run. If a dog failed
to perform the task during 5 min on two consecutive runs,
she was retested the following day. After each successful
run, the dog was collected by the handler, led out of the
room through an exit at the end of the runway, and then
was returned to the start arena. This cycle was repeated 5
times for a total of 6 test runs.
The latency for each experimental dog to successfully
perform the operant task was recorded. Control dogs were
then placed in the start arena for a time period matched to
the time it took the experimental dog in the pair to com-
plete the operant task. For this reason, experimental dogs
were tested first followed by their matched control. When
the dogs were acting as controls, the experimenter opened
the door to the runway at the same time point as when their
matched experimental dog had successfully completed the
operant task regardless of what action the dog acting as the
Fig. 2 Diagram of the test arena
Fig. 3 Yoked control design. Dogs acting as experimental animals
had the opportunity to learn a causal relationship between performing
a specific task and gaining access to a specific reward. Dogs acting as
controls did not have the opportunity to learn this relationship but did
gain access to the same reward
580 Anim Cogn (2014) 17:577–587
control made. When acting as controls, the dogs were,
therefore, granted access to the same reward independent
of their actions (Fig. 3).
This yoked control design ensured that when dogs were
acting as experimental, but not control animals, they had
the opportunity to learn a causal relationship between
performing a specific task and gaining access to a specific
reward. When acting as controls, the dogs did not have the
opportunity to learn this relationship but did gain access to
the same reward. Differences between the dogs’ responses
to both the experimental and control sessions could then be
used to differentiate emotional reactions to learning from
emotional reactions to the reward, as well as changes in
how this was experienced (changes in heart rate and
behavior) over the six runs. For dogs in the experimental
situation, access to the reward should have become pre-
dictable as they learned the causal relationship between
their actions and the door opening, while for the control
dogs the situation would remain unpredictable.
Training and testing sessions were repeated with each
matched pair (Fig. 4) to compare emotional reactions to
rewards catering to different motivational systems: (1) food
(40 small bits of highlypalatable kibblespread at the end of the
runway); (2) social contact with a human (a familiar human
sitting at the end of the runway, calmly petting the dog once
the dog made contact); and (3) social contact with other dogs
(two group members of the dog on leashes at the end of the
runway, allowing the opportunity for social interaction and
play). Dogs were trained to complete three different operant
tasks in order to gain access to the three different rewards. The
operant tasks, rewards, and their order were balanced between
dogs and across treatments to control for differences in the
difficulty level of tasks and any carryover effects of one
reward to another. Each matched pair was subject to three
training days and six testing days (three acting as an experi-
mental and three acting as a control dog) with a one-week time
gap between each training and testing session.
All test sessions were video recorded for the later analysis.
Each dog’s demeanor when entering the start arena was
noted, namely whether the dog led the handler into the start
arena or whether the handler had to coax the dog into the
start arena. Latency to perform the operant task, latency to
exit the start arena, and latency to reach the reward after the
runway door was opened were measured. In addition, each
dog’s behavior in the start arena was evaluated to assess the
frequency of steps (activity level) and tail wags (excite-
ment level) that occurred during the problem-solving event
when acting as experimental dogs and the corresponding
waiting period when acting as controls. Steps from all four
paws were counted when the foot was lifted completely off
the floor and placed down again. A tail wag was counted
each time the tail moved from a central position (in line
with the spine) to either the right or left and back again.
Wags were counted in this manner regardless of tail car-
riage position (e.g., high or low); however, high tail car-
riage was most common with low tail carriage being
observed only rarely in the context of this study. The
manner in which the dogs manipulated the operant devices
was also noted. Specifically, whether the dogs manipulated
the device appropriately (pawing or nosing) or inappro-
priately (chewing on the device). All videos were scored by
a single observer in a random order and a test of intra-
observer concordance (on six videos chosen at random
between experimental and control sessions across matched
pairs for the three reward types) indicated that the reli-
ability of data scoring was C95.6 %.
Mean heart rate (recorded every 5 s) for each dog
throughout the entire test session was also measured using
Polar S810 (Polar Electro Oy, Kempele, Finland) heart rate
monitors along with Polar Precision Performance Soft-
. The monitors were strapped around the chest of
the dog before the start of each test session and recording
started immediately upon each dog’s entry into the start
area for the first of the eight runs. All dogs were habituated
to the heart rate monitors prior to the beginning of the test
Statistical analysis
We used a mixed linear model (Proc Mixed) of the SAS
Institute (version 9.1) with run as a repeated measure; dog
as a random effect; and pair, task, device, treatment, and
reward as fixed effects in the model. We tested for overall
effects of treatment, task, reward, and their interactions on
the latencies and mean heart rate throughout the test ses-
sion as well as the number of steps, tail wags, and mean
heart rate when the dog was in the start arena. Analyses
conducted on both raw and ranked data yielded similar
Fig. 4 Dogs were assigned to matched pairs and served as both
experimental and control animals at different stages of the exper-
iment. We trained all dogs to perform distinct operant tasks
(experimental) and exposed them to additional operant devices to
which they were not trained (control)
Anim Cogn (2014) 17:577–587 581
results, suggesting that valid assessment could be con-
ducted with parametric statistics. Results from the analyses
on ranked data are reported. Separate analyses were con-
ducted for the latencies, heart rate, steps, and tail wags.
Comparisons between variables were made based on the
differences in least-squares means, with p values adjusted
for multiple comparisons using the Tukey’s option.
In addition, we took a retroactive approach looking at
the data collected as part of another experiment where
these same dogs were trained on a cognitive bias task
(Burman et al. 2011) paired with the heart rate data col-
lected in this study to look at how the physiological
responses of the dogs in this study compared with their
cognitive abilities during a previous study. These ad hoc
comparisons were made using paired t tests in Minitab
(version 16).
From the onset of the test sessions, it was noted by the
animal handlers that when acting as experimental animals,
the dogs were eager to enter the test room. They were
pulling the handler toward the door leading into the test
room and in most cases would enter the start arena ahead of
the handler. When acting as controls, on the other hand, the
dogs were initially eager to enter the test room during their
first two or three test runs, but soon grew reluctant to enter
the test room. By the end of the test sessions, these dogs
would enter the start arena only after some coaxing from
the handler. These observations are in line with the idea
that apathy will develop when the animal has no way to
control their environment, whereas hyperreactivity may
occur when an animal is under the impression that it is able
to control such events (Boissy et al. 2007).
All dogs acting as experimental animals were successful in
manipulating the operant device within the time frame
provided in the start arena (mean ± SE; 50.53 ± 7.48 s)
on all test days. As expected, there were differences
between individuals with some dogs learning to manipulate
the device more quickly than others (Fig. 5). Nine out of
twelve of the dogs manipulated the operant device cor-
rectly on at least one occasion when acting as a control
dog, and this occurred most frequently during the last test
session after the control dogs had served as experimental
dogs on three occasions. However, as explained, this did
not have the effect of opening the door, but shows that the
dogs were transferring their experience of being an
experimental dog and that they had learnt the association
between manipulating a familiar operant device and the
opening of the door to the novel operant device.
There was a treatment effect on the time it took dogs to
exit the start arena after the door to the runway was opened,
with dogs acting as experimental animals taking longer
(mean ± SE; 5.81 ± 1.40 s) than when they were acting
as controls (4.17 ± 0.47 s) (t
= 2.76, p = 0.03). The
latencies to exit the start arena were also influenced by
reward type (Fig. 6), with experimental dogs taking longer
than when they were acting as control dogs to leave the
start arena when there was a food reward (t
= 3.71,
p = 0.014) or a social opportunity with other dogs
= 2.41, p = 0.041). However, there were no differ-
ences between acting as an experimental and a control dog
when the reward was a social opportunity with a human
=-0.24, p = 0.817).
The dogs remained consistent in their approach speed
for the reward at the end of the runway over the three tasks
suggesting that the event was rewarding, with no apparent
decline in interest over the three tasks. There was no
treatment effect on the time it took dogs to reach the
reward at the end of the runway once they had exited the
start arena irrespective of the reward type (t
B 0.82,
p [ 0.05).
Fig. 5 Means ± SE latencies to complete the operant task across all
reward types for dogs acting as experimental animals
Fig. 6 Means ± SE latencies to exit the start area expressed by
reward type
582 Anim Cogn (2014) 17:577–587
Activity level
There was a treatment effect on the activity level in the
start arena, with dogs acting as experimental animals
(mean ± SE; 2.63 ± 0.08 steps/s) being more active
(taking more steps) than when acting as controls
(2.29 ± 0.16 steps/s) (F
= 37.36, p \ 0.0001). Overall,
irrespective of whether they were acting as experimental
dogs or controls, dogs were less active during the third
round of testing (task 3) than they were during the first
= 4.29, p \ 0.001) or second (t
= 5.26, p \ 0.0001)
rounds of testing.
The expected reward influenced the activity levels of the
dogs in both treatments (Fig. 7). When dogs were expect-
ing a food reward, they were more active than when
expecting access to other dogs (t
= 3.41, p = 0.0067).
Comparing activity in dogs expecting access to a human
and those expecting access to other dogs, t
= 2.48,
p = 0.053.
When acting as control animals, the dogs were observed to
bite and chew the operant devices in a manner not appro-
priate for manipulating the device. No dog acting as an
experimental animal chewed a device in this manner.
Chewing of the devices by control dogs occurred
throughout the experiment, but most frequently during the
third round of testing (Fig. 8). This behavior was not
influenced by the reward the dogs were expecting at the
end of the runway.
Tail wags
There was a treatment effect on tail wagging in the start
arena with the dogs acting as experimental animals
(mean ± SE; 2.70 ± 0.01 wags/s) wagging their tails more
than when acting as controls (1.21 ± 0.08 wags/s)
= 205, p \ 0.0001). Tail-wagging frequency did not
change over time (i.e., no difference across tasks,
= 2.04, p = 0.15).
The expected reward influenced tail-wagging frequency
for dogs acting as experimental animals (Fig. 9) with dogs
expecting a food reward wagging their tails more than
when expecting access to other dogs (t
= 3.02,
p = 0.006) and a tendency for dogs expecting access to a
human to wag their tails more than when expecting access
to other dogs (t
= 1.81, p = 0.083).
Heart rate
There was no overall difference in mean heart rate between
dogs when dogs were acting as experimental animals
(mean ± SE; 126.1 ± 3.4 bpm) and acting as controls
(127.5 ± 2.2 bpm) when considering the entire test ses-
sion, nor there was a difference in mean heart rate for these
dogs in the start arena during the problem-solving oppor-
tunity for the dogs acting as experimental animals
(132.1 ± 2.9 bpm) or during the corresponding waiting
period for the dogs acting as controls (131.0 ± 2.0 bpm).
Burman et al. (2011) found that it took the dogs
93.2 ± 15.2 trials to reach criterion during initial training
on a cognitive task. In this study, dogs that had higher heart
rates in the start arena when acting as experimental animals
than when acting as controls averaged 137.8 ± 19.2 trials
Fig. 7 Means ± SE number of steps/second in the start arena during
the problem-solving opportunity for experimental dogs or the
corresponding waiting period for control dogs, expressed by reward
Fig. 8 Means ± SE frequency of chewing the operant device for
control dogs in the start arena over time
Fig. 9 Means ± SE number of wags/second in the start area during
the problem-solving opportunity for experimental dogs or the
corresponding waiting period for control dogs, expressed by reward
Anim Cogn (2014) 17:577–587 583
to reach criterion in the Burman et al. (2011) study. Dogs
that had higher heart rates in the start arena when acting as
controls than when acting as experimental animals aver-
aged 61.3 ± 11.9 trials to reach criterion in the Burman
et al. (2011) study (t
= 2.36, p = 0.011).
As predicted, we found differences in behavior between the
dogs when they were acting as experimental and control
animals in our study. In general, the dogs showed more
signs of positive excitement (e.g., more activity and more
tail wagging) when acting as experimental animals than
when acting as controls. Hagen and Broom (2004) sug-
gested that differences in emotional response to learning
might occur either specifically during the process of
understanding, or only occur once a task has been acquired.
They found evidence for the latter as behavioral differences
in cattle were detected only in the runway after the animals
had learned that they could control access to the reward.
Because they found these behavioral differences after the
cattle had learned the causal relationship between their
actions and gaining access to the reward, Hagen and Broom
(2004) speculated that the cattle were reacting to their own
learning success and thus, in a sense, to their own
achievement. In our study, we found behavioral differences
during the actual process of understanding (e.g., in the start
arena), providing evidence that it was success in the
problem-solving that elicited a positive affective state in
the experimental animals.
Differences in demeanor were observed in that dogs
were quick to enter the test arena initially, but control dogs
became increasingly reluctant. Behavioral differences were
also reflected in the fact that dogs acting as controls, but
not when acting as experimental animals, were observed to
chew the operant device on several occasions. Chewing of
the devices by control dogs occurred throughout the
experiment, but most frequently toward the end of the
study during the last matched pair of testing after they had
already served as experimental animals on three occasions.
The dogs may have developed a set of expectations about
the test environment, with the understanding that they
could open the door to the runway through the operation of
the operant device. When faced with being in the control
situation where they no longer had the ability to open the
door to the runway by manipulating the operant device,
they may have suffered from a mismatch between their
expectations and the situation at hand. This mismatch most
likely would lead to frustration (Cuenya et al. 2012).
Because manipulation of the operant device did not lead to
the door opening, their frustration escalated into biting, and
chewing at the operant device.
Although some degree of negative stress and frustration
will probably occur in the initial stage of learning (Lang-
bein et al. 2004; Meehan and Mench 2007), successful
actions with a positive outcome are, as explained in the
introduction, likely to induce positive feelings (Kalbe and
Puppe 2010; Zebunke et al. 2011) and thus motivate the
animal to continue the behavior. Hagen and Broom (2004)
noted more agitation in their experimental group when the
cattle were starting to learn the causal relationship. We did
not observe any clear signs of agitation when our dogs
were acting as experimental animals. However, this may
have been due to the fact that our dogs were pre-trained on
manipulating the operant devices that they were later
exposed to during the problem-solving opportunity. Hagen
and Broom (2004) shaped their experimental subjects to
use the operant device during the test situation. This
entailed providing food in the start arena near the operant
device. The cattle, therefore, may have learned to associate
both the start arena and the runway with a food reward. To
avoid this, we pre-trained our dogs on how to manipulate
the operant devices during sessions in a special training
room, then after a delay of 1 week tested them in a new
context where correct manipulation of the device led to the
door to the runway being open and access to the reward.
Through this process, the dogs never associated the start
arena, but only the runway, with a reward.
Experimental dogs were more active in the start arena
than control dogs despite the fact that when acting in both
roles, the dogs had equal knowledge of the reward at the
end of the runway and thus should have demonstrated
similar levels of anticipatory excitement in the start arena
(Spruijt et al. 2001). The dogs were clearly more excited
when acting as experimental animals than as controls, not
generally (e.g., in the runway), but in relation to the only
difference between the treatments (e.g., in the start arena).
That is to say, the excitement was when the dogs were
experiencing a learning process that they did not experi-
ence when they were acting as controls. Upon entrance into
the start arena and recognition of the operant device on
which they had been trained, the experimental dogs
immediately went to work on attempting to manipulate the
device. Control dogs were often standing directly in front
of the runway door sniffing or pawing at the door as they
waited for it to open. This meant that they were quick to
exit as soon as the door opened. Experimental dogs, on the
other hand, were standing near to the operant device when
the door opened and had to run over to the door before
exiting. This behavior may have contributed to the treat-
ment differences we detected in the time it took the dogs to
exit the start arena; however, it would not explain the
differences according to the reward type.
Tail wagging is an indicator of arousal (Beerda et al.
1999; Prescott et al. 2004), and confident dogs express
584 Anim Cogn (2014) 17:577–587
more tail wagging than unsure dogs (Goddard and Beilharz
1985; Svartberg and Forkman 2002). There is also behav-
ioral and neurochemical evidence to suggest that tail
wagging is tied into emotion. Dogs in playful or positive
situations (McLeod 1996; Broom 1988) and dogs shown
positive stimuli (Horva
th et al. 2007; Quaranta et al. 2007;
Norling et al. 2012) may increase tail-wagging behavior. It
has also been shown that opioid agonists decrease (Pank-
sepp et al. 1983; Knowles et al. 1989) while opioid
antagonists increase tail wagging (Knowles et al. 1989).
Our findings that having the opportunity to solve a problem
and control access to a reward increased tail wagging
suggests that tail wagging can be used as an indicator of a
positive affective state in dogs.
There are two plausible explanations for the different
levels of tail wagging we observed when dogs were
expecting different reward types. Tail wagging could (1)
directly reflect the ‘positiveness’ of the reward or (2)
serve as a better indicator for some motivational systems
over others. Dogs wagged their tails more in the test arena
when they were expecting a food reward or contact with a
human and less when they were expecting contact with
conspecifics. It may be that contact with conspecifics was
experienced as the least positive reward since they were
never deprived of contact with other dogs. The dogs were
removed from their groups immediately before testing and
then returned to their groups immediately after testing.
This did not give them a chance to miss being with their
group mates. The dogs were, however, very much food-
motivated and did not receive treat items on a regular basis
so they were most likely motivated to reach this reward. By
the same light, the dogs received less human contact than
they did dog contact, so were probably more motivated to
reach a friendly human for extra attention than they were to
reach their group mates. Plus reunion with a familiar per-
son is suggested to be positive (Rehn and Keeling 2010).
On the other hand, there is evidence to support the view
that tail wagging could be a better indicator for some
motivational systems than others. Motivation for food is
distinct from motivation for social contact, and dog–dog
and dog–human interaction cater to different motivational
systems as is supported by the fact that the performance of
dog–dog play does not suppress dogs’ motivation to play
with their owners as would be predicted if they were
motivationally interchangeable (Rooney et al. 2000). But,
given the evidence that tail wagging evolved as a mecha-
nism for social signaling and other studies report more tail
wagging toward familiar people than treats (e.g., Norling
et al. 2012), neither of these explanations is entirely
It is difficult to determine the exact ‘Eureka’ moment,
i.e., when the dogs acting as experimental animals made
the connection between their action and the door to the
runway opening. During the first two or three test runs,
most dogs would remain in the start arena investigating the
operant device for a few seconds after the door to the
runway was opened. After these initial test runs, the dogs
would immediately orient themselves toward the door to
the runway upon successful completion of the operant task,
suggesting that their expectation was for the door to open.
We took an extensive look at the heart rate data collected
for each session the dogs spent in the start arena as both an
experimental and control animal in an attempt to identify
this moment of realization. We analyzed the data collected
immediately before, immediately after, and during each
session in the arena as well as compared the data between
each of the six test runs in attempt to find any association
of changes in heart rate with learning. Given that there are
very few published studies looking explicitly at how heart
rate changes in relation to emotional situations, and given
the overall ambiguity of the studies that are available, it
was difficult to predict what specific reactions we might
have expected to see when dogs are experiencing frustra-
tion or reward during a problem-solving opportunity. We
had however predicted that changes in heart rate would
depend on the personality of the dogs (Carere and Locurto
2011) and the way in which they experienced the problem-
solving event (i.e., with excitement or frustration (Black-
well et al. 2010; Zebunke et al. 2011; Gygax et al. 2013)).
Unfortunately, we were unable to detect any such differ-
ences. It may be that such a change occurs rapidly, ‘in the
Eureka moment,’ and is lost when collecting data with a
sampling rate of every 5 s. Given the known connection
between heart rate and physical activity, it is surprising that
we did not find an increase in heart rate in dogs acting as
experimental animals as they were more active (taking
more steps and wagging their tails more) than when acting
as controls. We did however find an interesting connection
between the physiological response of the dogs in this
study and their cognitive performance in a previous study.
Dogs that had higher heart rates when acting as experi-
mental animals required significantly more training to
reach criterion in a cognitive task (see Burman et al. 2011)
than the dogs that had higher heart rates when acting as
controls. This may provide evidence that success or failure
in problem-solving tasks affects dogs with different per-
sonalities differently (Carere and Locurto 2011). It might
also support the work of Groothuis and Carere (2005) who
classified individuals into those that were good at learning
new tasks (in our case, solving the learning task) and those
who are good at sensing environmental change within a
familiar task (in our case, the cognitive bias task). Indi-
viduals that are skilled in one aspect tend to not be good at
the other, in which case the argument might be that dogs
with different personalities find problem-solving tasks
differently rewarding.
Anim Cogn (2014) 17:577–587 585
In conclusion, we found differences between the dogs
acting as experimental and control animals when the only
difference in treatment between these two situations was
the opportunity to learn the causal relationship between
their action and a reward. The yoked control design,
therefore, was effective in separating the emotional effects
of the learning process from those associated with the
expectation of reward. The experimental animals in our
study were excited not only by the expectation of a reward,
but also about realizing that they themselves could control
their access to the reward. These results support the idea
that opportunities to solve problems, make decisions, and
exercise cognitive skills are important to an animal’s
emotional experiences and ultimately, its welfare. From an
evolutionary standpoint, it makes sense that animals should
react emotionally to their own achievements during prob-
lem-solving tasks as, to some degree, heightened states of
emotion can facilitate learning and memory (Hu et al.
2007; Broom 2010; Blackwell et al. 2010) as long as they
are not too intense (i.e., too much excitement or fear can
interfere with the learning process). Positive affective
feelings help animals to better identify behaviors that are
biologically useful and to encourage animals to carry out
these behaviors to their benefit in the long term (Panksepp
1998; Mendl et al. 2010). By providing dogs with a bio-
logically based circumstance under which positive emo-
tional states could develop, we were able to identify tail
wagging as an indicator for measuring such positive states.
The fact that we found clear differences in tail wagging
between treatments and across rewards catering to different
motivational systems (e.g., not just in social situations)
suggests its robustness as an indicator of a positive affec-
tive state in dogs.
Acknowledgments This project was funded by the Swedish
Research Council for Environment, Agricultural Sciences and Spatial
Planning (FORMAS). The final stages of this work were carried out in
collaboration within the Centre of Excellence in Animal Welfare
Science, a Swedish collaborative research environment.
Conflict of interest None.
Ethical standards This study was reviewed and approved by the
Swedish Ethical Committee on Animal Research in Uppsala, Sweden.
All aspects of the study comply with the current laws of Sweden
where the study was performed.
Beerda B, Schilder BH, Van Hooff JARAM, DeVries HW, Mol JA
(1999) Chronic stress in dogs subjected to social and spatial
restriction. I. Behavioral responses. Physiol Behav 66:233–242
Bethus I, Tse D, Morris RG (2010) Dopamine and memory: modulation
of the persistence of memory for novel hippocampal NMDA
receptor-dependent paired associates. J Neurosci 30:1610–1618
Blackwell E-J, Bodnariu A, Tyson J, Bradshaw JWS, Casey RA
(2010) Rapid shaping of behaviour associated with high urinary
cortisol in domestic dogs. Appl Anim Behav Sci 124:113–120
Boissy A, Arnould C, Chaillou E, De
L, Duvaux-Ponter C,
Greiveldinger L, Leterrier C, Richard S, Roussel S, Saint-Dizier
H, Meunier-Salau
n MC, Valance D, Veissier I (2007) Emotions
and cognition: a new approach to animal welfare. Anim Welf
Broom DM (1988) The scientific assessment of animal welfare. Appl
Anim Behav Sci 20:5–19
Broom DM (2010) Cognitive ability and awareness in domestic
animals and decisions about obligations to animals. Appl Anim
Behav Sci 126:1–11
Burman OHP, Parker RMA, Paul ES, Mendl M (2008) Sensitivity to
reward loss as an indicator of animal emotion and welfare. Biol
Lett 4:330–333
Burman O, McGowan R, Mendl M, Norling Y, Paul E, Rehn T,
Keeling L (2011) Using judgement bias to measure positive
affective states in dogs. Appl Anim Behav Sci 132:160–168
Buttelmann D, Tomasello M (2012) Can domestic dogs (Canis
familiaris) use referential emotional expressions to locate hidden
food? Anim Cogn. doi:10.1007/s10071-012-0560-4
Carere C, Locurto C (2011) Interaction between animal personality
and animal cognition. Curr Zool 57:491–498
Chowdhury R, Guitart-Masip M, Bunzeck N, Dolan RJ, Du
zel E
(2012) Dopamine modulates episodic memory persistence in old
age. J Neurosci 32:14193–14204
Cuenya L, Fosacheca S, Mustaca A, Kamenetzky G (2012) Effects of
isolation in adulthood on frustration and anxiety. Behav Process
Fraser D, Duncan IJH (1998) ‘Pleasures’, ‘pains’ and animal welfare:
toward a natural history of affect. Anim Welfare 7:383–396
Goddard ME, Beilharz RG (1985) Individual variation in agonistic
behaviour in dogs. Anim Behav 33:1338–1342
Green TC, Mellor F (2011) Extending ideas about animal welfare
assessment to include ‘quality of life’ and related concepts. N Z
Vet J 59:263–271
Groothuis TGG, Carere C (2005) Avian personalities: characteriza-
tion and epigenesis. Neuro Biobehav Rev 29:137–150
Gygax L, Reefmann N, Wolf M, Langbein J (2013) Prefrontal cortex
activity, sympatho-vagal reaction and behaviour distinguish
between situations of feed reward and frustration in dwarf goats.
Behav Brain Res 239:104–114
Hagen K, Broom DM (2004) Emotional reactions to learning in cattle.
Appl Anim Behav Sci 85:203–213
Harding EJ, Paul ES, Mendl M (2004) Animal behavior: cognitive
bias and affective state. Nature 427:312
th Z, Igya
BZ, Magyar A, Miklo
si A
(2007) Three different
coping styles in police dogs exposed to a short-term challenge.
Horm Behav 52:621–630
Hu H, Real E, Takamiya K, Kang M-G, Ledoux J, Huganir RL,
Malinow R (2007) Emotion enhances learning via norepineph-
rine regulation of AMPA-receptor trafficking. Cell
Kalbe C, Puppe B (2010) Long-term cognitive enrichment affects
opioid receptor expression in the amygdala of domestic pigs.
Genes Brain Behav 9:75–83
Knowles PA, Conner RL, Panksepp J (1989) Opiate effects on social
behavior of juvenile dogs as a function of social deprivation.
Pharmocol Biochem Behav 33:533–537
n K, Miklo
si A
, Gergely G, Topa
l J (2011) Why do dogs (Canis
familiaris) select the empty container in an observational
learning task? Anim Cogn 14:259–268
Langbein J, Nu
rnberg G, Manteuffel G (2004) Visual discrimination
learning in dwarf goats and associated changes in heart rate and
heart rate variability. Physiol Behav 82:601–609
586 Anim Cogn (2014) 17:577–587
Langbein J, Siebert K, Nu
rnberg G (2009) On the use of an automated
learning device by group-housed dwarf goats: do goats seek
cognitive challenges? Appl Anim Behav Sci 120:150–158
Lit L, Schweitzer JB, Oberbauer AM (2011) Handler beliefs affect
scent detection dog outcomes. Anim Cogn 14:387–394
McGowan RTS, Robbins CT, Alldredge JR, Newberry RC (2010)
Contrafreeloading in grizzly bears: implications for captive
foraging enrichment. Zoo Biol 29:484–502
McLeod PJ (1996) Developmental changes in associations among
timber wolf (Canis lupos) postures. Behav Process 38:105–118
Meehan CL, Mench JA (2007) The challenge of challenge: can
problem solving opportunities enhance animal welfare? Appl
Anim Behav Sci 102:246–261
Mendl M, Burman OHP, Paul ES (2010) An integrative and
functional framework for the study of animal emotion and
mood. Proc R Soc B 277:2895–2904
Norling Y, Wiss V, Gorjanc G, Keeling LJ (2012) Body language of
dogs responding to different types of stimuli. In: Proceedings of
the 46th congress of the international society for applied
ethology, July 31st–August 4th, Vienna, p 199
Panksepp J (1998) Affective neuroscience: the foundations of human
and animal emotions. Oxford University Press, New York
Panksepp J (2011) The basic emotional circuits of mammalian brains:
do animals have affective lives? Neurosci Biobehav Rev
Panksepp J, Conner R, Forster PK, Bishop P, Scott JP (1983) Opiod
effects on social behavior of kennel dogs. J Appl Ethol 10:63–74
Paul ES, Harding EJ, Mendl M (2005) Measuring emotional
processes in animals: the utility of a cognitive approach.
Neurosci Biobehav Rev 29:469–491
Prescott MJ, Morton DB, Anderson D, Buckwell A, Heath S,
Hubrecht R, Jennings M, Robb D, Ruane B, Swallow J,
Thompson P (2004) Refining dog husbandry and care.
BVAAWF/FRAME/RSPCA/UFAW joint working group on
refinement. Lab Anim 38(S1):11–24
Quaranta A, Siniscalchi M, Vallortigara G (2007) Asymmetric tail-
wagging response by dogs to different emotive stimuli. Curr Biol
Rehn T, Keeling LJ (2010) Investigating greeting behaviour in dogs
reunited with a familiar person. In: Proceedings of the 44th
congress of the international society for applied ethology,
August 4–7, Uppsala, p 54
Rooney NJ, Bradshaw JWS, Robinson IH (2000) A comparison of
dog–dog and dog-human play behaviour. Appl Anim Behav Sci
Sakaki M, Niki K, Mather M (2012) Beyond arousal and valence: the
importance of the biological versus social relevance of emotional
stimuli. Cogn Affect Behav Neurosci 12:115–139
Spruijt BM, Van den Bos R, Pijlman FTA (2001) A concept of
welfare based on reward evaluating mechanisms in the brain:
anticipatory behaviour as an indicator for the state of reward
systems. Appl Anim Behav Sci 72:145–171
Svartberg K, Forkman B (2002) Personality traits in the domestic dog
(Canis familiaris). Appl Anim Behav Sci 79:133–155
Wemelsfelder F (2007) How animals communicate quality of life: the
qualitative assessment of behaviour. Anim Welf 16(S):25–31
Zebunke M, Langbein J, Manteuffel G, Puppe B (2011) Autonomic
reactions indicating positive affect during acoustic reward
learning in domestic pigs. Anim Behav 81:481–489
Anim Cogn (2014) 17:577–587 587
... For companion animals, who were genetically modified by humans, human environments comprise dogs' natural ecological niche, and dog-owner attachment is functionally analogous to human infantmother attachment [100,101]. Dogs have been observed wagging their tails more when granted access to human contact compared to access to conspecifics [102], prefer petting over food when the petting is provided by their owners in unfamiliar contexts [103], play more with conspecifics when receiving owner attention [104], and can communicate with owners via "showing" behavior [12]. Dogs and humans have a mutualistic relationship, with dogs bred to serve human purposes including hunting, guarding, and herding [105]. ...
... In situations that experimenters assume to be exciting (successful problem-solving results in reward delivery), dogs demonstrated increased tail wagging and overall activity; in situations experimenters assume to be frustrating (reward delivery is unpredictable and independent of a dog's behavior), dogs chewed the operant device available to them [102]. The relationship between consequence and behavior was consistent across reward types, which included food, social contact with a familiar human, and social contact with other dogs. ...
... This highlights an additional way to gauge how a learner is experiencing a contingency in effect in order to promote a positive learning experience. For example, while a learner may ultimately express frustration by mouthing on an object, as was observed by McGowan et al. [102], being aware of and looking for a more subtle change, such as the flattening of ears [194], would allow practitioners to stop and modify the intervention before frustration, and the responses that accompany it, which are not part of the target response, escalate; (3) Practitioners should improve the chance that an intervention is socially valid to the learner by ensuring that interventions (a) stem from educated hypotheses created based on both population and individual data, taking the learner's adaptations, perception, and cognition into account, (b) use functional reinforcers evaluated by functional analysis and/or preference assessments, rather than presumed or contrived reinforcers, (c) program for choice, allowing the learner to choose to participate, (d) provide genuine choice within the intervention by providing the learner the opportunity to perform an alternate, non-target behavior to earn the same reinforcer available for performance of the target behavior, (e) improve the learner's relationship to, or teach additional coping skills that can be used when the learner must come into contact with an unavoidable aversive stimuli that exists, and will exist, in their environment, where appropriate, and (f) program for contact with positive reinforcement, even when positive reinforcement is not used at the outset of an intervention. These recommendations set the occasion for learner-centered interventions and increase the likelihood that welfare is positive, or at least improved, in learning contexts; (4) To ensure that the intervention is having a positive impact on welfare, quality of life metrics that can be repeated across time should be completed before, during, and after the intervention, and affective state should be measured during the intervention using validated metrics, such as body language, HR, and HRV. ...
Full-text available
Social validity refers to the social significance and acceptability of intervention goals, procedures, and outcomes. Animal practitioners, who are often guided by the principles of ABA, lack the benefit of verbal participants (at least with respect to target animals) with which to assess a client's needs and preferences. The study of a learner's welfare is useful for determining areas where intervention is needed or how the learner feels about an intervention that is underway. Three tenets of animal welfare measurement include physiological function, naturalistic behavior, and affect, where affect refers to private events, including emotions, which are a function of the same variables and contingencies responsible for controlling public behavior. The development of new technologies allows us to look "under the skin" and account for subjective experiences that can now be observed objectively. We introduce the reader to tools available from the animal welfare sciences for the objective measurement of social validity from the learner's perspective.
... However, humans are not the only species to have a 'technical brain' (see Healy, 2021 for an examination of technology including tool-use driving the evolution of large brains), or to perform intrinsically motivated work associated with positive affect. We know animals can also be intrinsically motivated to work rather than pursue other activities (reviewed by Meehan & Mench, 2007; also see Clark & Smith, 2013;Langbein et al., 2009), work for food even when free food is concurrently available (contrafreeloading; Osborne, 1977), and experience pleasurable feelings when they are successful or at least progressing towards a goal (Hagen & Broom, 2004;McGowan et al., 2014;Perkins, 2000). Therefore, it seems feasible that the selection pressure/s for Flow could exist in other species. ...
... While cognitive enrichment is an increasingly popular subset of enrichment and already cited in proposals of Flow (Clark, 2017(Clark, , 2022, it has been difficult to disassociate challenge participation from external food reward (Clark et al., 2019;Matrai et al., 2022;Schmelz et al., 2021). Researchers will need to incorporate more intrinsic rewards into cognitive enrichment designs, and investigate how the process of being challenged, not just the final outcome (e.g., Hagen & Broom, 2004;McGowan et al., 2014), impacts welfare. If Flow can be recognized using the aforementioned computerized challenge paradigm (Section 3.2.5), ...
Flow is an altered state of feeling ‘in the zone’ when fully absorbed in a challenge and is associated with positive affective state (feelings). Despite almost five decades of research, Flow has not yet been recognized in non- human animals, despite repeated suggestions from animal researchers it could exist. Recent advancements in behavioral and neurophysiological indicators of experience in humans and animals make it more possible than ever to detect Flow in other species. In this article, I propose a framework for comparative Flow research on humans and great apes. I conserve the original nine-component definition of human Flow developed by Csikszentmihalyi and its three conditional components, but re-structure the six experiential components into three dimensions: Focus, Motivation, and Affect. I evaluate the evidence for each dimension and component in great apes, and how current human Flow methods may translate to great apes. If Flow state exists beyond our species, this has major implications. It would provide insight into the evolution of internally derived happiness and ignite more comparative research in the field of positive psychology. Second, knowledge of Flow or a Flow-like state in other species would inform the design of more effective enrichment and therefore promote higher captive animal welfare. I hope to spark new discussions among human positive psychologists, comparative psychologists, and animal cognition and welfare scientists, so that we may begin to conceptualize and recognize non-human Flow.
... Beyond choice and control, it has also been suggested that providing animals with situations and devices that challenge them cognitively could further improve their welfare [128,129,143,144]. Multiple studies have demonstrated that introducing cognitive challenges can lead to indications of improved welfare such as increases in movement, habitat utilization, and signs of positive excitement, along with decreases in stereotypies and other stress behaviors [145][146][147][148][149][150]. With dolphins, such cognitive challenges might come in a variety of forms, including cognitive research, puzzle devices, computer tasks, or "thinking games" (i.e., training of conceptual rules such as repeat, imitate, and innovate) [91,129,[150][151][152][153][154]. ...
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Numerous studies have demonstrated the negative effects of impoverished environments versus the positive effects of enriched environments on animals’ cognitive and neural functioning. Recently, a hypothesis was raised suggesting that conditions for dolphins in zoological facilities may be inherently impoverished, and thus lead to neural and cognitive deficits. This review directly examines that hypothesis in light of the existing scientific literature relevant to dolphin welfare in zoological facilities. Specifically, it examines how dolphins are housed in modern zoological facilities, where the characteristics of such housing fall on the continuum of impoverished-to-enriched environments, and the extent to which dolphins show behavioral evidence characteristic of living in impoverished environments. The results of this analysis show that contrary to the original hypothesis, modern zoological facilities do not inherently, or even typically, house dolphins in impoverished conditions. However, it also notes that there is variation in animal welfare across different zoological facilities, and that “not impoverished” would be a particularly low bar to set as an animal welfare standard. To optimize cognitive well-being, strategies for providing additional cognitive challenges for dolphins in zoological facilities are suggested.
... The animals wagged their tails more often in sessions in which nice speech was used for longer. This result suggests that friendly interactions between trainer and animal have the potential to improve the emotional conditions of the animals, since tail wagging has already been reported as an expression of a positive emotional disposition (e.g., [30][31][32][33]). The highpitched tone-one of the aspects that characterizes the nice speech-was also characteristic of DDS-type speeches. ...
Full-text available
In a previous study, we found that Positive Reinforcement Training reduced cortisol of wolves and dogs; however, this effect varied across trainer–animal dyads. Here we investigate whether and how the trainers’ use of speech may contribute to this effect. Dogs’ great interest in high-pitched, intense speech (also known as Dog Directed Speech) has already been reported, but whether and how wolves respond similarly/differently to voice characteristics has never been studied before. We analyzed 270 training sessions, conducted by five trainers, with nine mixed-breed dogs and nine wolves, all human-socialized. Through Generalized Linear Mixed Models, we analyzed the effects of (a) three speech categories (nice, neutral, reprehensive) and laugh; and (b) acoustic characteristics of trainers’ voices on animals’ responses (correct responses, latency, orientation, time at less than 1 m, non-training behaviors, tail position/movements, cortisol variation). In both subspecies, tail wagging occurred more often in sessions with longer durations of nice speech, and less often in sessions with reprehensive speech. For dogs, the duration of reprehensive speech within a session was also negatively related to correct responses. For wolves, retreat time was associated with more reprehensive speech, whereas duration of nice speech was positively associated with time spent within one meter from the trainer. In addition, most dog behavioral responses were associated with higher average intonations within sessions, while wolf responses were correlated with lower intonations within sessions. We did not find any effects of the variables considered on cortisol variation. Our study highlights the relevance of voice tone and speech in a training context on animals’ performances and emotional reactions.
... Therefore, care must be taken to ensure that such curious animals are provided with an appropriate environment to seek information. Such opportunities may include problem solving tasks, as the success of completing such tasks itself is shown to be intrinsically rewarding in cattle (Hagen and Broom, 2004) and canines (Mcgowan et al., 2014). For example, physiological indicators of arousal were greater when cattle were rewarded with a food treat after completing a problem solving task compared to simply being provided with the food reward alone (Hagen and Broom, 2004). ...
Range use by free-range laying hen flocks is heterogeneous. We hypothesized that ranging behaviour may be motivated by curiosity and thwarted by fearfulness. This project aimed to increase a hen’s motivation to explore by enriching the rearing environment and identify relationships between exploration, fear and ranging. Day-old Hy-Line chicks (n = 1700) were reared in environments that provided novel items, structures for perching or an industry standard floor rearing environment. Prior to range access, fear and exploratory behaviors were assessed at 18 weeks of age (cohort 1; n = 30 hens/treatment) via novel arena and novel object tests and at 22 weeks of age (cohort 2; n = 30 hens/treatment) using an 8-arm radial maze choice paradigm adapted from previous rodent research. Hens were trained to expect success in two arms (reward) and failure in two arms (mild punishment), the remaining four arms (ambiguous arms) were not available during training. After training, all hens were retested for 8 minutes with access to the four familiar arms only, then for four minutes with access to the ambiguous arms for the first time, in addition to the success and failure arms. Latency to enter the ambiguous arms and the number of ambiguous arms entered were assessed as an indicator of a hen’s willingness to forgo reward and risk punishment to explore a novel area. At 25 weeks of age, hens were provided with range access and individual range access was monitored for three weeks. Latency to access the range and the number of days the range was accessed was not related to rearing treatment (p > 0.05) and was only weakly correlated with behavior during the novel arena, novel object and 8-arm radial maze tests (r < 0.3). However, hens reared in the novelty rearing environment were more willing to forgo reward to explore the ambiguous arms than hens reared in the control environment (p = 0.004). We did not identify strong evidence that exploration or fearfulness was related to early ranging behavior. However, we show that motivation to explore increases when hens are reared in an enriched environment.
... It was only a decade later that Broom (2015) used the term Eureka effect when referring to this study. McGowan et al. (2014) aimed to identify the Eureka moment in dogs trained on a problem-solving task, again using a yoked control experiment. They found behavioural signs of excitement, for example, increased tailwagging, in the experimental dogs that could control their access to rewards but not in control dogs. ...
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The concept of flow, a state of complete absorption in an intrinsically rewarding activity, has played a pivotal role in advancing notions of human well‐being beyond minimising suffering towards promoting flourishing and thriving. While flow has played a fundamental role in human positive psychology, it has not yet been explored in non‐human animals, leaving an enormous void in our understanding of intrinsic motivation in animals. As ethology and related fields keep progressing in uncovering complex cognitive and affective capacities of non‐human animals, we propose the time is ripe to translate the concept of flow to animals. We start by embedding flow in the topic of intrinsic motivation and describe its impact on positive human psychology and potentially positive animal welfare. We then disambiguate flow from related concepts discussed in the animal literature. Next, we derive experimental approaches in animals from the canonical characteristics of flow in humans and provide guidelines for both inducing and assessing flow by focusing on two characteristics that do not necessarily depend on self‐report, namely resistance to distraction and time distortion. Not all aspects of the human flow experience are (yet) translatable, but those that are may improve quality of life in captive non‐human animals.
... Importantly, when dogs are deployed in the field and the disease of interest has a low prevalence, reducing the opportunity for the animals to succeed in detection, positive affective and motivational states of dogs have to be sustained in order to avoid frustration (68). This can be achieved, for example, through regular rewards for the respective detection procedure or for detecting specifically prepared (positive) samples (69)(70)(71). ...
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The respiratory coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) quickly developed into a pandemic (1). Even though laboratory diagnostic tests and vaccines were consequently developed (2, 3), the exploration of rapidly deployable, more reliable tools for addressing the current and future pandemics was vital. Toward this goal, researchers worldwide evaluated the use of medical detection dogs as a rapid, reliable and cost-effective screening method for SARS-CoV-2 infections (4). The ability of dogs to distinguish diseases by their high-resolution sense of smell is based on the volatile organic compound (VOC)-hypothesis (5). Numerous infectious and non-infectious diseases change metabolic processes releasing characteristic VOC-patterns in the form of an “olfactory fingerprint” (6–10). Many studies have shown that dogs can detect metabolic disorders, such as cancer (11) and hypoglycemia (12), predict epileptic seizures (13, 14), or even distinguish various pathogens (8, 15–17). Approximately 78% of the 27 SARS-CoV-2-canine detection studies reviewed by Meller et al. yielded > 80% sensitivity and approximately 60% of studies yielded > 95% of specificity (4), highlighting the potential of the dog as a “diagnostic system” and its recommendation for certain settings. Despite these promising results, all studies published up to now differed in numerous design features. They were mostly designed as pilot studies and case-control selection of patients was mostly favored over a more preferable cross-sectional (“cohort”) selection [study quality assessment was conducted and presented by Meller et al. (4)]. The aim of this comprehensive review summary is to provide a general overview of the divergent aspects that may impact canine disease detection and to provide recommendations for future deployment of medical detection dogs (see also summary in Table 1). Specific emphasis is placed on the choice of dogs, training paradigms, safety aspects, sample characteristics, pre-screen processing (e.g., inactivation), and screening-population and its environment related aspects, respectively (see also Figure 1 and Supplementary Figure 1), providing an outlook and proposals for the future standardization in the use of dogs for disease detection. Ultimately, this report provides a blueprint for the potential use of medical detection dogs in future epidemics and pandemics.
... However, reindeer do generally not perform affiliative social behaviours such as mutual grooming, contrary to other deer species (red deer (Cervus elaphus): Liehrmann et al., 2018;Albery et al., 2022;Roe deer (Capreolus capreolus): Brucks et al., 2022). Therefore, during the taming process, herders cannot rely on positive physical interaction such as scratching (used in dogs training as a reward, McGowan et al., 2014), but only use food rewards. For this reason, the working reindeer is an interesting species for investigating the human-animal relationship. ...
Veterinary care that incorporates a proactive, practical approach to reducing fear and stress (often referred to as stress-reducing or low-stress veterinary care) in companion animals in the veterinary context is becoming increasingly prevalent. However, the attitude of veterinary professionals toward these techniques is not well understood. This mixed-methods study utilized an online survey to provide an initial benchmark of the certifications for stress-reducing veterinary care within the Australian veterinary industry and to gauge the attitude and experience of veterinary professionals (n = 291, 91% female) toward reducing stress during veterinary care for domestic dogs. One in five (n = 56) participants reported having a stress-reducing veterinary care certification (e.g., Fear-FreeTM Veterinary Professional, or similar). Respondents generally held a positive attitude toward stress-reducing veterinary care. Factors that predicted a positive attitude toward stress-reducing veterinary care included attitudes to animals (F = 7.83, p = 0.006) and whether the participant held a certification in stress-reducing veterinary care (F = 4.73, p = 0.031). Professionals with a certification reported higher frequency of use of stress-reducing techniques in general (p = 0.005) and of specific techniques (p = 0.001) in comparison with those without a certification. Commonly reported strategies included handling and interactions, training and distractions, environment, patient management, pharmaceutical interventions, and preventative strategies. Reported barriers to implementation centered on themes of workplace and practice management, colleagues, clients, clinic environment, work-specific conflict, personal abilities, and patients. While stress-reducing veterinary care is important to veterinary professionals, implementing strategies to improve patient welfare as part of routine practice likely still requires significant changes in workplace and industry culture.
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An estimated 140 000 dogs are used worldwide in research and testing every year. Although there is a growing trend of providing more complex environments for laboratory dogs, worldwide much dog husbandry and care fails to incorporate what is known about their natural behaviour and their behavioural and welfare needs. With this in mind, the BVAAWF/FRAME/ RSPCA/UFAW Joint Working Group on Refinement set out to identify and document ways in which dog husbandry and care can be refined to make significant reductions in suffering and improvements in animal welfare. The Working Group's report contains recommendations on housing and on physical environment, food and feeding, environmental enrichment and exercise, health and hygiene, identification and record keeping, breeding, balancing supply and demand, grouping, transport, handling and restraint, procedures, long-term use, rehoming, staff training, and areas for future research for refining dog husbandry and care. Advice is also given on interpreting dog signals, preventing and managing aggression, and controlling noise in dog facilities. Particular emphasis is placed on providing an enriched environment for dogs which permits them to express a wide range of normal behaviour and to exercise a degree of choice, and on combining this with a socialization, habituation and training programme. Together these measures should significantly reduce and/or eliminate fear-related behavioural responses and stereotypic behaviours. They will also have a positive effect on the behavioural development of the dogs, helping to ensure that calm, confident, and well-adjusted individuals are issued to the end-use areas. This in turn will assist in the collection of reliable and accurate experimental data from dog studies and will avoid unnecessary wastage of life. The report represents a valuable resource for staff training. It should be read and thought about, and the recommendations acted upon, by all those involved with the management, care and use of dogs bred and used for research and testing. Where standards fall below those detailed here, a programme of improvement should be put in place. This should aim to achieve a proper balance between conspecific and human social interaction for dogs, and provide pens and other environments developed with an understanding of the natural behaviours of the dog, and empathetic personnel trained and competent to care for them. Employing a canine behaviour specialist can help to achieve these aims. It may be necessary for managers of facilities to rethink the way that dog husbandry and care has been practised in the past in order to allocate the time, staffing and funding required to implement the programme. Only through sincere commitment, adequate resources and sufficient will to change can significant reductions in suffering and improvements in animal welfare be guaranteed.
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Observation of behaviour, especially social behaviour, and experimental studies of learning and brain function give us information about the complexity of concepts that animals have. In order to learn to obtain a resource or carry out an action, domestic animals may: relate stimuli such as human words to the reward, perform sequences of actions including navigation or detours, discriminate amongst other individuals, copy the actions of other individuals, distinguish between individuals who do or do not have information, or communicate so as to cause humans or other animals to carry out actions. Some parrots, that are accustomed to humans but not domesticated, can use words to have specific meanings. In some cases, stimuli, individuals or actions are remembered for days, weeks or years. Events likely to occur in the future may be predicted and changes over time taken into account. Scientific evidence for the needs of animals depends, in part, on studies assessing motivational strength whose methodology depends on the cognitive ability of the animals.
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It has been suggested that during instrumental learning, animals are likely to react emotionally to the reinforcer. They may in addition react emotionally to their own achievements. These reactions are of interest with regard to the animals’ capacity for self-awareness. Therefore, we devised a yoked control experiment involving the acquisition of an operant task. We aimed to identify the emotional reactions of young cattle to their own learning and to separate these from reactions to a food reward. Twelve Holstein–Friesian heifers aged 7–12 months were divided into two groups. Heifers in the experimental group were conditioned over a 14-day period to press a panel in order to open a gate for access to a food reward. For heifers in the control group, the gate opened after a delay equal to their matched partner’s latency to open it. To allow for observation of the heifers’ movements during locomotion after the gate had opened, there was a 15m distance in the form of a race from the gate to the food trough. The heart rate of the heifers, and their behaviour when moving along the race towards the food reward were measured. When experimental heifers made clear improvements in learning, they were more likely than on other occasions to have higher heart rates and tended to move more vigorously along the race in comparison with their controls. This experiment found some, albeit inconclusive, indication that cattle may react emotionally to their own learning improvement.
In the popular literature, it is often assumed that a single conceptual framework can be applied to both dog–dog and dog–human interactions, including play. We have, through three studies, tested the hypothesis that dog–dog and dog–human play are motivationally distinct. In an observational study of dogs being walked by their owners (N=402), dogs which were walked together, and had opportunities to play with one another, played with their owners with the same frequency as dogs being walked alone. This finding was supported by a questionnaire survey of 2585 dog owners in which dogs in multi-dog households played slightly more often with their owners than dogs in single-dog households. The performance of dog–dog play does not, therefore, seem to suppress the dogs' motivation to play with their owners as would be predicted if they were motivationally interchangeable. In an experimental comparison of dog–dog and dog–human toy-centred play, the dogs were more likely to give up on a competition, to show and present the toy to their play partner, if that partner was human. When two toys were available, dogs playing with other dogs spent less time showing interest in both toys and possessed one of the toys for longer, than dogs playing with people. Overall, the dogs were more interactive and less likely to possess the object when playing with a person. We conclude that dog–dog and dog–human play are structurally different, supporting the idea that they are motivationally distinct. We therefore suggest there is no reason to assume that the consequences of dog–dog play can be extrapolated to play with humans.
Interest in the induction and measurement of positive affective states in non-human animals is increasing. Here, we used a test of cognitive (judgement) bias, based on the finding that individuals experiencing different affective states judge ambiguous stimuli differently, to measure whether a positive low arousal affective state (e.g. ‘satisfaction’/‘contentment’) could be induced in domestic dogs as a result of their experiencing a food-based rewarding event. In this rewarding event, subjects (1year old female Beagles) had to search for small amounts of food randomly placed within a maze arena. Using a balanced within-subjects design, the dogs (N=12) received a cognitive bias test either without experiencing the rewarding event (the ‘Neutral’ treatment), or directly after experiencing the rewarding event (the ‘Post-consumption’ treatment). In the test, dogs were trained that one visual cue (e.g. dark grey card) predicted a positive event (food in a bowl) whilst a different cue (e.g. light grey card) predicted a relatively ‘negative’ event (empty bowl). We hypothesised that dogs tested after experiencing the rewarding event, and in a presumed post-consummatory positive affective state, would be more likely to judge visually ambiguous stimuli (intermediate grey cards) positively, compared to dogs in the ‘Neutral’ treatment. In contrast, we found that they took significantly longer to approach an intermediate ambiguous stimulus, suggesting that they were less likely to anticipate food (a negative judgement) compared to dogs in the ‘Neutral’ treatment group. Various explanations for the observed results are discussed, in particular how reward acquisition and consumption may influence positive affective state induction in animals.
The occurrence of stress has widely been associated with impairments in learning abilities in animals, although the influence of stress appears to differ with the complexity of tasks. Previous research has suggested that some domestic dogs exhibit both physiological (elevated cortisol) and behavioural signs of stress when newly admitted to re-homing centres. In this study we have investigated whether levels of stress as measured by urinary cortisol: creatinine is sufficient to impair the learning of simple associations. On the day following their admission to a re-homing centre, 32 dogs were trained on one classical conditioning task and one operant conditioning task; 6 days later, they were trained on a second operant conditioning task. Their mean urinary cortisol:creatinine ratio (C/C) fell from 27.1×10−6 to 22.3×10−6 (nmol/l:nmol/l) between these 2 days; a substantial proportion (78% on day 1, 63% on day 7) of dogs had ratios above the range of 5–20×10−6, which is that defined as clinically normal (Bush, 1991), suggesting high levels of stress. The dogs’ average time to reach criterion on either task on day 1 was unrelated to C/C or to behavioural signs of stress; this lack of correspondence may reflect the diverse previous experiences of the dogs. On day 7, the six dogs which failed to reach criterion for the operant association were significantly less active and interactive in their kennels than the others. For the remainder, a high rate of learning the operant association was associated with high C/C (in excess of 40×10−6), and a poor performance was associated with fearful behaviour in the kennel. Dogs appear to have adopted one of two coping strategies: either the display of fearful behaviours and an impaired ability to learn the tasks, which may reflect a ‘reactive’ style of responding, or a higher level of HPA axis activation and an enhanced ability to rapidly learn a new task, which may be indicative of a more ‘proactive’ coping style.
Cognitive mechanisms are an important part of the organization of the behavior systems of animals. In the wild, animals regularly face problems that they must overcome in order to survive and thrive. Solving such problems often requires animals to process, store, retrieve, and act upon information from the environment—in other words, to use their cognitive skills. For example, animals may have to use navigational, tool-making or cooperative social skills in order to procure their food. However, many enrichment programs for captive animals do not include the integration of these types of cognitive challenges. Thus, foraging enrichments typically are designed to facilitate the physical expression of feeding behaviors such as food-searching and food consumption, but not to facilitate complex problem solving behaviors related to food acquisition. Challenging animals by presenting them with problems is almost certainly a source of frustration and stress. However, we suggest here that this is an important, and even necessary, feature of an enrichment program, as long as animals also possess the skills and resources to effectively solve the problems with which they are presented. We discuss this with reference to theories about the emotional consequences of coping with challenge, the association between lack of challenge and the development of abnormal behavior, and the benefits of stress (arousal) in facilitating learning and memory of relevant skills. Much remains to be done to provide empirical support for these theories. However, they do point the way to a practical approach to improving animal welfare—to design enrichments to facilitate the cognitive mechanisms which underlie the performance of complex behaviors that cannot be performed due to the restrictions inherent to the captive environment.