Physiology & Behavior (2009) Volume 98: 345-350
10.1016/j.physbeh.2009.06.012
Final Revision – NOT EDITED by the journal
Anxiety-induced cognitive bias in non-human animals
OLIVER H. P. BURMAN, RICHARD M. A. PARKER, ELIZABETH S. PAUL,
MICHAEL .T. MENDL
University of Bristol, Bristol, BS40 5DU, U.K.
Corresponding author: Oliver H. P. Burman
Word count: 5019
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OLIVER H. P. BURMAN, RICHARD M. A. PARKER, ELIZABETH S. PAUL,
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MICHAEL .T. MENDL. Anxiety-induced cognitive bias in non-human animals.
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PHYSIOL BEHAV. - As in humans, ‘cognitive biases’ in the way in which
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animals judge ambiguous stimuli may be influenced by emotional state and
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hence a valuable new indicator of animal emotion. There is increasing evidence
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that animals experiencing different emotional states following exposure to long-
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term environmental manipulations show contrasting biases in their judgement of
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ambiguous stimuli. However, the specific type of induced emotional state is
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usually unknown. We investigated whether a short-term manipulation of
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emotional state has a similar effect on cognitive bias, using changes in light
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intensity; a treatment specifically related to anxiety induction. Twenty-four male
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rats were trained to discriminate between two different locations, in either high
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(‘H’) or low (‘L’) light levels. One location was rewarded with palatable food
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and the other with aversive food. Once the rats had shown spatial discrimination,
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by running significantly faster to the rewarded location, they were tested with
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three ambiguous locations intermediate between the rewarded and aversive
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locations, and their latency to approach each location recorded. Half the rats were
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tested in the same light levels as during training, the remainder were switched.
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Rats switched from high to low light levels (putatively the least negative
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emotional manipulation) ran significantly faster to all three ambiguous probes
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than those rats switched from low to high light levels (putatively the most
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negative manipulation). This suggests that the judgement bias technique might be
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useful as an indicator of short-term changes in anxiety for non-human animals.
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Keywords: Emotion; Cognition; Anxiety; Cognitive Bias; Emotional state;
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Behaviour; Animal Welfare
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Introduction
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Humans experiencing different background emotional states display contrasting
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cognitive-affective biases (henceforth referred to as ‘cognitive bias’) in their
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judgement of ambiguous stimuli. For example, people in a negative state tend to
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make negative judgements about ambiguous situations or stimuli [e.g. 1,2,3].
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Since Harding et al. [4] first demonstrated a novel technique to determine the
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emotional state of non-human animals by measuring changes in judgement bias,
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there has been considerable interest in the further development and validation of
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this technique [e.g. 5,6-9]. Compared to many existing behavioural and
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physiological measures of non-human emotional state, one potential advantage of
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a cognitive bias approach is the ability to discriminate between similarly-
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valenced emotional states such as depression and anxiety [3]. However, this
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potential benefit has yet to be demonstrated.
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Previous studies have manipulated emotional state by using unpredictable
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housing events, each designed to be mildly stressful [rats: 4], or the
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absence/removal of enrichment [starlings: 5,6, rats: 7,8]. However, these
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affective (emotional) manipulations have been relatively long-term/chronic in
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duration (e.g. enrichment absence: 21 days [8]; 7 days [5]; unpredictable
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housing: 9 days [4]), and have induced negative emotional states that, whilst of
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unknown specificity, are perhaps more likely to be related to states of depression
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rather than anxiety (e.g. unpredictable housing: [10]; enrichment
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absence/removal: depression and the experience of loss in humans, [11]). It is
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therefore of considerable interest to investigate whether cognitive bias tasks in
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non-human animals can be influenced by acute anxiety-related emotions as well
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as the more chronic depression-like mood states studied previously, as has been
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demonstrated in humans [e.g. 12].
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The current study addresses this issue by employing a treatment designed to
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induce an acute/short-term change in anxiety. This treatment involves varying
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the level of ambient light, since higher light levels are considered increasingly
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anxiety inducing for a nocturnal species such as the laboratory rat [e.g. 13,14,15];
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presumably as an evolved response to increased threat of predation. For example,
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the acoustic startle reflex in rats is potentiated by exposure to high light levels
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[16] whereas in humans it is potentiated by exposure to darkness [17]. Light
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levels can therefore be manipulated in order to generate different levels of
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anxiety, as evidenced by the use of different light levels during anxiety testing
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[e.g. 18] depending on whether anxiogenic or anxiolytic treatment effects are to
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be studied. There is also evidence that a change/switch in light levels can itself
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influence emotional state, for example, sudden darkness can result in clear
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anxiolytic effects on rodent behaviour [e.g. 19,20,21]. For this reason, we
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decided to investigate the effect of both constant and changing light levels on
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cognitive bias in this study. Light intensity satisfies the requirement for an
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appropriate affective (emotional) manipulation, namely that there is a previously
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demonstrated effectiveness for inducing a change in emotional state (specifically
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anxiety), therefore allowing the construction of clear predictions concerning the
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potential impact of our treatment on cognitive bias.
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The aim of this study was therefore to test the prediction that rats exposed to high
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light levels will judge ambiguous stimuli negatively in comparison to those rats
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exposed to low light levels, due to being in a putative negative emotional state
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(anxiety). Furthermore, we predicted that rats tested in high light levels following
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previous experience of the apparatus under low light conditions would be most
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anxious and those tested under low light levels after experiencing high light
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conditions would be least anxious, and hence these two groups of rats would
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show the strongest contrast in their judgements of ambiguous stimuli.
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In addition to choosing the appropriate treatment necessary to induce the desired
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emotional state, it is also important to select an appropriate reward contingency
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for the cognitive bias task that is being used as a proxy indicator of that
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emotional state. It has been proposed that depression, being related to the
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experience of loss [11], may be more commonly associated with a decreased
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expectation of positive events, whereas anxiety, being threat-related [11], may be
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more commonly associated with an increased expectation of negative events
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[22]. In a previous study [8], we used both a treatment (loss of enrichment) most
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likely to induce a depression-like state, and a reward contingency
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(presence/absence of a reward) most likely to be sensitive to cognitive biases
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associated with that state. In contrast, in this study we employ a treatment
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designed to induce a change in anxiety (light levels), and a reward contingency
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designed to be most sensitive to cognitive biases likely to be associated with that
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state, namely the presence/absence of a negative event (the perceived ‘threat’ of
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ingesting an aversive food).
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Materials and Methods
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Subjects
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This work was carried out under UK Home Office licence (PPL 30/2249). We
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used twenty four male Lister-hooded rats (Harlan, UK), approximately nine
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months old at the start of testing. The rats had previously been used (at least three
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months previously) in studies of incentive contrast and cognitive bias [7,8], and
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so individuals were randomly allocated between the different treatments in the
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current study in order to minimize any potential influence of previous
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experience. The rats were housed in groups of three in standard cages (33cm X
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50cm X 21cm) on a 12hr reversed light cycle, lights off 0800-2000, with food
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(Harlan Teklad Laboratory Diet) and water available ad libitum. The housing
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room was lit with a 60W (380 lumen) red light bulb allowing researcher
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visibility. Rats could be individually identified by natural variation in their coat
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markings. All the cages were provided with identical enrichment items (e.g.
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nesting material, shelter).
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Apparatus
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In a different room to that in which the rats were housed, we positioned an eight
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arm radial maze (arm length 70cm, arm width 10cm, hub diameter & height
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30cm, Panlab) made of black Perspex with manually operated guillotine doors
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leading from the decision area to each arm. The whole maze was raised 100cm
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above the ground. Only one side of the maze was used (5 arms; see Figure One).
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For the other side of the maze, the three unused arms had their doors
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permanently closed, and a piece of white card (width 10cm, height 30cm) was
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placed in front of the central unused arm (see Figure One) to provide a visual
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landmark within the central maze hub. There were recessed goal pots (width
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4cm, depth 3cm) located 6cm from the end of each arm; these could be removed
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and cleaned between trials.
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Figure One
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In each trial, one goal pot was placed at the end of one of the five different maze
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arms. The two ‘reference’ arms (rewarded or ‘aversive’) were positioned at 180˚
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from each other. The three ambiguous ‘probe’ arms were positioned at
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equidistant angles between the two reference locations, each separated by 45˚,
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such that one probe arm was located midway between the two reference locations
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(90˚), and the other two probe arms halfway between the central probe arm and
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each reference arm (45˚ & 135˚; see Figure One). To let the rats into the arms
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from the maze hub, guillotine doors located at the entrance to each arm were
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opened/closed manually using a pulley system operated from behind a screen so
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that the researcher was not visible to the subjects during training/testing. Also
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behind the screen were a video and monitor linked to an overhead video camera
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allowing the subjects to be recorded and their behaviour observed remotely.
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The apparatus was based on that used in a previous judgement bias task [8] with
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a few modifications. Firstly, the distance from the start box to the goal pot was
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shorter (70cm vs. 80cm). Secondly, because the arms were enclosed, the subject
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only had the option to move to the goal pot or not, and was not able to investigate
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other locations. Thirdly, the angle between the locations was 45˚ rather than 15˚.
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Finally, the location of the door to each arm acted as the cue for the subject to
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approach the goal pot or not, whereas in the previous study it was the location of
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the goal pot. All of these changes were made in an attempt to decrease the time
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taken for the rats to learn the task, thus shortening the duration of the whole
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cognitive bias test.
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Treatments
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For this study we manipulated the level of illumination of the test apparatus to
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induce a change in emotional state (see Introduction). We illuminated the test
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apparatus by suspending a light bulb 1m above the centre of the maze. A 60W
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bulb was used to produce higher (white) light levels (700 lumen, 100lux (centre
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of maze), 65lux (end of arms)), designed to induce a state of relatively moderate
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anxiety, whilst a 10W bulb was used to produce lower (white) light levels (50
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lumen, 15lux (centre of maze), 10lux (end of arms)), designed to induce a state
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of relatively low anxiety [e.g. 14,16,23].
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Half of the rats in this study (n=12) were exposed to high light conditions during
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training, with half of these (i.e. n=6) exposed again to high light conditions
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during testing (‘HH’), whilst the remainder were switched to low light conditions
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during testing (‘HL’). The other 12 rats were exposed to low light conditions
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during training, and then either continued to be exposed to low light during
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testing (‘LL’; n=6) or were switched to high light conditions during testing
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(‘LH’). The inclusion of both HL and LH treatments was important to test for the
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contrasting predictions proposed by a light-induced change in emotional state
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(namely that LH rats should be more anxious than HL rats) and that of a non-
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emotional learning/context-based explanation, that would predict that any change
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in light conditions (in either direction) would result in a similar performance
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decrement [e.g. 24,25].
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Rats were habituated to the apparatus, then trained and tested in two replicates
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separated by a two day interval. We randomly allocated rats to the different
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treatments, and they were counter-balanced between replicates and in the order
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of testing.
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Procedure
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Habituation
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Before habituation to the radial arm maze, we gave the rats prior exposure to the
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food used as a reward in the task (Dustless Precision Pellets, 45mg, Bio-Serv),
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placing nine pellets in each cage of three rats for three consecutive days. Rats
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were then habituated to the apparatus on three occasions in order to ensure
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familiarity with the test conditions, with obtaining food in the apparatus, with
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being enclosed in the maze hub, and with all five maze arms (so that the ‘probe’
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arms were not novel at testing). For each habituation session we placed
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individual rats into the central maze hub with all the arm doors closed, and with
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10 randomly scattered food pellets, for two minutes, and then opened the doors
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of all five maze arms for a further three minutes. No food pellets were placed in
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any of the maze arms to avoid associations between particular arms and the
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presence of food being formed before training/testing commenced. We recorded
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the number of pellets eaten (max. 10), the number of faecal boli produced (used
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elsewhere as a measure of stress/anxiety (e.g. Ferre et al., 1995)) and the number
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of arms visited (defined as a rat reaching the end of the arm).
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Training
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After habituation, we started training the rats. In each training trial only one goal
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pot was present, either in the rewarded maze arm (containing four pellets) or in
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the ‘aversive’ arm (containing one quinine-soaked pellet). We soaked the pellets
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in quinine by briefly placing them into a 2% quinine sulphate (SIGMA) solution
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before allowing them to dry overnight. The position of the rewarded and
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‘aversive’ arms was balanced between individuals and treatments. During
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training, subjects received 12 trials per day, half rewarded and half ‘aversive’.
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The training schedules/sequences for each day were as follows. Day One: in
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order to make it easier for the rats to learn the discrimination, for trials 1-8 the
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goal pot was in the same location for two consecutive trials and was then placed
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in the opposite location for the next two trials, always starting off with the
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rewarded location for the first two trials (i.e. ++--++--). For trials 9-12, the goal
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pot changed location with each trial. Day Two: we used a pseudo-random
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sequence with no more than two consecutive presentations of the goal pot in the
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same location, and equal numbers of both locations in trials 1-6 and trials 7-12
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(e.g. ++--+-+-++--).
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Before each trial all maze arms were cleaned with 70% alcohol. The goal pot was
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also cleaned before being placed at the end of the appropriate arm, and contained
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either four pellets or one quinine-soaked pellet according to the training/testing
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schedule. Each rat was removed from its home cage in the housing room before
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being transported to the test room in a clean cage. The rat was then placed into
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the central maze hub for the 2min inter-trial interval (ITI), initially positioned
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facing the intra-maze cue (the white card). Once the 2min ITI had elapsed, the
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appropriate guillotine door (i.e. either the door of the rewarded or aversive arm)
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was opened and the rat was able to enter that maze arm. We then recorded the
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time taken for the nose of the rat to become level with the goal pot (because at
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that point it could see the difference between one pellet (aversive) and four
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pellets).
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Once the rat had reached the goal pot, it was allowed a few seconds to eat the
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reward if it chose, before being returned to the start box for the 2min ITI during
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which time the maze was cleaned and prepared for the next trial. The first trial of
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the first training day was open-ended and continued until the rat had eaten the
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food pellets. For the rest of the trials there was a cut-off point of 2mins, and if the
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rat failed to reach the goal pot in this time, it was returned to the start box for the
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2min ITI and the arena prepared for the next trial as normal. Trials in which rats
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failed to reach the goal pot within the 2min cut-off were not repeated. Once the
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rat had completed all 12 trials it was transported back to the housing room and
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returned to its home cage. The central maze hub, as well as the floor and walls of
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each of the maze arms, were then cleaned before the next rat was collected.
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Testing
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Once the rats had successfully discriminated between the reference maze arms,
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as determined by showing a significant difference in their latency to approach the
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rewarded and ‘aversive’ goal pots, they were tested for three days during which
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subjects were exposed to each of the three ambiguous maze arms once per day,
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interspersed within a sequence of exposures to the rewarded and ‘aversive’
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reference maze arms. The testing schedule consisted of 13 trials in total, with
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five rewarded trials, five ‘aversive’ trials, and the three ambiguous locations (one
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trial each). The three ambiguous trials were positioned at trial 5, trial 9 and trial
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13, and the order in which they were presented was counterbalanced over the
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three test days. The overall sequence consisted of alternated single rewarded and
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‘aversive’ trials, starting either with a rewarded trial or an ‘aversive’ trial,
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counterbalanced between treatments. This testing schedule/sequence was
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designed so that there were equal numbers of ambiguous trials preceded by
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rewarded trials as there were preceded by ‘aversive’ trials, and that this was the
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same for all treatments.
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The goal pots at the end of the ambiguous maze arms contained no food pellets,
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and so we only carried out three trials for each of the ambiguous maze arms in
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order to minimise the opportunity for associations to develop. Latency to reach
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the goal pot was recorded in all ambiguous trials.
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Data analysis
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Unless specifically mentioned in the text, all data met the requirements for
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parametric tests (e.g. normality, homogeneity of variance etc.,) either in an
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untransformed or transformed state. The statistics package used was SPSS
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version 14. This study was carried out in two replicates separated by a two day
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interval, with treatment groups equally balanced across the replicates. The
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training data were analysed separately for both replicates, since this analysis was
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conducted during training to determine when the rats were ready for testing.
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Testing, however, was analysed with both replicates combined. For training, the
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data for high and low level lighting were compared separately (i.e. as Treatments
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H or L) because at this point the rats had only experienced either high or low
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light levels. However, for testing, Treatment was modelled with four levels (i.e.
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as Treatments HH, HL, LH, LL) so that the results incorporated the complete
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experience of each rat, in terms of the light levels to which they had been
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exposed, taken together over the course of both training and testing.
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Results
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Habituation
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Only during the first habituation trial were enough faeces produced to be able to
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carry out a statistical analysis. Using a one-way ANOVA, we found that there
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was no difference between the treatments (high vs. low light level) in the number
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of faecal boli produced during this first habituation trial (F3, 20=0.237, P>0.1). All
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the rats ate all of the food pellets in each of the three habituation trials. The rats,
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regardless of treatment, showed an increase over the three habituation trials in
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the number of visits made to the maze arms (F2, 40=3.566, P=0.038), with post-
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hoc tests indicating that significantly more visits to maze arms were made in the
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third trial than in the previous two. There were no significant differences
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between treatments nor a significant interaction between treatment and trial
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(P>0.1) for maze arm visits.
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Training
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For the training analysis we calculated the average latency to access the goal pot
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on the six rewarded trials and on the six ‘aversive’ trials for each rat/day, with
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the exception of the first day of training in which the open-ended first trial (to the
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rewarded location) and the first trial to the ‘aversive’ location were both
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excluded. This was because for both these trials the reward outcome was
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unknown to the subjects as it was their first experience of either location. One rat
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from the HL treatment (in the second replicate) was removed from the
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experiment because it failed to eat from the rewarded location following
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exposure to the ‘aversive’ food. We continued to train the rats until they showed
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a clear difference in their average latency to reach the rewarded and ‘aversive’
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locations, and for both replicates this was clearly observed after the second day
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of training (see Figure Two). We used a repeated measures General Linear
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Model (GLM) with Treatment (high light level vs. low light level) as a between
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subject factor, and Location (rewarded vs. ‘aversive’) and Day (1&2) as within
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subjects factors. For both replicates (analysed separately) we observed a
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significant Day*Location interaction (Replicate One: F1, 10=7.48, P=0.021;
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Replicate Two: F1, 9=9.48, P=0.013), but no significant differences in the time
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taken to reach the goal pot between the treatments, either as a main effect or
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interaction (P>0.1).
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Post-hoc analysis of the Day*Location interactions revealed an increasing
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difference in the latency to approach the two locations over time, predominantly
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due to the increased speed in running to the rewarded location over the two days,
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and with more variation in the latency to approach the aversive location (paired t-
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tests: Replicate One: D1 rewarded vs. D1 ‘aversive’ t11=-2.56, P=0.026; D2
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rewarded vs. D2 ‘aversive’ t11=-4.67, P=0.001; D1 rewarded vs. D2 rewarded
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t11=5.46, P<0.001; D1 ‘aversive’ vs. D2 ‘aversive’ t11=0.11, P>0.1; Replicate
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Two: D1 rewarded vs. D1 ‘aversive’ t10=0.64, P>0.1; D2 rewarded vs. D2
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‘aversive’ t10=-2.38, P=0.038; D1 rewarded vs. D2 rewarded t10=5.89, P<0.001;
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D1 ‘aversive’ vs. D2 ‘aversive’ t10=0.51, P>0.1). Testing was therefore
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implemented after the second day of training.
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Figure Two
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Testing
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Testing was carried out over three days for each rat, with five rewarded trials,
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five ‘aversive’ trials, and one trial for each of the three ‘probe’ locations per day.
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For each rat, we calculated the average latency for the 15 rewarded trials, the
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average latency for the 15 ‘aversive’ trials, and the average latency over the three
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trials for each of the three different ‘probe’ locations (see Figure Three). Probe
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and reference locations were analysed separately because of the difference
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between them in the number of trials used to calculate the means.
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Figure Three
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We used a repeated measures GLM to compare the latency to approach the two
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‘reference’ locations (rewarded and ‘aversive’) to determine whether the subjects
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still accurately discriminated between the locations during testing, and whether
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or not there was any treatment effect. Data were log-transformed, and we
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included Treatment (HH, HL, LH, LL, between subjects) and Location (rewarded
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vs. ‘aversive’, within subjects) as factors. As expected, we found a highly
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significant effect of location (F1, 19=63.32, P<0.001), with subjects taking
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significantly longer to approach the ‘aversive’ location than the rewarded
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location. There was no overall effect of Treatment nor any interactions (P>0.1).
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Our next analysis was to determine whether or not the animals responded
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differently to the probe locations during testing, and whether this response
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differed between the four treatments. In order to take into account individual
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differences in performance (i.e. the latency to approach the reference locations),
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we calculated the average value between the time taken to reach the rewarded
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and aversive locations during testing for each rat, and included this as a covariate
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in the analysis [e.g. 8]. We found a significant Treatment effect (F3,18=3.228,
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P=0.047), indicating that there was a difference between the treatments in the
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latency to approach the probe locations. This did not depend on the specific
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probe location (Probe*Treatment interaction (F6,36=0.357, P=0.901)), and there
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was no main effect of Probe location (repeated measures GLM: F2,36=0.48,
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P=0.623). Post-hoc pairwise investigation of the overall Treatment effect using
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Bonferroni adjustment revealed that rats in the HL treatment ran significantly
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faster to the probe locations (P=0.043) than rats in the LH treatment (see Figure
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Four). There were no further significant differences between the treatments
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(P>0.1).
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Figure Four
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Discussion
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Habituation
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The rats quickly habituated to the experimental apparatus, as demonstrated by
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their increased investigation of the maze arms over time. The fact that all the
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food pellets were eaten in each of the habituation trials, together with the low
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levels of defaecation, suggests that the apparatus did not induce high levels of
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anxiety during this habituation period. The lack of a treatment difference (high
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light level vs. low light level) at this stage suggests that this initial contrast in
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light levels did not affect the behaviours measured during habituation.
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Training
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The results demonstrated that after two days, the rats were able to discriminate
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between the rewarded and ‘aversive’ locations based on the time taken to
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approach the goal pot, with an increasing difference across training days as a
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consequence of the rats speeding up their approach to the rewarded location. This
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confirms the findings of a previous study in which we used location as the basis
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for a spatial judgement task [8]. In the current study, our new technique reduced
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the time required to learn the discrimination (from six to two days). As
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mentioned earlier (see ‘Apparatus’), the design of the current study differed in a
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number of aspects to our previous study [8]. For example, in Burman et al., [8]
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the stimuli were either rewarded or unrewarded, whereas in the current study we
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used rewarded versus ‘aversive’ stimuli. These modifications appeared to be
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reflected in faster learning speeds. The difference in reward contingency may
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also explain differences in the ‘pattern’ of discrimination learning between the
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two experiments. In Burman et al., [8] the rats initially ran quickly to both
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locations, before slowing their approach to the unrewarded location (a gradual
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recognition of the absence of a food reward), whereas in the current study the
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rats showed an initially slow approach to both locations before increasing their
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approach to the ‘rewarded’ location (a gradual recognition of the presence of a
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non-aversive food reward).
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There was no difference in training performance between the two
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treatments (high light level vs. low light level) suggesting that there was no
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difference in either the level of food motivation, learning ability or general
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locomotor activity as a consequence of being exposed to the different light
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levels. Any differences between the treatments during testing were therefore
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unlikely to be due to alterations in motivational state or general activity. In terms
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of visual perception, it also does not appear that the task was either more or less
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difficult to perform in the two different light levels. There was also little
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difference between the two replicates in the time taken to learn the task, and both
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replicates showed a similar learning pattern (see above).
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Testing
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During testing the subject rats continued to discriminate accurately between the
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rewarded and ‘aversive’ reference locations, and this ability was shown not to be
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influenced by treatment. This presents further evidence, additional to that
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gathered during training, that any treatment effects on the subjects’ response to
426
the ambiguous probe locations was less likely to have arisen as a consequence of
427
general changes in motivation rather than due to a specific influence on the
428
appraisal of the ambiguous probe locations. This includes any motivational
19
429
influences arising specifically due to the change in light levels which occurred
430
for half the rats between training and testing (in comparison to the unchanged
431
light levels received by all subjects during training).
432
433
In line with our initial predictions, we found that rats tested under high light
434
conditions after having previously experienced the apparatus under low light
435
conditions (LH) and those tested under low light conditions after previously
436
experiencing the apparatus under high light conditions (HL) differed most
437
strongly in their judgement of the ambiguous stimuli, with HL rats running faster
438
to all probe locations. However, in contrast to our predictions, those animals
439
trained and tested in high light levels (HH) did not show a more negative
440
judgment of the ambiguous stimuli than those trained and tested in low light
441
levels (LL).
442
443
The difference between HL and LH rats indicates that a change in light
444
conditions per se resulting in a performance decrement (see Methods
445
‘Treatments’) was unlikely to be responsible for the findings, but rather that a
446
specific difference in emotional state was a more likely explanation. Being
447
switched from a high light to a low light level likely resulted in a relative
448
decrease in anxiety compared to those animals switched from a low to a high
449
light level, and this may have resulted in the less negative (or more positive)
450
judgement of the ambiguous stimuli. Certainly, it appears that exposure to
451
sudden darkness can result in a reduced state of anxiety in rats [e.g. 19], although
452
sudden darkness is a more extreme change in light levels than was used in the
453
current study. It is possible that a form of relief was experienced by those
20
454
animals in the HL treatment following the omission of a more anxiety-inducing
455
light level [e.g. 26]. The observed results could also be explained in a similar
456
way to incentive contrast theory [e.g. 27], where emotional state and subsequent
457
behaviour is determined by relative (and contrasting), rather than absolute,
458
experience. If this were the case, then experiencing a change in light levels is
459
likely to have, at least temporarily, more of an influence on emotional state than
460
exposure to unchanging illumination. Changes in motivation or general activity
461
due to the change in light levels could possibly account for the results observed
462
but, if this was the explanation, we would also have expected to see differences
463
in responses of HL and LH rats to the unambiguous training locations and, as
464
discussed above, these were not observed.
465
466
It is worth taking time to consider why we did not observe the predicted
467
difference between the HH and LL treatments in their judgement of the
468
ambiguous locations. One possibility is that, on their own, the HH and LL
469
treatments were not strong enough to induce a measurable difference in
470
emotional state, as tentatively demonstrated by the lack of difference during
471
habituation, and only became strong enough once a contrast was established by
472
changing the light levels at testing. A further possibility is that those rats tested in
473
the unchanging light conditions (HH & LL) had become habituated to the anxiety
474
inducing effect of the light level over the course of training (two days) thereby
475
‘normalizing’ their subsequent response at testing, whereas those rats that
476
changed light levels following training (HL & LH) had a ‘refreshed’ reaction to a
477
light level that they only experienced for the first time at testing.
478
21
479
Our present finding extends previous research [e.g. 4,5-9] into the use of
480
cognitive bias to assess animal emotions, demonstrating that acute/short-term
481
inductions of anxiety can generate an apparent bias in cognitive processing, in
482
terms of judgements of ambiguity. It thus appears that such cognitive bias tasks
483
may be able to identify different, but similarly valenced, emotional states, as
484
proposed by Paul et al. [3]. This would help advance understanding of the
485
affective (emotional) mechanisms underpinning cognitive bias, as well as
486
methods for the assessment of animal emotion and welfare.
487
488
Unlike other studies [e.g. 4,8], we found no difference between treatments in
489
their judgement of specific ambiguous probe locations (e.g. either the probe
490
nearest the ‘negative’ end or the probe nearest the ‘positive’ end), but instead
491
found an overall difference inclusive of all three probe locations. One possible
492
reason for this is that the probe locations in this study were more easily
493
distinguishable to the rats than in a previous study [8] because they were
494
positioned further apart from one another and from the reference locations (45˚
495
rather than 15˚). It could, therefore, have been that all three probe locations were
496
viewed similarly, as being of ambiguous outcome (i.e. they might contain either
497
palatable or aversive food), rather than being of ambiguous location (i.e. they
498
were not confused with the actual reference locations).
499
500
501
Conclusion
502
To conclude, we observed a treatment difference in the judgement of three
503
ambiguous locations in a judgement bias task, with rats switched from high
22
504
(60W) to low (10W) light levels displaying a more positive judgement of
505
ambiguous locations compared to rats switched from low to high light levels.
506
This result suggests that the judgement bias technique might be useful as an
507
indicator of acute changes in anxiety and other emotional states, as well as
508
allowing differentiation between acute and more chronic negative emotional
509
states such as depression. Finally, as a quickly learned task, it has the potential
510
benefit of being adaptable for a wide range of animal species.
511
512
513
Acknowledgements
514
515
This work was funded by the BBSRC Animal Welfare Initiative.
516
517
23
518
Figure One:
519
520
521
Visual cue
Guillotine door
522
523
524
Rewarded location
Probe location
‘Aversive’ location
525
526
527
528
529
24
530
Figure Two:
531
532
Latency to approach (s)
25.00
20.00
Rewarded R1
15.00
Aversive R1
Rewarded R2
10.00
Aversive R2
5.00
0.00
1
Training Day
533
534
535
25
2
536
Figure Three:
537
Latency to approach (s)
538
16.00
***
14.00
12.00
10.00
8.00
6.00
4.00
2.00
0.00
Aversive
Probe
nearest
aversive
Middle
probe
Location
539
540
541
26
Probe
nearest
rewarded
Rewarded
542
Figure Four:
543
544
*
545
546
547
548
549
27
550
551
Figure One: A diagram of the experimental apparatus, showing the two reference
552
locations (either rewarded or aversive), the three ambiguous probe locations, the
553
guillotine doors and the position of the visual cue.
554
555
Figure Two: A graph displaying the subjects’ ability to discriminate between the
556
rewarded and aversive locations over the two days of training, as determined by
557
differences in latency to approach (seconds). Data are presented for each of the
558
two replicates (R1 & R2), and averaged for treatment. Data are means ± standard
559
error of the mean.
560
561
Figure Three: A graph displaying the latency for the subjects to approach
562
(seconds) the five different locations (either reference or probe locations) during
563
testing (averaged for the three test days) and averaged for treatment. Data are
564
combined for the two replicates. Data are means ± standard error of the mean.
565
***P<0.001
566
567
Figure Four: A graph displaying the difference between the treatments (HH, HL,
568
LH & LL) in the latency to approach (seconds) the ambiguous probe locations
569
(averaged for the three probe locations) during testing (averaged for the three test
570
days). Data are combined for the two replicates. Data are presented as estimated
571
marginal means from the GLM output in order to account for the use of a
572
covariate. *P<0.05
573
574
28
575
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576
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