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Contents lists available at ScienceDirect

Behavioural Brain Research journal homepage: www.elsevier.com/locate/bbr

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Research report

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Short-term memory in zebrafish (Danio rerio)

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Jason Jia b,c,1 , Yohaan Fernandes a,1 , Robert Gerlai a,c,∗

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Department of Cell and Systems Biology, University of Toronto, Canada McMaster University, Canada c Department of Psychology, University of Toronto Mississauga, Canada b

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h i g h l i g h t s • • • • •

Animated images serving as reward were presented for 1-min intervals. Stimulus presentation intervals were separated by inter-stimulus intervals (ISI). Zebrafish preferred the prior stimulus location even during the longest ISI (16 min). Zebrafish showed no performance improvement across repeated stimulus/ISI periods. The paradigm is an automated method to test short term memory in zebrafish.

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Article history: Received 5 March 2014 Received in revised form 25 April 2014 Accepted 28 April 2014 Available online xxx

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Keywords: Learning Memory Short-term memory Zebrafish

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1. Introduction

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Learning and memory represent perhaps the most complex behavioral phenomena. Although their underlying mechanisms have been extensively analyzed, only a fraction of the potential molecular components have been identified. The zebrafish has been proposed as a screening tool with which mechanisms of complex brain functions may be systematically uncovered. However, as a relative newcomer in behavioral neuroscience, the zebrafish has not been well characterized for its cognitive and mnemonic features, thus learning and/or memory screens with adults have not been feasible. Here we study short-term memory of adult zebrafish. We show animated images of conspecifics (the stimulus) to the experimental subject during 1 min intervals on ten occasions separated by different (2, 4, 8 or 16 min long) inter-stimulus intervals (ISI), a between subject experimental design. We quantify the distance of the subject from the image presentation screen during each stimulus presentation interval, during each of the 1-min post-stimulus intervals immediately following the stimulus presentations and during each of the 1-min intervals furthest away from the last stimulus presentation interval and just before the next interval (pre-stimulus interval), respectively. Our results demonstrate significant retention of short-term memory even in the longest ISI group but suggest no acquisition of reference memory. Because in the employed paradigm both stimulus presentation and behavioral response quantification is computer automated, we argue that high-throughput screening for drugs or mutations that alter short-term memory performance of adult zebrafish is now becoming feasible. © 2014 Published by Elsevier B.V.

Learning and memory have been extensively studied by a large number of laboratories from the perspectives of behavioral organization through neuroanatomical and electrophysiological

∗ Corresponding author at: Department of Psychology University of Toronto Mississauga 3359 Mississauga Road North, Rm DV4023C Mississauga, Ontario L5L 1C6, Canada. Tel.: +1 905 569 4255/57 lab fax: +1 905 569 4326. E-mail address: robert [email protected] (R. Gerlai). 1 1 These authors contributed equally to this publication

correlates to the molecular components of underlying mechanisms. Despite the progress made to date, much remains to be discovered. For example, a recent book on the mechanisms of memory [1] lists several hundred molecular players involved in some forms of neuronal plasticity, however, the brain is known to express over 50% of all the genes of the genome at any given point of time [2]. Therefore, despite the hundreds of gene products studied so far, there are still potentially several thousand proteins involved in learning and memory yet to be discovered and functionally analyzed. How could analysis of such complexity be possible? Some argue that systematic, unbiased, large scale screening for random mutagenesis induced mutations that affect learning and memory is

http://dx.doi.org/10.1016/j.bbr.2014.04.046 0166-4328/© 2014 Published by Elsevier B.V.

Please cite this article in press as: Jia J, et al. Short-term memory in zebrafish (Danio rerio). Behav Brain Res (2014), http://dx.doi.org/10.1016/j.bbr.2014.04.046

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needed. However, such screens have not been possible or have been prohibitively expensive even with the most favored laboratory organism of pre-clinical biomedical research, the house mouse [3]. The zebrafish has been suggested as a potentially viable alternative [4]. This small vertebrate species is complex enough for translational relevance. For example, the homology of the nucleotide sequence of its genes has been often found to reach or exceed 70% as compared to that of human genes [5]. At the same time, the zebrafish has several practical features that make it amenable to high throughput mutation and/or drug screening. It is small, reaching only 4 cm length when fully grown. It is prolific: a female can produce 200 eggs per spawning every other day. It can be housed cheaply in small fish tanks, because it prefers forming groups. Thus, crowding the subjects to a certain degree (about 5–6 fish per liter) is not stressful for zebrafish in systems that provide appropriate water filtration (removal of organic waste and oxygenation). In fact keeping many zebrafish in the same tank represents proper environmental enrichment as it allows the social interaction and group cohesion this species requires. However, the zebrafish suffers from a major disadvantage compared to classical rodent laboratory species (rats and mice). Our understanding of its cognitive and mnemonic characteristics and abilities is limited and the number of behavioral paradigms with which these features may be tested and measured is rather small [4,6,7]. Adult zebrafish are expected to possess the most complex learning and memory repertoire, yet only a handful of learning and memory tasks have been tried, most of which are slow and labor intensive, thus inappropriate for high throughput screening [4]. In summary, there is a need for better understanding of learning and memory capabilities of zebrafish, and there is a need for behavioral tasks that can quantify these characteristics in an efficient manner. The aim of the current study is to work towards alleviating these needs. Previously, we developed a simple behavioral task with which we have been able to induce acquisition of memory relatively quickly and in a manner that was amenable to automation [8]. The task was based upon a shuttle box design in which the experimental subject was shown a rewarding stimulus, the sight of conspecifics [9]. In one version of the paradigm, the subject received repeated short bouts of stimulus presentations on alternating sides of the tank. Using this task, we were able to show that with repeated alternating presentations of the rewarding stimulus fish, the experimental subject developed anticipation of where the next stimulus would appear and moved closer to the future presentation site [8]. The distance to stimulus screen has been regarded as a measure of the strength of response to social stimuli [8,9] and it is also used as a measure of memory of the location of previously shown social stimuli [4,8,9,15]. Although the results showed a good acquisition of memory, i.e. reduction of distance to the side opposite to where the stimulus was just shown, one could argue that speciesspecific characteristics of the movement patterns of zebrafish may have been a confound. The fast moving zebrafish has a tendency not to stay in one location but to move away from it. Thus, upon the disappearance of the stimulus, the experimental fish may have swum towards the opposite side not because of their memory of the alternating stimulus sequence. The current study aims at removing this confound. The rewarding stimulus fish (animated shoal) are presented on the same side of the experimental tank and the experimental fish are required to stay close to this side during inter-stimulus intervals (no stimulus shown). Briefly, we believe that requiring zebrafish not to swim away from a given location is a more demanding task for them and thus may allow us to better quantify memory performance of these fish. Furthermore, and most importantly, in the current study we ask whether the length of the inter-stimulus interval (ISI) influences the ability of the experimental subject to stay near the side of the tank where

the stimulus was shown. That is, we vary the ISI length between 2 min and 16 min, and measure how far the experimental subjects stay from the stimulus presentation screen during these ISI periods, a between subject experimental design. This task primarily taps into short-term memory. Short-term memory is defined as experience dependent changes in behavior that last for a few minutes. The mechanisms of short-term memory investigated using mammals have been found distinct from those of medium or long-term memory [1], which gives credence to its definition as biologically valid. Our hope is that characterization of short-term memory performance of zebrafish will in the future help us to explore the mechanisms of memory in this vertebrate species.

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2. Methods

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2.1. Animals and housing

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AB strain zebrafish bred in our facility at the University of Toronto Mississauga (Mississauga, ON, Canada) were used in the current study. The fish originated from the Zebrafish International Resource Center (ZIRC, Eugene, OR, USA) and the fish used in this study was the third generation from the original founders. Eighty adult zebrafish (50–50% males and females) were randomly chosen from a pool of hundreds of fish kept in our Vivarium. Animals were housed in 37 L tanks in groups of 25 as previously described [10]. 2.2. Experimental design and procedure Experimental zebrafish were randomly assigned to one of 4 groups. Each group received a different inter-stimulus interval (ISI) length, the treatment factor, i.e., 2 min, 4 min, 8 min, or 16 min, a between subject experimental design. The test apparatus was an elongated rectangular aquarium (70 cm × 17 cm × 17 cm, length × height × depth) made of transparent acrylic. It was filled with water of identical characteristics as the housing tank water (system water that was reverse osmosis filtered and reconstituted with 60 mg/l Instant Ocean salt, Big Al’s Aquarium Warehouse, Mississauga ON, Canada). The back and bottom of the experimental aquarium was covered with white corrugated plastic and the aquarium was illuminated from above by a 15 Watt fluorescent light tube to enhance contrast and achieve optimal lighting conditions for video-tracking. A computer screen was positioned flush against each short side of the tank (right and left side) facing inwards. These computer screens were connected to laptops running GFA, a software application developed in-house [11,12] that allowed us to present animated images of conspecifics. A video-camera (JVC Everio, GZ-MG330AU) facing the long side of the experimental aquarium recorded the behavior of the experimental subject. The experimental subject was placed into the testing tank gently (slowly moving net, net with a fish placed into a beaker and moved to the test tank, net removed from beaker and placed into test tank and fish slowly released from the net) for a 10 min long habituation session during which both computer screens were blank (no images shown). Subsequently, i.e. during the 11th min in the experimental tank the first 1 min long stimulus presentation commenced. During this period, animated images of 5 zebrafish were displayed on one of the screens in a manner described elsewhere [13], while the other screen remained blank. The stimulus presentation was followed by an inter-stimulus interval (ISI) during which neither screen displayed any images. After the ISI, a new stimulus presentation period started, and the process repeated itself for a total of 10 stimulus periods and 9 ISIs. The side of stimulus presentation remained the same for the given experimental subject. This represents a simplification compared to a previously employed alternating side presentation [8] because the experimental fish are

Please cite this article in press as: Jia J, et al. Short-term memory in zebrafish (Danio rerio). Behav Brain Res (2014), http://dx.doi.org/10.1016/j.bbr.2014.04.046

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not required to switch between sides and abandon the location where the rewarding stimulus fish were shown. The length of ISI varied across subjects according to their group designation but always remained the same for the given experimental animal. The order in which fish of different ISI groups was tested was randomized. Testing could not be conducted blind given the obvious ISI length differences, but quantification of behavior was completed in an automated manner, and data extraction and analyses were conducted blind to the group designation of the fish.

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2.3. Quantification of behavioral responses

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Video-recordings were transferred to the hard drive of a PC (Dell, Vostro desktop) running Ethovision 8.5, a video-tracking system (Noldus, Wageningen, The Netherlands). Numerous behavioral parameters were extracted and quantified using this system, including swim speed, distance from bottom, absolute and relative turn angle, heading, duration of immobility, and distance to stimulus screen. The analyses were conducted for both the mean and the inter-individual temporal variance of the above measures. The data were quantified for the following periods: 1 min intervals of the entire habituation period, 1 min stimulus presentation intervals, the 1 min intervals that immediately followed the stimulus period (post-stimulus), and the 1 min intervals that were furthest away from the stimulus presentation interval, i.e. those that immediately preceded the next stimulus period (pre-stimulus) (Fig. 1). Note that responses during the post-stimulus interval require a 1 min long memory span only, but the pre-stimulus interval, depending on the ISI group designation of fish, requires short-term memory spanning 2, 4, 8 or 16 min (Fig. 1). Also note that although we have quantified and analyzed all the above behavioral parameters, here we only report on the distance to the stimulus screen, the temporal variance of the distance to the stimulus screen, and the swim speed because the other behavioral variables showed no significant effect of ISI and no significant interaction between ISI and any other factors and did not contribute to the interpretation of results.

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2.4. Statistical analysis

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Statistical analyses were conducted using SPSS 14 written for the PC. The effect of sex was found non-significant and thus data for sexes were pooled. First, nested repeated measures variance analysis (ANOVA) was conducted with Interval-type (stimulus, post-stimulus and pre-stimulus intervals) and time (nine 1 min intervals), the two nested repeated measures factors, and InterStimulus Interval (2, 4, 8, or 16 min), the between subject treatment factor. Given that post hoc multiple range comparison tests capable of reducing type I error are inappropriate for repeated measures designs, to investigate which ISI group differed from another and during which interval-type we first averaged the 10 stimulus intervals, the 9 post-stimulus intervals and the 9 pre-stimulus intervals, respectively. We then analyzed these averages using a two-factorial repeated measures ANOVA with Interval-type as the only repeated measure factor and ISI length as the between subject factor. Subsequently, we conducted two post hoc analyses for each behavioral measure. For example, for the distance to stimulus screen measure we conducted one tailed one sample t-tests with Bonferroni correction for multiple comparisons separately for each interval type to investigate whether the distance of experimental fish to the stimulus screen was lower than random chance (the midpoint of the tank, i.e. 35 cm). Subsequently, we also investigated whether the ISI groups differed from each other for any particular intervaltype using the Tukey Honestly Significant Difference (HSD) post hoc multiple range comparison test.

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Fig. 1. The experimental aquarium (A), conspecific image used as the stimulus (B) and an example of stimulus presentation and the intervals selected for quantification of behavioral responses (C). Note that only one of the two computer screens presented the stimulus (five moving images of zebrafish). The location of presentation was constant throughout the ten stimulus presentation intervals for the given experimental subject, but the side of presentation location (left or right) varied randomly across the subjects. Also note that the conspecific image is a photograph of a female zebrafish identical in coloration, stripe pattern, and size to the experimental zebrafish. Shoals made up of females are preferred by both male and female zebrafish and thus this image choice was made to reduce potential sex differences in our subjects [[13] and references therein]. Last, observe that the example of stimulus presentation schedule shows the eight minute inter-stimulus interval (ISI) treatment with the stimulus presentation interval indicated by black, and the post- and pre-stimulus intervals used for quantification of responses indicated by different shades of grey.

3. Results The distance to stimulus screen has been regarded as a measure of the strength of response to social stimuli [8,9]. In our study, it is also used as a measure of memory of the location of previously shown social stimuli. During the habituation period, fish of all ISI groups were treated in the same manner (they have not received the stimulus and the differential ISI treatment yet), inline with this they showed no significant differences and thus their data were pooled for statistical analysis of the habituation behavior performance. This analysis revealed that fish did not significantly change their distance from the stimulus screen across the ten 1-minute intervals of the habituation period (repeated measures ANOVA, F(9, 711) = 0.443, p > 0.90). Furthermore, fish appeared to prefer no sides and swam at a distance from the stimulus screen that was statistically indistinguishable from random chance (35 cm) during each of the ten 1-min intervals of this period (t < /1.059/, df = 79, p > 0.95 (Fig. 2, first graph). In response to stimulus presentation, however, the distance to the stimulus screen was robustly reduced from 35 cm to about 10–12 cm. This reduction

Please cite this article in press as: Jia J, et al. Short-term memory in zebrafish (Danio rerio). Behav Brain Res (2014), http://dx.doi.org/10.1016/j.bbr.2014.04.046

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Fig. 2. Distance to stimulus screen is significantly shorter during the stimulus, post-stimulus and pre-stimulus intervals as compared to the habituation period (random chance) value. Mean ± S.E.M. are shown. Sample sizes for the different ISI groups are as follows nISI2 = 20, nISI4 = 21, nISI8 = 20, nISI16 = 19. The broken horizontal line shows the midpoint of the tank, which is 35 cm away from the stimulus side, a value that represents random chance. Note that the distance to stimulus side is not statistically distinguishable from random chance during habituation (first graph) but robustly decreases during stimulus presentation (second graph). Also note that the distance is still very short during the interval that immediately follows the stimulus interval (the post-stimulus interval, third graph). Last, observe that the distance appears somewhat longer during the pre-stimulus interval (the interval that is furthest away from the previous stimulus interval) as compared to the stimulus interval value but it is still lower than random chance. For further details and statistical analysis results see Section 3.

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was observable during all stimulus presentation intervals (Fig. 2, second graph). It also appears that the reduction remained robust during the 1 min interval that followed the stimulus presentation (post-stimulus interval, Fig. 2, third graph). Lastly, during the prestimulus interval, i.e. during the interval that was furthest away from the previous stimulus presentation interval, the distance to stimulus screen still appeared to be below random chance, i.e. 35 cm (Fig. 2, fourth graph). These observations were confirmed by a nested three-factorial repeated measures ANOVA. It showed a significant Interval-type effect (F(2, 152) = 83.881, p < 0.001) and Interval-Type × ISI interaction (F(6, 152) = 3.408, p < 0.01), but found the Time effect (F(8, 608) = 0.596, p > 0.75), Time × ISI interaction (F(24, 608) = 0.554, p > 0.95), Interval-type × Time interaction (F(16, 1216) = 1.215, p > 0.20), Interval-Type × Time × ISI interaction (F(48, 1216) = 0.996, p > 0.45) and the effect of ISI main factor (F(3, 76) = 0.580, p > 0.60) non-significant. In summary, these results suggest that fish did not change their distance significantly across time during any of the three interval types and also in any of the ISI groups. However, whether the stimulus was present or the fish were measured just after or before the stimulus presentation did make a significant difference and this difference was dependent upon ISI treatment condition. To further explore these results and to aid their interpretation, we collapsed the data across time (the effect of Time and the Time-interaction terms were all non-significant) by averaging the time data for each ISI × Interval-type cell. The results are shown in Fig. 3. ANOVA confirmed a significant Interval-type effect (F(2, 152) = 78.640, p < 0.001), a significant Interval-Type × ISI interaction (F(6, 152) = 3.370, p < 0.01) and a non-significant ISI length main effect (F(3, 76) = 0.504, p > 0.65) demonstrating that the effect of different ISI lengths was dependent upon the Interval-type. The results presented in Fig. 3 suggest that during stimulus presentation fish of all ISI treatment groups were equally close to the stimulus, but during the post-stimulus and pre-stimulus intervals fish of some of these ISI treatment groups differed from each other. To further examine this observation, we conducted one sample one tailed t-tests with Bonferroni correction and asked which ISI group and under what interval-type condition was significantly closer to the stimulus side than random chance, i.e. compared to the midpoint, 35 cm distance. The results showed that during stimulus presentation fish of all groups were significantly closer to the stimulus side than random chance, as expected for the shoaling zebrafish (t > /−8.046/, df > 19, p < 0.001). We obtained the same results for the post-stimulus intervals, showing that the distance of fish to the stimulus side remained significantly smaller than random chance

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Interval type Fig. 3. The average of distance to stimulus screen is significantly shorter during the stimulus, post-stimulus and pre-stimulus intervals as compared to the habituation period (random chance) value. The average of the multiple time points quantified for each interval-type and each ISI treatment is shown. The bars represent the mean of this average and the error bars show the S.E.M. Sample sizes for the different ISI groups are as described in Fig. 2. The broken horizontal line shows the midpoint of the tank, which is 35 cm away from the stimulus side. This value represents random chance. Note that the distance to the stimulus side is significantly shorter than random chance during the stimulus interval, during the post-stimulus interval (the interval that immediately follows the stimulus interval) and also during the pre-stimulus interval (the interval that is furthest away from the previous stimulus interval). Also note that the fish of the different ISI groups were not found to significantly differ for any of the interval-type. For further details and statistical analysis results see Results.

for all ISI groups during this interval (t > /−7.334/, df > 19, p < 0.001). It is also notable that although there is an apparent difference among the ISI treatment groups during the post-stimulus interval (for example, the 16 min ISI fish appear to stay closer to the stimulus side than the 4 min ISI fish), Tukey HSD multiple range comparison test found no significant difference between any of these groups (p > 0.05). For the pre-stimulus interval, the most important interval for the evaluation of short-term memory, we found again that fish of all ISI treatment groups stayed significantly closer to the stimulus side than random chance (ISI 2 min t = −5489, df = 19, p < 0.01; ISI 4 min t = −3.812, df = 20, p < 0.01; ISI 8 min t = −3.321, df = 19, p < 0.01; ISI 16 min t = −2.444, df = 18, p = 0.05) and despite

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Fig. 4. Variance of distance to stimulus is significantly reduced in response to stimulus presentation. Mean ± S.E.M. are shown. Sample sizes for the different ISI groups are the same as given for Fig. 2. The first graph shows the variance value obtained for the intervals of the habituation session. The average of these variance values is regarded as baseline shown by the broken horizontal line. Note that variance of distance represents the within individual temporal variability of distance, which is a measure of how consistently close or far particular fish swam from the stimulus side. Also note that the variance of distance to stimulus side is lowest during stimulus presentation (second graph) and during the post-stimulus interval (the interval that immediately followed the stimulus interval, third graph). For further details and statistical analysis results see Section 3.

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the apparent trend suggesting an ISI length dependent increase of distance to the stimulus, Tukey HSD revealed no significant differences among the ISI treatment groups (p > 0.05). In addition to the analysis of the distance to the stimulus screen, we also examined the variance of this response. It is notable that this variance is not the variance of the mean characterizing the population of fish tested, but rather it represents within individual temporal variability of each subject, i.e. how consistently close or far the particular fish swam from the stimulus. Higher variance indicates less consistency in the distance from the stimulus. The temporal within individual variance of distance to stimulus may be regarded as a measure of exploratory activity in the horizontal dimension. We first examined the baseline, i.e. the variance value obtained during the habituation period in the absence of the stimulus (Fig. 4, first graph). As expected, we found the within individual temporal variance of distance from the stimulus screen not to significantly change (average = 343.58) across the 1-min intervals of the habituation period (F(9, 711) = 1.457, p > 0.15). However, Fig. 4 also suggests that in response to the stimulus presentation and immediately after it, this temporal within individual variance was reduced. The fish reduced their horizontal exploration, i.e. swam consistently closer to the conspecific images (Fig. 4, second and third graphs). During the pre-stimulus interval, the temporal within individual variance appears somewhat higher compared to the stimulus and post-stimulus interval values but still seems to be below what was observed during habituation (Fig. 4, fourth graph). Nested repeated measures ANOVA confirmed these observations and found a significant Interval-type effect (F(2, 152) = 13.044, p < 0.001), a significant Time effect (F(8, 608) = 3.006, p < 0.01) and a non-significant ISI effect F(3, 76) = 0.580., p > 0.60). ANOVA also found all interaction terms to be non-significant (Interval-type × ISI interaction, F(6, 152) = 1.420, p > 0.20; Time × ISI interaction, F(24, 608) = 1.178, p > 0.25; Interval-type × Time, F(16, 1216) = 0.802, p > 0.65; Interval-type × Time × ISI, F(48, 1216) = 0.823, p > 0.75). In summary, these results suggest that fish varied their distance to the stimulus significantly depending upon the Interval type, with prestimulus interval performance being characterized by apparently higher variance values compared to that obtained for the stimulus and post-stimulus intervals. Fish also changed their temporal within individual variance of distance to stimulus across time independently of the interval-type and ISI length. Notably however, this time effect appears to reflect stochastic temporal fluctuations and not a consistent change or temporal trend. To further analyze these results we collapsed the data across time by averaging the time point data for each ISI x Intervaltype cell. The results are shown in Fig. 5. Repeated measures

Fig. 5. The average of the variance of distance to stimulus screen is significantly lower during the stimulus, post-stimulus and pre-stimulus intervals as compared to baseline. The average of the multiple time points quantified for each intervaltype and each ISI treatment is shown. The bars represent the mean of this average and the error bars show the S.E.M. Sample sizes for the different ISI groups are as described in Fig. 2. The broken horizontal line shows the baseline calculated as the mean of the variance of distance to stimulus values obtained during the habituation session. Note that the variance of distance to the stimulus side is significantly shorter than random chance during the stimulus interval, during the post-stimulus interval (the interval that immediately follows the stimulus interval) and also during the pre-stimulus interval (the interval that is furthest away from the previous stimulus interval). Also note that the ISI groups were not found to significantly differ from each other for any of the interval-type. For further details and statistical analysis results see Section 3.

ANOVA found a significant Interval-Type effect (F(2, 152) = 12.619, p < 0.001), a non-significant Interval-Type × ISI interaction (F(6, 152) = 1.508, p > 0.15) and a non-significant ISI length main effect (F(3, 76) = 0.910, p > 0.44). One sample one tailed t-tests with Bonferroni correction demonstrated that fish of all groups and during all intervals reduced the within individual temporal variance significantly below that of the habituation period (Vhabit = 343.58; t > /−2.957/, df > 19, p < 0.05) and Tukey HSD test found no significant (p > 0.05) differences among ISI treatment groups for each interval-type. The next behavioral variable we report on is swim speed. We decided to include the analysis of this variable because

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Fig. 6. Swim speed of zebrafish during the habituation session (first graph), stimulus presentation intervals (second graph), post-stimulus intervals (third graph) and prestimulus intervals (fourth graph). Mean ± S.E.M. are shown. Sample sizes for the different ISI groups are the same as given for Fig. 2. The broken horizontal line represents the mean of the speed recorded during the last five minutes of the habituation session, a period during which speed remained unchanged. We regard this mean value the baseline. Note the reduction of speed in response to the presentation of the stimulus. Also note that compared to the stimulus intervals, swim speed rises during the post-stimulus intervals and especially during the pre-stimulus intervals. Last, observe that even the slowest mean speed value (around 300 cm/min) would allow zebrafish to traverse the entire length of their experimental aquarium (70 cm) more than four times within a minute. For further details of statistical analyses and results see Section 3.

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the distance to the stimulus screen, and thus the interpretation of memory performance, may be affected by immobility, or reduced swim speed, and we wanted to explore whether this was a potential confounding factor in our study. Swim speed significantly changed (increased) with time during the ten 1-min intervals of the habituation session (F(9, 711) = 6.815, p < 0.001) but not during the last five minutes of this session (F(4, 316) = 0.705, p > 0.55) (Fig. 6, first graph). Thus we calculated the average of the swim speed values of the last five minutes of the habituation session to obtain what we regard as baseline, for which we obtained 475.88 cm/min. Subsequently, we analyzed swim speed during the stimulus, post-stimulus and pre-stimulus intervals using nested repeated measures ANOVA. This analysis showed a significant Interval-type effect (F(2, 152) = 106.590, p < 0.001), a significant Time effect (F(8, 608) = 3.609, p < 0.001) and a non-significant ISI length effect (F(3, 76) = 1.992., p > 0.10). All interaction terms were found non-significant (Intervaltype × ISI F(6, 152) = 1.323, p > 0.25; Time × ISI F(24, 608) = 0.985, p > 0.45; Interval-type × Time F(16, 1216) = 1.602, p > 0.05; Intervaltype × Time × ISI F(48, 1216) = 0.823, p > 0.80). These results together with Fig. 6 suggest that swim speed significantly increased from the stimulus interval through the post-stimulus interval to the pre-stimulus interval and that it decreased with time similarly within each of these interval-types. It is also notable that even the slowest average swim speed observed (around 300 cm/min) would allow the experimental fish to traverse the entire length of the tank (70 cm) more than four times within each 1-min interval, an important observation that suggest fish could easily quickly away from any location in the tank. Although suggestive, fast swim speed does not necessarily mean that fish staying in a particular location of the tank did actually move further away from that location. One could argue that staying close to the stimulus side during the inter-stimulus intervals may not be indicative of memory of the prior presentation of the stimulus on that side. It may be the result of not being able to swim away from the side where the stimulus was shown. To investigate how fast fish actually moved away from a location we first analyzed the performance of experimental fish during the habituation session in the following manner. We identified the first instance (distance threshold) when a given experimental fish was closer than 15 cm from a particular side of the tank (during actual stimulus presentation the distance between experimental zebrafish and stimulus decreased below 15 cm). The side corresponded to the location where the stimulus would be shown

during training. Subsequently, we quantified the location of this fish during the 1-min period that followed the distance threshold event. We measured the distances every 5 s, i.e. obtained 12 data points for the one-minute interval. This analysis allowed us to quantify how fast fish swam away from a sidewall before any stimulus was presented (baseline). Subsequently, we also conducted a similar high-temporal resolution (5 s intervals) analysis for the last one-minute stimulus presentation interval. This allowed us to quantify the behavioral responses directly induced by the presence of the stimulus. Most importantly, we also conducted this high temporal resolution analysis for the minute that followed the last stimulus presentation (post-stimulus period) and during the minute that preceded the last stimulus presentation period (prestimulus). For the high temporal-resolution analysis we pooled the different ISI treatment groups, as our prior analysis found no main ISI-length effect or interaction between this and other factors. The results are shown in Fig. 7. Our nested repeated measures ANOVA found a significant interval-type effect (F(3, 105) = 8.457, p < 0.001) confirming that performance during the four different periods (habituation, stimulus, post- and pre-stimulus periods) differs. ANOVA also confirmed that during the one minute observation the temporal changes across the 5 s intervals were significant (F(11, 385) = 4.894, p < 0.001) and it also revealed that the temporal trajectory was dependent upon interval-type (interval type × 5 s interval interaction F(33, 1155) = 8.475, p < 0.001). Perusal of Fig. 7 shows that during habituation fish that were on average 8 cm away from the target side quickly swam away and within 20 s (and for the remaining part of the studied 1-min period) they were more than 30 cm away from that side, a distance that is statistically indistinguishable (t = −1.543, df = 79, p > 0.10) from random chance (35 cm). During stimulus presentation, the temporal trajectory of distance from stimulus side was the opposite (Fig. 7). Fish rapidly reduced their distance from (moved closer to) the stimulus, and within 10 s they were significantly below random chance (t = −2.477, df = 36, p < 0.05) and continued to decrease their distance subsequently. Perhaps most importantly, during the last post-stimulus period, i.e. during the minute that followed the last stimulus presentation, zebrafish remained close to the significantly below random chance (comparison of the largest distance at time point 55 s with 35 cm, t = −6.291, df = 80, p < 0.001) throughout the one minute period, a performance that is in stark contrast to how fast fish swam away from the side during habituation (Fig. 7). Last, we also found that although generally further away compared to the distance obtained during the last stimulus and post-stimulus periods, during the last

Please cite this article in press as: Jia J, et al. Short-term memory in zebrafish (Danio rerio). Behav Brain Res (2014), http://dx.doi.org/10.1016/j.bbr.2014.04.046

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Fig. 7. Distance (cm) from stimulus screen during a one minute period of the habituation session, stimulus presentation and post- and pre-stimulus intervals. Mean ± S.E.M. are shown. Sample sizes are the same as given for Fig. 2 (ISI groups pooled). The broken horizontal line shows the midpoint of the tank, which is 35 cm away from the stimulus side, a value that represents random chance. Note the sampling frequency (5 s interval high temporal resolution). Also note that the minute analyzed for the habituation session was selected as the period that started with fish being closer than 15 cm from the future stimulus presentation side. The stimulus period represents the last 1-min stimulus presentation period, and the postand pre-stimulus periods show data collected during the one minute that followed and preceded the last stimulus period respectively. Note the robust increase of distance (rapid swimming away) from the future stimulus side during habituation that reaches random chance within 20 s, and the opposite response, a rapid decrease of distance from the stimulus side that becomes significantly less than random chance within 10 s during stimulus presentation. Also note that during both the post- and the pre-stimulus minute, fish remained significantly below random chance and stayed closer to location of past stimulus presentation throughout the analyzed period.

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pre-stimulus period fish also remained significantly below random chance (comparison of the largest distance at time point 40 s with 35 cm, t = −1.821, df = 80, p < 0.05).

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In the current study, we have investigated the behavioral responses of zebrafish to appetitive social stimuli (sight of moving images of conspecifics) that were presented intermittently, i.e. for 1 min long intervals separated by inter-stimulus intervals (ISIs) whose length differed for four ISI treatment groups. The main goal of our study was to test short-term memory spanning a period from 1 min up to 16 min. We measured the distance to the stimulus screen during stimulus presentation, during the minute that followed the stimulus presentation (post-stimulus interval) and 2, 4, 8, and 16 min later (the one minute interval that was just before the next stimulus interval, the interval that we termed the pre-stimulus interval). Performance during the post-stimulus but especially during the pre-stimulus intervals we regard as a measure of short-term memory because during these intervals the experimental zebrafish do not see the stimulus but will have to decide where to swim based upon their memory of the prior location of conspecific images. In line with our expectations, zebrafish continued to swim close to the location of the previously shown stimulus even after a 16 min inter-stimulus interval. They also showed reduction of horizontal

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exploration of their experimental aquarium as demonstrated by the reduced within individual temporal variance of distance to stimulus. There may be two fundamentally different explanations for the reduced distance to stimulus (and its variance) during the postand pre-stimulus intervals. One, the experimental fish remembered the location of the stimulus and thus attempted to stay close to this location, or two, the experimental fish could not move away from the location where they stayed during the stimulus presentation. We obtained evidence for the latter possibility being unlikely. Quantification of the subjects’ swim speeds revealed that even the lowest average swim speed amongst the ISI groups exceeded 300 cm/min. At this speed, within a single minute the subjects could traverse more than four times the entire length of their experimental tank (70 cm). It is thus unlikely that immobility, or reduced ability to move away from the location of prior stimulus presentation, could explain why the experimental fish stayed closer to this location. Furthermore, we analyzed high temporal resolution data and investigated how quickly zebrafish move away from the location of future stimulus presentation during habituation, during stimulus presentation and during the minute that followed (post-stimulus period) or preceded (pre-stimulus period) the last stimulus presentation minute. The results showed that zebrafish do not normally stay in one position (during habituation) but in response to the stimulus and most importantly during both the post- and pre-stimulus periods they do: fish do not swim away from the prior location of stimulus presentation. It is also notable that even after a 16 min ISI, the experimental subjects showed significant preference for the prior location of stimulus presentation. Therefore, we conclude that the preference for the prior stimulus presentation side shown during the inter-stimulus intervals is an indication of short-term memory. It is also notable that as the inter-stimulus interval length increased there was a trend towards reduced preference for the stimulus side, however, this trend was not significant, i.e. all ISI groups remained significantly closer to the stimulus than random chance and there were no significant differences among these groups. This was an unexpected finding as we hypothesized that the longer the inter-stimulus interval was, the less strong the preference should have been. We do not have a clear explanation why we found no correlation between ISI length and response strength. However, it is possible that zebrafish have a short-term memory that can span periods substantially longer than sixteen minutes and thus our test paradigm suffered from a floor effect, i.e. it was too easy for the experimental fish. Future studies will explore how long-lasting short-term memory may be in zebrafish. Another point we considered concerns short-term memory vs. longer-term reference memory. In our study, the stimulus was shown ten times in the same location (one side of the experimental aquarium). This training is expected to lead to the acquisition of short-term working memory, i.e. the memory of where the stimulus was just seen a few minutes before, but also longer-term memory, i.e. where the stimulus is usually seen across multiple trials or sessions. The latter type of memory may be regarded as reference memory, a type of memory that is stable over multiple repeated sessions or trials. However, we found no evidence for the development of reference memory. The strength of preference for the stimulus side, as indicated by the distance to the stimulus, did not change significantly as the testing progressed, i.e. across the multiple post- and pre-stimulus intervals. We cannot yet offer a definitive explanation for this finding, although it does replicate the previous results of a study [8] which employed principally the same experimental design as used here. Albeit with application of a slightly shorter stimulus presentation length (20 vs. 60 s) and different inter-stimulus interval lengths (90 s vs. 2, 4, 8, or 16 min), Pather & Gerlai found only a non-significant trend for fish staying closer to the stimulus side as training progressed [8]. In the current

Please cite this article in press as: Jia J, et al. Short-term memory in zebrafish (Danio rerio). Behav Brain Res (2014), http://dx.doi.org/10.1016/j.bbr.2014.04.046

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study, we attempted to make the stimulus more salient by presenting the images for a longer period (for 60 s), and more memory demanding by lengthening the inter-stimulus interval up to 16 min. Furthermore, in the current study we employed a longer experimental aquarium than before (70 vs. 50 cm) because we argued this would increase the motor demand of the task for the experimental subject and thus also the importance of making the right choice for where to stay with respect to the location of the stimulus presentation and we also required the fish to stay in one position as opposed to move away, a more stringent motor demand for the zebrafish. Despite these modifications, we found the same result: no indication of significant reference memory. The explanation for this is speculative at this point. Excellent reference memory has been demonstrated in zebrafish using multiple associative learning tasks. For example, zebrafish have been found to be able to learn both an associative visual cue (conditioned stimulus) and the location (spatial cues) of food reward in a plus maze experimental design [14]. Similarly, zebrafish have been able to acquire memory of the conditioned stimulus (a visual cue) as well as the location of the reward, when the reward was sight of conspecifics [9,15]. It is thus unlikely that the lack of reference memory observed in the current study is due to the inability of the zebrafish to form such memory. It is more likely that short-term memory formed even after a single stimulus presentation already led to a level of performance (short distance to the stimulus screen) that could not be improved further, a ceiling effect with regard to evaluation of potential reference memory related further improvements. Thus, we expect that further increasing the short-term memory demand, i.e. the length of the inter-stimulus interval, and perhaps further increasing the physical length of the experimental aquarium will allow us to overcome the current ceiling effect, working hypotheses whose validity will be tested by systematically varying these parameters. Although our current study raised several questions about memory performance of zebrafish and answering these questions will undoubtedly require further refinement of methods, we argue that our results are promising for two main reasons. One, they clearly show that the zebrafish has short-term memory that can be quantified, and two; they also demonstrate that induction and quantification of this memory can be conducted in an automated manner. Unlike in our previous paradigm, in which quantification of behavior was conducted manually and the presentation of stimuli also required substantial experimenter involvement [8], in the current study we employed a more automated stimulus

delivery software application and most importantly also a fully automated response quantification, video-tracking. The employed computerized automation techniques are noteworthy because they allow running multiple behavioral tasks in parallel, which increases throughput of the paradigm. Insufficient throughput has been the Achilles heel of systematic screening for mutations and drugs that affect learning and memory. The current study presents an example of how sufficient throughput may be achieved and thus paints a promising future for the zebrafish in the analysis of the mechanisms of learning and memory.

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Acknowledgements Supported by an NSERC (Canada) Discovery grant to RG.

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References [1] Sweatt JD. Mechanisms of Memory. Academic Press; 2009. [2] Pan Y, Kaiguo M, Razak Z, Westwood JT, Gerlai R. Chronic alcohol exposure induced gene expression changes in the zebrafish brain. Behav Brain Res 2011;216:66–76. [3] Reijmers LG. A mutant mouse with a highly specific contextual fearconditioning deficit found in an N-ethyl-N-nitrosourea (ENU) mutagenesis screen. Learn Memory 2006;13:143–9. [4] Gerlai R. Associative Learning in Zebrafish (Danio rerio). Method Cell Biol 2011;101:249–70. Third Edition. Elsevier Ltd. [5] Howe K, Clark MD, Torroja CF, Torrance J, Berthelot C, Muffato M, et al. Nature 2013;496:498–503. [6] Sison M, Cawker J, Buske C, Gerlai R. Fishing for genes influencing vertebrate behavior: zebrafish making headway. Lab Anim (NY) 2006;35:33–9. [7] Kalueff AV, Stewart AM, Gerlai R. Zebrafish as an emerging model for studying complex brain disorders. Trends Pharmacol Sci 2014;35:63–75. [8] Pather S, Gerlai R. Shuttle box learning in zebrafish (Danio rerio). Behav Brain Res 2009;196:323–7. [9] Al-Imari L, Gerlai R. Sight of conspecifics as reward in associative learning in zebrafish (Danio rerio). Behav Brain Res 2008;189:216–9. [10] Pannia E, Tran S, Rampersad M, Gerlai R. Acute ethanol exposure induces behavioural differences in two zebrafish (Danio rerio) strains: a time course analysis. Behav Brain Res 2014;259:174–85. [11] Saverino C, Gerlai R. The social zebrafish: behavioral responses to conspecific, heterospecific, and computer animated fish. Behav Brain Res 2008;191:77–87. [12] Qin M, Wong A, Seguin D, Gerlai R. Induction of social behaviour in zebrafish: Q4 Live versus computer-animated fish as stimuli. Zebrafish 2014, in press. [13] Fernandes Y, Gerlai R. Long-term behavioral changes in response to early developmental exposure to ethanol in zebrafish. Alcohol Clin Exp Res 2009;33:601–9. [14] Sison M, Gerlai R. Associative learning in zebrafish (Danio rerio) in the plus maze. Behav Brain Res 2010;207:99–104. [15] Karnik I, Gerlai R. Can zebrafish learn spatial tasks? An empirical analysis of place and single CS–US associative learning. Behav Brain Res 2012;233:415–21.

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Short-term memory in zebrafish (Danio rerio).

Learning and memory represent perhaps the most complex behavioral phenomena. Although their underlying mechanisms have been extensively analyzed, only...
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