Automated analysis of courtship suppression learning and memory in Drosophila melanogaster

Study of the fruit fly, Drosophila melanogaster, has yielded important insights into the underlying molecular mechanisms of learning and memory. Courtship conditioning is a well-established behavioral assay used to study Drosophila learning and memory. Here, we describe the development of software to analyze courtship suppression assay data that correctly identifies normal or abnormal learning and memory traits of individual flies. Development of this automated analysis software will significantly enhance our ability to use this assay in large-scale genetic screens and disease modeling. The software increases the consistency, objectivity, and types of data generated.     

Automated,Quantitative Cognitive/Behavioral Screening of Mice: For Genetics,Pharmacology, Animal Cognition and Undergraduate Instruction

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the "cloud" and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in cabinet; two such cabinets (16 environments) may be controlled by one computer.     

Male and female contributions to behavioral isolation in darters as a function of genetic distance and color distance

Determining which reproductive isolating barriers arise first between geographically isolated lineages is critical to understanding allopatric speciation. We examined behavioral isolation among four recently diverged allopatric species in the orangethroat darter clade (Etheostoma: Ceasia). We also examined behavioral isolation between each Ceasia species and the sympatric rainbow darter Etheostoma caeruleum. We asked (1) is behavioral isolation present between allopatric Ceasia species, and how does this compare to behavioral isolation with E. caeruleum, (2) does male color distance and/or genetic distance predict behavioral isolation between species, and (3) what are the relative contributions of female choice, male choice, and male competition to behavioral isolation? We found that behavioral isolation, genetic differentiation, and male color pattern differentiation were present between allopatric Ceasia species. Males, but not females, discerned between conspecific and heterospecific mates. Males also directed more aggression toward conspecific rival males. The high levels of behavioral isolation among Ceasia species showed no obvious pattern with genetic distance or male color distance. However, when the E. caeruleum was included in the analysis, an association between male aggression and male color distance was apparent. We discuss the possibility that reinforcement between Ceasia and E. caeruleum is driving behavioral isolation among allopatric Ceasia species.     

Rhesus monkey (Macaca mulatta) complex learning skills reassessed

Results from three experiments on basic learning and transfer in rhesus monkeys (Macaca mulatta) are reported in which fully automated testing paradigms, afforded by the Language Research Center's Computerized Test System (LRC-CTS), were employed. Performance levels for discrimination learning set, transfer index, and mediational-learning testing were uniformly higher than was predicted from the literature, in contrast to previous reports of compromised learning under similar conditions (automated apparatus, planimetric stimuli, spatial discontiguity between stimuli and response loci). Analyses reveal relatively advanced learning set performance, transfer-index ratios, and positive transfer of learning even at stringent criterion levels. Moreover, the data suggest that rhesus monkeys tested in these experiments exhibit mediational instead of associative learning strategies, as do great apes and in contrast to previous reports of rhesus learning. We argue that the LRC-CTS enhances learning by nonhuman primate subjects, obviating those factors, reported in the literature from experiments in which manual or other automated systems were employed, that compromise learning.     

The use of an unsupervised learning approach for characterizing latent behaviors in accelerometer data

The recent increase in data accuracy from high resolution accelerometers offers substantial potential for improved understanding and prediction of animal movements. However, current approaches used for analysing these multivariable datasets typically require existing knowledge of the behaviors of the animals to inform the behavioral classification process. These methods are thus not well‐suited for the many cases where limited knowledge of the different behaviors performed exist. Here, we introduce the use of an unsupervised learning algorithm. To illustrate the method's capability we analyse data collected using a combination of GPS and Accelerometers on two seabird species: razorbills (Alca torda) and common guillemots (Uria aalge). We applied the unsupervised learning algorithm Expectation Maximization to characterize latent behavioral states both above and below water at both individual and group level. The application of this flexible approach yielded significant new insights into the foraging strategies of the two study species, both above and below the surface of the water. In addition to general behavioral modes such as flying, floating, as well as descending and ascending phases within the water column, this approach allowed an exploration of previously unstudied and important behaviors such as searching and prey chasing/capture events. We propose that this unsupervised learning approach provides an ideal tool for the systematic analysis of such complex multivariable movement data that are increasingly being obtained with accelerometer tags across species. In particular, we recommend its application in cases where we have limited current knowledge of the behaviors performed and existing supervised learning approaches may have limited utility.     

Reactions to Potential Predators in Captive-Born Marmosets (Callithrix penicillata)

We describe the behavioral repertoire of captive-born black tufted-eared marmosets (Callithrix penicillata) elicited by brief exposures to three potential mounted taxidermized predators (caracara hawk, Polyborus plancus; rattlesnake, Crotalus durissus; oncilla, Leopardus tigrina), and a stuffed toy. For each of the four stimuli, we submitted the subjects to a 9-min trial divided into three consecutive intervals: a 4-min pre-exposure baseline observation, a 1-min stimulus exposure, and a 4-min postexposure observation period. We positioned stimuli in front of each subject's home cage, and video-taped trials for behavioral analysis. During exposures to the potential taxidermized predators, we heard tsik-tsik vocalization and alarm behavior. After exposures, only the cat induced these reactions. All stimuli elicited observational reaction, albeit only during exposure intervals. Further comparisons between the three trial intervals indicated a decrease in the time spent in proximity to the cat during exposures, while an increase in proximity occurred when subjects were exposed to either the hawk or snake for the same period. Taken together, the behavioral responses during and after exposures to the taxidermized oncilla suggest that this stimulus is capable of inducing strong and persistent emotional reactions in Callithrix penicillata.     

Resistance to change and vulnerability to stress: autistic‐like features of GAP43‐deficient mice

There is an urgent need for animal models of autism spectrum disorder (ASD) to understand the underlying pathology and facilitate development and testing of new treatments. The synaptic growth‐associated protein‐43 (GAP43) has recently been identified as an autism candidate gene of interest. Our previous studies show many brain abnormalities in mice lacking one allele for GAP43 [GAP43 (+/?)] that are consistent with the disordered connectivity theory of ASD. Thus, we hypothesized that GAP43 (+/?) mice would show at least some autistic‐like behaviors. We found that GAP43 (+/?) mice, relative to wild‐type (+/+) littermates, displayed resistance to change, consistent with one of the diagnostic criteria for ASD. GAP43 (+/?) mice also displayed stress‐induced behavioral withdrawal and anxiety, as seen in many autistic individuals. In addition, both GAP43 (+/?) mice and (+/+) littermates showed low social approach and lack of preference for social novelty, consistent with another diagnostic criterion for ASD. This low sociability is likely because of the mixed C57BL/6J 129S3/SvImJ background. We conclude that GAP43 deficiency leads to the development of a subset of autistic‐like behaviors. As these behaviors occur in a mouse that displays disordered connectivity, we propose that future anatomical and functional studies in this mouse may help uncover underlying mechanisms for these specific behaviors. Strain‐specific low sociability may be advantageous in these studies, creating a more autistic‐like environment for study of the GAP43‐mediated deficits of resistance to change and vulnerability to stress.     

Search and foraging behaviors from movement data: A comparison of methods

Search behavior is often used as a proxy for foraging effort within studies of animal movement, despite it being only one part of the foraging process, which also includes prey capture. While methods for validating prey capture exist, many studies rely solely on behavioral annotation of animal movement data to identify search and infer prey capture attempts. However, the degree to which search correlates with prey capture is largely untested. This study applied seven behavioral annotation methods to identify search behavior from GPS tracks of northern gannets (Morus bassanus), and compared outputs to the occurrence of dives recorded by simultaneously deployed time–depth recorders. We tested how behavioral annotation methods vary in their ability to identify search behavior leading to dive events. There was considerable variation in the number of dives occurring within search areas across methods. Hidden Markov models proved to be the most successful, with 81% of all dives occurring within areas identified as search. k‐Means clustering and first passage time had the highest rates of dives occurring outside identified search behavior. First passage time and hidden Markov models had the lowest rates of false positives, identifying fewer search areas with no dives. All behavioral annotation methods had advantages and drawbacks in terms of the complexity of analysis and ability to reflect prey capture events while minimizing the number of false positives and false negatives. We used these results, with consideration of analytical difficulty, to provide advice on the most appropriate methods for use where prey capture behavior is not available. This study highlights a need to critically assess and carefully choose a behavioral annotation method suitable for the research question being addressed, or resulting species management frameworks established.     

Operant Procedures for Assessing Behavioral Flexibility in Rats

Executive functions consist of multiple high-level cognitive processes that drive rule generation and behavioral selection. An emergent property of these processes is the ability to adjust behavior in response to changes in one’s environment (i.e., behavioral flexibility). These processes are essential to normal human behavior, and may be disrupted in diverse neuropsychiatric conditions, including schizophrenia, alcoholism, depression, stroke, and Alzheimer’s disease. Understanding of the neurobiology of executive functions has been greatly advanced by the availability of animal tasks for assessing discrete components of behavioral flexibility, particularly strategy shifting and reversal learning. While several types of tasks have been developed, most are non-automated, labor intensive, and allow testing of only one animal at a time. The recent development of automated, operant-based tasks for assessing behavioral flexibility streamlines testing, standardizes stimulus presentation and data recording, and dramatically improves throughput. Here, we describe automated strategy shifting and reversal tasks, using operant chambers controlled by custom written software programs. Using these tasks, we have shown that the medial prefrontal cortex governs strategy shifting but not reversal learning in the rat, similar to the dissociation observed in humans. Moreover, animals with a neonatal hippocampal lesion, a neurodevelopmental model of schizophrenia, are selectively impaired on the strategy shifting task but not the reversal task. The strategy shifting task also allows the identification of separate types of performance errors, each of which is attributable to distinct neural substrates. The availability of these automated tasks, and the evidence supporting the dissociable contributions of separate prefrontal areas, makes them particularly well-suited assays for the investigation of basic neurobiological processes as well as drug discovery and screening in disease models.     

Genetic disruptions of Drosophila Pavlovian learning leave extinction learning intact

Individuals who experience traumatic events may develop persistent posttraumatic stress disorder. Patients with this disorder are commonly treated with exposure therapy, which has had limited long‐term success. In experimental neurobiology, fear extinction is a model for exposure therapy. In this behavioral paradigm, animals are repeatedly exposed in a safe environment to the fearful stimulus, which leads to greatly reduced fear. Studying animal models of extinction already has lead to better therapeutic strategies and development of new candidate drugs. Lack of a powerful genetic model of extinction, however, has limited progress in identifying underlying molecular and genetic factors. In this study, we established a robust behavioral paradigm to study the short‐term effect (acquisition) of extinction in Drosophila melanogaster. We focused on the extinction of olfactory aversive 1‐day memory with a task that has been the main workhorse for genetics of memory in flies. Using this paradigm, we show that extinction can inhibit each of two genetically distinct forms of consolidated memory. We then used a series of single‐gene mutants with known impact on associative learning to examine the effects on extinction. We find that extinction is intact in each of these mutants, suggesting that extinction learning relies on different molecular mechanisms than does Pavlovian learning.     

Automated Visual Cognitive Tasks for Recording Neural Activity Using a Floor Projection Maze

Neuropsychological tasks used in primates to investigate mechanisms of learning and memory are typically visually guided cognitive tasks. We have developed visual cognitive tasks for rats using the Floor Projection Maze^1,2 that are optimized for visual abilities of rats permitting stronger comparisons of experimental findings with other species.In order to investigate neural correlates of learning and memory, we have integrated electrophysiological recordings into fully automated cognitive tasks on the Floor Projection Maze^1,2. Behavioral software interfaced with an animal tracking system allows monitoring of the animal''s behavior with precise control of image presentation and reward contingencies for better trained animals. Integration with an in vivo electrophysiological recording system enables examination of behavioral correlates of neural activity at selected epochs of a given cognitive task.We describe protocols for a model system that combines automated visual presentation of information to rodents and intracranial reward with electrophysiological approaches. Our model system offers a sophisticated set of tools as a framework for other cognitive tasks to better isolate and identify specific mechanisms contributing to particular cognitive processes.     

Estimating the speed of Drosophila locomotion using an automated behavior detection and analysis system

A fundamental phenotypic trait in Drosophila melanogaster is the speed of movement. Its quantification in response to environmental and experimental factors is highly useful for behavioral and neurological studies. Quantifying this behavioral characteristic in freely moving flies is difficult, and many current systems are limited to evaluating the speed of movement of one fly at a time or rely on expensive, time-consuming methods. Here, we present a novel signal processing method of quantifying the speed of multiple flies using a system with automatic behavior detection and analysis that we previously developed to quantify general activity. By evaluating the shape of the signal wave from recordings of a live and simulated single fly, a metric for speed of movement was found. The feasibility of using this metric to estimate the speed of movement in a population of flies was then confirmed by evaluating recordings taken from populations of flies maintained at two different temperatures. The results were consistent with those reported in the literature. This method provides an automated way of measuring speed of locomotion in a fly population, which will further quantify fly behavioral responses to the environment.     

A variable-response model for parasitoid foraging behavior

An important factor inducing variability in foraging behavior in parasitic wasps is experience gained by the insect. Together with the insect's genetic constitution and physiological state, experience ultimately defines the behavioral repertoire under specified environmental circumstances. We present a conceptual variable-response model based on several major observations of a foraging parasitoid's responses to stimuli involved in the hostfinding process. These major observations are that (1) different stimuli evoke different responses or levels of response, (2) strong responses are less variable than weak ones, (3) learning can change response levels, (4) learning increases originally low responses more than originally high responses, and (5) hostderived stimuli serve as rewards in associative learning of other stimuli. The model specifies how the intrinsic variability of a response will depend on the magnitude of the response and predicts when and how learning will modify the insect's behavior. Additional hypotheses related to the model concern how experience with a stimulus modifies behavioral responses to other stimuli, how animals respond in multistimulus situations, which stimuli act to reinforce behavioral responses to other stimuli in the learning process, and finally, how generalist and specialist species differ in their behavioral plasticity. We postulate that insight into behavioral variability in the foraging behavior of natural enemies may be a help, if not a prerequisite, for the efficient application of parasitoids in pest management.     

Automated analysis of behavior: A computer‐controlled system for drug screening and the investigation of learning

Efforts to understand cognition will be greatly facilitated by computerized systems that enable the automated analysis of animal behavior. A number of controversies in the invertebrate learning field have resulted from difficulties inherent in manual experiments. Driven by the necessity to overcome these problems during investigation of neural function in planarian flatworms and frog larvae, we designed and developed a prototype for an inexpensive, flexible system that enables automated control and analysis of behavior and learning. Applicable to a variety of small animals such as flatworms and zebrafish, this system allows automated analysis of innate behavior, as well as of learning and memory in a plethora of conditioning paradigms. We present here the schematics of a basic prototype, which overcomes experimenter effects and operator tedium, enabling a large number of animals to be analyzed with transparent on‐line access to primary data. A scaled‐up version of this technology represents an efficient methodology to screen pharmacological and genetic libraries for novel neuroactive reagents of basic and biomedical relevance. © 2006 Wiley Periodicals, Inc. J Neurobiol, 2006     

Intelligent high‐throughput intervention testing platform in Daphnia

We present a novel platform for testing the effects of interventions on the life‐ and healthspan of a short‐lived freshwater organism with complex behavior and physiology—the planktonic crustacean Daphnia magna. Within this platform, dozens of complex behavioral features of both routine motion and response to stimuli are continuously quantified over large synchronized cohorts via an automated phenotyping pipeline. We build predictive machine‐learning models calibrated using chronological age and extrapolate onto phenotypic age. We further apply the model to estimate the phenotypic age under pharmacological perturbation. Our platform provides a scalable framework for drug screening and characterization in both life‐long and instant assays as illustrated using a long‐term dose‐response profile of metformin and a short‐term assay of well‐studied substances such as caffeine and alcohol.     

Hyperactivity,startle reactivity and cell‐proliferation deficits are resistant to chronic lithium treatment in adult Nr2e1frc/frc mice

The NR2E1 region on Chromosome 6q21‐22 has been repeatedly linked to bipolar disorder (BP) and NR2E1 has been associated with BP, and more specifically bipolar I disorder (BPI). In addition, patient sequencing has shown an enrichment of rare candidate‐regulatory variants. Interestingly, mice carrying either spontaneous (Nr2e1^frc) or targeted (Tlx^?) deletions of Nr2e1 (here collectively known as Nr2e1‐null) show similar neurological and behavioral anomalies, including hypoplasia of the cerebrum, reduced neural stem cell proliferation, extreme aggression and deficits in fear conditioning; these are the traits that have been observed in some patients with BP. Thus, NR2E1 is a positional and functional candidate for a role in BP. However, no Nr2e1‐null mice have been fully evaluated for behaviors used to model BP in rodents or pharmacological responses to drugs effective in treating BP symptoms. In this study we examine Nr2e1^frc/frc mice, homozygous for the spontaneous deletion, for abnormalities in activity, learning and information processing, and cell proliferation; these are the phenotypes that are either affected in patients with BP or commonly assessed in rodent models of BP. The effect of lithium, a drug used to treat BP, was also evaluated for its ability to attenuate Nr2e1^frc/frc behavioral and neural stem cell‐proliferation phenotypes. We show for the first time that Nr2e1‐null mice exhibit extreme hyperactivity in the open field as early as postnatal day 18 and in the home cage, deficits in open‐field habituation and passive avoidance, and surprisingly, an absence of acoustic startle. We observed a reduction in neural stem/progenitor cell proliferation in Nr2e1^frc/frc mice, similar to that seen in other Nr2e1‐null strains. These behavioral and cell‐proliferation phenotypes were resistant to chronic‐adult‐lithium treatment. Thus, Nr2e1^frc/frc mice exhibit behavioral traits used to model BP in rodents, but our results do not support Nr2e1^frc/frc mice as pharmacological models for BP.     

Learning set formation in a group of Guinea baboons (Papio papio): Importance of the behavioral variable measured

A recent report of one-trial learning in a group of saddle-back tamarins (Saguinus fuscicollis) conflicted with views of learning set formation based on traditional techniques employing isolated subjects. An experiment is reported in which a group of Guinea baboons (Papio papio) was given a series of discrimination and habit reversal tasks. Both one-trial learning and learning set formation occurred. Analysis of spatial behavior revealed that the group learned in a single trial to discriminate stocked from unstocked zones. Improvement in successes (reinforced “digging”) was progressive but not rapid, indicating learning set formation. It appears that outcomes depend on the behavioral variables chosen.     

Early‐life foraging: Behavioral responses of newly fledged albatrosses to environmental conditions

In order to survive and later recruit into a population, juvenile animals need to acquire resources through the use of innate and/or learnt behaviors in an environment new to them. For far‐ranging marine species, such as the wandering albatross Diomedea exulans, this is particularly challenging as individuals need to be able to rapidly adapt and optimize their movement strategies in response to the highly dynamic and heterogeneous nature of their open‐ocean pelagic habitats. Critical to this is the development and flexibility of dispersal and exploratory behaviors. Here, we examine the movements of eight juvenile wandering albatrosses, tracked using GPS/Argos satellite transmitters for eight months following fledging, and compare these to the trajectories of 17 adults to assess differences and similarities in behavioral strategies through time. Behavioral clustering algorithms (Expectation Maximization binary Clustering) were combined with multinomial regression analyses to investigate changes in behavioral mode probabilities over time, and how these may be influenced by variations in day duration and in biophysical oceanographic conditions. We found that juveniles appeared to quickly acquire the same large‐scale behavioral strategies as those employed by adults, although generally more time was spent resting at night. Moreover, individuals were able to detect and exploit specific oceanographic features in a manner similar to that observed in adults. Together, the results of this study suggest that while shortly after fledging juvenile wandering albatrosses are able to employ similar foraging strategies to those observed in adults, additional skills need to be acquired during the immature period before the efficiency of these behaviors matches that of adults.     

Individual acquisition of “stick pounding” behavior by naïve chimpanzees

Many studies investigating culture in nonhuman animals tend to focus on the inferred need of social learning mechanisms that transmit the form of a behavior to explain the population differences observed in wild animal behavioral repertoires. This research focus often results in studies overlooking the possibility of individuals being able to develop behavioral forms without requiring social learning. The disregard of individual learning abilities is most clearly observed in the nonhuman great ape literature, where there is a persistent claim that chimpanzee behaviors, in particular, require various forms of social learning mechanisms. These special social learning abilities have been argued to explain the acquisition of the relatively large behavioral repertoires observed across chimpanzee populations. However, current evidence suggests that although low‐fidelity social learning plays a role in harmonizing and stabilizing the frequency of behaviors within chimpanzee populations, some (if not all) of the forms that chimpanzee behaviors take may develop independently of social learning. If so, they would be latent solutions—behavioral forms that can (re‐)emerge even in the absence of observational opportunities, via individual (re)innovations. Through a combination of individual and low‐fidelity social learning, the population‐wide patterns of behaviors observed in great ape species are then established and stably maintained. This is the Zone of Latent Solutions (ZLS) hypothesis. The current study experimentally tested the ZLS hypothesis for pestle pounding, a wild chimpanzee behavior. We tested the reinnovation of this behavior in semi‐wild chimpanzees at Chimfunshi Wildlife Orphanage in Zambia, Africa, (N = 90, tested in four social groups). Crucially, all subjects were naïve to stick pounding before testing. Three out of the four tested groups reinnovated stick pounding—clearly demonstrating that this behavioral form does not require social learning. These findings provide support for the ZLS hypothesis alongside further evidence for the individual learning abilities of chimpanzees.