A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment

Behavioral and genetic correlates of heterogeneity in learning performance in individual honeybees, Apis mellifera

Learning an olfactory discrimination task leads to heterogeneous results in honeybees with some bees performing very well and others at low rates. Here we investigated this behavioral heterogeneity and asked whether it was associated with particular gene expression patterns in the bee's brain. Bees were individually conditioned using a sequential conditioning protocol involving several phases of olfactory learning and retention tests. A cumulative score was used to differentiate the tested bees into high and low performers. The rate of CS+ odor learning was found to correlate most strongly with a cumulative performance score extracted from all learning and retention tests. Microarray analysis of gene expression in the mushroom body area of the brains of these bees identified a number of differentially expressed genes between high and low performers. These genes are associated with diverse biological functions, such as neurotransmission, memory formation, cargo trafficking and development.

Dysregulation of BMP, Wnt, and Insulin Signaling in Fragile X Syndrome

Drosophila models of neurological disease contribute tremendously to research progress due to the high conservation of human disease genes, the powerful and sophisticated genetic toolkit, and the rapid generation time. Fragile X syndrome (FXS) is the most prevalent heritable cause of intellectual disability and autism spectrum disorders, and the Drosophila FXS disease model has been critical for the genetic screening discovery of new intercellular secretion mechanisms. Here, we focus on the roles of three major signaling pathways: BMP, Wnt, and insulin-like peptides. We present Drosophila FXS model defects compared to mouse models in stem cells/embryos, the glutamatergic neuromuscular junction (NMJ) synapse model, and the developing adult brain. All three of these secreted signaling pathways are strikingly altered in FXS disease models, giving new mechanistic insights into impaired cellular outcomes and neurological phenotypes. Drosophila provides a powerful genetic screening platform to expand understanding of these secretory mechanisms and to test cellular roles in both peripheral and central nervous systems. The studies demonstrate the importance of exploring broad genetic interactions and unexpected regulatory mechanisms. We discuss a number of research avenues to pursue BMP, Wnt, and insulin signaling in future FXS investigations and the development of potential therapeutics.

Behavior Individuality: A Focus on Drosophila melanogaster

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

Active Inferants: An Active Inference Framework for Ant Colony Behavior

In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. Active inference is a multiscale approach to behavioral modeling that is being applied across settings in theoretical biology and ethology. The ant colony is a classic case system in the function of distributed systems in terms of stigmergic decision-making and information sharing. Here we specify and simulate a Markov decision process (MDP) model for ant colony foraging. We investigate a well-known paradigm from laboratory ant colony behavioral experiments, the alternating T-maze paradigm, to illustrate the ability of the model to recover basic colony phenomena such as trail formation after food location discovery. We conclude by outlining how the active inference ant colony foraging behavioral model can be extended and situated within a nested multiscale framework and systems approaches to biology more generally.

Multi-camera field monitoring reveals costs of learning for parasitoid foraging behaviour

Dynamic conditions in nature have led to the evolution of behavioural traits that allow animals to use information on local circumstances and adjust their behaviour accordingly, for example through learning. Although learning can improve foraging efficiency, the learned information can become unreliable as the environment continues to change. This could lead to potential fitness costs when memories holding such unreliable information persist. Indeed, persistent unreliable memory was found to reduce the foraging efficiency of the parasitoid Cotesia glomerata under laboratory conditions.

Here, we evaluated the effect of such persistent unreliable memory on the foraging behaviour of C. glomerata in the field. This is a critical step in studies of foraging theory, since animal behaviour evolved under the complex conditions present in nature.

Existing methods provide little detail on how parasitoids interact with their environment in the field, therefore we developed a novel multi‐camera system that allowed us to trace parasitoid foraging behaviour in detail. With this multi‐camera system, we studied how persistent unreliable memory affected the foraging behaviour of C. glomerata when these memories led parasitoids to plants infested with non‐host caterpillars in a semi‐field set‐up.

Our results demonstrate that persistent unreliable memory can lead to maladaptive foraging behaviour in C. glomerata under field conditions and increased the likelihood of oviposition in the non‐host caterpillar Mamestra brassica. Furthermore, these time‐ and egg‐related costs can be context dependent, since they rely on the plant species used.

These results provide us with new insight on how animals use previously obtained information in naturally complex and dynamic foraging situations and confirm that costs and benefits of learning depend on the environment animals forage in. Although behavioural studies of small animals in natural habitats remain challenging, novel methods such as our multi‐camera system contribute to understanding the nuances of animal foraging behaviour.

Spontaneous motor-behavior abnormalities in two Drosophila models of neurodevelopmental disorders

Mutations in hundreds of genes cause neurodevelopmental disorders with abnormal motor behavior alongside cognitive deficits. Boys with fragile X syndrome (FXS), a leading monogenic cause of intellectual disability, often display repetitive behaviors, a core feature of autism. By direct observation and manual analysis, we characterized spontaneous-motor-behavior phenotypes of Drosophila dfmr1 mutants, an established model for FXS. We recorded individual 1-day-old adult flies, with mature nervous systems and prior to the onset of aging, in small arenas. We scored behavior using open-source video-annotation software to generate continuous activity timelines, which were represented graphically and quantitatively. Young dfmr1 mutants spent excessive time grooming, with increased bout number and duration; both were rescued by transgenic wild-type dfmr1⁺. By two grooming-pattern measures, dfmr1-mutant flies showed elevated repetitions consistent with perseveration, which is common in FXS. In addition, the mutant flies display a preference for grooming posterior body structures, and an increased rate of grooming transitions from one site to another. We raise the possibility that courtship and circadian rhythm defects, previously reported for dfmr1 mutants, are complicated by excessive grooming. We also observed significantly increased grooming in CASK mutants, despite their dramatically decreased walking phenotype. The mutant flies, a model for human CASK-related neurodevelopmental disorders, displayed consistently elevated grooming indices throughout the assay, but transient locomotory activation immediately after placement in the arena. Based on published data identifying FMRP-target transcripts and functional analyses of mutations causing human genetic neurodevelopmental disorders, we propose the following proteins as candidate mediators of excessive repetitive behaviors in FXS: CaMKIIα, NMDA receptor subunits 2A and 2B, NLGN3, and SHANK3. Together, these fly-mutant phenotypes and mechanistic insights provide starting points for drug discovery to identify compounds that reduce dysfunctional repetitive behaviors.

Automated high-throughput individual tracking system for insect behavior: Applications on memory retention in parasitic wasps

BACKGROUND

Insects are important models to study learning and memory formation in both an ecological and neuroscience context due to their small size, behavioral flexibility and ecological diversity. Measuring memory retention is often done through simple time-consuming set-ups, producing only a single parameter for conditioned behavior. We wished to obtain higher sample sizes with fewer individuals to measure olfactory memory retention more efficiently.

NEW METHOD

The high-throughput individual T-maze uses commercially available tracking software, Ethovision XT^®, in combination with a Perspex stack of plates as small as 18 × 18 cm, which accommodates 36 olfactory T-mazes, where each individual wasp could choose between two artificial odors. Various behavioral parameters, relevant to memory retention, were acquired in this set-up; first choice, residence time, giving up time and zone entries. From these parameters a performance index was calculated as a measure of memory retention. Groups of 36 wasps were simultaneously tested within minutes, resulting in efficient acquisition of sufficiently high sample sizes.

RESULTS

This system was tested with two very different parasitic wasp species, the larval parasitoid Cotesia glomerata and the pupal parasitoid Nasonia vitripennis, and has proven to be highly suitable for testing memory retention in both these species.

COMPARISON WITH EXISTING METHODS

Unlike other bioassays, this system allows for both high-throughput and recording of detailed individual behavior.

CONCLUSIONS

The high-throughput individual T-maze provides us with a standardized high-throughput, labor-efficient and cost-effective method to test various kinds of behavior, offering excellent opportunities for comparative studies of various aspects of insect behavior.

Ethoscopes: An open platform for high-throughput ethomics

Here, we present the use of ethoscopes, which are machines for high-throughput analysis of behavior in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable. They perform, in real-time, tracking and profiling of behavior by using a supervised machine learning algorithm, are able to deliver behaviorally triggered stimuli to flies in a feedback-loop mode, and are highly customizable and open source. Ethoscopes can be built easily by using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope.

Logical fallacies in animal model research

Background

Animal models of human behavioural deficits involve conducting experiments on animals with the hope of gaining new knowledge that can be applied to humans. This paper aims to address risks, biases, and fallacies associated with drawing conclusions when conducting experiments on animals, with focus on animal models of mental illness.

Conclusions

Researchers using animal models are susceptible to a fallacy known as false analogy, where inferences based on assumptions of similarities between animals and humans can potentially lead to an incorrect conclusion. There is also a risk of false positive results when evaluating the validity of a putative animal model, particularly if the experiment is not conducted double-blind. It is further argued that animal model experiments are reconstructions of human experiments, and not replications per se, because the animals cannot follow instructions. This leads to an experimental setup that is altered to accommodate the animals, and typically involves a smaller sample size than a human experiment. Researchers on animal models of human behaviour should increase focus on mechanistic validity in order to ensure that the underlying causal mechanisms driving the behaviour are the same, as relying on face validity makes the model susceptible to logical fallacies and a higher risk of Type 1 errors. We discuss measures to reduce bias and risk of making logical fallacies in animal research, and provide a guideline that researchers can follow to increase the rigour of their experiments.