An automated learning apparatus for classical conditioning of Lymnaea stagnalis

Toward Real-Time Animal Tracking with Integrated Stimulus Control for Automated Conditioning in Aquatic Eco-Neurotoxicology

Aquatic eco-neurotoxicology is an emerging field that requires new analytical systems to study the effects of pollutants on animal behaviors. This is especially true if we are to gain insights into one of the least studied aspects: the potential perturbations that neurotoxicants can have on cognitive behaviors. The paucity of experimental data is partly caused by a lack of low-cost technologies for the analysis of higher-level neurological functions (e.g., associative learning) in small aquatic organisms. Here, we present a proof-of-concept prototype that utilizes a new real-time animal tracking software for on-the-fly video analysis and closed-loop, external hardware communications to deliver stimuli based on specific behaviors in aquatic organisms, spanning three animal phyla: chordates (fish, frog), platyhelminthes (flatworm), and arthropods (crustacean). The system's open-source software features an intuitive graphical user interface and advanced adaptive threshold-based image segmentation for precise animal detection. We demonstrate the precision of animal tracking across multiple aquatic species with varying modes of locomotion. The presented technology interfaces easily with low-cost and open-source hardware such as the Arduino microcontroller family for closed-loop stimuli control. The new system has potential future applications in eco-neurotoxicology, where it could enable new opportunities for cognitive research in diverse small aquatic model organisms.

Induction of LTM following an Insulin Injection

The pond snail Lymnaea stagnalis learns conditioned taste aversion (CTA) and consolidates it into long-term memory (LTM). One-day food-deprived snails (day 1 snails) show the best CTA learning and memory, whereas more severely food-deprived snails (5 d) do not express good memory. However, previous studies showed that CTA-LTM was indeed formed in 5-d food-deprived snails (day 5 snails), but its recall was prevented by the effects of food deprivation. CTA-LTM recall in day 5 snails was expressed following 7 d of feeding and then 1 d of food deprivation (day 13 snails). In the present study, we thus hypothesized that memory recall occurs because day 13 snails are in an optimal internal state. One day of food deprivation before the memory test in day 13 snails increased the mRNA level of molluscan insulin-related peptide (MIP) in the CNS. Thus, we further hypothesized that an injection of insulin into day 5 snails following seven additional days with access to food (day 12 snails) activates CTA neurons and mimics the food deprivation state before the memory test in day 13 snails. Day 12 snails injected with insulin could recall the memory. In addition, the simultaneous injection of an anti-insulin receptor antibody and insulin into day 12 snails did not allow memory recall. Insulin injection also decreased the hemolymph glucose concentration. Together, the results suggest that an optimal internal state (i.e., a spike in insulin release and specific glucose levels) are necessary for LTM recall following CTA training in snails.

Real-Time Analysis of Animal Feeding Behavior With a Low-Calculation-Power CPU

Our goal was to develop an automated system to determine whether animals have learned and changed their behavior in real-time using a low calculation-power central processing unit (CPU). The bottleneck of real-time analysis is the speed of image recognition. For fast image recognition, 99.5% of the image was excluded from image recognition by distinguishing between the subject and the background. We achieved this by applying a binarization and connected-component labeling technique. This task is important for developing a fully automated learning apparatus. The use of such an automated system can improve the efficiency and accuracy of biological studies. The pond snail Lymnaea stagnails can be classically conditioned to avoid food that naturally elicits feeding behavior, and to consolidate this aversion into long-term memory. Determining memory status in the snail requires real-time analysis of the number of bites the snail makes in response to food presentation. The main algorithm for counting bites comprises two parts: extracting the mouth images from the recorded video and measuring the bite rate corresponding to the memory status. Reinforcement-supervised learning and image recognition were used to extract the mouth images. A change in the size of the mouth area was used as the cue for counting the number of bites. The accuracy of the final judgment of whether or not the snail had learned was the same as that determined by human observation. This method to improve the processing speed of image recognition has the potential for broad application beyond biological fields.

Monoamines, Insulin and the Roles They Play in Associative Learning in Pond Snails

Molluscan gastropods have long been used for studying the cellular and molecular mechanisms underlying learning and memory. One such gastropod, the pond snail Lymnaea stagnalis, exhibits long-term memory (LTM) following both classical and operant conditioning. Using Lymnaea, we have successfully elucidated cellular mechanisms of learning and memory utilizing an aversive classical conditioning procedure, conditioned taste aversion (CTA). Here, we present the behavioral changes following CTA training and show that the memory score depends on the duration of food deprivation. Then, we describe the relationship between the memory scores and the monoamine contents of the central nervous system (CNS). A comparison of learning capability in two different strains of Lymnaea, as well as the filial 1 (F1) cross from the two strains, presents how the memory scores are correlated in these populations with monoamine contents. Overall, when the memory scores are better, the monoamine contents of the CNS are lower. We also found that as the insulin content of the CNS decreases so does the monoamine contents which are correlated with higher memory scores. The present review deepens the relationship between monoamine and insulin contents with the memory score.

Comparison of brain monoamine content in three populations of Lymnaea that correlates with taste-aversive learning ability

To find a causal mechanism of learning and memory is a heuristically important topic in neuroscience. In the pond snail Lymnaea stagnalis, the following experimental facts have accrued regarding a classical conditioning procedure known as conditioned taste aversion (CTA): (1) one-day food-deprived Dutch snails have superior CTA memory formation; (2) the one-day food-deprived snails have a low monoamine content (e.g., serotonin, dopamine, octopamine) in their central nervous system (CNS); (3) fed or five-day food-deprived snails have poorer CTA memory and a higher monoamine content; (4) the Dutch snails form better CTA memory than the Canadian TC1 strain; and, (5) the F₁ cross snails between the Dutch and Canadian TC1 strains also form poor CTA memory. Here, in one-day food-deprived snails, we measured the monoamine content in the CNSs of the 3 populations. In most instances, the monoamine content of the Dutch strain was lower than in the other two populations. The F₁ cross snails had the highest monoamine content. A lower monoamine content is correlated with the better CTA memory formation.

Two Strains of Lymnaea stagnalis and the Progeny from Their Mating Display Differential Memory-Forming Ability on Associative Learning Tasks

The pond snail Lymnaea stagnalis learns and forms long-term memory (LTM) following both operant conditioning of aerial respiratory behavior and classical conditioning of taste aversive behavior. In the present study, we examined whether there are interstrain differences in the ability to form LTM following these two types of conditioning. A strain of Lymnaea (TC1) collected in Alberta, Canada exhibits superior memory-forming ability following aerial respiratory operant conditioning compared to a laboratory-reared strain of Lymnaea from Netherlands known as the Dutch strain. We asked whether the offspring of the Canadian TC1 and Dutch snails (i.e., filial 1 (F₁) cross snails) would have the superior memory ability and found, rather, that their memory ability was average like the Dutch snails. That is, the Canadian TC1 snails have superior ability for LTM formation following aerial respiratory operant conditioning, but the Dutch and the generated F₁ cross have average ability for memory forming. We next examined the Canadian TC1, Dutch and F₁ cross snails for their ability to learn and form memory following conditioned taste aversion (CTA). All three populations showed similar associative CTA responses. However, both LTM formation and the ratio of good-to-poor performers in the memory retention test were much better in the Dutch snails than the Canadian TC1 and F₁ cross snails. The memory abilities of the Canadian TC1 and F₁ cross snails were average. Our present findings, therefore, suggest that snails of different strains have different memory abilities, and the F₁ cross snails do not inherit the memory ability from the smart strain. To our knowledge, there have been a limited number of studies examining differences in memory ability among invertebrate strains, with the exception of studies using mutant flies.