A reinforcement-learning model of active avoidance behavior: Differences between Sprague Dawley and Wistar-Kyoto rats

A primer on the use of computational modelling to investigate affective states, affective disorders and animal welfare in non-human animals

Objective measures of animal emotion-like and mood-like states are essential for preclinical studies of affective disorders and for assessing the welfare of laboratory and other animals. However, the development and validation of measures of these affective states poses a challenge partly because the relationships between affect and its behavioural, physiological and cognitive signatures are complex. Here, we suggest that the crisp characterisations offered by computational modelling of the underlying, but unobservable, processes that mediate these signatures should provide better insights. Although this computational psychiatry approach has been widely used in human research in both health and disease, translational computational psychiatry studies remain few and far between. We explain how building computational models with data from animal studies could play a pivotal role in furthering our understanding of the aetiology of affective disorders, associated affective states and the likely underlying cognitive processes involved. We end by outlining the basic steps involved in a simple computational analysis.

Strain differences in the drug transport capacity of intestinal glucose transporters in Sprague-Dawley versus Wistar rats, C57BL/6J versus Kunming mice

Designing oral drug delivery systems using intestinal glucose transporters (IGTs) may be one of the strategies for improving oral bioavailability of drugs. However, little is known about the biological factors affecting the drug transport capacity of IGTs. Gastrodin is a sedative drug with a structure very similar to glucose. It is a highly water-soluble phenolic glucoside. It can hardly enter the intestine through simple diffusion but exhibits good oral bioavailability of over 80%. We confirmed that gastrodin is absorbed via the intestinal glucose transport pathway. It has the highest oral bioavailability among the reported glycosides' active ingredients through this pathway. Thus, gastrodin is the most selective drug substrate of IGTs and can be used to evaluate the drug transport capacity of IGTs. Obviously, strain is one of the main biological factors affecting drug absorption. This study firstly compared the drug transport capacity of IGTs between SD rats and Wistar rats and between C57 mice and KM mice by pharmacokinetic experiments and single-pass intestinal perfusion experiments of gastrodin. Then, the sodium-dependent glucose transporter type 1 (SGLT1) and sodium-independent glucose transporters type 2 (GLUT2) in the duodenum, jejunum, ileum and colon of these animals were quantified using RT-qPCR and Western blot. The results showed that the oral bioavailability of gastrodin in Wistar rats was significantly higher than in SD rats and significantly higher in KM mice than in C57 mice. Gastrodin absorption significantly differed among different intestinal segments in SD rats, C57 mice and KM mice, except Wistar rats. RT-qPCR and Western blot demonstrated that the intestinal expression distribution of SGLT1 and GLUT2 in SD rats and C57 mice was duodenum ≈ jejunum > ileum > colon. SGLT1 expression did not differ among different intestinal segments in KM mice, whereas the intestinal expression distribution of GLUT2 was duodenum ≈ jejunum ≈ ileum > colon. However, the expression of SGLT1 and GLUT2 did not differ among different intestinal segments in Wistar rats. It was reported that the intestinal expression distribution of SGLT1 and GLUT2 in humans is duodenum > jejunum > ileum > colon. Hence, the intestinal expression distribution of SGLT1 and GLUT2 of SD rats and C57 mice was more similar to that in humans. In conclusion, the drug transport capacity of IGTs differs in different strains of rats and mice. SD rats and C57 mice are more suitable for evaluating the pharmacokinetics of glycosides' active ingredients absorbed via the intestinal glucose transport pathway.

Spontaneous instrumental avoidance learning in social contexts

Adaptation to our social environment requires learning how to avoid potentially harmful situations, such as encounters with aggressive individuals. Threatening facial expressions can evoke automatic stimulus-driven reactions, but whether their aversive motivational value suffices to drive instrumental active avoidance remains unclear. When asked to freely choose between different action alternatives, participants spontaneously-without instruction or monetary reward-developed a preference for choices that maximized the probability of avoiding angry individuals (sitting away from them in a waiting room). Most participants showed clear behavioral signs of instrumental learning, even in the absence of an explicit avoidance strategy. Inter-individual variability in learning depended on participants' subjective evaluations and sensitivity to threat approach feedback. Counterfactual learning best accounted for avoidance behaviors, especially in participants who developed an explicit avoidance strategy. Our results demonstrate that implicit defensive behaviors in social contexts are likely the product of several learning processes, including instrumental learning.

Preventive Effect of Limosilactobacillus fermentum SCHY34 on Lead Acetate-Induced Neurological Damage in SD Rats

Lead poisoning caused by lead pollution seriously affects people's health. Lactic acid bacteria has been shown to be useful for biological scavenging of lead. In this experiment, Sprague-Dawley (SD) rats were treated with 200 mg/L of lead acetate solution daily to induce chronic lead poisoning, and oral Limosilactobacillus fermentum (L. fermentum) SCHY34 to study its mitigation effects and mechanisms on rat neurotoxicity. The L. fermentum SCHY34 showed competent results on in vitro survival rate and the lead ion adsorption rate. Animal experiments showed that L. fermentum SCHY34 maintained the morphology of rat liver, kidney, and hippocampi, reduced the accumulation of lead in the blood, liver, kidney, and brain tissue. Further, L. fermentum SCHY34 alleviated the lead-induced decline in spatial memory and response capacity of SD rats, and also regulated the secretion of neurotransmitters and related enzyme activities in the brain tissue of rats, such as glutamate (Glu), monoamine oxidase (MAO), acetylcholinesterase (AchE), cyclic adenosine monophosphate (cAMP), and adenylate cyclase (AC). In addition, the expression of genes related to cognitive capacity, antioxidation, and anti-apoptotic in rat brain tissues were increased L. fermentum SCHY34 treatment, such as brain-derived neurotrophic factor (BDNF), c-fos, c-jun, superoxide dismutase (SOD)1/2, Nuclear factor erythroid 2-related factor 2 (Nrf2), and B-cell lymphoma 2 (Bcl-2), and so on. L. fermentum SCHY34 showed a great biological scavenging and potential effect on alleviating the toxicity of lead ions.

Dataset of active avoidance in Wistar-Kyoto and Sprague Dawley rats: Experimental data and reinforcement learning model code and output

Data were collected from 40 Wistar-Kyoto (WKY) and 40 Sprague Dawley (SD) rats during an active escape-avoidance experiment. Footshock could be avoided by pressing a lever during a danger period prior to onset of shock. If avoidance did not occur, a series of footshocks was administered, and the rat could press a lever to escape (terminate shocks). For each animal, data were simplified to the presence or absence of lever press and stimuli in each 12-second time frame. Using the pre-processed dataset, a reinforcement learning (RL) model, based on an actor-critic architecture, was utilized to estimate several different model parameters that best characterized each rat's behaviour during the experiment. Once individual model parameters were determined for all 80 rats, behavioural recovery simulations were run using the RL model with each animal's "best-fit" parameters; the simulated behaviour generated avoidance data (percent of trials avoided during a given experimental session) that could be compared across simulated rats, as is customarily done with empirical data. The datasets representing both the experimental data and the model-generated data can be interpreted in various ways to gain further insight into rat behaviour during avoidance and escape learning. Furthermore, the estimated parameters for each individual rat can be compared across groups. Thus, possible between-strain differences in model parameters can be detected, which might provide insights into strain differences in learning. The software implementing the RL model can also be applied to or serve as a template for other experiments involving acquisition learning. Reference for Co-Submission: K.M. Spiegler, J. Palmieri, K.C.H. Pang, C.E. Myers, A reinforcement-learning model of active avoidance behavior: Differences between Sprague-Dawley and Wistar-Kyoto rats. Behav. Brain Res. (2020 Jun 22[epub ahead of print])  doi: 10.1016/j.bbr.2020.112784.