Automated maternal behavior during early life in rodents (AMBER) pipeline

Pubertal maternal presence reduces anxiety and increases adult neurogenesis in Kunming mice offspring

Puberty is a critical period of emotional development and neuroplasticity. However, most studies have focused on early development, with limited research on puberty, particularly the parental presence. In this study, four groups were established, and pubertal maternal presence (PMP) was assessed until postnatal days 21 (PD21), 28 (PD28), 35 (PD35), and 42 (PD42), respectively. The social interaction and anxiety behaviors, as well as the expression of oxytocin (OT) in the paraventricular nucleus (PVN) and supraoptic nucleus (SON), and the number of new generated neurons and the expression of estrogen receptor alpha (ERα) in the dentate gyrus (DG) were assessed. The results suggest that there is a lot of physical contact between the mother and offspring from 21 to 42 days of age, which reduces anxiety in both female and male offspring in adulthood; for example, the PMP increased the amount of time mice spent in the center area in the open field experiment and in the bright area in the light-dark box experiment. PMP increased OT expression in the PVN and SON and the number of newly generated neurons in the DG. However, there was a sexual difference in ERα, with ERα increasing in females but decreasing in males. In conclusion, PMP reduces the anxiety of offspring in adulthood, increases OT in the PVN and SON, and adult neurogenesis; ERα in the DG may be involved in this process.

Comprehensive ethological analysis of fear expression in rats using DeepLabCut and SimBA machine learning model

Introduction

Defensive responses to threat-associated cues are commonly evaluated using conditioned freezing or suppression of operant responding. However, rats display a broad range of behaviors and shift their defensive behaviors based on immediacy of threats and context. This study aimed to systematically quantify the defensive behaviors that are triggered in response to threat-associated cues and assess whether they can accurately be identified using DeepLabCut in conjunction with SimBA.

Methods

We evaluated behavioral responses to fear using the auditory fear conditioning paradigm. Observable behaviors triggered by threat-associated cues were manually scored using Ethovision XT. Subsequently, we investigated the effects of diazepam (0, 0.3, or 1 mg/kg), administered intraperitoneally before fear memory testing, to assess its anxiolytic impact on these behaviors. We then developed a DeepLabCut + SimBA workflow for ethological analysis employing a series of machine learning models. The accuracy of behavior classifications generated by this pipeline was evaluated by comparing its output scores to the manually annotated scores.

Results

Our findings show that, besides conditioned suppression and freezing, rats exhibit heightened risk assessment behaviors, including sniffing, rearing, free-air whisking, and head scanning. We observed that diazepam dose-dependently mitigates these risk-assessment behaviors in both sexes, suggesting a good predictive validity of our readouts. With adequate amount of training data (approximately > 30,000 frames containing such behavior), DeepLabCut + SimBA workflow yields high accuracy with a reasonable transferability to classify well-represented behaviors in a different experimental condition. We also found that maintaining the same condition between training and evaluation data sets is recommended while developing DeepLabCut + SimBA workflow to achieve the highest accuracy.

Discussion

Our findings suggest that an ethological analysis can be used to assess fear learning. With the application of DeepLabCut and SimBA, this approach provides an alternative method to decode ongoing defensive behaviors in both male and female rats for further investigation of fear-related neurobiological underpinnings.

Computer vision analysis of mother-infant interaction identified efficient pup retrieval in V1b receptor knockout mice

Close contact between lactating rodent mothers and their infants is essential for effective nursing. Whether the mother's effort to retrieve the infants to their nest requires the vasopressin-signaling via V1b receptor has not been fully defined. To address this question, V1b receptor knockout (V1bKO) and control mice were analyzed in pup retrieval test. Because an exploring mother in a new test cage randomly accessed to multiple infants in changing backgrounds over time, a computer vision-based deep learning analysis was applied to continuously calculate the distances between the mother and the infants as a parameter of their relationship. In an open-field, a virgin female V1bKO mice entered fewer times into the center area and moved shorter distances than wild-type (WT). While this behavioral pattern persisted in V1bKO mother, the pup retrieval test demonstrated that total distances between a V1bKO mother and infants came closer in a shorter time than with a WT mother. Moreover, in the medial preoptic area, parts of the V1b receptor transcripts were detected in galanin- and c-fos-positive neurons following maternal stimulation by infants. This research highlights the effectiveness of deep learning analysis in evaluating the mother-infant relationship and the critical role of V1b receptor in pup retrieval during the early lactation phase.

Simple Behavioral Analysis (SimBA) as a platform for explainable machine learning in behavioral neuroscience

The study of complex behaviors is often challenging when using manual annotation due to the absence of quantifiable behavioral definitions and the subjective nature of behavioral annotation. Integration of supervised machine learning approaches mitigates some of these issues through the inclusion of accessible and explainable model interpretation. To decrease barriers to access, and with an emphasis on accessible model explainability, we developed the open-source Simple Behavioral Analysis (SimBA) platform for behavioral neuroscientists. SimBA introduces several machine learning interpretability tools, including SHapley Additive exPlanation (SHAP) scores, that aid in creating explainable and transparent behavioral classifiers. Here we show how the addition of explainability metrics allows for quantifiable comparisons of aggressive social behavior across research groups and species, reconceptualizing behavior as a sharable reagent and providing an open-source framework. We provide an open-source, graphical user interface (GUI)-driven, well-documented package to facilitate the movement toward improved automation and sharing of behavioral classification tools across laboratories.

Postnatal maternal care moderates the effects of prenatal bisphenol exposure on offspring neurodevelopmental, behavioral, and transcriptomic outcomes

Bisphenols (BP), including BPA and "BPA-free" structural analogs, are commonly used plasticizers that are present in many plastics and are known endocrine disrupting chemicals. Prenatal exposure to BPA has been associated with negative neurodevelopmental and behavioral outcomes in children and in rodent models. Prenatal BPA exposure has also been shown to impair postnatal maternal care provisioning, which can also affect offspring neurodevelopment and behavior. However, there is limited knowledge regarding the biological effects of prenatal exposure to bisphenols other than BPA and the interplay between prenatal bisphenol exposure and postnatal maternal care on adult behavior. The purpose of the current study was to determine the interactive impact of prenatal bisphenol exposure and postnatal maternal care on neurodevelopment and behavior in rats. Our findings suggest that the effects of prenatal bisphenol exposure on eye-opening, adult attentional set shifting and anxiety-like behavior in the open field are dependent on maternal care in the first five days of life. Interestingly, maternal care might also attenuate the effects of prenatal bisphenol exposure on eye opening and adult attentional set shifting. Finally, transcriptomic profiles in male and female medial prefrontal cortex and amygdala suggest that the interactive effects of prenatal bisphenol exposure and postnatal maternal care converge on estrogen receptor signaling and are involved in biological processes related to gene expression and protein translation and synthesis. Overall, these findings indicate that postnatal maternal care plays a critical role in the expression of the effects of prenatal bisphenol exposure on neurodevelopment and adult behavior. Understanding the underlying biological mechanisms involved might allow us to identify potential avenues to mitigate the adverse effects of prenatal bisphenol exposure and improve health and well-being in human populations.

Effects of ketamine on rat social behavior as analyzed by DeepLabCut and SimBA deep learning algorithms

Traditional methods of rat social behavior assessment are extremely time-consuming and susceptible to the subjective biases. In contrast, novel digital techniques allow for rapid and objective measurements. This study sought to assess the feasibility of implementing a digital workflow to compare the effects of (R,S)-ketamine and a veterinary ketamine preparation Vetoquinol (both at 20 mg/kg) on the social behaviors of rat pairs. Historical and novel videos were used to train the DeepLabCut neural network. The numerical data generated by DeepLabCut from 14 video samples, representing various body parts in time and space were subjected to the Simple Behavioral Analysis (SimBA) toolkit, to build classifiers for 12 distinct social and non-social behaviors. To validate the workflow, previously annotated by the trained observer historical videos were analyzed with SimBA classifiers, and regression analysis of the total time of social interactions yielded R 2 = 0.75, slope 1.04; p < 0.001 (N = 101). Remarkable similarities between human and computer annotations allowed for using the digital workflow to analyze 24 novel videos of rats treated with vehicle and ketamine preparations. Digital workflow revealed similarities in the reduction of social behavior by both compounds, and no substantial differences between them. However, the digital workflow also demonstrated ketamine-induced increases in self-grooming, increased transitions from social contacts to self-grooming, and no effects on adjacent lying time. This study confirms and extends the utility of deep learning in analyzing rat social behavior and highlights its efficiency and objectivity. It provides a faster and objective alternative to human workflow.