The effect of a prosocial environment on health and well-being during the first COVID-19 lockdown and a year later.

The outset of the COVID-19 pandemic was characterized by prolonged periods of chronic stress and social isolation. While studies have investigated the changes to well-being (WB) during this period, the impact of the social environment on long-term physical and mental health requires further study. This study aimed to assess the factors influencing WB and health outcomes, with the hypothesis that a positive social environment would play a significant immediate and long-term role in improving WB and preventing the effects of anxiety associated with the pandemic. At time point 1 (April 2020), an Israeli sample of 206 participants (84% female, mean age 31.5) responded to traditional questionnaires assessing mental health and social support. Factors affecting WB were assessed within subjects during the first COVID-19 lockdown for 6 weeks using a daily survey (Beiwe phone application). A year later, in May 2021, at time point 2, the initial questionnaires were readministered to a subset of the same participants (N = 94). We found that anxiety during the first lockdown adversely affected WB and predicted health and WB deterioration a year later. In contrast, a high quality of social relationships was associated with better short- and long-term WB, and mitigated the adverse effects of anxiety. Daily activities, including physical activity, meditation, and romantic relations, were also positively associated with WB during the first lockdown but did not have long-term effects. In summary, our study underscores the enduring health advantages of a positive social environment, particularly during stressful periods. These results have implications for health policymakers: programs which support individuals with high anxiety and low support, by integrating them into community-based interventions, promise to enhance well-being (WB) and health, as well as to fortify the community as a whole.

Memoryless Optimality: Neurons Do Not Need Adaptation to Optimally Encode Stimuli With Arbitrarily Complex Statistics.

Our neurons seem capable of handling any type of data, regardless of its scale or statistical properties. In this letter, we suggest that optimal coding may occur at the single-neuron level without requiring memory, adaptation, or evolutionary-driven fit to the stimuli. We refer to a neural circuit as optimal if it maximizes the mutual information between its inputs and outputs. We show that often encountered differentiator neurons, or neurons that respond mainly to changes in the input, are capable of using all their information capacity when handling samples of any statistical distribution. We demonstrate this optimality using both analytical methods and simulations. In addition to demonstrating the simplicity and elegance of neural processing, this result might provide a way to improve the handling of data by artificial neural networks.

Animal behavior and animal personality from a non-human perspective: Getting help from the machine.

We can now track the position of every fly's leg or immerse a tiny fish inside a virtual world by monitoring its gaze in real time. Yet capturing animals' posture or gaze is not like understanding their behavior. Instead, behaviors are still often interpreted by human observers in an anthropomorphic manner. Even newer tools that automatically classify behaviors rely on human observers for the choice of behaviors. In this perspective, we suggest a roadmap toward a "human-free" interpretation of behavior. We present several recent advances, including our recent work on animal personalities. Personality both underlies behavioral differences among individuals and is consistent over time. A mathematical formulation of this idea has allowed us to measure mouse traits objectively, map behaviors across species (humans included), and explore the biological basis of behavior. Our goal is to enable "machine translation" of raw movement data into intelligible human concepts en route to improving our understanding of animals and people.

Wireless Optogenetic Stimulation of Oxytocin Neurons in a Semi-natural Setup Dynamically Elevates Both Pro-social and Agonistic Behaviors.

Complex behavioral phenotyping techniques are becoming more prevalent in the field of behavioral neuroscience, and thus methods for manipulating neuronal activity must be adapted to fit into such paradigms. Here, we present a head-mounted, magnetically activated device for wireless optogenetic manipulation that is compact, simple to construct, and suitable for use in group-living mice in an enriched semi-natural arena over several days. Using this device, we demonstrate that repeated activation of oxytocin neurons in male mice can have different effects on pro-social and agonistic behaviors, depending on the social context. Our findings support the social salience hypothesis of oxytocin and emphasize the importance of the environment in the study of social neuromodulators. Our wireless optogenetic device can be easily adapted for use in a variety of behavioral paradigms, which are normally hindered by tethered light delivery or a limited environment.

Identity domains capture individual differences from across the behavioral repertoire.

Personality traits can offer considerable insight into the biological basis of individual differences. However, existing approaches toward understanding personality across species rely on subjective criteria and limited sets of behavioral readouts, which result in noisy and often inconsistent outcomes. Here we introduce a mathematical framework for describing individual differences along dimensions with maximum consistency and discriminative power. We validate this framework in mice, using data from a system for high-throughput longitudinal monitoring of group-housed male mice that yields a variety of readouts from across the behavioral repertoire of individual animals. We demonstrate a set of stable traits that capture variability in behavior and gene expression in the brain, allowing for better-informed mechanistic investigations into the biology of individual differences.

Ucn3 and CRF-R2 in the medial amygdala regulate complex social dynamics.

Social encounters are associated with varying degrees of emotional arousal and stress. The mechanisms underlying adequate socioemotional balance are unknown. The medial amygdala (MeA) is a brain region associated with social behavior in mice. Corticotropin-releasing factor receptor type-2 (CRF-R2) and its specific ligand urocortin-3 (Ucn3), known components of the behavioral stress response system, are highly expressed in the MeA. Here we show that mice deficient in CRF-R2 or Ucn3 exhibit abnormally low preference for novel conspecifics. MeA-specific knockdown of Crfr2 (Crhr2) in adulthood recapitulated this phenotype. In contrast, pharmacological activation of MeA CRF-R2 or optogenetic activation of MeA Ucn3 neurons increased preference for novel mice. Furthermore, chemogenetic inhibition of MeA Ucn3 neurons elicited pro-social behavior in freely behaving groups of mice without affecting their hierarchal structure. These findings collectively suggest that the MeA Ucn3-CRF-R2 system modulates the ability of mice to cope with social challenges.

High-order social interactions in groups of mice.

Social behavior in mammals is often studied in pairs under artificial conditions, yet groups may rely on more complicated social structures. Here, we use a novel system for tracking multiple animals in a rich environment to characterize the nature of group behavior and interactions, and show strongly correlated group behavior in mice. We have found that the minimal models that rely only on individual traits and pairwise correlations between animals are not enough to capture group behavior, but that models that include third-order interactions give a very accurate description of the group. These models allow us to infer social interaction maps for individual groups. Using this approach, we show that environmental complexity during adolescence affects the collective group behavior of adult mice, in particular altering the role of high-order structure. Our results provide new experimental and mathematical frameworks for studying group behavior and social interactions. DOI:http://dx.doi.org/10.7554/eLife.00759.001.

Postnatal ablation of POMC neurons induces an obese phenotype characterized by decreased food intake and enhanced anxiety-like behavior.

Proopiomelanocortin (POMC) neurons in the arcuate nucleus of the hypothalamus are central components of systems regulating appetite and energy homeostasis. Here we report on the establishment of a mouse model in which the ribonuclease III ribonuclease Dicer-1 has been specifically deleted from POMC-expressing neurons (POMC(ΔDCR)), leading to postnatal cell death. Mice are born phenotypically normal, at the expected genetic ratio and with normal hypothalamic POMC-mRNA levels. At 6 weeks of age, no POMC neurons/cells could be detected either in the arcuate nucleus or in the pituitary of POMC(ΔDCR) mice. POMC(ΔDCR) develop progressive obesity secondary to decreased energy expenditure but unrelated to food intake, which was surprisingly lower than in control mice. Reduced expression of AgRP and ghrelin receptor in the hypothalamus and reduced uncoupling protein 1 expression in brown adipose tissue can potentially explain the decreased food intake and decreased heat production, respectively, in these mice. Fasting glucose levels were dramatically elevated in POMC(ΔDCR) mice and the glucose tolerance test revealed marked glucose intolerance in these mice. Secondary to corticotrope ablation, basal and stress-induced corticosterone levels were undetectable in POMC(ΔDCR) mice. Despite this lack of activation of the neuroendocrine stress response, POMC(ΔDCR) mice exhibited an anxiogenic phenotype, which was accompanied with elevated levels of hypothalamic corticotropin-releasing factor and arginine-vasopressin transcripts. In conclusion, postnatal ablation of POMC neurons leads to enhanced anxiety and the development of obesity despite decreased food intake and glucocorticoid deficiency.