An Evolutionary Hypothesis of Binary Opposition in Functional Incompatibility about Habenular Asymmetry in Vertebrates

Many vertebrates have asymmetrical circuits in the nervous system. There are two types of circuit asymmetry. Asymmetrical circuits in sensory and/or motor systems are usually related to lateralized behaviors. It has been hypothesized that spatial asymmetry in the environment and/or social interactions has led to the evolution of asymmetrical circuits by natural selection. There are also asymmetrical circuits that are not related to lateralized behaviors. These circuits lie outside of the sensory and motor systems. A typical example is found in the habenula (Hb), which has long been known to be asymmetrical in many vertebrates, but has no remarkable relationship to lateralized behaviors. Instead, the Hb is a hub wherein information conveyed to the unilateral Hb is relayed to diverging bilateral nuclei, which is unlikely to lead to lateralized behavior. Until now, there has been no hypothesis regarding the evolution of Hb asymmetry. Here, we propose a new hypothesis that binary opposition in functional incompatibility applies selection pressure on the habenular circuit and leads to asymmetry. Segregation of the incompatible functions on either side of the habenula is likely to enhance information processing ability via creating shorter circuits and reducing the cost of circuit duplication, resulting in benefits for survival. In zebrafish and mice, different evolutionary strategies are thought to be involved in Hb asymmetry. In zebrafish, which use a strategy of structurally fixed asymmetry, the asymmetrical dorsal Hb leads to constant behavioral choices in binary opposition. In contrast, in mice, which use a strategy of functionally flexible lateralization, the symmetrical lateral Hb is functionally lateralized. This makes it possible to process complicated information and to come to variable behavioral choices, depending on the specific situation. These strategies are thought to be selected for and preserved by evolution under selection pressures of rigidity and flexibility of sociability in zebrafish and mice, respectively, as they are beneficial for survival. This hypothesis is highly valuable because it explains how the Hb evolved differently in terms of asymmetry and lateralization among different species. In addition, one can propose possible experiments for the verification of this hypothesis in future research

Enriched Environment Experience Overcomes Learning Deficits and Depressive-Like Behavior Induced by Juvenile Stress

Mood disorders affect the lives and functioning of millions each year. Epidemiological studies indicate that childhood trauma is predominantly associated with higher rates of both mood and anxiety disorders. Exposure of rats to stress during juvenility (JS) (27–29 days of age) has comparable effects and was suggested as a model of induced predisposition for these disorders. The importance of the environment in the regulation of brain, behavior and physiology has long been recognized in biological, social and medical sciences. Here, we studied the effects of JS on emotional and cognitive aspects of depressive-like behavior in adulthood, on Hypothalamic-Pituitary-Adrenal (HPA) axis reactivity and on the expression of cell adhesion molecule L1 (L1-CAM). Furthermore, we combined it with the examination of potential reversibility by enriched environment (EE) of JS – induced disturbances of emotional and cognitive aspects of behavior in adulthood. Three groups were tested: Juvenile Stress –subjected to Juvenile stress; Enriched Environment – subjected to Juvenile stress and then, from day 30 on to EE; and Naïves. In adulthood, coping and stress responses were examined using the elevated plus-maze, open field, novel setting exploration and two way shuttle avoidance learning. We found that, JS rats showed anxiety- and depressive-like behaviors in adulthood, altered HPA axis activity and altered L1-CAM expression. Increased expression of L1-CAM was evident among JS rats in the basolateral amygdala (BLA) and Thalamus (TL). Furthermore, we found that EE could reverse most of the effects of Juvenile stress, both at the behavioral, endocrine and at the biochemical levels. The interaction between JS and EE resulted in an increased expression of L1-CAM in dorsal cornu ammonis (CA) area 1 (dCA1)

Abundance models improve spatial and temporal prioritization of conservation resources

Conservation prioritization requires knowledge about organism distribution and density. This information is often inferred from models that estimate the probability of species occurrence rather than from models that estimate species abundance, because abundance data are harder to obtain and model. However, occurrence and abundance may not display similar patterns and therefore development of robust, scalable, abundance models is critical to ensuring that scarce conservation resources are applied where they can have the greatest benefits. Motivated by a dynamic land conservation program, we develop and assess a general method for modeling relative abundance using citizen science monitoring data. Weekly estimates of relative abundance and occurrence were compared for prioritizing times and locations of conservation actions for migratory waterbird species in California, USA. We found that abundance estimates consistently provided better rankings of observed counts than occurrence estimates. Additionally, the relationship between abundance and occurrence was nonlinear and varied by species and season. Across species, locations prioritized by occurrence models had only 10-58% overlap with locations prioritized by abundance models, highlighting that occurrence models will not typically identify the locations of highest abundance that are vital for conservation of populations.</p

Appendix A. Extended descriptions of the data sources, data processing, STEM modeling framework, and local occurrence and abundance models.

Extended descriptions of the data sources, data processing, STEM modeling framework, and local occurrence and abundance models