Biology subjects

Forkosh, O.

Publications and source records attributed to Forkosh, O..

6 recordsLinked to original sources

bioRxiv2025

Identity Domains Reveal How Life Experiences and the Microbiome Shape Individuality and Uncover the Presence of Social Memory in Drosophila

Personality is comprised of enduring traits that shape behavior across contexts and over time. Yet outside humans, research often equates individuality with personality, focusing on how one animal differs from another in each behavior. This overlooks the latent space that spans an animals behavioral repertoire, how it is shaped by innate tendencies and prior experiences, and how it differs from transient factors. Here, we bridge this gap by integrating a data-driven framework with unbiased trait interpretation via large language models, revealing how social, sexual, and physiological conditions systematically alter the expression of personality-like traits in Drosophila melanogaster. This approach yielded four identities: space-use (exploration), time-use (social investment), avoidance, and aggression. Large language models produced strong consensus on the interpretation of some of these axes and divergence on others. These dimensions proved stable within individuals yet shifted predictably following mating, isolation, and microbiome manipulation, often in sex dependent ways. Notably, flies behaved differently toward familiar and unfamiliar peers, revealing a capacity for social memory. These findings bridge temperament and personality, showing how life history reshapes baseline tendencies into individualized profiles within constrained dimensions. They establish Drosophila as a tractable system for uncovering the biological logic of personality and advancing cross-species principles for individuality research. Significance StatementPersonality is often treated as a hallmark of complex brains, yet we show that fruit flies express stable behavioral identities with systematic, experience driven plasticity. Using a mathematical framework, we resolve four stable traits and map how sex, social experience, and the gut microbiome shift their expression. We further demonstrate social recognition in flies: they treat familiar cage mates differently from newcomers over repeated encounters, evidencing social memory, a striking result given their simple nervous system. Finally, we introduce large language models to provide objective, reproducible interpretations of trait dimensions, reducing human bias. These advances establish a general, quantitative approach to personality and social behavior in a tractable genetic model.

neuroscience↗

bioRxiv2024

Group social dynamics in a semi-natural setup reveal an adaptive value for aggression in male mice

BackgroundMaladaptive aggression in humans is associated with several psychiatric conditions and lacks effective treatment. Nevertheless, aggression constitutes an essential behavior throughout the animal kingdom as long as it is tightly regulated. Studying how social dominance hierarchies (SDH) regulate aggression and access to resources in an enriched environment (EE) can narrow the translational gap between aggression in animal models and humans normal and pathological behavior. MethodsThe social box (SB) is a semi-natural setup for automatic and prolonged monitoring of mouse group dynamics. We utilized the SB to decipher complex tradeoffs between aggression, social avoidance, resource allocation, and dominance in two mouse models of increased aggression: (i) a model of early exposure to EE and (ii) a model of oxytocin receptor deficiency (OxtR-/-). While EE increases aggression as an adaptive response to external stimuli, hyper-aggression in OxtR-/- mice is accompanied by marked abnormalities in social behavior. ResultsEE groups exhibited significant social avoidance, and an increased proportion of their encounters developed into aggressive interactions, resulting in lower levels of exploratory activity and overall aggression. The hierarchy in EE was more stable than in control groups, and dominance was correlated with access to resources. In OxtR-/- groups, mice engaged in excessive social encounters and aggressive chasing, accompanied by increased overall activity. In OxtR-/- groups, dominance hierarchies existed but were not correlated with access to resources. ConclusionMeasuring aggression and social dominance hierarchies in a semi-natural setup reveals the adaptive value of aggression in EE and OxtR-/- mice, respectively. This approach can enhance translational research of pathological aggression.

neuroscience↗

bioRxiv2022

The triadic structure of personality space in the house mouse resembles that of species with known personality badges; suggesting reciprocal hierarchies are an evolutionary motif with mixed strategies being more common

Differences in animal personalities are generally hard to measure - even in an animal as common as the house mouse. Yet, in some rare cases, nature has provided us with clear visual cues as to the nature of a specific individual. These so-called badges are the case for the side botched lizard, often referred to as the rock-paper-scissor lizard. Here, we show that mice have behavioral archetypes that are similar to the triadic social dynamics of the lizards. We find analogs in territoriality, aggressiveness, and pro-social behavior linking ultra-dominant, dominant, and subordinate mice to the lizards orange, blue, and yellow morphs accordingly. Yet, unlike the lizards, most mice in the study displayed mixed strategies rather than fall into clear behavioral archetypes. In such a case, it makes less sense to have distinct visual cues to distinguish between personalities. The result implies that, although visual distinctions are infrequent in nature, having multiple behavioral archetypes might serve as an evolutionary motif. In addition, we find that mammals, like mice, might have circular hierarchies, similar to the lizards, where no single behavioral strategy outweighs others.

animal behavior and cognition↗

bioRxiv2021

Cryptographic-like mechanism allows scatter-hoarders to cache and retrieve their food secretly

The brains extraordinary abilities are often associated with its ability to learn and adapt. But memory and plasticity have their limitations, especially when faced with tasks such as retrieving thousands of food items such as in the case of scatter-hoarding animals. Here, we suggest a brain mechanism that works by utilizing cryptographic principles in lieu of plasticity. Rather than memorizing the locations of their caches, as previously suggested, we propose that cache-hoarding animals use a single cryptographic-like mechanism for both caching and retrieval. The mathematical model we developed functions similarly to hippocampal spatial cells, which respond to an animals positional attention. We know that the region that activates each spatial cell remains consistent across subsequent visits to the same area but not between areas. This remapping, combined with the uniqueness of cognitive maps, produces a persistent crypto-hash function for both food caching and retrieval. We show that our model is consistent with previous observations, such as animals ability to prioritize food items that are perishable or by their nutritional value. The model makes several measurable predictions regarding scattered hoarding and what factors can limit an animals retrieval success. Finally, while focusing here on scatter-hoarding, the mechanism we present might be utilized by the brain in other ways providing essentially infinite retention capacity for structured data.

animal behavior and cognition↗

bioRxiv2020

Neurons need no adaptation to optimally code arbitrarily complex stimuli

Neural networks seem to be able to handle almost any task they face. This feat involves coping efficiently with different data types, at multiple scales, and with varying statistical properties. Here, we show that this so-called optimal coding can occur at the single-neuron level and does not require adaptation. Differentiator neurons, i.e., neurons that spike whenever there is an increase in the input stimuli, are capable of capturing arbitrary statistics and scale of practically any stimulus they encounter. We show this optimality both analytically and using simulations, which demonstrate how an ideal neuron can handle drastically different probability distributions. While the mechanism we present is an oversimplification of "real" neurons and does not necessarily capture all neuron types, this is also its strength since it can function alongside other neuronal goals such as data manipulation and learning. Depicting the simplicity of neural response to complex stimuli, this result may also indicate a straightforward way to improve current artificial neural networks.

neuroscience↗

bioRxiv2018

Identity domains in complex behavior: Toward a biology of personality

Personality traits 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, resulting in noisy and often inconsistent outcomes. Here, we introduce a mathematical framework for studying 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 mice that yields a variety of readouts from all across an individuals behavioral repertoire. We describe 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.

animal behavior and cognition↗