Sparsity in an artificial neural network predicts beauty: Towards a model of processing-based aesthetics.

Generations of scientists have pursued the goal of defining beauty. While early scientists initially focused on objective criteria of beauty ('feature-based aesthetics'), philosophers and artists alike have since proposed that beauty arises from the interaction between the object and the individual who perceives it. The aesthetic theory of fluency formalizes this idea of interaction by proposing that beauty is determined by the efficiency of information processing in the perceiver's brain ('processing-based aesthetics'), and that efficient processing induces a positive aesthetic experience. The theory is supported by numerous psychological results, however, to date there is no quantitative predictive model to test it on a large scale. In this work, we propose to leverage the capacity of deep convolutional neural networks (DCNN) to model the processing of information in the brain by studying the link between beauty and neuronal sparsity, a measure of information processing efficiency. Whether analyzing pictures of faces, figurative or abstract art paintings, neuronal sparsity explains up to 28% of variance in beauty scores, and up to 47% when combined with a feature-based metric. However, we also found that sparsity is either positively or negatively correlated with beauty across the multiple layers of the DCNN. Our quantitative model stresses the importance of considering how information is processed, in addition to the content of that information, when predicting beauty, but also suggests an unexpectedly complex relationship between fluency and beauty.

Social and sexual consequences of facial femininity in a non-human primate.

In humans, femininity shapes women's interactions with both genders, but its influence on animals remains unknown. Using 10 years of data on a wild primate, we developed an artificial intelligence-based method to estimate facial femininity from naturalistic portraits. Our method explains up to 30% of the variance in perceived femininity in humans, competing with classical methods using standardized pictures taken under laboratory conditions. We then showed that femininity estimated on 95 female mandrills significantly correlated with various socio-sexual behaviors. Unexpectedly, less feminine female mandrills were approached and aggressed more frequently by both sexes and received more male copulations, suggesting a positive valuation of masculinity attributes rather than a perception bias. This study contributes to understand the role of femininity on animal's sociality and offers a framework for non-invasive research on visual communication in behavioral ecology.

Deep learning for studying drawing behavior: A review.

In recent years, computer science has made major advances in understanding drawing behavior. Artificial intelligence, and more precisely deep learning, has displayed unprecedented performance in the automatic recognition and classification of large databases of sketches and drawings collected through touchpad devices. Although deep learning can perform these tasks with high accuracy, the way they are performed by the algorithms remains largely unexplored. Improving the interpretability of deep neural networks is a very active research area, with promising recent advances in understanding human cognition. Deep learning thus offers a powerful framework to study drawing behavior and the underlying cognitive processes, particularly in children and non-human animals, on whom knowledge is incomplete. In this literature review, we first explore the history of deep learning as applied to the study of drawing along with the main discoveries in this area, while proposing open challenges. Second, multiple ideas are discussed to understand the inherent structure of deep learning models. A non-exhaustive list of drawing datasets relevant to deep learning approaches is further provided. Finally, the potential benefits of coupling deep learning with comparative cultural analyses are discussed.

The Mandrillus Face Database: A portrait image database for individual and sex recognition, and age prediction in a non-human primate.

The Mandrillus Project is a long-term field research project in ecology and evolutionary biology, monitoring, since 2012, a natural population of mandrills (Mandrillus sphinx; primate) located in Southern Gabon. The Mandrillus Face Database was launched at the beginning of the project and now contains 29,495 photographic portraits collected on 397 individuals from this population, from birth to death for some of them. Portrait images have been obtained by manually processing images taken in the field with DSLR cameras: faces have been cropped to remove the ears and rotated to align the eyes horizontally. The database provides portrait images resized to 224 × 224 pixels associated with several manually annotated labels: individual identity, sex, age, face view, and image quality. Labels are stored within the image metadata and in a table accompanying the image database. This database will allow training and comparing methods on individual and sex recognition, and age prediction in a non-human animal.

Mandrill mothers associate with infants who look like their own offspring using phenotype matching.

Behavioral discrimination of kin is a key process structuring social relationships in animals. In this study, we provide evidence for discrimination towards non-kin by third-parties through a mechanism of phenotype matching. In mandrills, we recently demonstrated increased facial resemblance among paternally related juvenile and adult females indicating adaptive opportunities for paternal kin recognition. Here, we hypothesize that mandrill mothers use offspring's facial resemblance with other infants to guide offspring's social opportunities towards similar-looking ones. Using deep learning for face recognition in 80 wild mandrill infants, we first show that infants sired by the same father resemble each other the most, independently of their age, sex or maternal origin, extending previous results to the youngest age class. Using long-term behavioral observations on association patterns, and controlling for matrilineal origin, maternal relatedness and infant age and sex, we then show, as predicted, that mothers are spatially closer to infants that resemble their own offspring more, and that this maternal behavior leads to similar-looking infants being spatially associated. We then discuss the different scenarios explaining this result, arguing that an adaptive maternal behavior is a likely explanation. In support of this mechanism and using theoretical modeling, we finally describe a plausible evolutionary process whereby mothers gain fitness benefits by promoting nepotism among paternally related infants. This mechanism, that we call 'second-order kin selection', may extend beyond mother-infant interactions and has the potential to explain cooperative behaviors among non-kin in other social species, including humans.

Using Artificial Intelligence to Analyze Non-Human Drawings: A First Step with Orangutan Productions.

Drawings have been widely used as a window to the mind; as such, they can reveal some aspects of the cognitive and emotional worlds of other animals that can produce them. The study of non-human drawings, however, is limited by human perception, which can bias the methodology and interpretation of the results. Artificial intelligence can circumvent this issue by allowing automated, objective selection of features used to analyze drawings. In this study, we use artificial intelligence to investigate seasonal variations in drawings made by Molly, a female orangutan who produced more than 1299 drawings between 2006 and 2011 at the Tama Zoological Park in Japan. We train the VGG19 model to first classify the drawings according to the season in which they are produced. The results show that deep learning is able to identify subtle but significant seasonal variations in Molly's drawings, with a classification accuracy of 41.6%. We use VGG19 to investigate the features that influence this seasonal variation. We analyze separate features, both simple and complex, related to color and patterning, and to drawing content and style. Content and style classification show maximum performance for moderately complex, highly complex, and holistic features, respectively. We also show that both color and patterning drive seasonal variation, with the latter being more important than the former. This study demonstrates how deep learning can be used to objectively analyze non-figurative drawings and calls for applications to non-primate species and scribbles made by human toddlers.

Identification of Mediterranean marine gobies (Actinopterygii: Gobiidae) of the continental shelf from photographs of in situ individuals.

Numerous photographs of live fishes posted by anglers and divers on social media and citizen science databases are important sources of information for ichthyological research. However, validating records that extend the known ecology and bathymetric or geographic distribution of species should rely on a rigorous identification process. The family Gobiidae, with their small size, superficial resemblance among species and high species richness are particularly difficult to identify. Therefore, the identification from photographs of live individuals of Mediterranean marine gobies from the continental shelf was studied. A dichotomous identification key is provided based on photographs of live individuals, allowing positive identification of 41 out of the 66 species reviewed in this publication. Then, for all 66 species we provide a brief description of important characters, which can be used for provisional identification for those species that could not be positively identified using the key. Pending further progress in identification of live individuals, we suggest that records extending the known geographic and ecological species distribution be taken into account only if they could be validated using the dichotomous identification key.

Identification of enigmatic Mediterranean fish Gobius ater Bellotti, 1888 (Teleostei: Gobiidae) based on morphology from underwater photographs.

Gobius ater Bellotti, 1888 is the Mediterranean gobiid species whose live appearance has remained unknown the longest since its description. A goby observed in southern France in 2021 is here identified as G. ater based on a diagnosis of morphological characters visible on high-quality underwater photographs. Then, the authors provide the first description of colouration in live G. ater and a species diagnosis based on colouration. This diagnosis allows the authors to validate a previous photographic record, also from France. Reviewing all claims of G. ater, they argue that only seven records are unambiguously valid, including the two photographic records presented here.

The aesthetic value of reef fishes is globally mismatched to their conservation priorities.

Reef fishes are closely connected to many human populations, yet their contributions to society are mostly considered through their economic and ecological values. Cultural and intrinsic values of reef fishes to the public can be critical drivers of conservation investment and success, but remain challenging to quantify. Aesthetic value represents one of the most immediate and direct means by which human societies engage with biodiversity, and can be evaluated from species to ecosystems. Here, we provide the aesthetic value of 2,417 ray-finned reef fish species by combining intensive evaluation of photographs of fishes by humans with predicted values from machine learning. We identified important biases in species' aesthetic value relating to evolutionary history, ecological traits, and International Union for Conservation of Nature (IUCN) threat status. The most beautiful fishes are tightly packed into small parts of both the phylogenetic tree and the ecological trait space. In contrast, the less attractive fishes are the most ecologically and evolutionary distinct species and those recognized as threatened. Our study highlights likely important mismatches between potential public support for conservation and the species most in need of this support. It also provides a pathway for scaling-up our understanding of what are both an important nonmaterial facet of biodiversity and a key component of nature's contribution to people, which could help better anticipate consequences of species loss and assist in developing appropriate communication strategies.

Sexual signaling pattern correlates with habitat pattern in visually ornamented fishes.

Sexual signal design is an evolutionary puzzle that has been partially solved by the hypothesis of sensory drive. Framed in signal detection theory, sensory drive posits that the attractiveness of a signal depends on its detectability, measured as contrast with the background. Yet, cognitive scientists have shown that humans prefer images that match the spatial statistics of natural scenes. The explanation is framed in information theory, whereby attractiveness is determined by the efficiency of information processing. Here, we apply this framework to animals, using Fourier analysis to compare the spatial statistics of body patterning in ten species of darters (Etheostoma spp.) with those of their respective habitats. We find a significant correlation between the spatial statistics of darter patterns and those of their habitats for males, but not for females. Our results support a sensory drive hypothesis that recognizes efficient information processing as a driving force in signal evolution.

Examining the link between relaxed predation and bird coloration on islands.

Insular ecosystems share analogous ecological conditions, leading to patterns of convergent evolution that are collectively termed as the 'island syndrome'. In birds, part of this syndrome is a tendency for a duller plumage, possibly as a result of relaxed sexual selection. Despite this global pattern, some insular species display a more colourful plumage than their mainland relatives, but why this occurs has remained unexplained. Here, we examine the hypothesis that these cases of increased plumage coloration on islands could arise through a relaxation of predation pressure. We used comparative analyses to investigate whether average insular richness of raptors of suitable mass influences the plumage colourfulness and brightness across 110 pairs of insular endemic species and their closest mainland relatives. As predicted, we find a likely negative relationship between insular coloration and insular predation while controlling for mainland predation and coloration, suggesting that species were more likely to become more colourful as the number of insular predators decreased. By contrast, plumage brightness was not influenced by predation pressure. Relaxation from predation, together with drift, might thus be a key mechanism of species phenotypic responses to insularity.

Comparing theory-driven and data-driven attractiveness models using images of real women's faces.

Facial attractiveness plays a critical role in social interaction, influencing many different social outcomes. However, the factors that influence facial attractiveness judgments remain relatively poorly understood. Here, we used a sample of 594 young adult female face images to compare the performance of existing theory-driven models of facial attractiveness and a data-driven (i.e., theory-neutral) model. Our data-driven model and a theory-driven model including various traits commonly studied in facial attractiveness research (asymmetry, averageness, sexual dimorphism, body mass index, and representational sparseness) performed similarly well. By contrast, univariate theory-driven models performed relatively poorly. These results (a) highlight the utility of data driven models of facial attractiveness and (b) suggest that theory-driven research on facial attractiveness would benefit from greater adoption of multivariate approaches, rather than the univariate approaches that they currently almost exclusively employ. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Processing bias: extending sensory drive to include efficacy and efficiency in information processing.

Communication signals often comprise an array of colours, lines, spots, notes or odours that are arranged in complex patterns, melodies or blends. Receiver perception is assumed to influence preference and thus the evolution of signal design, but evolutionary biologists still struggle to understand how perception, preference and signal design are mechanistically linked. In parallel, the field of empirical aesthetics aims to understand why people like some designs more than others. The model of processing bias discussed here is rooted in empirical aesthetics, which posits that preferences are influenced by the emotional system as it monitors the dynamics of information processing and that attractive signals have effective designs that maximize information transmission, efficient designs that allow information processing at low metabolic cost, or both. We refer to the causal link between preference and the emotionally rewarding experience of effective and efficient information processing as the processing bias, and we apply it to the evolutionary model of sensory drive. A sensory drive model that incorporates processing bias hypothesizes a causal chain of relationships between the environment, perception, pleasure, preference and ultimately the evolution of signal design, both simple and complex.

Colour spaces in ecology and evolutionary biology.

The recognition that animals sense the world in a different way than we do has unlocked important lines of research in ecology and evolutionary biology. In practice, the subjective study of natural stimuli has been permitted by perceptual spaces, which are graphical models of how stimuli are perceived by a given animal. Because colour vision is arguably the best-known sensory modality in most animals, a diversity of colour spaces are now available to visual ecologists, ranging from generalist and basic models allowing rough but robust predictions on colour perception, to species-specific, more complex models giving accurate but context-dependent predictions. Selecting among these models is most often influenced by historical contingencies that have associated models to specific questions and organisms; however, these associations are not always optimal. The aim of this review is to provide visual ecologists with a critical perspective on how models of colour space are built, how well they perform and where their main limitations are with regard to their most frequent uses in ecology and evolutionary biology. We propose a classification of models based on their complexity, defined as whether and how they model the mechanisms of chromatic adaptation and receptor opponency, the nonlinear association between the stimulus and its perception, and whether or not models have been fitted to experimental data. Then, we review the effect of modelling these mechanisms on predictions of colour detection and discrimination, colour conspicuousness, colour diversity and diversification, and for comparing the perception of colour traits between distinct perceivers. While a few rules emerge (e.g. opponent log-linear models should be preferred when analysing very distinct colours), in general model parameters still have poorly known effects. Colour spaces have nonetheless permitted significant advances in ecology and evolutionary biology, and more progress is expected if ecologists compare results between models and perform behavioural experiments more routinely. Such an approach would further contribute to a better understanding of colour vision and its links to the behavioural ecology of animals. While visual ecology is essentially a transfer of knowledge from visual sciences to evolutionary ecology, we hope that the discipline will benefit both fields more evenly in the future.

Beauty is in the efficient coding of the beholder.

Sexual ornaments are often assumed to be indicators of mate quality. Yet it remains poorly known how certain ornaments are chosen before any coevolutionary race makes them indicative. Perceptual biases have been proposed to play this role, but known biases are mostly restricted to a specific taxon, which precludes evaluating their general importance in sexual selection. Here we identify a potentially universal perceptual bias in mate choice. We used an algorithm that models the sparseness of the activity of simple cells in the primary visual cortex (or V1) of humans when coding images of female faces. Sparseness was found positively correlated with attractiveness as rated by men and explained up to 17% of variance in attractiveness. Because V1 is adapted to process signals from natural scenes, in general, not faces specifically, our results indicate that attractiveness for female faces is influenced by a visual bias. Sparseness and more generally efficient neural coding are ubiquitous, occurring in various animals and sensory modalities, suggesting that the influence of efficient coding on mate choice can be widespread in animals.

Worldwide patterns of bird colouration on islands.

Island environments share distinctive characteristics that offer unique opportunities to investigate parallel evolution. Previous research has produced evidence of an island syndrome for morphological traits, life-history strategies and ecological niches, but little is known about the response to insularity of other important traits such as animal signals. Here, we tested whether birds' plumage colouration is part of the island syndrome. We analysed with spectrophotometry the colouration of 116 species endemic to islands and their 116 closest mainland relatives. We found a pattern of reduced brightness and colour intensity for both sexes on islands. In addition, we found a decrease in the number of colour patches on islands that, in males, was associated with a decrease in the number of same-family sympatric species. These results demonstrate a worldwide pattern of parallel colour changes on islands and suggest that a relaxation of selection on species recognition may be one of the mechanisms involved.

Adaptation of flower and fruit colours to multiple, distinct mutualists.

Communication in plant-animal mutualisms frequently involves multiple perceivers. A fundamental uncertainty is whether and how species adapt to communicate with groups of mutualists having distinct sensory abilities. We quantified the colour conspicuousness of flowers and fruits originating from one European and two South American plant communities, using visual models of pollinators (bee and fly) and seed dispersers (bird, primate and marten). We show that flowers are more conspicuous than fruits to pollinators, and the reverse to seed dispersers. In addition, flowers are more conspicuous to pollinators than to seed dispersers and the reverse for fruits. Thus, despite marked differences in the visual systems of mutualists, flower and fruit colours have evolved to attract multiple, distinct mutualists but not unintended perceivers. We show that this adaptation is facilitated by a limited correlation between flower and fruit colours, and by the fact that colour signals as coded at the photoreceptor level are more similar within than between functional groups (pollinators and seed dispersers). Overall, these results provide the first quantitative demonstration that flower and fruit colours are adaptations allowing plants to communicate simultaneously with distinct groups of mutualists.

Increasing land-use intensity decreases floral colour diversity of plant communities in temperate grasslands.

To preserve biodiversity and ecosystem functions in a globally changing world it is crucial to understand the effect of land use on ecosystem processes such as pollination. Floral colouration is known to be central in plant-pollinator interactions. To date, it is still unknown whether land use affects the colouration of flowering plant communities. To assess the effect of land use on the diversity and composition of flower colours in temperate grasslands, we collected data on the number of flowering plant species, blossom cover and flower reflectance spectra from 69 plant communities in two German regions, Schwäbische Alb (SA) and Hainich-Dün (HD). We analysed reflectance data of flower colours as they are perceived by honeybees and studied floral colour diversity based upon spectral loci of each flowering plant species in the Maxwell triangle. Before the first mowing, flower colour diversity decreased with increasing land-use intensity in SA, accompanied by a shift of mean flower colours of communities towards an increasing proportion of white blossom cover in both regions. By changing colour characteristics of grasslands, we suggest that increasing land-use intensity can affect the flower visitor fauna in terms of visitor behaviour and diversity. These changes may in turn influence plant reproduction in grassland plant communities. Our results indicate that land use is likely to affect communication processes between plants and flower visitors by altering flower colour traits.

The evolution of the multicoloured face of mandrills: insights from the perceptual space of colour vision.

Multicomponent signals consist of several traits that are perceived as a whole. Although many animals rely on multicomponent signals to communicate, the selective pressures shaping these signals are still poorly understood. Previous work has mainly investigated the evolution of multicomponent signals by studying each trait individually, which may not accurately reflect the selective pressures exerted by the holistic perception of signal receivers. Here, we study the design of the multicoloured face of an Old World primate, the mandrill (Mandrillus sphinx), in relation to two aspects of signalling that are expected to be selected by receivers: conspicuousness and information. Using reflectance data on the blue and red colours of the faces of 34 males and a new method of hue vectorisation in a perceptual space of colour vision, we show that the blue hue maximises contrasts to both the red hue and the foliage background colouration, thereby increasing the conspicuousness of the whole display. We further show that although blue saturation, red saturation and the contrast between blue and red colours are all correlated with dominance, dominance is most accurately indicated by the blue-red contrast. Taken together our results suggest that the evolution of blue and red facial colours in male mandrills are not independent and are likely driven by the holistic perception of conspecifics. In this view, we propose that the multicoloured face of mandrills acts as a multicomponent signal. Last, we show that information accuracy increases with the conspicuousness of the whole display, indicating that both aspects of signalling can evolve in concert.

Cyto-nuclear discordance in the phylogeny of Ficus section Galoglychia and host shifts in plant-pollinator associations.

BACKGROUND: Hybridization events are relatively common in vascular plants. However, the frequency of these events is unevenly distributed across the plant phylogeny. Plant families in which individual species are pollinated by specific pollinator species are predicted to be less prone to hybridization than other families. However, exceptions may occur within these families, when pollinators shift host-plant species. Indeed, host shifts are expected to increase the rate of hybridization events. Pollinators of Ficus section Galoglychia are suspected to have changed host repeatedly, based on several cases of incongruence between plant phylogeny and taxonomy, and insect phylogeny and taxonomy. We tracked cyto-nuclear discordance across section Galoglychia as evidence for hybridization. To achieve a proper global view, we first clarified the monophyly of section Galoglychia as it had been questioned by recent phylogenetic studies. Moreover, we investigated if fig size could be a factor facilitating host shifts. RESULTS: Phylogenetic chloroplast and nuclear results demonstrated the monophyly of section Galoglychia. Within section Galoglychia, we detected several cases of statistically significant cyto-nuclear discordance. Discordances concern both terminal nodes of the phylogenetic trees and one deep node defining relationships between subsections. Because nuclear phylogeny is congruent with morphological taxonomy, discordances were caused by the chloroplast phylogeny. Introgressive hybridization was the most likely explanation for these discordances. We also detected that subsections pollinated by several wasp genera had smaller figs and were pollinated by smaller wasps than subsections pollinated by a single wasp genus. CONCLUSION: As hypothesized, we discovered evidences of past hybridization in Ficus section Galoglychia. Further, introgression was only detected in subsections presenting incongruence between plant and pollinator phylogenies and taxonomy. This supports the hypothesis that host shift is the cause for plant-pollinator incongruence. Moreover, small fig size could facilitate host shifts. Eventually, this study demonstrates that non-coding chloroplast markers are valuable to resolve deep nodes in Ficus phylogeny.