Sure enough: efficient Bayesian learning and choice

Does Amount of Information Support Aesthetic Values?

Obtaining information from the world is important for survival. The brain, therefore, has special mechanisms to extract as much information as possible from sensory stimuli. Hence, given its importance, the amount of available information may underlie aesthetic values. Such information-based aesthetic values would be significant because they would compete with others to drive decision-making. In this article, we ask, "What is the evidence that amount of information support aesthetic values?" An important concept in the measurement of informational volume is entropy. Research on aesthetic values has thus used Shannon entropy to evaluate the contribution of quantity of information. We review here the concepts of information and aesthetic values, and research on the visual and auditory systems to probe whether the brain uses entropy or other relevant measures, specially, Fisher information, in aesthetic decisions. We conclude that information measures contribute to these decisions in two ways: first, the absolute quantity of information can modulate aesthetic preferences for certain sensory patterns. However, the preference for volume of information is highly individualized, with information-measures competing with organizing principles, such as rhythm and symmetry. In addition, people tend to be resistant to too much entropy, but not necessarily, high amounts of Fisher information. We show that this resistance may stem in part from the distribution of amount of information in natural sensory stimuli. Second, the measurement of entropic-like quantities over time reveal that they can modulate aesthetic decisions by varying degrees of surprise given temporally integrated expectations. We propose that amount of information underpins complex aesthetic values, possibly informing the brain on the allocation of resources or the situational appropriateness of some cognitive models.

Two-dimensional reward evaluation in mice

When choosing among multi-attribute options, integrating the full information may be computationally costly and time-consuming. So-called non-compensatory decision rules only rely on partial information, for example when a difference on a single attribute overrides all others. Such rules may be ecologically more advantageous, despite being economically suboptimal. Here, we present a study that investigates to what extent animals rely on integrative rules (using the full information) versus non-compensatory rules when choosing where to forage. Groups of mice were trained to obtain water from dispensers varying along two reward dimensions: volume and probability. The mice’s choices over the course of the experiment suggested an initial reliance on integrative rules, later displaced by a sequential rule, in which volume was evaluated before probability. Our results also demonstrate that while the evaluation of probability differences may depend on the reward volumes, the evaluation of volume differences is seemingly unaffected by the reward probabilities.

Bayesian updating during development predicts genotypic differences in plasticity

Interactions between genotypes and environments are central to evolutionary genetics, but such interactions are typically described, rather than predicted from theory. Recent Bayesian models of development generate specific predictions about genotypic differences in developmental plasticity (changes in the value of a given trait as a result of a given experience) based on genotypic differences in the value of the trait that is expressed by naïve subjects. We used these models to make a priori predictions about the effects of an aversive olfactory conditioning regime on the response of Drosophila melanogaster larvae to the odor of ethyl acetate. As predicted, across 116 genotypes initial trait values were related to plasticity. Genotypes most strongly attracted to the odor of ethyl acetate when naïve reduced their attraction scores more as a result of the aversive training regime than those less attracted to the same odor when naïve. Thus, as predicted, the variance across genotypes in attraction scores was higher before than after the shared experience. These results support predictions generated by Bayesian models of development and indicate that such models can be successfully used to investigate how variation across genotypes in information derived from ancestors combines with personal experience to differentially affect developmental plasticity in response to specific types of experience.

Response to Comment on "Cognition-mediated evolution of low-quality floral nectars"

Pyke and Waser claim that our virtual pollination ecology model makes unrealistic assumptions and fails to predict observed nectar concentrations of bat flowers and negative correlations between pollinator body size and sugar concentration. In their comment, crucial model features are misrepresented, misunderstood, or ignored. Sensitivity to the supply/demand ratio explains both the equilibrium concentrations and the selection for lower concentrations by larger pollinators.