A mathematical model of the evolution of individual differences in developmental plasticity arising through parental bet‐hedging

Children vary in the extent to which their development is shaped by particular experiences (e.g. maltreatment, social support). This variation raises a question: Is there no single level of plasticity that maximizes biological fitness? One influential hypothesis states that when different levels of plasticity are optimal in different environmental states and the environment fluctuates unpredictably, natural selection may favor parents producing offspring with varying levels of plasticity. The current article presents a mathematical model assessing the logic of this hypothesis – specifically, it examines what conditions are required for natural selection to favor parents to bet‐hedge by varying their offspring's plasticity. Consistent with existing theory from biology, results show that between‐individual variation in plasticity cannot evolve when the environment only varies across space. If, however, the environment varies across time, selection can favor differential plasticity, provided fitness effects are large (i.e. variation in individuals’ plasticity is correlated with substantial variation in fitness). Our model also generates a novel restriction: Differential plasticity only evolves when the cost of being mismatched to the environment exceeds the benefits of being well matched. Based on mechanistic considerations, we argue that bet‐hedging by varying offspring plasticity, if it were to evolve, would be more likely instantiated via epigenetic mechanisms (e.g. pre‐ or postnatal developmental programming) than genetic ones (e.g. mating with genetically diverse partners). Our model suggests novel avenues for testing the bet‐hedging hypothesis of differential plasticity, including empirical predictions and relevant measures. We also discuss several ways in which future work might extend our model.     

Bridging developmental systems theory and evolutionary psychology using dynamic optimization

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists’ focus on dynamics and contingency with the ‘design stance’ of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach.     

Form ‘defines’ function: Neural connectivity between aesthetic perception and product purchase decisions in an fMRI study

In the aesthetics literature, object beauty has been emphasized for its non‐instrumental benefits, in other words, beauty that is ‘rewarding’ in itself, without functional considerations. In the context of consumer products, this study examines the influence of aesthetic perceptions on purchase decisions based on integrating both reward (hedonic) and functional value attribution mechanisms. Brain connectivity analysis of functional magnetic resonance imaging (fMRI) data sheds light on the neural route for the influence of product beauty on purchase. Notably, a significant directional connectivity from brain networks mediating ‘aesthetic perception’ to ‘functional value’ to ‘purchase decision’ shows that the left Amygdala, an emotion‐related region of the aesthetic network, influences all five regions in the functional network, which then influences the purchase network of the brain, thus supporting the utilitarian goals of aesthetic appraisals and the Antonio Damasio's somatic/emotional marker hypothesis. Further, we find clear evidence that the reward (hedonic) network, which also influences the purchase network, receives information from the functional network of the brain, integrating both the non‐instrumental and instrumental value of the product. In other words, beauty in consumer products influences purchase decisions by evoking emotions that importantly define the functional value of products, in addition to their hedonic/reward value uncovered in previous literature. In light of the novel findings, the authors discuss important implications for marketing theory, methodology, and practice. Copyright © 2016 John Wiley & Sons, Ltd.     

Haptic concepts in the blind

We investigated and compared the acquisition of haptic concepts by the blind with the acquisition of haptic concepts by sighted controls. Each subject—blind, sighted but blindfolded, sighted and touching, and sighted only-initially classified eight objects into two categories using a study/test format, followed by a recognition/classification test involving old, new, and prototype forms. Each object varied along the dimensions of shape, size, and texture, with each dimension having five values. The categories were linearly separable in three dimensions, but no single dimension permitted 100% accurate classification. The results revealed that blind subjects learned the categories quickly and comparably with sighted controls. On the classification test, all groups performed equivalently, with the category prototype classified more accurately than the old or new stimuli. The blind subjects differed from the other subjects on the recognition test in two ways: They were least likely to false alarm to novel patterns that belonged to the category but most likely to false alarm to the category prototype, which they falsely called “old” 100% of the time. We discuss these results in terms of current views of categorization.     

Sequential learning using temporal context

The temporal context model (TCM) has been extensively applied to recall phenomena from episodic memory. Here we use the same formulation of temporal context to construct a sequential learning model called the predictive temporal context model (pTCM) to extract the generating function of a language from sequentially-presented words. In pTCM, temporal context is used to generate a prediction vector at each step of learning and these prediction vectors are in turn used to construct semantic representations of words on the fly. The semantic representation of a word is defined as the superposition of prediction vectors that occur prior to the presentation of the word in the sequence. Here we create a formal framework for pTCM and prove several useful results. We explore the effect of manipulating the parameters of the model on learning a sequence of words generated by a bi-gram generating function. In this simple case, we demonstrate that feeding back the constructed semantic representation into the temporal context during learning improves the performance of the model when trained with a finite training sequence from a language with equivalence classes among some words. We also describe , a variant of the model that is identical to pTCM at steady state. has significant computational advantages over pTCM and can improve the quality of its prediction for some training sequences.     

The bystander effect in an N-person dictator game

Dozens of studies show that bystanders are less likely to help victims as bystander number increases. However, these studies model one particular situation, in which victims need only one helper. Using a multi-player dictator game, we study a different but common situation, in which a recipient’s welfare increases with the amount of help, and donors can share the burden of helping. We find that dictators transfer less when there are more dictators, and recipients earn less when there are multiple dictators. This effect persisted despite mechanisms eliminating uncertainty about other dictators’ behavior (a strategy method and communication). In a typical public goods game, people seem to transform the situation into an assurance game, willing to contribute if certain others will too. Despite similarities, people do not treat a recipient’s welfare like a public good. Instead, people seem to transform the situation into a prisoner’s dilemma, refusing to help whatever others do.     

Shape‐ and Trait‐Congruency: Using Appearance‐based Cues as a Basis for Product Recommendations

This research demonstrates that a consumer's physical appearance—and, more specifically, his or her body size—predictably influences the product(s) that the consumer is recommended. Four studies conducted in both field and lab settings show that agents more frequently recommend round (vs. angular) shaped products to heavier targets, notably for products and categories in which body size is irrelevant (e.g., lamps and perfume). We attribute this to a combination of shape‐congruency and trait‐congruency, whereby individuals choose products for others based on shared dimensions of the person and product.