Behavioral and Brain Sciences最新文献

ER&K recurrently emphasize one side of three equations: (1) extrinsic rather than intrinsic mortality pressures; (2) developmental rather than genetic influence; and (3) individual rather than population-level effects. Furthermore, they insufficiently disambiguate extrinsic from intrinsic mortality, especially confounding how mortality evolutionarily constrains and developmentally calibrates genotypic life history speed, and struggle to explain population-level differences in fast maturation among modern populations.

The two-tiered life history (LH) model proposes that different sources of extrinsic mortality (EM) have opposing effects that regulate development toward both slower and faster LH traits. Although the 53 commentators generally endorsed the two-tiered model and empirical conclusions of the target article, the devil is in the details. Some commentators challenged model assumptions (e.g., the mechanistic basis of the two-tiered model; whether the model is genetically confounded; the relative importance of child versus adult mortality). Other commentators proposed extensions/modifications of model concepts and hypotheses (e.g., incorporating density-dependent regulation; use of formal models to generate and test hypotheses; connection to the internal predictive adaptive response [PAR] model). In this reply, we review and address these challenges and proposed extensions/modifications. We hope that this iterative process advances our understanding of the complexity of EM, its opposing tiers, and their dualistic effects-both hierarchical and countervailing-on variation in human life histories.

After presenting their two-tier model, Ellis, Reid, and Kramer (2024) tentatively state that child mortality risk should predict offspring quantity, while adult mortality risk should accelerate reproductive timing. I test these assertions using mortality risk and fertility data from the Global Burden of Disease (GBD) project for 204 countries and territories over 32 years, finding partial support for their predictions.

The force of selection on survival changes with age and models of reproductive effort (RE) reflect this finding that increases in infant and adult mortality have different effects on optimal effort. Using an age-structured demographic model, I show that infant mortality constrains selection on the human life cycle. Effort directed at increasing infant survival is strongly favored over efforts to increase adult survival. Complete accounts of human reproductive decisions require age-specificity of effects.

While Ellis, Reid, and Kramer's life history framework is convincing in explaining individual variation in life history strategies, it has certain limitations, which we discuss - drawing notably on the economic theory of fertility choice. In particular, we suggest that ambient cues to extrinsic mortality alone are not sufficient to trigger sustained net fertility decline.

This commentary integrates Coombs and Trestman's trait-linkage hypothesis with Teufel and Fletcher's neurocomputational predictive framework to propose that high-resolution visual systems operate as intrinsic bottom-up predictive mechanisms. By merging these concepts, we emphasize the significance of early sensory prediction in perception and provide a biologically inspired foundation for developing more adaptive, embodied, and cognitively resilient artificial intelligence (AI) systems.

In canvassing the animal kingdom for cognitive capacity by a multitrait approach, much hinges on how traits are operationally defined. In my commentary, I call attention to problematic aspects of the perspective on learning, a central component of cognition, adopted by Coombs and Trestman in their phylogenetic survey of cognitive capacity.

It is argued that there are huge differences between species of the "advanced" three phyla, both cognitively and neurally, and that more sophisticated attributes than vision and motion characterize only a few of them, and these are mainly found in vertebrates. Especially with respect to learning and memory, only some vertebrate species may possess sophisticated memory processing abilities.

The target article identifies non-cognitive traits co-occurring with major transitions in complex cognition. We argue that observed trait associations are really the phenomenon to be explained, and propose that changes in the nervous system are the explanatory driver for transitional events. Changes in neural architecture uniquely enable organisms to utilise complex and specialised traits, and thus, explain their linked nature.

Assuming that cognitive complexity follows a single, centralized trajectory overlooks key gaps: (1) the scarcity of cognitive studies on non-centralized species; (2) the potential of alternative neural architectures to support complex behavior; and (3) the influence of ecological niche pressures. Here we present evidence of curiosity-like behavior in a jellyfish, challenging the assumed link between centralized brains and complex cognition.