Neural Reuse and the Nature of Evolutionary Constraints

In humans, the reuse of neural structure is particularly pronounced at short, task-relevant timescales. Here, an argument is developed for the claim that facts about neural reuse at task-relevant timescales conflict with at least one characterization of neural reuse at an evolutionary timescale. It is then argued that, in order to resolve the conflict, we must conceptualize evolutionary-scale reuse more abstractly than has been generally recognized. The final section of the paper explores the relationship between neural reuse and human nature. It is argued that neural reuse is not well-described as a process that constrains our present cognitive capacities. Instead, it liberates those capacities from the ancestral tethers that might otherwise have constrained them

Quasi-Normal Modes of Stars and Black Holes

Perturbations of stars and black holes have been one of the main topics of relativistic astrophysics for the last few decades. They are of particular importance today, because of their relevance to gravitational wave astronomy. In this review we present the theory of quasi-normal modes of compact objects from both the mathematical and astrophysical points of view. The discussion includes perturbations of black holes (Schwarzschild, Reissner-Nordstr\"om, Kerr and Kerr-Newman) and relativistic stars (non-rotating and slowly-rotating). The properties of the various families of quasi-normal modes are described, and numerical techniques for calculating quasi-normal modes reviewed. The successes, as well as the limits, of perturbation theory are presented, and its role in the emerging era of numerical relativity and supercomputers is discussed.Comment: 74 pages, 7 figures, Review article for "Living Reviews in Relativity

A call for more clarity around causality in neuroscience

In neuroscience, the term ‘causality’ is used to refer to different concepts, leading to confusion. Here we illustrate some of those variations and we suggest names for them. We then introduce four ways to enhance clarity around causality in neuroscience