Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal–conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.

Cowan's revisiting of the magic number is very timely and the case he makes for a more moderate number than seven is persuasive. It is also appropriate to frame his case within a theoretical context, since this will influence what evidence to include and how to interpret it. He presents his model however, as a contrast to the working memory model of Baddeley (1986). I suggest that this reflects a misinterpretation of our model resulting in a danger of focusing attention on pseudo-problems rather than genuine disparities between his approach and my own.

On a now orthodox view, humans and many other animals possess a “number sense,” or approximate number system (ANS), that represents number. Recently, this orthodox view has been subject to numerous critiques that question whether the ANS genuinely represents number. We distinguish three lines of critique – the arguments from congruency, confounds, and imprecision – and show that none succeed. We then provide positive reasons to think that the ANS genuinely represents numbers, and not just non-numerical confounds or exotic substitutes for number, such as “numerosities” or “quanticals,” as critics propose. In so doing, we raise a neglected question: numbers of what kind? Proponents of the orthodox view have been remarkably coy on this issue. But this is unsatisfactory since the predictions of the orthodox view, including the situations in which the ANS is expected to succeed or fail, turn on the kind(s) of number being represented. In response, we propose that the ANS represents not only natural numbers (e.g., 7), but also non-natural rational numbers (e.g., 3.5). It does not represent irrational numbers (e.g., √2), however, and thereby fails to represent the real numbers more generally. This distances our proposal from existing conjectures, refines our understanding of the ANS, and paves the way for future research.

In The Cognitive-Emotional Brain (Pessoa 2013), I describe the many ways that emotion and cognition interact and are integrated in the brain. The book summarizes five areas of research that support this integrative view and makes four arguments to organize each area. (1) Based on rodent and human data, I propose that the amygdala's functions go beyond emotion as traditionally conceived. Furthermore, the processing of emotion-laden information is capacity limited, thus not independent of attention and awareness. (2) Cognitive-emotional interactions in the human prefrontal cortex (PFC) assume diverse forms and are not limited to mutual suppression. Particularly, the lateral PFC is a focal point for cognitive-emotional interactions. (3) Interactions between motivation and cognition can be seen across a range of perceptual and cognitive tasks. Motivation shapes behavior in specific ways – for example, by reducing response conflict or via selective effects on working memory. Traditional accounts, by contrast, typically describe motivation as a global activation independent of particular control demands. (4) Perception and cognition are directly influenced by information with affective or motivational content in powerful ways. A dual competition model outlines a framework for such interactions at the perceptual and executive levels. A specific neural architecture is proposed that embeds emotional and motivational signals into perception and cognition through multiple channels. (5) A network perspective should supplant the strategy of understanding the brain in terms of individual regions. More broadly, in a network view of brain architecture, “emotion” and “cognition” may be used as labels of certain behaviors, but will not map cleanly into compartmentalized pieces of the brain.

What Chow calls NHSTP is an inconsistent hybrid of Fisherian and Neyman-Pearsonian ideas. In psychology it has been practiced like ritualistic handwashing and sustained by wishful thinking about its utility. Chow argues that NHSTP is an important tool for ruling out chance as an explanation for data. I disagree. This ritual discourages theory development by providing researchers with no incentive to specify hypotheses.

Strong recent selection for social cognition may well explain the persistence of genes that predispose to schizophrenia. The specific mechanism responsible may be a skewed fitness function in which selection pushes the mean for advantageous mental traits perilously close to a “fitness cliff” where the system fails catastrophically in some individuals.

Several target articles in this BBS special issue address the topic of cerebellar and olivary functions, especially as they pertain to motor earning. Another important topic is the neural interaction between the limbic system and the cerebellum during associative learning. In this commentary we present some of our data on olivo-cerebellar and limbic-cerebellar interactions during eyeblink conditioning. [HOUK et al.; SIMPSON et al.; THACH]

Microbiota-gut-brain (MGB) research is a fast-growing field of inquiry with important implications for how human brain function and behaviour are understood. Researchers manipulate gut microbes (“microbiota”) to reveal connections between intestinal microbiota and normal brain functions (e.g., cognition, emotion, and memory) or pathological states (e.g., anxiety, mood disorders, and neural developmental disorders such as autism). Many claims are made about causal relationships between gut microbiota and human behaviour. By uncovering these relationships, MGB research aims to offer new explanations of mental health and potential avenues of treatment.

So far, limited evaluation has been made of MGB's methods and its core experimental findings, many of which are extensively reiterated in copious reviews of the field. These factors, plus the self-help potential of MGB, have combined to encourage uncritical public uptake of MGB discoveries. Both social and professional media focus on the potential for dietary intervention in mental health, and causal relationships are assumed to be established.

Our target article has two main aims. One is to examine critically the core practices and findings of experimental MGB research and to raise questions about them for brain and behavioural scientists who may not be familiar with the field. The other is to challenge the way in which MGB findings are presented. Our positive goal is to suggest how current problems and weaknesses may be addressed, in order for both scientific and public audiences to gain a clearer picture of MGB research and its strengths and limitations.