How to Find Decision Makers in Neural Networks

Nervous systems often face the problem of classifying stimuli and making decisions based on these classifications. The neurons involved in these tasks can be characterized as sensory or motor, according to their correlation with sensory stimulus or motor response. In this study we define a third class of neurons responsible for making perceptual decisions. Our mathematical formalism enables the weighting of neuronal units according to their contribution to decision making, thus narrowing the field for more detailed studies of underlying mechanisms. We develop two definitions of a contribution to decision making. The first definition states that decision making activity can be found at the points of emergence for behavioral correlations in the system. The second definition involves the study of propagation of noise in the network. The latter definition is shown to be equivalent to the first one in the cases when they can be compared. Our results suggest a new approach to analyzing decision making networks An erratum to this article can be found at     

Two Failures to Replicate High-Performance-Goal Priming Effects

Bargh et al. (2001) reported two experiments in which people were exposed to words related to achievement (e.g., strive, attain) or to neutral words, and then performed a demanding cognitive task. Performance on the task was enhanced after exposure to the achievement related words. Bargh and colleagues concluded that better performance was due to the achievement words having activated a "high-performance goal". Because the paper has been cited well over 1100 times, an attempt to replicate its findings would seem warranted. Two direct replication attempts were performed. Results from the first experiment (n = 98) found no effect of priming, and the means were in the opposite direction from those reported by Bargh and colleagues. The second experiment followed up on the observation by Bargh et al. (2001) that high-performance-goal priming was enhanced by a 5-minute delay between priming and test. Adding such a delay, we still found no evidence for high-performance-goal priming (n = 66). These failures to replicate, along with other recent results, suggest that the literature on goal priming requires some skeptical scrutiny.     

Being Human in the Age of the Brain: Models of Mind and Their Social Effects

Culture, Medicine, and Psychiatry -     

Measuring Neural and Behavioral Activity During Ongoing Computerized Social Interactions: An Examination of Event-Related Brain Potentials

Social exclusion is a complex social phenomenon with powerful negative consequences. Given the impact of social exclusion on mental and emotional health, an understanding of how perceptions of social exclusion develop over the course of a social interaction is important for advancing treatments aimed at lessening the harmful costs of being excluded. To date, most scientific examinations of social exclusion have looked at exclusion after a social interaction has been completed. While this has been very helpful in developing an understanding of what happens to a person following exclusion, it has not helped to clarify the moment-to-moment dynamics of the process of social exclusion. Accordingly, the current protocol was developed to obtain an improved understanding of social exclusion by examining the patterns of event-related brain activation that are present during social interactions. This protocol allows greater precision and sensitivity in detailing the social processes that lead people to feel as though they have been excluded from a social interaction. Importantly, the current protocol can be adapted to include research projects that vary the nature of exclusionary social interactions by altering how frequently participants are included, how long the periods of exclusion will last in each interaction, and when exclusion will take place during the social interactions. Further, the current protocol can be used to examine variables and constructs beyond those related to social exclusion. This capability to address a variety of applications across psychology by obtaining both neural and behavioral data during ongoing social interactions suggests the present protocol could be at the core of a developing area of scientific inquiry related to social interactions.     

How People Use Social Information to Find out What to Want in the Paradigmatic Case of Inter-temporal Preferences

The weight with which a specific outcome feature contributes to preference quantifies a person’s ‘taste’ for that feature. However, far from being fixed personality characteristics, tastes are plastic. They tend to align, for example, with those of others even if such conformity is not rewarded. We hypothesised that people can be uncertain about their tastes. Personal tastes are therefore uncertain beliefs. People can thus learn about them by considering evidence, such as the preferences of relevant others, and then performing Bayesian updating. If a person’s choice variability reflects uncertainty, as in random-preference models, then a signature of Bayesian updating is that the degree of taste change should correlate with that person’s choice variability. Temporal discounting coefficients are an important example of taste–for patience. These coefficients quantify impulsivity, have good psychometric properties and can change upon observing others’ choices. We examined discounting preferences in a novel, large community study of 14–24 year olds. We assessed discounting behaviour, including decision variability, before and after participants observed another person’s choices. We found good evidence for taste uncertainty and for Bayesian taste updating. First, participants displayed decision variability which was better accounted for by a random-taste than by a response-noise model. Second, apparent taste shifts were well described by a Bayesian model taking into account taste uncertainty and the relevance of social information. Our findings have important neuroscientific, clinical and developmental significance.     

Cadherin Expression in the Developing Vertebrate CNS: From Neuromeres to Brain Nuclei and Neural Circuits

Cadherins are a family of cell surface glycoproteins which mediate cell-cell adhesion by a Ca²⁺-dependent mechanism. Results from in vitro studies with cadherin-transfected cell lines show that cadherins preferentially bind to each other in a homophilic fashion. In the developing vertebrate brain, at least 10 cadherins are found. Some of these cadherins are expressed in a restricted fashion in particular developing brain nuclei and neural circuits. Based on these results, specific morphogenetic roles for cadherins during CNS development have been proposed. This review focuses on the possible role of cadherin-mediated sorting and aggregation of early neurons and neurites in the formation of brain nuclei, fiber tracts, and neural circuits. Moreover, at least 1 cadherin is also expressed in a segmental ("neuromeric") fashion in the early chicken forebrain, suggesting that this cadherin regulates developmental processes involved in the transformation from the neuromeric organization of the early neuroepithelium to the functional organization of the mature brain.     

Priming for stress resistance: from the lab to the field

Upon treatment with necrotizing pathogens, many plants develop an enhanced capacity for activating defense responses to biotic and abiotic stress--a process called priming. The primed state can also be induced by colonization of plant roots with beneficial micro-organisms or by treatment of plants with various natural and synthetic compounds. Priming is thought to be the mechanism by which plants can show induced resistance against ostensibly virulent pathogens after a conditioning treatment. Although the phenomenon has been known for years, it has been appreciated just recently that priming for enhanced defense responses can result from plant-plant communication in nature and that priming can also boost the resistance of crops to biotic and abiotic stresses in the field.     

When Problem Size Matters: Differential Effects of Brain Stimulation on Arithmetic Problem Solving and Neural Oscillations

The problem size effect is a well-established finding in arithmetic problem solving and is characterized by worse performance in problems with larger compared to smaller operand size. Solving small and large arithmetic problems has also been shown to involve different cognitive processes and distinct electroencephalography (EEG) oscillations over the left posterior parietal cortex (LPPC). In this study, we aimed to provide further evidence for these dissociations by using transcranial direct current stimulation (tDCS). Participants underwent anodal (30min, 1.5 mA, LPPC) and sham tDCS. After the stimulation, we recorded their neural activity using EEG while the participants solved small and large arithmetic problems. We found that the tDCS effects on performance and oscillatory activity critically depended on the problem size. While anodal tDCS improved response latencies in large arithmetic problems, it decreased solution rates in small arithmetic problems. Likewise, the lower-alpha desynchronization in large problems increased, whereas the theta synchronization in small problems decreased. These findings reveal that the LPPC is differentially involved in solving small and large arithmetic problems and demonstrate that the effects of brain stimulation strikingly differ depending on the involved neuro-cognitive processes.     

Promoting the Avoidance of High-Calorie Snacks: Priming Autonomy Moderates Message Framing Effects

The beneficial effects of gain-framed vs. loss-framed messages promoting health protective behaviors have been found to be inconsistent, and consideration of potential moderating variables is essential if framed health promotion messages are to be effective. This research aimed to determine the influence of highlighting autonomy (choice and freedom) and heteronomy (coercion) on the avoidance of high-calorie snacks following reading gain-framed or loss-framed health messages. In Study 1 (N = 152) participants completed an autonomy, neutral, or heteronomy priming task, and read a gain-framed or loss-framed health message. In Study 2 (N = 242) participants read a gain-framed or loss-framed health message with embedded autonomy or heteronomy primes. In both studies, snacking intentions and behavior were recorded after seven days. In both studies, when autonomy was highlighted, the gain-framed message (compared to the loss-framed message) resulted in stronger intentions to avoid high-calorie snacks, and lower self-reported snack consumption after seven days. Study 2 demonstrated this effect occurred only for participants to whom the information was most relevant (BMI>25). The results suggest that messages promoting healthy dietary behavior may be more persuasive if the autonomy-supportive vs. coercive nature of the health information is matched to the message frame. Further research is needed to examine potential mediating processes.     

Diversity of Neural Precursors in the Adult Mammalian Brain

Aided by advances in technology, recent studies of neural precursor identity and regulation have revealed various cell types as contributors to ongoing cell genesis in the adult mammalian brain. Here, we use stem-cell biology as a framework to highlight the diversity of adult neural precursor populations and emphasize their hierarchy, organization, and plasticity under physiological and pathological conditions.The adult mammalian brain displays remarkable structural plasticity by generating and incorporating new neural cell types into an already formed brain (Kempermann and Gage 1999). Largely restricted within the subventricular zone (SVZ) along the lateral ventricle and the subgranular zone (SGZ) in the dentate gyrus (DG), neural genesis is thought to arise from neural stem cells (NSCs) (Ming and Song 2011). Stem cells are defined by hallmark functions: capacity to self-renew, maintenance of an immature state over a long duration, and ability to generate specialized cell types (Fig. 1). These features distinguish stem cells from committed progenitor cells that more readily differentiate into specialized cell types (Fig. 1). Stem and progenitor cells (collectively called precursors) are additionally characterized by their lineage capacity. For example, multipotential neural precursors generate neurons and glia, whereas unipotential cells produce only one cell type, such as neurons (Gage 2000; Ma et al. 2009). The classical NSC definition is based on cell culture experiments in which a single cell can self-renew and generate neurons, astrocytes, and oligodendrocytes (Gage 2000; Ma et al. 2009). Yet, reprogramming studies have raised the question of whether cultured lineage-restricted neural progenitors acquire additional potential not evident in vivo (Palmer et al. 1999; Kondo and Raff 2000; Gabay et al. 2003). As a result, various lineage models have been proposed to explain cell generation in the adult brain (Fig. 1) (Ming and Song 2011). In one model, bona fide adult stem cells generate multiple lineages at the individual cell level. In another, cell genesis represents a collective property from a mixed population of unipotent progenitors. Importantly, these models are not mutually exclusive as evidence for the coexistence of multiple precursors has been observed in several adult somatic tissues, in which one population preferentially maintains homeostasis and another serves as a cellular reserve (Li and Clevers 2010; Mascre et al. 2012). Recent technical advances, including single-cell lineage tracing (Kretzschmar and Watt 2012), have made it possible to dissect basic cellular and behavioral processes of neural precursors in vivo (Fig. 4) (Bonaguidi et al. 2012). In this work, we review our current knowledge of precursor cell identity, hierarchical organization, and regulation to examine the diverse origins of cell genesis in the adult mammalian brain.Open in a separate windowFigure 1.Models of generating cell diversity in the adult tissues. (A,B) Definitions of stem and progenitor cells. In A, quiescent stem cells (S_q) become active stem cells (S_a) that proliferate to generate different types of specialized cells (C₁, C₂, C₃) and new stem cells (S). The active stem cell can return to quiescence and remain quiescent over long periods of time. In B, lineage-restricted progenitor cells lacking self-renewal capacity (P₁, P₂, P₃) each give rise to distinct populations of specialized cells (C₁, C₂, C₃). (C) Generation of specialized cells in a tissue could be explained by three models. (1) The stem-cell model, in which multipotent stem cells give rise to all the specialized cells in the tissue. (2) The progenitor cell model, in which diverse, lineage-restricted progenitor cells give rise to different cell types in the tissue. (3) A hybrid model, in which a mixture of stem cells and lineage-restricted progenitor cells generate specialized cells of the adult tissue.

Table 1.

Comparison of different methods used to study the generation of new cells in the adult mammalian nervous system