New directions in self-regulation: the role of metamotivational beliefs

Research on self-regulation has primarily focused on how people exert control over their thoughts, emotions, and behavior. Less attention has been paid to the ways in which people manage their motivational states in the service of achieving valued goals. In the present paper, we explore an emerging line of research that focuses on people’s beliefs about their own motivation (i.e., their metamotivational knowledge), as well as the influence of these beliefs on their selection of regulatory strategies. In particular, we review evidence showing that people are often quite sensitive to the fact that distinct motivational states (e.g., eagerness vs. vigilance) are adaptive for different kinds of tasks. We also discuss how other metamotivational beliefs are inaccurate on average (e.g., beliefs about how rewards affect intrinsic motivation). Finally, we consider the implications of metamotivation research for the field of self-regulation and discuss future directions

Dissociating Neural Correlates of Action Monitoring and Metacognition of Agency

Judgments of agency refer to people's self-reflective assessments concerning their own control: their assessments of the extent to which they themselves are responsible for an action. These self-reflective metacognitive judgments can be distinguished from action monitoring, which involves the detection of the divergence (or lack of divergence) between observed states and expected states. Presumably, people form judgments of agency by metacognitively reflecting on the output of their action monitoring and then consciously inferring the extent to which they caused the action in question. Although a number of previous imaging studies have been directed at action monitoring, none have assessed judgments of agency as a potentially separate process. The present fMRI study used an agency paradigm that not only allowed us to examine the brain activity associated with action monitoring but that also enabled us to investigate those regions associated with metacognition of agency. Regarding action monitoring, we found that being “out of control” during the task (i.e., detection of a discrepancy between observed and expected states) was associated with increased brain activity in the right TPJ, whereas being “in control” was associated with increased activity in the pre-SMA, rostral cingulate zone, and dorsal striatum (regions linked to self-initiated action). In contrast, when participants made self-reflective metacognitive judgments about the extent of their own control (i.e., judgments of agency) compared with when they made judgments that were not about control (i.e., judgments of performance), increased activity was observed in the anterior PFC, a region associated with self-reflective processing. These results indicate that action monitoring is dissociable from people's conscious self-attributions of control

The relationship between metamotivational knowledge and performance

Self-regulation research highlights the performance trade-offs of different motivational states. For instance, within the context of regulatory focus theory, promotion motivation enhances performance on eager tasks and prevention motivation enhances performance on vigilant tasks (i.e., regulatory focus task-motivation fit). Work on metamotivation—people’s understanding and regulation of their motivational states—reveals that, on average, people demonstrate knowledge of how to create such task-motivation fit; at the same time, there is substantial variability in this normative accuracy. The present research examines whether having accurate normative metamotivational knowledge predicts performance. Results revealed that more accurate metamotivational knowledge predicts better performance on brief, single-shot tasks (Study 1) and in a consequential setting (course grades; Study 2). The effect was more robust in Study 2; potential implications of this variability are discussed for understanding when and why knowledge may be associated with performance

The notch regulator MAML1 interacts with p53 and functions as a coactivator.

Members of the evolutionarily conserved Mastermind (MAM) protein family, including the three related mammalian Mastermind-like (MAML) proteins MAML1-3, function as crucial coactivators of Notch-mediated transcriptional activation. Given the recent evidence of cross-talk between the p53 and Notch signal transduction pathways, we have investigated whether MAML1 may also be a transcriptional coactivator of p53. Indeed, we show here that MAML1 is able to interact with p53. We show that MAML1-p53 interaction involves the N-terminal region of MAML1 and the DNA-binding domain of p53, and we use a chromatin immunoprecipitation assay to show that MAML1 is part of the activator complex that binds to native p53-response elements within the promoter of the p53 target genes. Overexpression of wild-type MAML1 as well as a mutant, defective in Notch signaling, enhanced the p53-dependent gene induction in mammalian cells, whereas MAML1 knockdown reduced the p53-dependent gene expression. MAML1 increases the half-life of p53 protein and enhances its phosphorylation/acetylation upon DNA damage of cells. Finally, RNA interference-mediated knockdown of the single Caenorhabditis elegans MAML homolog, Lag-3, led to substantial abrogation of p53-mediated germ-cell apoptotic response to DNA damage and markedly reduced the expression of Ced-13 and Egl-1, downstream pro-apoptotic targets of the C. elegans p53 homolog Cep-1. Thus, we present evidence for a novel coactivator function of MAML1 for p53, independent of its function as a coactivator of Notch signaling pathway

Mediator and cohesin connect gene expression and chromatin architecture

Transcription factors control cell-specific gene expression programs through interactions with diverse coactivators and the transcription apparatus. Gene activation may involve DNA loop formation between enhancer-bound transcription factors and the transcription apparatus at the core promoter, but this process is not well understood. Here we report that mediator and cohesin physically and functionally connect the enhancers and core promoters of active genes in murine embryonic stem cells. Mediator, a transcriptional coactivator, forms a complex with cohesin, which can form rings that connect two DNA segments. The cohesin-loading factor Nipbl is associated with mediator–cohesin complexes, providing a means to load cohesin at promoters. DNA looping is observed between the enhancers and promoters occupied by mediator and cohesin. Mediator and cohesin co-occupy different promoters in different cells, thus generating cell-type-specific DNA loops linked to the gene expression program of each cell.National Institutes of Health (U.S.) (Fellowship)Canadian Institutes of Health Research (Research Fellowship)National Institutes of Health (U.S.) (Grant R01 HG002668

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases