Dorsomedial Prefrontal Cortex Mediates Rapid Evaluations Predicting the Outcome of Romantic Interactions

Humans frequently make real-world decisions based on rapid evaluations of minimal information; for example, should we talk to an attractive stranger at a party? Little is known, however, about how the brain makes rapid evaluations with real and immediate social consequences. To address this question, we scanned participants with functional magnetic resonance imaging (fMRI) while they viewed photos of individuals that they subsequently met at real-life “speed-dating” events. Neural activity in two areas of dorsomedial prefrontal cortex (DMPFC), paracingulate cortex, and rostromedial prefrontal cortex (RMPFC) was predictive of whether each individual would be ultimately pursued for a romantic relationship or rejected. Activity in these areas was attributable to two distinct components of romantic evaluation: either consensus judgments about physical beauty (paracingulate cortex) or individualized preferences based on a partner's perceived personality (RMPFC). These data identify novel computational roles for these regions of the DMPFC in even very rapid social evaluations. Even a first glance, then, can accurately predict romantic desire, but that glance involves a mix of physical and psychological judgments that depend on specific regions of DMPFC

The Role of the Posterior Temporal and Medial Prefrontal Cortices in Mediating Learning from Romantic Interest and Rejection

Romantic interest or rejection can be powerful incentives not merely for their emotional impact, but for their potential to transform, in a single interaction, what we think we know about another person—or ourselves. Little is known, though, about how the brain computes expectations for, and learns from, real-world romantic signals. In a novel “speed-dating” paradigm, we had participants meet potential romantic partners in a series of 5-min “dates,” and decide whether they would be interested in seeing each partner again. Afterward, participants were scanned with functional magnetic resonance imaging while they were told, for the first time, whether that partner was interested in them or rejected them. Expressions of interest and rejection activated regions previously associated with “mentalizing,” including the posterior superior temporal sulcus (pSTS) and rostromedial prefrontal cortex (RMPFC); while pSTS responded to differences from the participant's own decision, RMPFC responded to prediction errors from a reinforcement-learning model of personal desirability. Responses in affective regions were also highly sensitive to participants' expectations. Far from being inscrutable, then, responses to romantic expressions seem to involve a quantitative learning process, rooted in distinct sources of expectations, and encoded in neural networks that process both affective value and social beliefs

Human Dorsal Striatum Encodes Prediction Errors during Observational Learning of Instrumental Actions

The dorsal striatum plays a key role in the learning and expression of instrumental reward associations that are acquired through direct experience. However, not all learning about instrumental actions require direct experience. Instead, humans and other animals are also capable of acquiring instrumental actions by observing the experiences of others. In this study, we investigated the extent to which human dorsal striatum is involved in observational as well as experiential instrumental reward learning. Human participants were scanned with fMRI while they observed a confederate over a live video performing an instrumental conditioning task to obtain liquid juice rewards. Participants also performed a similar instrumental task for their own rewards. Using a computational model-based analysis, we found reward prediction errors in the dorsal striatum not only during the experiential learning condition but also during observational learning. These results suggest a key role for the dorsal striatum in learning instrumental associations, even when those associations are acquired purely by observing others

Food Insecurity and Lived Experience of Students (FILES)

This paper provides evidence of the impact of Covid-19 on higher education students’ levels of food security and lived experiences. We surveyed higher education students, attending three universities in the UK and one in the USA, from 1st April to 30th April 2020, during the Covid-19 pandemic and after universities closed the majority of their buildings and ceased campus-based teaching. A total of 1,234 surveys were returned. The preliminary findings show that nearly 35% of students surveyed reported low or very low levels of food security and 41% of students were worried that their food would run out. We also found high levels of poor mental health and well-being; and mental health was associated with level of food security. The best predictor of the level of food security was students’ living arrangements during the Covid-19 pandemic. Students who were living on their own or with other students were more likely to experience low or very low levels of food insecurity compared to those students living with family members. The financial data collected show that many students relied on employment as their main source of income, and students are very worried about their current financial security. Furthermore, we found a relatively high reliance on ultra-processed foods as the main food type in students’ diets. The data from open-ended questions lend further support to the quantitative findings reported and provide further insight into students’ lived experiences. Finally, this paper concludes with key recommendations for policy makers, universities and student unions. (Submitted to the Education Select Committee Inquiry on The impact of COVID-19 on education and children’s services, 03 June 2020) FILES is a research collaboration involving a number of academics and student union officers from across England, Northern Ireland and the USA. The group’s key objective is to research food insecurity and lived experiences of students in Higher Education. Food insecurity has been explored in other populations, but no evidence has been presented that examines food insecurity and lived experiences of students in higher education following Covid-19 lockdown. Authors: Professor Greta Defeyter, Professor Paul Stretesky, Dr Mike Long, Dr Sinéad Furey, Dr Christian Reynolds, Dr Alyson Dodds, Dr Debbie Porteous, Dr Emily Mann, Mrs Christine Stretesky, Ms Anna Kemp, Mr James Fox, Mr Andrew McAnalle

Identification of disease-causing genes using microarray data mining and gene ontology

Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers

One-loop f(R) gravity in de Sitter universe

Motivated by the dark energy issue, the one-loop quantization approach for a family of relativistic cosmological theories is discussed in some detail. Specifically, general $f(R)$ gravity at the one-loop level in a de Sitter universe is investigated, extending a similar program developed for the case of pure Einstein gravity. Using generalized zeta regularization, the one-loop effective action is explicitly obtained off-shell, what allows to study in detail the possibility of (de)stabilization of the de Sitter background by quantum effects. The one-loop effective action maybe useful also for the study of constant curvature black hole nucleation rate and it provides the plausible way of resolving the cosmological constant problem.Comment: 25 pages, Latex file. Discussion enlarged, new references added. Version accepted in JCA

Notes on wormhole existence in scalar-tensor and F(R) gravity

Some recent papers have claimed the existence of static, spherically symmetric wormhole solutions to gravitational field equations in the absence of ghost (or phantom) degrees of freedom. We show that in some such cases the solutions in question are actually not of wormhole nature while in cases where a wormhole is obtained, the effective gravitational constant G_eff is negative in some region of space, i.e., the graviton becomes a ghost. In particular, it is confirmed that there are no vacuum wormhole solutions of the Brans-Dicke theory with zero potential and the coupling constant \omega > -3/2, except for the case \omega = 0; in the latter case, G_eff < 0 in the region beyond the throat. The same is true for wormhole solutions of F(R) gravity: special wormhole solutions are only possible if F(R) contains an extremum at which G_eff changes its sign.Comment: 7 two-column pages, no figures, to appear in Grav. Cosmol. A misprint corrected, references update

Solid phase extraction for removal of matrix effects in lipophilic marine toxin analysis by liquid chromatography-tandem mass spectrometry

The potential of solid phase extraction (SPE) clean-up has been assessed to reduce matrix effects (signal suppression or enhancement) in the liquid chromatography-tandem mass spectrometry (LC¿MS/MS) analysis of lipophilic marine toxins. A large array of ion-exchange, silica-based, and mixed-function SPE sorbents was tested. Polymeric sorbents were found to retain most of the toxins. Optimization experiments were carried out to maximize recoveries and the effectiveness of the clean-up. In LC¿MS/MS analysis, the observed matrix effects can depend on the chromatographic conditions used, therefore, two different HPLC methods were tested, using either an acidic or an alkaline mobile phase. The recovery of the optimized SPE protocol was around 90% for all toxins studied and no break-through was observed. The matrix effects were determined by comparing signal response from toxins spiked in crude and SPE-cleaned extracts with those derived from toxins prepared in methanol. In crude extracts, all toxins suffered from matrix effects, although in varying amounts. The most serious effects were observed for okadaic acid (OA) and pectenotoxin-2 (PTX2) in the positive electrospray ionization mode (ESI+). SPE clean-up on polymeric sorbents in combination with the alkaline LC method resulted in a substantial reduction of matrix effects to less than 15% (apparent recovery between 85 and 115%) for OA, yessotoxin (YTX) in ESI¿ and azaspiracid-1 (AZA1), PTX2, 13-desmethyl spirolides C (SPX1), and gymnodimine (GYM) in ESI+. In combination with the acidic LC method, the matrix effects after SPE were also reduced but nevertheless approximately 30% of the matrix effects remained for PTX2, SPX1, and GYM in ESI+. It was concluded that SPE of methanolic shellfish extracts can be very useful for reduction of matrix effects. However, the type of LC and MS methods used is also of great importance. SPE on polymeric sorbents in combination with LC under alkaline conditions was found the most effective method

Detection of regulator genes and eQTLs in gene networks

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression levels of nearby genes (they are "expression quantitative trait loci" or eQTLs for short) and presumably play a gene regulatory role, affecting the status of molecular networks of interacting genes, proteins and metabolites. Computational systems biology approaches to reconstruct causal gene networks from large-scale omics data have therefore become essential to understand the structure of networks controlled by eQTLs together with other regulatory genes, and to generate detailed hypotheses about the molecular mechanisms that lead from genotype to phenotype. Here we review the main analytical methods and softwares to identify eQTLs and their associated genes, to reconstruct co-expression networks and modules, to reconstruct causal Bayesian gene and module networks, and to validate predicted networks in silico.Comment: minor revision with typos corrected; review article; 24 pages, 2 figure

The Kochen-Specker Theorem Revisited in Quantum Measure Theory

The Kochen-Specker Theorem is widely interpreted to imply that non-contextual hidden variable theories that agree with the predictions of Copenhagen quantum mechanics are impossible. The import of the theorem for a novel observer independent interpretation of quantum mechanics, due to Sorkin, is investigated.Comment: 17 pages. Revised after refereein