Executive Functions and Prefrontal Cortex: A Matter of Persistence?

Executive function is thought to originates from the dynamics of frontal cortical networks. We examined the dynamic properties of the blood oxygen level dependent time-series measured with functional MRI (fMRI) within the prefrontal cortex (PFC) to test the hypothesis that temporally persistent neural activity underlies performance in three tasks of executive function. A numerical estimate of signal persistence, the Hurst exponent, postulated to represent the coherent firing of cortical networks, was determined and correlated with task performance. Increasing persistence in the lateral PFC was shown to correlate with improved performance during an n-back task. Conversely, we observed a correlation between persistence and increasing commission error – indicating a failure to inhibit a prepotent response – during a Go/No-Go task. We propose that persistence within the PFC reflects dynamic network formation and these findings underline the importance of frequency analysis of fMRI time-series in the study of executive functions

Towards a threat assessment framework for ecosystem services

How can we tell if the ecosystem services upon which we rely are at risk of being lost, potentially permanently? Ecosystem services underpin human well-being, but we lack a consistent approach for categorizing the extent to which they are threatened. We present an assessment framework for assessing the degree to which the adequate and sustainable provision of a given ecosystem service is threatened. Our framework combines information on the states and trends of both ecosystem service supply and demand, with reference to two critical thresholds: demand exceeding supply and ecosystem service ‘extinction’. This framework can provide a basis for global, national, and regional assessments of threat to ecosystem services, and accompany existing assessments of threat to species and ecosystems

Preferences across the Menstrual Cycle for Masculinity and Symmetry in Photographs of Male Faces and Bodies

Background: Previous studies have shown that women increase their preference for masculinity during the fertile phase of the menstrual cycle. Evidence for a similar preference shift for symmetry is equivocal. These studies have required participants to choose between subtle variations in computer-generated stimuli, and preferences for more natural stimuli have not been investigated. Methodology/Principal Findings: Our study employed photographs of individual males to investigate women’s preferences for face and body masculinity and symmetry across the menstrual cycle. We collected attractiveness ratings from 25 normally cycling women at high- and low-fertility days of the menstrual cycle. Attractiveness ratings made by these women were correlated with independent ratings of masculinity and symmetry provided by different sets of raters. We found no evidence for any cyclic shift in female preferences. Correlations between attractiveness and masculinity, and attractiveness and symmetry did not differ significantly between high- and low-fertility test sessions. Furthermore, there was no significant difference between high- and low-fertility ratings of attractiveness. Conclusions: These results suggest that a menstrual cycle shift in visual preferences for masculinity and symmetry may be too subtle to influence responses to real faces and bodies, and subsequent mate-choice decisions

Meta-Analysis of the Reasoned Action Approach (RAA) to Understanding Health Behaviors

YesBackground: Reasoned action approach (RAA) includes subcomponents of attitude (experiential/instrumental), perceived norm (injunctive/descriptive), and perceived behavioral control (capacity/autonomy) to predict intention and behavior. Purpose: To provide a meta-analysis of the RAA for health behaviors focusing on comparing the pairs of RAA subcomponents and differences between health protection and health-risk behaviors. Methods: The present research reports a meta-analysis of correlational tests of RAA subcomponents, examination of moderators, and combined effects of subcomponents on intention and behavior. Regressions were used to predict intention and behavior based on data from studies measuring all variables. Results: Capacity and experiential attitude had large, and other constructs had small-medium-sized correlations with intention; all constructs except autonomy were significant independent predictors of intention in regressions. Intention, capacity, and experiential attitude had medium-large, and other constructs had small-medium-sized correlations with behavior; intention, capacity, experiential attitude, and descriptive norm were significant independent predictors of behavior in regressions. Conclusions: The RAA subcomponents have utility in predicting and understanding health behaviors

A solution scan of societal options to reduce transmission and spread of respiratory viruses: SARS-CoV-2 as a case study.

Societal biosecurity - measures built into everyday society to minimize risks from pests and diseases - is an important aspect of managing epidemics and pandemics. We aimed to identify societal options for reducing the transmission and spread of respiratory viruses. We used SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) as a case study to meet the immediate need to manage the COVID-19 pandemic and eventually transition to more normal societal conditions, and to catalog options for managing similar pandemics in the future. We used a 'solution scanning' approach. We read the literature; consulted psychology, public health, medical, and solution scanning experts; crowd-sourced options using social media; and collated comments on a preprint. Here, we present a list of 519 possible measures to reduce SARS-CoV-2 transmission and spread. We provide a long list of options for policymakers and businesses to consider when designing biosecurity plans to combat SARS-CoV-2 and similar pathogens in the future. We also developed an online application to help with this process. We encourage testing of actions, documentation of outcomes, revisions to the current list, and the addition of further options

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

West Nile virus(WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input

Transethnic insight into the genetics of glycaemic traits: fine-mapping results from the Population Architecture using Genomics and Epidemiology (PAGE) consortium

AIMS/HYPOTHESIS: Elevated levels of fasting glucose and fasting insulin in non-diabetic individuals are markers of dysregulation of glucose metabolism and are strong risk factors for type 2 diabetes. Genome-wide association studies have discovered over 50 SNPs associated with these traits. Most of these loci were discovered in European populations and have not been tested in a well-powered multi-ethnic study. We hypothesised that a large, ancestrally diverse, fine-mapping genetic study of glycaemic traits would identify novel and population-specific associations that were previously undetectable by European-centric studies. METHODS: A multiethnic study of up to 26,760 unrelated individuals without diabetes, of predominantly Hispanic/Latino and African ancestries, were genotyped using the Metabochip. Transethnic meta-analysis of racial/ethnic-specific linear regression analyses were performed for fasting glucose and fasting insulin. We attempted to replicate 39 fasting glucose and 17 fasting insulin loci. Genetic fine-mapping was performed through sequential conditional analyses in 15 regions that included both the initially reported SNP association(s) and denser coverage of SNP markers. In addition, Metabochip-wide analyses were performed to discover novel fasting glucose and fasting insulin loci. The most significant SNP associations were further examined using bioinformatic functional annotation. RESULTS: Previously reported SNP associations were significantly replicated (p ≤ 0.05) in 31/39 fasting glucose loci and 14/17 fasting insulin loci. Eleven glycaemic trait loci were refined to a smaller list of potentially causal variants through transethnic meta-analysis. Stepwise conditional analysis identified two loci with independent secondary signals (G6PC2-rs477224 and GCK-rs2908290), which had not previously been reported. Population-specific conditional analyses identified an independent signal in G6PC2 tagged by the rare variant rs77719485 in African ancestry. Further Metabochip-wide analysis uncovered one novel fasting insulin locus at SLC17A2-rs75862513. CONCLUSIONS/INTERPRETATION: These findings suggest that while glycaemic trait loci often have generalisable effects across the studied populations, transethnic genetic studies help to prioritise likely functional SNPs, identify novel associations that may be population-specific and in turn have the potential to influence screening efforts or therapeutic discoveries. DATA AVAILABILITY: The summary statistics from each of the ancestry-specific and transethnic (combined ancestry) results can be found under the PAGE study on dbGaP here: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000356.v1.p1

Views of addiction neuroscientists and clinicians on the clinical impact of a ‘Brain Disease Model of Addiction’

Addiction is increasingly described as a "chronic and relapsing brain disease". The potential impact of the brain disease model on the treatment of addiction or addicted individuals' treatment behaviour remains uncertain. We conducted a qualitative study to examine: (i) the extent to which leading Australian addiction neuroscientists and clinicians accept the brain disease view of addiction; and (ii) their views on the likely impacts of this view on addicted individuals' beliefs and behaviour. Thirty-one Australian addiction neuroscientists and clinicians (10 females and 21 males; 16 with clinical experience and 15 with no clinical experience) took part in 1 h semi-structured interviews. Most addiction neuroscientists and clinicians did not uncritically support the use of brain disease model of addiction. Most were cautious about the potential for adverse impacts on individuals' recovery and motivation to enter treatment. While some recognised the possibility that the brain disease model of addiction may provide a rationale for addicted persons to seek treatment and motivate behaviour change, Australian addiction neuroscientist and clinicians do not assume that messages about "diseased brains" will always lead to increased treatment-seeking and reduced drug use. Research is needed on how neuroscience research could be used in ways that optimise positive outcomes for addicted persons