Auditory and visual sequence learning in humans and monkeys using an artificial grammar learning paradigm

Language flexibly supports the human ability to communicate using different sensory modalities, such as writing and reading in the visual modality and speaking and listening in the auditory domain. Although it has been argued that nonhuman primate communication abilities are inherently multisensory, direct behavioural comparisons between human and nonhuman primates are scant. Artificial grammar learning (AGL) tasks and statistical learning experiments can be used to emulate ordering relationships between words in a sentence. However, previous comparative work using such paradigms has primarily investigated sequence learning within a single sensory modality. We used an AGL paradigm to evaluate how humans and macaque monkeys learn and respond to identically structured sequences of either auditory or visual stimuli. In the auditory and visual experiments, we found that both species were sensitive to the ordering relationships between elements in the sequences. Moreover, the humans and monkeys produced largely similar response patterns to the visual and auditory sequences, indicating that the sequences are processed in comparable ways across the sensory modalities. These results provide evidence that human sequence processing abilities stem from an evolutionarily conserved capacity that appears to operate comparably across the sensory modalities in both human and nonhuman primates. The findings set the stage for future neurobiological studies to investigate the multisensory nature of these sequencing operations in nonhuman primates and how they compare to related processes in humans

What makes or breaks a campaign to stop an invading plant pathogen?

Diseases in humans, animals and plants remain an important challenge in our society. Effective control of invasive pathogens often requires coordinated concerted action of a large group of stakeholders. Both epidemiological and human behavioural factors influence the outcome of a disease control campaign. In mathematical models that are frequently used to guide such campaigns, human behaviour is often ill-represented, if at all. Existing models of human, animal and plant disease that do incorporate participation or compliance are often driven by pay-offs or direct observations of the disease state. It is however very well known that opinion is an important driving factor of human decision making. Here we consider the case study of Citrus Huanglongbing disease (HLB), which is an acute bacterial disease that threatens the sustainability of citrus production across the world. We show how by coupling an epidemiological model of this invasive disease with an opinion dynamics model we are able to answer the question: What makes or breaks the effectiveness of a disease control campaign? Frequent contact between stakeholders and advisors is shown to increase the probability of successful control. More surprisingly, we show that informing stakeholders about the effectiveness of control methods is of much greater importance than prematurely increasing their perceptions of the risk of infection. We discuss the overarching consequences of this finding and the effect on human as well as plant disease epidemics

Structured sequence learning across sensory modalities in humans and nonhuman primates

Structured sequence processing tasks inform us about statistical learning abilities that are relevant to many areas of cognition, including language. Despite the ubiquity of these abilities across different tasks and cognitive domains, recent research in humans has demonstrated that these cognitive capacities do not represent a single, domain-general system, but are subject to modality-specific and stimulus-specific constraints. Sequence processing studies in nonhuman primates have provided initial insights into the evolution of these abilities. However, few studies have examined similarities and/or differences in sequence learning across sensory modalities. We review how behavioural and neuroimaging experiments assess sequence processing abilities across sensory modalities, and how these tasks could be implemented in nonhuman primates to better understand the evolution of these cognitive systems

Explainable neural networks for trait-based multispecies distribution modelling—A case study with butterflies and moths

Species response traits mediate environmental effects on species distribution. Traits are used in joint and multispecies distribution models (JSDMs and MSDMs) to enable community-wide shared parameters that characterise niche filtering along environmental gradients. Multispecies machine learning SDMs, however, do not use traits as their inclusion requires an additional taxonomic dimension that is incompatible with their usual tabular inputs. This has confined trait mediation in SDMs to hierarchical Bayesian models. Here we provide a novel artificial neural network (ANN) architecture that solves this dimensionality problem. Our ANN includes species traits (via a time distributed layer) and is therefore able to identify not only species-specific responses to the environment, but also shared responses across the community that are mediated by species traits. Model performance evaluated at the species level not only quantifies the reliability of species predictions, but also their departure from an average response dictated by traits only. We apply our model to two unique long-term spatio-temporal of butterfly and moth datasets collected across the United Kingdom between 1990 and 2019. In addition to species traits, predictors include numerous metrics derived from weather, land-cover and topology data. For butterflies and moths we show convincing model performance for classifying species occupancy. We use SHAP (Shapley Additive exPlanations) to explain the ANN and show how trait-mediated and species-specific responses can be approximated, hence yielding ecological insights on the key drivers of species distribution. We highlight a range of drivers of change that determine occupancy, including wind, temperature as well as habitat type. We demonstrate that a trait-based approach can be encoded as an ANN by using a time distributed layer. This brings ANNs unmatched predictive capabilities to the field of MSDMs, at the same time of lifting their reputed drawback of poor explainability

Sea-level constraints on the amplitude and source distribution of Meltwater Pulse 1A.

During the last deglaciation, sea levels rose as ice sheets retreated. This climate transition was punctuated by periods of more intense melting; the largest and most rapid of these—Meltwater Pulse 1A—occurred about 14,500 years ago, with rates of sea-level rise reaching approximately 4 m per century1, 2, 3. Such rates of rise suggest ice-sheet instability, but the meltwater sources are poorly constrained, thus limiting our understanding of the causes and impacts of the event4, 5, 6, 7. In particular, geophysical modelling studies constrained by tropical sea-level records1, 8, 9 suggest an Antarctic contribution of more than seven metres, whereas most reconstructions10 from Antarctica indicate no substantial change in ice-sheet volume around the time of Meltwater Pulse 1A. Here we use a glacial isostatic adjustment model to reinterpret tropical sea-level reconstructions from Barbados2, the Sunda Shelf3 and Tahiti1. According to our results, global mean sea-level rise during Meltwater Pulse 1A was between 8.6 and 14.6 m (95% probability). As for the melt partitioning, we find an allowable contribution from Antarctica of either 4.1 to 10.0 m or 0 to 6.9 m (95% probability), using two recent estimates11, 12 of the contribution from the North American ice sheets. We conclude that with current geologic constraints, the method applied here is unable to support or refute the possibility of a significant Antarctic contribution to Meltwater Pulse 1A

Increasing picocyanobacteria success in shelf waters contributes to long-term food web degradation

Continental margins are disproportionally important for global primary production, fisheries and CO2 uptake. However, across the Northeast Atlantic shelves, there has been an ongoing summertime decline of key biota—large diatoms, dinoflagellates and copepods—that traditionally fuel higher tropic levels such as fish, sea birds and marine mammals. Here, we combine multiple time series with in situ process studies to link these declines to summer nutrient stress and increasing proportions of picophytoplankton that can comprise up to 90% of the combined pico- and nanophytoplankton biomass in coastal areas. Among the pico-fraction, it is the cyanobacterium Synechococcus that flourishes when iron and nitrogen resupply to surface waters are diminished. Our field data show how traits beyond small size give Synechococcus a competitive edge over pico- and nanoeukaryotes. Key is their ability to grow at low irradiances near the nutricline, which is aided by their superior light-harvesting system and high affinity to iron. However, minute size and lack of essential biomolecules (e.g. omega-3 polyunsaturated fatty acids and sterols) render Synechococcus poor primary producers to sustain shelf sea food webs efficiently. The combination of earlier spring blooms and lower summer food quantity and quality creates an increasing period of suboptimal feeding conditions for zooplankton at a time of year when their metabolic demand is highest. We suggest that this nutrition-related mismatch has contributed to the widespread, ~50% decline in summer copepod abundance we observe over the last 60 years. With Synechococcus clades being prominent from the tropics to the Arctic and their abundances increasing worldwide, our study informs projections of future food web dynamics in coastal and shelf areas where droughts and stratification lead to increasing nutrient starvation of surface waters

Prevalence and predictors of complementary and alternative medicine use among people with coronary heart disease or at risk for this in the sixth Tromsø study: a comparative analysis using protection motivation theory

Background Engagement in healthy lifestyle behaviors, such as healthy diet and regular physical activity, are known to reduce the risk of developing coronary heart disease (CHD). Complementary and alternative medicine (CAM) is known to be associated with having a healthy lifestyle. The primary aim of this study was to examine the prevalence and predictors of CAM use in CHD patients, and in those without CHD but at risk for developing CHD, using Protection Motivation Theory (PMT) as a guiding conceptual framework. Method Questionnaire data were collected from 12,981 adult participants in the cross-sectional sixth Tromsø Study (2007–8). Eligible for analyses were 11,103 participants who reported whether they had used CAM or not. Of those, 830 participants reported to have or have had CHD (CHD group), 4830 reported to have parents, children or siblings with CHD (no CHD but family risk), while 5443 reported no CHD nor family risk of CHD. We first compared the patterns of CAM use in each group, and then examined the PMT predictors of CAM use. Health vulnerability from the threat appraisal process of PMT was assessed by self-rated health and expectations for future health. Response efficacy from the coping appraisal process of PMT was assessed as preventive health beliefs and health behavior frequency. Results Use of CAM was most commonly seen in people with no CHD themselves, but family risk of developing CHD (35.8%), compared to people already diagnosed with CHD (30.2%) and people with no CHD nor family risk (32.1%). All four of the PMT factors; self-rated health, expectations for future health, preventive health beliefs, and the health behavior index – were predictors for CAM use in the no CHD but family risk group. Conclusion These findings suggest that people use CAM in response to a perceived risk of developing CHD, and to prevent disease and to maintain health

Plausible self-reported dietary intakes in a residential facility are not necessarily reliable

Background/Objectives: Comparing reported energy intakes with estimated energy requirements as multiples of basal metabolic rate (Ein:BMR) is an established method of identifying implausible food intake records. The present study aimed to examine the validity of self-reported food intakes believed to be plausible. Subjects/Methods: One hundred and eighty men and women were provided with all food and beverages for two consecutive days in a residential laboratory setting. Subjects self-reported their food and beverage intakes using the weighed food diary method (WDR). Investigators covertly measured subjects’ actual consumption over the same period. Subjects also reported intakes over four consecutive days at home. BMR was measured by indirect calorimetry. Results: Average reported energy intakes were significantly lower than actual intakes (11.2 and 11.8 MJ/d, respectively, P<0.001). Two-thirds (121) of the WDR were under-reported to varying degrees. Only five of these were considered as implausible using an Ein:BMR cut-off value of 1.03*BMR. Under-reporting of food and beverage intakes, as measured by the difference between reported and actual intake, was evident at all levels of Ein;BMR. Reported energy intakes were lower still (10.2 MJ/d) while subjects were at home. Conclusions: Under-recording of self-reported food intake records was extensive but very few under-reported food intake records were identified as implausible using energy intake to BMR ratios. Under-recording was evident at all levels of energy intake

Acute Intrathoracic Gastric Volvulus due to Diaphragmatic Hernia: A Rare Emergency Easily Overlooked

Acute intrathoracic gastric volvulus occurs when the stomach undergoes organoaxial torsion in the chest due to either concomitant enlargement of the hiatus or a diaphragmatic hernia. Iatrogenic diaphragmatic hernia can occur after hiatal hernia repair and other surgical procedures, such as nephrectomy, esophagogastrectomy and splenopancreatectomy. We describe a 49-year-old woman who presented to our emergency department with acute moderate epigastric soreness and vomiting. She had undergone extensive gynecologic surgery including splenectomy 1 year before. The chest radiograph obtained in the emergency department demonstrated an elevated gastric air-fluid level in the left lower lung field. An urgent gastroscopy showed twisted structural abnormality of the stomach body. A computed tomography scan demonstrated the distended stomach, located in the left lower hemithorax through a left diaphragmatic defect. Emergent transthoracic repair was performed. Postoperative recovery was uneventful, and the patient did not experience any pain or difficulty with eating