Assessing bimodality to detect the presence of a dual cognitive process

Regime shifts in the thermal dynamics of offshore China due to accelerated global warming

Thermal dynamics play a pivotal role in offshore ecosystems, influencing a multitude of ecological and biogeochemical processes. Assessing how water temperature (WT) responds to climate change is vital for the sustainable development of marine ecosystems. Despite the scarcity of long-term sea surface temperature (SST) data, this study reconstructs SSTs from 1973 to 2020 in China's coastal zones using the data-driven Air2water model. A probabilistic approach was applied to investigate the joint dependency structures between air temperature (AT) and WT at offshore oceanic stations in China, focusing on variations during periods of decelerated and accelerated warming. The results indicate that the Air2water model performs well in reconstructing SSTs of the coastal zone of China. Furthermore, the joint probability of AT-WT events, characterized by bimodal distributions, tends to increase during accelerated warming. This suggests intensified extreme SST events in the coastal zone of China due to global warming, with the significant warming primarily related with regional oscillations, atmospheric dynamics, and the complex temperature trends in the regional marine environment. These findings highlight the escalating impact of global warming on marine ecosystems in China's coastal regions, underscoring the urgency of developing adaptive strategies to mitigate these effects.

Learning and transfer of response-effect relations

Acting means changing the environment according to one's own goals, and this often requires bodily movements as responses. How these responses are selected is a central question in contemporary cognitive psychology. The ideomotor principle offers a simple answer based on two assumptions: An agent first learns an association between a response and its effects. Later, this association can be used in a reverse way: When the agent wants to achieve a desired effect and activates its representation, the associated response representation becomes activated as well. This reversed use of the learned association is considered the means to select the required response. In three experiments, we addressed two questions related to the first assumption: First, we tested whether effect representations generalise to more abstract conceptual knowledge. This is important, because outside the laboratory and in novel situations, effects are variable and not always exactly identical, such that generalisation is necessary for successful actions. Second, the nature of the response-effect relation has been debated recently, and more data are necessary to put theorising on firm empirical ground. Results of our experiments suggest that (a) abstraction to conceptual knowledge seems to occur only under very restricted situations, and (b) it seems that no (implicit) associations between responses and effects are learned, but rather (explicit) propositional knowledge in the form of rules.

The Tweedledum and Tweedledee of dynamic decisions: Discriminating between diffusion decision and accumulator models

Theories of dynamic decision-making are typically built on evidence accumulation, which is modeled using racing accumulators or diffusion models that track a shifting balance of support over time. However, these two types of models are only two special cases of a more general evidence accumulation process where options correspond to directions in an accumulation space. Using this generalized evidence accumulation approach as a starting point, I identify four ways to discriminate between absolute-evidence and relative-evidence models. First, an experimenter can look at the information that decision-makers considered to identify whether there is a filtering of near-zero evidence samples, which is characteristic of a relative-evidence decision rule (e.g., diffusion decision model). Second, an experimenter can disentangle different components of drift rates by manipulating the discriminability of the two response options relative to the stimulus to delineate the balance of evidence from the total amount of evidence. Third, a modeler can use machine learning to classify a set of data according to its generative model. Finally, machine learning can also be used to directly estimate the geometric relationships between choice options. I illustrate these different approaches by applying them to data from an orientation-discrimination task, showing converging conclusions across all four methods in favor of accumulator-based representations of evidence during choice. These tools can clearly delineate absolute-evidence and relative-evidence models, and should be useful for comparing many other types of decision theories.

Electronic descriptors for dislocation deformation behavior and intrinsic ductility in bcc high-entropy alloys

Controlling the balance between strength and damage tolerance in high-entropy alloys (HEAs) is central to their application as structural materials. Materials discovery efforts for HEAs are therefore impeded by an incomplete understanding of the chemical factors governing this balance. Through first-principles calculations, this study explores factors governing intrinsic ductility of a crucial subset of HEAs-those with a body-centered cubic (bcc) crystal structure. Analyses of three sets of bcc HEAs comprising nine different compositions reveal that alloy chemistry profoundly influences screw dislocation core structure, dislocation vibrational properties, and intrinsic ductility parameters derived from unstable stacking fault and surface energies. Key features in the electronic structure are identified that correlate with these properties: the fraction of occupied bonding states and bimodality of the d-orbital density of states. The findings enhance the fundamental understanding of the origins of intrinsic ductility and establish an electronic structure-based framework for computationally accelerated materials discovery and design.

Predictive power of deleterious single amino acid changes to infer on AAV2 and AAV2-13 capsids fitness

Adeno-associated virus (AAV) is the most widely used vector for in vivo gene transfer. A major limitation of capsid engineering is the incomplete understanding of the consequences of multiple amino acid variations on AAV capsid stability resulting in high frequency of non-viable capsids. In this context, the study of natural AAV variants can provide valuable insights into capsid regions that exhibit greater tolerance to mutations. Here, the characterization of AAV2 variants and the analysis of two public capsid libraries highlighted common features associated with deleterious mutations, suggesting that the impact of mutations on capsid viability is strictly dependent on their 3D location within the capsid structure. We developed a novel prediction method to infer the fitness of AAV2 variants containing multiple amino acid variations with 98% sensitivity, 98% accuracy, and 95% specificity. This novel approach might streamline the development of AAV vector libraries enriched in viable capsids, thus accelerating the identification of therapeutic candidates among engineered capsids.

Capturing biomarkers associated with Alzheimer disease subtypes using data distribution characteristics

Late-onset Alzheimer disease (AD) is a highly complex disease with multiple subtypes, as demonstrated by its disparate risk factors, pathological manifestations, and clinical traits. Discovery of biomarkers to diagnose specific AD subtypes is a key step towards understanding biological mechanisms underlying this enigmatic disease, generating candidate drug targets, and selecting participants for drug trials. Popular statistical methods for evaluating candidate biomarkers, fold change (FC) and area under the receiver operating characteristic curve (AUC), were designed for homogeneous data and we demonstrate the inherent weaknesses of these approaches when used to evaluate subtypes representing less than half of the diseased cases. We introduce a unique evaluation metric that is based on the distribution of the values, rather than the magnitude of the values, to identify analytes that are associated with a subset of the diseased cases, thereby revealing potential biomarkers for subtypes. Our approach, Bimodality Coefficient Difference (BCD), computes the difference between the degrees of bimodality for the cases and controls. We demonstrate the effectiveness of our approach with large-scale synthetic data trials containing nearly perfect subtypes. In order to reveal novel AD biomarkers for heterogeneous subtypes, we applied BCD to gene expression data for 8,650 genes for 176 AD cases and 187 controls. Our results confirm the utility of BCD for identifying subtypes of heterogeneous diseases.

Olfactory investigation in the home cage

We have developed a behavioral paradigm to study volitional olfactory investigation in mice over several months. We placed odor ports in the wall of a standard cage that administer a neutral odorant stimulus when a mouse pokes its nose inside. Even though animals were fed and watered ad libitum, and sampling from the port elicited no outcome other than the delivery of an odor, mice readily sampled these stimuli hundreds of times per day. This self-paced olfactory investigation persisted for weeks with only modest habituation following the first day of exposure to a given set of odorants. If an unexpected odorant stimulus was administered at the port, the sampling rate increased transiently (in the first 20 min) by an order of magnitude and remained higher than baseline throughout the subsequent day, indicating learned implicit knowledge. Thus, this system may be used to study naturalistic olfactory learning over extended time scales outside of conventional task structures.

Which distribution to choose for deriving a species sensitivity distribution? Implications from analysis of acute and chronic ecotoxicity data

Species sensitivity distributions (SSDs) estimated by fitting a statistical distribution to ecotoxicity data are indispensable tools used to derive the hazardous concentration for 5 % of species (HC5) and thereby a predicted no-effect concentration in environmental risk assessment. Whereas various statistical distributions are available for SSD estimation, the fundamental question of which statistical distribution should be used has received limited systematic analysis. We aimed to address this knowledge gap by applying four frequently used statistical distributions (log-normal, log-logistic, Burr type III, and Weibull distributions) to acute and chronic SSD estimation using aquatic toxicity data for 191 and 31 chemicals, respectively. Based on the differences in the corrected Akaike's information criterion (AICc) as well as visual inspection of the fitting of the lower tails of SSD curves, the log-normal SSD was generally better or equally good for the majority of chemicals examined. Together with the fact that the ratios of HC5 values of other alternative SSDs to those of log-normal SSDs generally fell within the range 0.1-10, our findings indicate that the log-normal distribution can be a reasonable first candidate for SSD derivation, which does not contest the existing widespread use of log-normal SSDs.

Peripheral direct current reduces naturally evoked nociceptive activity at the spinal cord in rodent models of pain

Objective.Electrical neuromodulation is an established non-pharmacological treatment for chronic pain. However, existing devices using pulsatile stimulation typically inhibit pain pathways indirectly and are not suitable for all types of chronic pain. Direct current (DC) stimulation is a recently developed technology which affects small-diameter fibres more strongly than pulsatile stimulation. Since nociceptors are predominantly small-diameter Aδand C fibres, we investigated if this property could be applied to preferentially reduce nociceptive signalling.Approach.We applied a DC waveform to the sciatic nerve in rats of both sexes and recorded multi-unit spinal activity evoked at the hindpaw using various natural stimuli corresponding to different sensory modalities rather than broad-spectrum electrical stimulus. To determine if DC neuromodulation is effective across different types of chronic pain, tests were performed in models of neuropathic and inflammatory pain.Main results.We found that in both pain models tested, DC application reduced responses evoked by noxious stimuli, as well as tactile-evoked responses which we suggest may be involved in allodynia. Different spinal activity of different modalities were reduced in naïve animals compared to the pain models, indicating that physiological changes such as those mediated by disease states could play a larger role than previously thought in determining neuromodulation outcomes.Significance.Our findings support the continued development of DC neuromodulation as a method for reduction of nociceptive signalling, and suggests that it may be effective at treating a broader range of aberrant pain conditions than existing devices.

Copulation Duration and Sperm Precedence with Reference to Larval Diapause Induction in Monochamus alternatus Hope (Coleoptera: Cerambycidae)

Adults of the pine sawyer Monochamus alternatus are the primary vector of Bursaphelenchus xylophilus, the causative agent of pine wilt disease. A sawyer subspecies in Taiwan (abbreviated 'T') has two generations a year (bivoltinism) due to facultative diapause, whereas another subspecies in Japan (abbreviated 'J') has a one- or two-year life cycle due to obligate diapause. T, with two infection periods a year, will cause more severe disease epidemics than J if it is introduced into Japan. Inter-subspecies hybridization may inhibit the expression of bivoltinism because many F1 hybrids induce diapause. To predict the effects of introducing T into Japan, the present study investigated copulation duration and late-male sperm precedence to fertilize eggs. The results indicated that a single copulation for more than 65 s supplied sufficient sperm to fertilize a lifetime production of eggs. The incidence of larval diapause was 0.15 for the offspring of T females that mated with a T male and increased to 0.292-0.333 after remating with a J male, while the incidence of larval diapause was 0.900-1.000 for hybrids from T females mated with a J male. Consequently, the estimated proportion of second-male sperm used by T females was 0.185-0.217. The effects of introducing T populations into Japan on the severity of disease epidemics were also discussed.

Perseveration on cognitive strategies

To acquire and process information, performers can frequently rely on both internal and extended cognitive strategies. However, after becoming acquainted with two strategies, performers in previous studies exhibited a pronounced behavioral preference for just one strategy, which we refer to as perseveration. What is the origin of such perseveration? Previous research suggests that a prime reason for cognitive strategy choice is performance: Perseveration could reflect the preference for a superior strategy as determined by accurately monitoring each strategy's performance. However, following our preregistered hypotheses, we conjectured that perseveration persisted even if the available strategies featured similar performances. Such persisting perseveration could be reasonable if costs related to decision making, performance monitoring, and strategy switching would be additionally taken into account on top of isolated strategy performances. Here, we used a calibration procedure to equalize performances of strategies as far as possible and tested whether perseveration persisted. In Experiment 1, performance adjustment of strategies succeeded in equating accuracy but not speed. Many participants perseverated on the faster strategy. In Experiment 2, calibration succeeded regarding both accuracy and speed. No substantial perseveration was detected, and residual perseveration was conceivably related to metacognitive performance evaluations. We conclude that perseveration on cognitive strategies is frequently rooted in performance: Performers willingly use multiple strategies for the same task if performance differences appear sufficiently small. Surprisingly, other possible reasons for perseveration like effort or switch cost avoidance, mental challenge seeking, satisficing, or episodic retrieval of previous stimulus-strategy-bindings, were less relevant in the present study.

Evidence for Shifting Cognitive Strategies when Icons Appear in Unexpected Locations

OBJECTIVE

The present study examines the cognitive effects of placing icons in unexpected spatial locations within websites.

BACKGROUND

Prior research has revealed evidence for cognitive conflict when web icons occur in unexpected locations (e.g., cart, top left), generally consistent with a dynamical systems models. Here, we compare the relative strength of evidence for both dual and dynamical systems models.

METHODS

Participants clicked on icons located in either expected (e.g., cart, top right) or unexpected (e.g., cart, top left) locations while mouse trajectories were continuously recorded. Trajectories were classified according to prototypes associated with each cognitive model. The dynamical systems model predicts curved trajectories, while the dual-systems model predicts straight and change of mind trajectories.

RESULTS

Trajectory classification revealed that curved trajectories increased (+11%), while straight and change of mind trajectories decreased (-12%) when target icons occurred in unexpected locations (p < .001).

CONCLUSION

Rather than employing a single cognitive strategy, users shift from a primarily dual-systems to dynamical systems strategy when icons occur in unexpected locations.

APPLICATION

Potential applications of this work include the assessment of cognitive impacts such as mental workload and cognitive conflict during real-time interaction with websites and other screen-based interfaces, personalization and adaptive interfaces based on an individual's cognitive strategy, and data-driven A/B testing of alternative interface designs.

Pathway-selective optogenetics reveals the functional anatomy of top-down attentional modulation in the macaque visual cortex

Spatial attention represents a powerful top-down influence on sensory responses in primate visual cortical areas. The frontal eye field (FEF) has emerged as a key candidate area for the source of this modulation. However, it is unclear whether the FEF exerts its effects via its direct axonal projections to visual areas or indirectly through other brain areas and whether the FEF affects both the enhancement of attended and the suppression of unattended sensory responses. We used pathway-selective optogenetics in rhesus macaques performing a spatial attention task to inhibit the direct input from the FEF to area MT, an area along the dorsal visual pathway specialized for the processing of visual motion information. Our results show that the optogenetic inhibition of the FEF input specifically reduces attentional modulation in MT by about a third without affecting the neurons' sensory response component. We find that the direct FEF-to-MT pathway contributes to both the enhanced processing of target stimuli and the suppression of distractors. The FEF, thus, selectively modulates firing rates in visual area MT, and it does so via its direct axonal projections.

The Functional and Anatomical Impacts of Healthy Muscle Ageing

Even "healthy" muscle ageing is often associated with substantial changes in muscle form and function and can lead to increased injury risks and significant negative impacts on quality of life. However, the impacts of healthy muscle ageing on the fibre architecture and microstructure of different muscles and muscle groups throughout the lower limb, and how these are related to their functional capabilities, are not fully understood. Here, a previously established framework of magnetic resonance and diffusion tensor imaging was used to measure the muscle volumes, intramuscular fat, fibre lengths and physiological cross-sectional areas of 12 lower limb muscles in a cohort of healthily aged individuals, which were compared to the same data from a young population. Maximum muscle forces were also measured from an isokinetic dynamometer. The more substantial interpopulation differences in architecture and functional performance were located within the knee extensor muscles, while the aged muscles were also more heterogeneous in muscle fibre type and atrophy. The relationships between architecture and muscle strength were also more significant in the knee extensors compared to other functional groups. These data highlight the importance of the knee extensors as a potential focus for interventions to negate the impacts of muscle ageing.

The influence of explainable vs non-explainable clinical decision support systems on rapid triage decisions: a mixed methods study

BACKGROUND

During the COVID-19 pandemic, a variety of clinical decision support systems (CDSS) were developed to aid patient triage. However, research focusing on the interaction between decision support systems and human experts is lacking.

METHODS

Thirty-two physicians were recruited to rate the survival probability of 59 critically ill patients by means of chart review. Subsequently, one of two artificial intelligence systems advised the physician of a computed survival probability. However, only one of these systems explained the reasons behind its decision-making. In the third step, physicians reviewed the chart once again to determine the final survival probability rating. We hypothesized that an explaining system would exhibit a higher impact on the physicians' second rating (i.e., higher weight-on-advice).

RESULTS

The survival probability rating given by the physician after receiving advice from the clinical decision support system was a median of 4 percentage points closer to the advice than the initial rating. Weight-on-advice was not significantly different (p = 0.115) between the two systems (with vs without explanation for its decision). Additionally, weight-on-advice showed no difference according to time of day or between board-qualified and not yet board-qualified physicians. Self-reported post-experiment overall trust was awarded a median of 4 out of 10 points. When asked after the conclusion of the experiment, overall trust was 5.5/10 (non-explaining median 4 (IQR 3.5-5.5), explaining median 7 (IQR 5.5-7.5), p = 0.007).

CONCLUSIONS

Although overall trust in the models was low, the median (IQR) weight-on-advice was high (0.33 (0.0-0.56)) and in line with published literature on expert advice. In contrast to the hypothesis, weight-on-advice was comparable between the explaining and non-explaining systems. In 30% of cases, weight-on-advice was 0, meaning the physician did not change their rating. The median of the remaining weight-on-advice values was 50%, suggesting that physicians either dismissed the recommendation or employed a "meeting halfway" approach. Newer technologies, such as clinical reasoning systems, may be able to augment the decision process rather than simply presenting unexplained bias.

Behavioral convergence in defense behaviors in pair bonded individuals correlates with neuroendocrine receptors in the medial amygdala

Monogamous, pair-bonded animals coordinate intra-pair behavior for spatially separated challenges including territorial defense and nest attendance. Paired California mice, a monogamous, territorial and biparental species, approach intruders together or separately, but often express behavioral convergence across intruder challenges. To gain a more systems-wide perspective of potential mechanisms contributing to behavioral convergence across two conspecific intruder challenges, we conducted an exploratory study correlating behavior and receptor mRNA (Days 10 and 17 post-pairing). We examined associations between convergence variability in pair time for intruder-oriented behaviors with a pair mRNA index for oxytocin (OXTR), androgen (AR), and estrogen alpha (ERα) receptors within the medial amygdala (MeA) and the anterior olfactory nucleus (AON), brain regions associated with social behavior. An intruder behavior index revealed a bimodal distribution of intruder-related behaviors in Challenge 1 and a unimodal distribution in Challenge 2, suggesting population behavioral convergence, but no significant correlations with neuroendocrine measures. However, OXTR, AR, and ERα mRNA in the MeA were positively associated with convergence in individual intruder-related behaviors, suggesting multiple mechanisms may influence convergence. Mice could also occupy the nest during intruder challenges and convergence in nest attendance was positively correlated with MeA OXTR. At an individual level, nest attendance was positively associated with MeA ERα. Vocalizations were positively associated with AR and ERα mRNA. No positive associations were found in the AON. Overall, neuroendocrine receptors were implicated in convergence of a monogamous pair's defense behavior, highlighting the potential importance of the MeA as part of a circuit underlying convergence.

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system's capabilities to perform continuous observation of exploratory search behavior over a duration of 6 hr with and without a thermal gradient present, and in a single larva for over 30 hr. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

Baseline comparative analysis and review of election forensics: Application to Ghana's 2012 and 2020 presidential elections

Many allegations have been levelled against the electoral process of many countries across the world by most opposition leaders, especially when they lose a presidential election e.g. Ghana in 2012 and 2020. Therefore, the need to apply election forensic techniques to the certified election results data of valid votes count to statistically verify if some suspected or possible anomalies and irregularities exist in the voting pattern. This paper seeks to provide a comprehensive review of election forensics techniques and make a comparative analysis of Benford's Second-order test of conformity (using the first two digits) and Hartigans' dip test of unimodality to examine the existence of possible anomalies and irregularities in the 2012 and 2020 presidential elections held in Ghana. The findings of the two tests suggest that the electoral process produced possible anomalous data in the 2012 presidential election results (with an overall 16.67% suspected anomalies), whilst possible non-anomalous data was produced in the 2020 presidential election results (with an overall 0% suspected anomaly) of valid votes count. Therefore, the study recommends that for better statistical data analysis on election anomaly detection, Benford's test of conformity and Hartigans' dip test of unimodality should serve as baseline tests (initial screening tools), highlighting areas that may require further investigation or more rigorous analysis and progressively dig deeper into the application of finite mixture fraud models and machine learning techniques. In spite of the promising results Benford's Law, dip test, machine learning algorithms, and network analysis have produced in detecting irregularities in election data, real-world applications remain challenging, particularly when dealing with complex and evolving forms of fraud. Therefore, there is the need for continuous research and innovation to improve the accuracy and effectiveness of these methods and promote transparency and accountability in democratic societies.

Seven years of studying the associations between political polarization and problematic information: a literature review

This literature review examines the intersection between political polarization and problematic information, two phenomena prominent in recent events like the 2016 Trump election and the 2020 COVID-19 pandemic. We analyzed 68 studies out of over 7,000 records using quantitative and qualitative methods. Our review revealed a lack of research on the relationship between political polarization and problematic information and a shortage of theoretical consideration of these phenomena. Additionally, US samples and Twitter and Facebook were frequently analyzed. The review also found that surveys and experiments were commonly used, with polarization significantly predicting problematic information consumption and sharing.

Mindreading by body: incorporating mediolateral balance and mouse-tracking measures to examine the motor basis of adults' false-belief tracking

The role played by motor representations in tracking others' belief-based actions remains unclear. In experiment 1, the dynamics of adults' anticipatory mediolateral motor activity (leftwards-rightwards leaning on a balance board) as well as hand trajectories were measured as they attempted to help an agent who had a true or false belief about an object's location. Participants' leaning was influenced by the agent's belief about the target's location when the agent was free to act but not when she was motorically constrained. However, the hand trajectories participants produced to provide a response were not modulated by the other person's beliefs. Therefore, we designed a simplified second experiment in which participants were instructed to click as fast as possible on the location of a target object. In experiment 2, mouse-movements deviated from an ideal direct path to the object location, with trajectories that were influenced by the location in which the agent falsely believed the object to be located. These experiments highlight that information about an agent's false-belief can be mapped onto the motor system of a passive observer, and that there are situations in which the motor system plays an important role in accurate belief-tracking.

Continuous cursor-captured conceptual competition: Investigating the spatiotemporal dynamics of spoken word comprehension

Semantically related concepts are coactivated during spoken word comprehension. Two internet-mediated cursor-tracking experiments examined the spatiotemporal dynamics of this coactivation. Participants viewed visual arrays containing images of a target (e.g., accordion) and a semantically related (e.g., banjo) or unrelated (e.g., plum) distractor whilst hearing the target word (e.g., "accordion"). Participants were tasked with moving their cursor from the bottom of the visual array to the target in one of the upper corners. In contrast to Experiment 1, the onset of stimulus presentation was triggered by cursor movement in Experiment 2. Across both experiments, temporal (e.g., RT) and spatial (e.g., AUC) measures revealed significantly greater attraction to images of semantically related compared with unrelated distractors. These results reveal that online cursor-tracking methods are sensitive to semantic competition and suitable for studying the activation of semantic knowledge during language comprehension.

Is there hierarchical generalization in response-effect learning?

Ideomotor theory is an influential approach to understand goal-directed behavior. In this framework, response-effect (R-E) learning is assumed as a prerequisite for voluntary action: Once associations between motor actions and their effects in the environment have been formed, the anticipation of these effects will automatically activate the associated motor pattern. R-E learning is typically investigated with (induction) experiments that comprise an acquisition phase, where R-E associations are presumably learned, and a subsequent test phase, where the previous effects serve as stimuli for a response. While most studies used stimuli in the test phase that were identical to the effects in the acquisition phase, one study reported generalization from exemplars to their superordinate category (Hommel et al., Vis Cogn 10:965-986, 2003, Exp. 1). However, studies on so-called R-E compatibility did not report such generalization. We aimed to conceptually replicate Experiment 1 of Hommel et al. (Vis Cogn 10:965-986, 2003) with a free-choice test phase. While we did observe effects consistent with R-E learning when the effects in the acquisition phase were identical to the stimuli in the test phase, we did not observe evidence for generalization. We discuss this with regard to recent studies suggesting that individual response biases might rather reflect rapidly inferred propositional knowledge instead of learned R-E associations.

What is left after an error? Towards a comprehensive account of goal-based binding and retrieval

The cognitive system readily detects and corrects erroneous actions by establishing episodic bindings between representations of the acted upon stimuli and the intended correct response. If these stimuli are encountered again, they trigger the retrieval of the correct response. Thus, binding and retrieval efficiently pave the way for future success. The current study set out to define the role of the erroneous response itself and explicit feedback for the error during these processes of goal-based binding and retrieval. Two experiments showed robust and similar binding and retrieval effects with and without feedback and pointed towards sustained activation of the unbound, erroneous response. The third experiment confirmed that the erroneous response is more readily available than a neutral alternative. Together, the results demonstrate that episodic binding biases future actions toward success, guided primarily through internal feedback processes, while the erroneous response still leaves detectable traces in human action control.

Making decisions about health information on social media: a mouse-tracking study

Health misinformation is a problem on social media, and more understanding is needed about how users cognitively process it. In this study, participants’ accuracy in determining whether 60 health claims were true (e.g., “Vaccines prevent disease outbreaks”) or false (e.g., “Vaccines cause disease outbreaks”) was assessed. The 60 claims were related to three domains of health risk behavior (i.e., smoking, alcohol and vaccines). Claims were presented as Tweets or as simple text statements. We employed mouse tracking to measure reaction times, whether processing happens in discrete stages, and response uncertainty. We also examined whether health literacy was a moderating variable. The results indicate that information in statements and tweets is evaluated incrementally most of the time, but with overrides happening on some trials. Adequate health literacy scorers were equally certain when responding to tweets and statements, but they were more accurate when responding to tweets. Inadequate scorers were more confident on statements than on tweets but equally accurate on both. These results have important implications for understanding the underlying cognition needed to combat health misinformation online.

A meiotic driver alters sperm form and function in house mice: a possible example of spite

The ability to subvert independent assortment of chromosomes is found in many meiotic drivers, such as the t haplotype in house mice Mus musculus, in which the t-bearing chromosomal homolog is preferentially transmitted to offspring. This is explained by a poison-antidote system, in which developing + and t sperm in testes of + /t males are exposed to 'poison' coded by t loci, from which t sperm are protected, allowing t sperm an overwhelming fertilisation advantage in monogamous matings. This system is thought to result in poorly and normally motile sperm subpopulations within + /t sperm, leaving t sperm unharmed. Conversely, we found that the fastest quartile of sperm from + /t males swam more slowly, both forwards and along their travel path, and had reduced straightness and linearity, compared to the fastest quartile of + / + sperm. Moreover, sperm from + /t males had shorter tails and narrower heads than + / + sperm, and these morphological differences covaried with motility differences. Finally, + /t traits did not show evidence of bimodal distributions. We conclude that the t haplotype drive results in lasting damage to the motility of both + and t developing sperm, although previous studies indicate that + must be more harmed than t sperm. This damage to all sperm may explain the low success of + /t males in sperm competition with + / + males, seen in earlier studies. We propose that the harm the t causes to itself could be termed 'spiteful', which may also be common to other gamete-harming meiotic drive systems.

Multiresolution spectrally-encoded terahertz reflection imaging through a highly diffusive cloak

Turbid media, made of wavelength-scale inhomogeneous particles, can give rise to many significant imaging and spectroscopy challenges. The random variation of the refractive index within such media distorts the spherical wavefronts, resulting in smeared and speckly images. The scattering-induced artifacts can obscure the characteristic spectral fingerprints of the chemicals in a sample. This in turn prevents accurate chemical imaging and characterization of the materials cloaked with a diffusive medium. In this work, we present a novel computational technique for creating spatially- and spectrally-resolved chemical maps through a diffusive cloak using terahertz time-domain spectroscopy. We use the maximal overlap discrete wavelet transform to obtain a multiresolution spectral decomposition of THz extinction coefficients. We define a new spectroscopic concept dubbed the "bimodality coefficient spectrum" using the skewness and kurtosis of the spectral images. We demonstrate that broadband wavelet-based reconstruction of the bimodality coefficient spectrum can resolve the signature resonant frequencies through the scattering layers. Additionally, we show that our approach can achieve spectral images with diffraction-limited resolution. This technique can be used for stand-off characterization of materials and spectral imaging in nondestructive testing and biological applications.

From fibre to function: are we accurately representing muscle architecture and performance?

The size and arrangement of fibres play a determinate role in the kinetic and energetic performance of muscles. Extrapolations between fibre architecture and performance underpin our understanding of how muscles function and how they are adapted to power specific motions within and across species. Here we provide a synopsis of how this 'fibre to function' paradigm has been applied to understand muscle design, performance and adaptation in animals. Our review highlights the widespread application of the fibre to function paradigm across a diverse breadth of biological disciplines but also reveals a potential and highly prevalent limitation running through past studies. Specifically, we find that quantification of muscle architectural properties is almost universally based on an extremely small number of fibre measurements. Despite the volume of research into muscle properties, across a diverse breadth of research disciplines, the fundamental assumption that a small proportion of fibre measurements can accurately represent the architectural properties of a muscle has never been quantitatively tested. Subsequently, we use a combination of medical imaging, statistical analysis, and physics-based computer simulation to address this issue for the first time. By combining diffusion tensor imaging (DTI) and deterministic fibre tractography we generated a large number of fibre measurements (>3000) rapidly for individual human lower limb muscles. Through statistical subsampling simulations of these measurements, we demonstrate that analysing a small number of fibres (n < 25) typically used in previous studies may lead to extremely large errors in the characterisation of overall muscle architectural properties such as mean fibre length and physiological cross-sectional area. Through dynamic musculoskeletal simulations of human walking and jumping, we demonstrate that recovered errors in fibre architecture characterisation have significant implications for quantitative predictions of in-vivo dynamics and muscle fibre function within a species. Furthermore, by applying data-subsampling simulations to comparisons of muscle function in humans and chimpanzees, we demonstrate that error magnitudes significantly impact both qualitative and quantitative assessment of muscle specialisation, potentially generating highly erroneous conclusions about the absolute and relative adaption of muscles across species and evolutionary transitions. Our findings have profound implications for how a broad diversity of research fields quantify muscle architecture and interpret muscle function.

The biased hand. Mouse-tracking metrics to examine the conflict processing in a race-implicit association test

In this study, we adapted a race-Implicit Association Test (race-IAT) to mouse-tracking (MT) technique to identify the more representative target observed MT-metrics and explore the temporal unfolding of the cognitive conflict emerging during the categorisation task. Participants of Western European descent performed a standard keyboard-response race-IAT (RT-race-IAT) and an MT-race-IAT with the same structure. From a behavioural point of view, our sample showed a typical Congruency Effect, thus a pro-White implicit bias, in the RT-race-IAT. In addition, in the MT-race-IAT, the MT-metrics showed a similar Congruency Effect mirroring the higher attraction of the averaged-trajectories towards the incorrect response button in incongruent than congruent trials. Moreover, these MT-metrics were positively associated with RT-race-IAT scores, strengthening the MT approach’s validity in characterising the implicit bias. Furthermore, the distributional analyses showed that mouse trajectories displayed a smooth profile both in congruent and incongruent trials to indicate that the unfolding of the decision process and the raised conflict is guided by dynamical cognitive processing. This latter continuous competition process was studied using a novel phase-based approach which allowed to temporally dissect an Early, a Mid and a Late phase, each of which may differently reflect the decision conflict between automatic and controlled responses in the evolution of the mouse movement towards the target response. Our results show that the MT approach provides an accurate and finer-grained characterisation of the implicit racial attitude than classical RT-IAT. Finally, our novel phase-based approach can be an effective tool to shed light on the implicit conflict processing emerging in a categorisation task with a promising transferable value in different cognitive and neuropsychological fields.

A probabilistic map of emotional experiences during competitive social interactions

Theories of emotion and decision-making argue that negative, high arousing emotions—such as anger—motivate competitive social choice (e.g., punishing and defecting). However, given the long-standing challenge of quantifying emotion and the narrow framework in which emotion is traditionally examined, it remains unclear which emotions are actually associated with motivating these types of choices. To address this gap, we combine machine learning algorithms with a measure of affect that is agnostic to any specific emotion label. The result is a probabilistic map of emotion that is used to classify the specific emotions experienced by participants in a variety of social interactions (Ultimatum Game, Prisoner’s Dilemma, and Public Goods Game). Our results reveal that punitive and uncooperative choices are linked to a diverse array of negative, neutrally arousing emotions, such as sadness and disappointment, while only weakly linked to anger. These findings stand in contrast to the commonly held assumption that anger drives decisions to punish, defect, and freeride—thus, offering new insight into the role of emotion in motiving social choice.

Emotions motivate decision-making but are difficult to measure. Here the authors use a data driven, machine learning approach to reveal that social choices are linked to a diverse array of emotions, including disappointment and sadness.

Frequency-Domain Electromagnetic Mapping of an Abandoned Waste Disposal Site: A Case in Sardinia (Italy)

For decades, bad practices in municipal and industrial waste management have had negative environmental impacts, generating high health risks for people and the environment. The use of badly designed, not engineered, and not well-operated landfills has, around the world, produced a large number of potentially contaminated sites, for which there are urgent needs to assess the actual risk and to proceed, in case, with reclamation activities. One of these sites, an abandoned waste disposal site located near a Site of Community Importance on the central-eastern coast of Sardinia (Italy), is the subject of the case history described in this work. As a part of a multi-method geophysical characterisation, a frequency-domain electromagnetic (FDEM) mapping survey was carried out with the specific aim of detecting the presence of buried materials (waste) and of delineating the lateral extent of the landfill by identifying the electrical conductivity anomalies produced, for the most part, by the conductive waste fill. Using an EM31 device in the vertical-dipole configuration, at a height of 0.9 m above the ground, both quadrature and in-phase electromagnetic responses were collected over a 7-hectare area with elevation varying between 6 m and 2.8 m above sea level. After removing the measurements identified as data coming from any recognisable surface man-made features within the survey area or near its perimeter, the filtered quadrature response (expressed as apparent conductivity) ranged from 5.5 mS/m to about 188.6 mS/m. All values are beyond the low induction number (LIN) condition and valid for the classical EM31 mapping, thus requiring advanced data processing. To obtain undistorted, meaningful, and interpretable high-resolution maps, measured data have been processed to correct the bias, introduced by the nonlinearity of the device, as a function of height above ground and the topography. The comparative analysis of the apparent conductivity map, obtained by the properly processed EM31 data and some aerial photos that clearly documented the site history, has allowed unequivocal delineation of the landfill extent, in good agreement with the results obtained with other geophysical methods (not described in this paper) and with the ground truthing data provided by three boreholes, which were core-drilled at the end of the study at three locations selected on the basis of the apparent conductivity map.

Validation of the Russianversion of the Maudsley Obsessive-Compulsive Inventory (MOCI) in Population and Clinical Samples

Relevance. Obsessive-compulsive disorder (OCD) is the third most common psychiatric disorder, potentially disabling with significant social and economic consequences. In Russia, little attention is paid to the study of OCD, which leads to the problem of differential diagnosis and effective treatment of OCD. One of the reasons for the insufficient attention to OCD is the lack of validated Russian questionnaires for diagnosing OCD. The purpose of this work is the initial validation of a translated version of the Maudsley Obsessive-Compulsive Inventory (MOCI). Characteristics of the surveyed groups. A population-based sample of 300 students (212 women and 88 men) and a clinical sample of 13 patients with anxiety and depressive disorders (8 women and 5 men) and 13 patients with OCD (11 women and 2 men) participated in the study. Severity of OCD symptoms were assessed with the translated version of Maudsley questionnaire. Results. According to our data, the MOCI questionnaire allows to differentiate reliably (p = 0,027) patients with OCD from patients with anxiety-depressive disorders and can be suitable as a primary diagnostic test for identifying OCD patients (p < 0,05) and the risk group. The reliability and convergent validity of the questionnaire were shown.

Laminar perfusion imaging with zoomed arterial spin labeling at 7 Tesla

Laminar fMRI based on BOLD and CBV contrast at ultrahigh magnetic fields has been applied for studying the dynamics of mesoscopic brain networks. However, the quantitative interpretations of BOLD/CBV fMRI results are confounded by different baseline physiology across cortical layers. Here we introduce a novel 3D zoomed pseudo-continuous arterial spin labeling (pCASL) technique at 7T that offers the capability for quantitative measurements of laminar cerebral blood flow (CBF) both at rest and during task activation with high spatial specificity and sensitivity. We found arterial transit time in superficial layers is ∼100 ms shorter than in middle/deep layers revealing the time course of labeled blood flowing from pial arteries to downstream microvasculature. Resting state CBF peaked in the middle layers which is highly consistent with microvascular density measured from human cortex specimens. Finger tapping induced a robust two-peak laminar profile of CBF increases in the superficial (somatosensory and premotor input) and deep (spinal output) layers of M1, while finger brushing task induced a weaker CBF increase in superficial layers (somatosensory input). This observation is highly consistent with reported laminar profiles of CBV activation on M1. We further demonstrated that visuospatial attention induced a predominant CBF increase in deep layers and a smaller CBF increase on top of the lower baseline CBF in superficial layers of V1 (feedback cortical input), while stimulus driven activity peaked in the middle layers (feedforward thalamic input). With the capability for quantitative CBF measurements both at baseline and during task activation, high-resolution ASL perfusion fMRI at 7T provides an important tool for in vivo assessment of neurovascular function and metabolic activities of neural circuits across cortical layers.

Bimodality in reentry latitude predictions for spacecraft in prograde orbits

Probability distribution functions (PDFs) of atmospheric reentry latitude predictions are shown to be bimodal for spacecraft in low-eccentricity, prograde low Earth orbits at altitudes of 300 km and lower. Using two-line element (TLE) data for initial orbit conditions, coupled with coarse estimates for spacecraft aerodynamic characteristics, parametric simulations produce bimodal distributions that suggest a greater likelihood of reentry near the latitudinal maxima of a given spacecraft's ground track. Various computational measures are used to test for and quantify bimodality in the reentry latitude data sets. Also, a method for approximating bandwidth is introduced for the kernel estimation of reentry latitude probability density. Overall, statistical analysis indicates that actual reentry latitudes are generally within 1-σ of observed hemisphere means as demonstrated by six historical reentry cases.

Diffuse terahertz spectroscopy in turbid media using a wavelet-based bimodality spectral analysis

Current terahertz (THz) spectroscopy techniques only use the coherent light beam for spectral imaging. In the presence of electromagnetic scattering, however, the scattering-mitigated incoherent beams allow for flexible emitter-detector geometries, which enable applications such as seeing through turbid media. Despite this potential, THz spectroscopy using diffuse waves has not been demonstrated. The main obstacles are the very poor signal to noise ratios of the diffused fields and the resonance-like spectral artifacts due to multiple Mie scattering events that obscure the material absorption signatures. In this work, we demonstrate diffuse THz spectroscopy of a heterogeneous sample through turbid media using a novel technique based on the wavelet multiresolution analysis and the bimodality coefficient spectrum, which we define here for the first time using the skewness and kurtosis of the spectral images. The proposed method yields broadband and simultaneous material characterization at detection angles as high as 90° with respect to the incident beam. We determined the accuracy of the wavelet-based diffuse spectroscopy at oblique detection angles, by evaluating the area under the receiver operating characteristic curves, to be higher than 95%. This technique is agnostic to any a priori information on the spectral signatures of the sample materials or the characteristics of the scattering medium, and can be expanded for other broadband spectroscopic modalities.

Two graphs walk into a bar: Readout-based measurement reveals the Bar-Tip Limit error, a common, categorical misinterpretation of mean bar graphs

How do viewers interpret graphs that abstract away from individual-level data to present only summaries of data such as means, intervals, distribution shapes, or effect sizes? Here, focusing on the mean bar graph as a prototypical example of such an abstracted presentation, we contribute three advances to the study of graph interpretation. First, we distill principles for Measurement of Abstract Graph Interpretation (MAGI principles) to guide the collection of valid interpretation data from viewers who may vary in expertise. Second, using these principles, we create the Draw Datapoints on Graphs (DDoG) measure, which collects drawn readouts (concrete, detailed, visuospatial records of thought) as a revealing window into each person's interpretation of a given graph. Third, using this new measure, we discover a common, categorical error in the interpretation of mean bar graphs: the Bar-Tip Limit (BTL) error. The BTL error is an apparent conflation of mean bar graphs with count bar graphs. It occurs when the raw data are assumed to be limited by the bar-tip, as in a count bar graph, rather than distributed across the bar-tip, as in a mean bar graph. In a large, demographically diverse sample, we observe the BTL error in about one in five persons; across educational levels, ages, and genders; and despite thoughtful responding and relevant foundational knowledge. The BTL error provides a case-in-point that simplification via abstraction in graph design can risk severe, high-prevalence misinterpretation. The ease with which our readout-based DDoG measure reveals the nature and likely cognitive mechanisms of the BTL error speaks to the value of both its readout-based approach and the MAGI principles that guided its creation. We conclude that mean bar graphs may be misinterpreted by a large portion of the population, and that enhanced measurement tools and strategies, like those introduced here, can fuel progress in the scientific study of graph interpretation.

UrbanMotion: Visual Analysis of Metropolitan-Scale Sparse Trajectories

Visualizing massive scale human movement in cities plays an important role in solving many of the problems that modern cities face (e.g., traffic optimization, business site configuration). In this article, we study a big mobile location dataset that covers millions of city residents, but is temporally sparse on the trajectory of individual user. Mapping sparse trajectories to illustrate population movement poses several challenges from both analysis and visualization perspectives. In the literature, there are a few techniques designed for sparse trajectory visualization; yet they do not consider trajectories collected from mobile apps that possess long-tailed sparsity with record intervals as long as hours. This article introduces UrbanMotion, a visual analytics system that extends the original wind map design by supporting map-matched local movements, multi-directional population flows, and population distributions. Effective methods are proposed to extract and aggregate population movements from dense parts of the trajectories leveraging their long-tailed sparsity. Both characteristic and anomalous patterns are discovered and visualized. We conducted three case studies, one comparative experiment, and collected expert feedback in the application domains of commuting analysis, event detection, and business site configuration. The study result demonstrates the significance and effectiveness of our system in helping to complete key analytics tasks for urban users.

Lack of assortative mating might explain reduced phenotypic differentiation where two grasshopper species meet

Hybridization is an evolutionary process with wide‐ranging potential outcomes, from providing populations with important genetic variation for adaptation to being a substantial fitness cost leading to extinction. Here, we focussed on putative hybridization between two morphologically distinct species of New Zealand grasshopper. We collected Phaulacridium marginale and Phaulacridium otagoense specimens from a region where mitochondrial introgression had been detected and where their habitat has been modified by introduced mammals eating the natural vegetation and by the colonization of many non‐native plant species. In contrast to observations in the 1970s, our sampling of wild pairs of grasshoppers in copula provided no evidence of assortative mating with respect to species. Geometric morphometrics on pronotum shape of individuals from areas of sympatry detected phenotypically intermediate specimens (putative hybrids), and the distribution of phenotypes in most areas of sympatry was found to be unimodal. These results suggest that hybridization associated with anthropogenic habitat changes has led to these closely related species forming a hybrid swarm, with random mating. Without evidence of hybrid disadvantage, we suggest a novel hybrid lineage might eventually result from the merging of these two species.

Dataset on viscosity and starch polymer properties to predict texture through modeling

Accurate classification tool for screening varieties with superior eating and cooking quality based on its pasting and starch structure properties is in demand to satisfy both consumers’ and farmers’ need. Here we showed the data related to the article entitled “Deploying viscosity and starch polymer properties to predict cooking and eating quality models: a novel breeding tool to predict texture” [1] which provides solution to this problem. The paper compiles all the pasting, starch structure, sensory and routine quality data of the rice sample used in the article into graphical form. It also shows how the data were processed and obtained.

The virtual loss function in the summary perception of motion and its limited adjustability

Humans can grasp the "average" feature of a visual ensemble quickly and effortlessly. However, it is largely unknown what is the exact form of the summary statistic humans perceive and it is even less known whether this form can be changed by feedback. Here we borrow the concept of loss function to characterize how the summary perception is related to the distribution of feature values in the ensemble, assuming that the summary statistic minimizes a virtual expected loss associated with its deviation from individual feature values. In two experiments, we investigated a random-dot motion estimation task to infer the virtual loss function implicit in ensemble perception and see whether it can be changed by feedback. On each trial, participants reported the average moving direction of an ensemble of moving dots whose distribution of moving directions was skewed. In Experiment 1, where no feedback was available, participants' estimates fell between the mean and the mode of the distribution and were closer to the mean. In particular, the deviation from the mean and toward the mode increased almost linearly with the mode-to-mean distance. The pattern was best modeled by an inverse Gaussian loss function, which punishes large errors less heavily than the quadratic loss function does. In Experiment 2, we tested whether this virtual loss function can be altered by feedback. Two groups of participants either received the mode or the mean as the correct answer. After extensive training up to five days, both groups' estimates moved slightly towards the mode. That is, feedback had no specific influence on participants' virtual loss function. To conclude, the virtual loss function in the summary perception of motion is close to inverse Gaussian, and it can hardly be changed by feedback.

Verbal count sequence knowledge underpins numeral order processing in children

Recent research has suggested that numeral order processing - the speed and accuracy with which individuals can determine whether a set of digits is in numerical order or not - is related to arithmetic and mathematics outcomes. It has therefore been proposed that ordinal relations are a fundamental property of symbolic numeral representations. However, order information is also inherent in the verbal count sequence, and thus verbal count sequence knowledge may instead explain the relationship between performance on numeral order tasks and arithmetic. We explored this question with 62 children aged 6- to 8-years-old. We found that performance on a verbal count sequence knowledge task explained the relationship between numeral order processing and arithmetic. Moreover many children appeared to explicitly base their judgments of numerical order on count sequence information. This suggests that insufficient attention may have been paid to verbal number knowledge in understanding the sources of information that give meaning to numbers.

'Statistical Irreproducibility' Does Not Improve with Larger Sample Size: How to Quantify and Address Disease Data Multimodality in Human and Animal Research

Poor study reproducibility is a concern in translational research. As a solution, it is recommended to increase sample size (N), i.e., add more subjects to experiments. The goal of this study was to examine/visualize data multimodality (data with >1 data peak/mode) as cause of study irreproducibility. To emulate the repetition of studies and random sampling of study subjects, we first used various simulation methods of random number generation based on preclinical published disease outcome data from human gut microbiota-transplantation rodent studies (e.g., intestinal inflammation and univariate/continuous). We first used unimodal distributions (one-mode, Gaussian, and binomial) to generate random numbers. We showed that increasing N does not reproducibly identify statistical differences when group comparisons are repeatedly simulated. We then used multimodal distributions (>1-modes and Markov chain Monte Carlo methods of random sampling) to simulate similar multimodal datasets A and B (t-test-p = 0.95; N = 100,000), and confirmed that increasing N does not improve the ‘reproducibility of statistical results or direction of the effects’. Data visualization with violin plots of categorical random data simulations with five-integer categories/five-groups illustrated how multimodality leads to irreproducibility. Re-analysis of data from a human clinical trial that used maltodextrin as dietary placebo illustrated multimodal responses between human groups, and after placebo consumption. In conclusion, increasing N does not necessarily ensure reproducible statistical findings across repeated simulations due to randomness and multimodality. Herein, we clarify how to quantify, visualize and address disease data multimodality in research. Data visualization could facilitate study designs focused on disease subtypes/modes to help understand person–person differences and personalized medicine.

The nature of genetic and environmental susceptibility to multiple sclerosis

OBJECTIVE

To understand the nature of genetic and environmental susceptibility to multiple sclerosis (MS) and, by extension, susceptibility to other complex genetic diseases.

BACKGROUND

Certain basic epidemiological parameters of MS (e.g., population-prevalence of MS, recurrence-risks for MS in siblings and twins, proportion of women among MS patients, and the time-dependent changes in the sex-ratio) are well-established. In addition, more than 233 genetic-loci have now been identified as being unequivocally MS-associated, including 32 loci within the major histocompatibility complex (MHC), and one locus on the X chromosome. Despite this recent explosion in genetic associations, however, the association of MS with the HLA-DRB1*15:01~HLA-DQB1*06:02~a1 (H+) haplotype has been known for decades.

DESIGN/METHODS

We define the "genetically-susceptible" subset (G) to include everyone with any non-zero life-time chance of developing MS. Individuals who have no chance of developing MS, regardless of their environmental experiences, belong to the mutually exclusive "non-susceptible" subset (G-). Using these well-established epidemiological parameters, we analyze, mathematically, the implications that these observations have regarding the genetic-susceptibility to MS. In addition, we use the sex-ratio change (observed over a 35-year interval in Canada), to derive the relationship between MS-probability and an increasing likelihood of a sufficient environmental exposure.

RESULTS

We demonstrate that genetic-susceptibitly is confined to less than 7.3% of populations throughout Europe and North America. Consequently, more than 92.7% of individuals in these populations have no chance whatsoever of developing MS, regardless of their environmental experiences. Even among carriers of the HLA-DRB1*15:01~HLA-DQB1*06:02~a1 haplotype, far fewer than 32% can possibly be members the (G) subset. Also, despite the current preponderance of women among MS patients, women are less likely to be in the susceptible (G) subset and have a higher environmental threshold for developing MS compared to men. Nevertheless, the penetrance of MS in susceptible women is considerably greater than it is in men. Moreover, the response-curves for MS-probability in susceptible individuals increases with an increasing likelihood of a sufficient environmental exposure, especially among women. However, these environmental response-curves plateau at under 50% for women and at a significantly lower level for men.

CONCLUSIONS

The pathogenesis of MS requires both a genetic predisposition and a suitable environmental exposure. Nevertheless, genetic-susceptibility is rare in the population (< 7.3%) and requires specific combinations of non-additive genetic risk-factors. For example, only a minority of carriers of the HLA-DRB1*15:01~HLA-DQB1*06:02~a1 haplotype are even in the (G) subset and, thus, genetic-susceptibility to MS in these carriers must result from the combined effect this haplotype together with the effects of certain other (as yet, unidentified) genetic factors. By itself, this haplotype poses no MS-risk. By contrast, a sufficient environmental exposure (however many events are involved, whenever these events need to act, and whatever these events might be) is common, currently occurring in, at least, 76% of susceptible individuals. In addition, the fact that environmental response-curves plateau well below 50% (especially in men), indicates that disease pathogenesis is partly stochastic. By extension, other diseases, for which monozygotic-twin recurrence-risks greatly exceed the disease-prevalence (e.g., rheumatoid arthritis, diabetes, and celiac disease), must have a similar genetic basis.

Deploying viscosity and starch polymer properties to predict cooking and eating quality models: A novel breeding tool to predict texture

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Multivariate analysis was used to develop twelve cooking and eating quality classes.

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Two-layered random forest model was used to predict rice classification.

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High classification accuracy of cooking and eating quality ideotypes were obtained.

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Mismatches from IRRI-released and consumer-preferred lines was capture by the model.

Acceptance of new rice genotypes demanded by rice value chain depends on premium value of varieties that match consumer demands of regional preferences. High throughput prediction tools are not available to breeders to classify cooking and eating quality (CEQ) ideotypes and to capture texture of varieties. The pasting properties in combination with starch properties were used to develop two layered models in order to classify the rice varieties into twelve distinct CEQ ideotypes with unique sensory profiles. Classification models developed using random forest method depicted the overall accuracy of 96 %. These CEQ models were found to be robust to predict ideotypes in both Indica and Japonica diversity panels grown under dry and wet seasons and across the years. We conducted random forest modeling using 1.8 million high density SNPs and identified top 1000 SNP features which explained CEQ model classification with the accuracy of 0.81. Furthermore these CEQ models were found to be valuable to predict textural preferences of IRRI breeding lines released during 1960–2013 and mega varieties preferred in South and South East Asia.

Recent Developments in Species Sensitivity Distribution Modeling

The species sensitivity distribution (SSD) is a statistical approach that is used to estimate either the concentration of a chemical that is hazardous to no more than x% of all species (the HCx) or the proportion of species potentially affected by a given concentration of a chemical. Despite a significant body of published research and critical reviews over the past 20 yr aimed at improving the methodology, the fundamentals remain unchanged. Although there have been some recent suggestions for improvements to SSD methods in the literature, in general, few of these suggestions have been formally adopted. Furthermore, critics of the approach can rightly point to the fact that differences in technical implementation can lead to marked differences in results, thereby undermining confidence in SSD approaches. Despite the limitations, SSDs remain a practical tool and, until a demonstrably better inferential framework is available, developments and enhancements to conventional SSD practice will and should continue. We therefore believe the time has come for the scientific community to decide how it wants SSD methods to evolve. The present study summarizes the current status of, and elaborates on several recent developments for, SSD methods, specifically, model averaging, multimodality, and software development. We also consider future directions with respect to the use of SSDs, with the ultimate aim of helping to facilitate greater international collaboration and, potentially, greater harmonization of SSD methods. Environ Toxicol Chem 2021;40:293-308. © 2020 SETAC.

Overestimation of volatility in schizophrenia and autism? A comparative study using a probabilistic reasoning task

BACKGROUND AND OBJECTIVES

A plethora of studies has investigated and compared social cognition in autism and schizophrenia ever since both conditions were first described in conjunction more than a century ago. Recent computational theories have proposed similar mechanistic explanations for various symptoms beyond social cognition. They are grounded in the idea of a general misestimation of uncertainty but so far, almost no studies have directly compared both conditions regarding uncertainty processing. The current study aimed to do so with a particular focus on estimation of volatility, i.e. the probability for the environment to change.

METHODS

A probabilistic decision-making task and a visual working (meta-)memory task were administered to a sample of 86 participants (19 with a diagnosis of high-functioning autism, 21 with a diagnosis of schizophrenia, and 46 neurotypically developing individuals).

RESULTS

While persons with schizophrenia showed lower visual working memory accuracy than neurotypical individuals, no significant group differences were found for metamemory or any of the probabilistic decision-making task variables. Nevertheless, exploratory analyses suggest that there may be an overestimation of volatility in subgroups of participants with autism and schizophrenia. Correlations revealed relationships between different variables reflecting (mis)estimation of uncertainty, visual working memory accuracy and metamemory.

LIMITATIONS

Limitations include the comparably small sample sizes of the autism and the schizophrenia group as well as the lack of cognitive ability and clinical symptom measures.

CONCLUSIONS

The results of the current study provide partial support for the notion of a general uncertainty misestimation account of autism and schizophrenia.