A neural network for religious fundamentalism derived from patients with brain lesions.

Religious fundamentalism, characterized by rigid adherence to a set of beliefs putatively revealing inerrant truths, is ubiquitous across cultures and has a global impact on society. Understanding the psychological and neurobiological processes producing religious fundamentalism may inform a variety of scientific, sociological, and cultural questions. Research indicates that brain damage can alter religious fundamentalism. However, the precise brain regions involved with these changes remain unknown. Here, we analyzed brain lesions associated with varying levels of religious fundamentalism in two large datasets from independent laboratories. Lesions associated with greater fundamentalism were connected to a specific brain network with nodes in the right orbitofrontal, dorsolateral prefrontal, and inferior parietal lobe. This fundamentalism network was strongly right hemisphere lateralized and highly reproducible across the independent datasets (r = 0.82) with cross-validations between datasets. To explore the relationship of this network to lesions previously studied by our group, we tested for similarities to twenty-one lesion-associated conditions. Lesions associated with confabulation and criminal behavior showed a similar connectivity pattern as lesions associated with greater fundamentalism. Moreover, lesions associated with poststroke pain showed a similar connectivity pattern as lesions associated with lower fundamentalism. These findings are consistent with the current understanding of hemispheric specializations for reasoning and lend insight into previously observed epidemiological associations with fundamentalism, such as cognitive rigidity and outgroup hostility.

Fatigue and vigilance in medical experts detecting breast cancer.

An abundance of laboratory-based experiments has described a vigilance decrement of reducing accuracy to detect targets with time on task, but there are few real-world studies, none of which have previously controlled the environment to control for bias. We describe accuracy in clinical practice for 360 experts who examined >1 million women's mammograms for signs of cancer, whilst controlling for potential biases. The vigilance decrement pattern was not observed. Instead, test accuracy improved over time, through a reduction in false alarms and an increase in speed, with no significant change in sensitivity. The multiple-decision model explains why experts miss targets in low prevalence settings through a change in decision threshold and search quit threshold and propose it should be adapted to explain these observed patterns of accuracy with time on task. What is typically thought of as standard and robust research findings in controlled laboratory settings may not directly apply to real-world environments and instead large, controlled studies in relevant environments are needed.

Encoding Manual Dexterity through Modulation of Intrinsic α Band Connectivity.

The human hand possesses both consolidated motor skills and remarkable flexibility in adapting to ongoing task demands. However, the underlying mechanisms by which the brain balances stability and flexibility remain unknown. In the absence of external input or behavior, spontaneous (intrinsic) brain connectivity is thought to represent a prior of stored memories. In this study, we investigated how manual dexterity modulates spontaneous functional connectivity in the motor cortex during hand movement. Using magnetoencephalography, in 47 human participants (both sexes), we examined connectivity modulations in the α and ß frequency bands at rest and during two motor tasks (i.e., finger tapping or toe squeezing). The flexibility and stability of such modulations allowed us to identify two groups of participants with different levels of performance (high and low performers) on the nine-hole peg test, a test of manual dexterity. In the α band, participants with higher manual dexterity showed distributed decreases of connectivity, specifically in the motor cortex, increased segregation, and reduced nodal centrality. Participants with lower manual dexterity showed an opposite pattern. Notably, these patterns from the brain to behavior are mirrored by results from behavior to the brain. Indeed, when participants were divided using the median split of the dexterity score, we found the same connectivity patterns. In summary, this experiment shows that a long-term motor skill-manual dexterity-influences the way the motor systems respond during movements.

Early morning anopheline mosquito biting, a potential driver of malaria transmission in Busia County, western Kenya.

BACKGROUND: Insecticide-treated nets (ITNs) contributed significantly to the decline in malaria since 2000. Their protective efficacy depends not only on access, use, and net integrity, but also location of people within the home environment and mosquito biting profiles. Anopheline mosquito biting and human location data were integrated to identify potential gaps in protection and better understand malaria transmission dynamics in Busia County, western Kenya. METHODS: Direct observation of human activities and human landing catches (HLC) were performed hourly between 1700 to 0700 h. Household members were recorded as home or away; and, if at home, as indoors/outdoors, awake/asleep, and under a net or not. Aggregated data was analysed by weighting hourly anopheline biting activity with human location. Standard indicators of human-vector interaction were calculated using a Microsoft Excel template. RESULTS: There was no significant difference between indoor and outdoor biting for Anopheles gambiae sensu lato (s.l.) (RR = 0.82; 95% CI 0.65-1.03); significantly fewer Anopheles funestus were captured outdoors than indoors (RR = 0.41; 95% CI 0.25-0.66). Biting peaked before dawn and extended into early morning hours when people began to awake and perform routine activities, between 0400-0700 h for An. gambiae and 0300-0700 h for An. funestus. The study population away from home peaked at 1700-1800 h (58%), gradually decreased and remained constant at 10% throughout the night, before rising again to 40% by 0600-0700 h. When accounting for resident location, nearly all bites within the peri-domestic space (defined as inside household structures and surrounding outdoor spaces) occurred indoors for unprotected people (98%). Using an ITN while sleeping was estimated to prevent 79% and 82% of bites for An. gambiae and An. funestus, respectively. For an ITN user, most remaining exposure to bites occurred indoors in the hours before bed and early morning. CONCLUSION: While use of an ITN was estimated to prevent most vector bites in this context, results suggest gaps in protection, particularly in the early hours of the morning when biting peaks and many people are awake and active. Assessment of additional human exposure points, including outside of the peri-domestic setting, are needed to guide supplementary interventions for transmission reduction.

A qualitative look at bed net access and use in Burkina Faso, Mozambique, Nigeria, and Rwanda following piloted distributions of dual-active ingredient insecticide-treated nets.

BACKGROUND: Universal coverage with insecticide-treated nets (ITNs) is important for malaria control and elimination. The emergence and intensification of insecticide resistance threatens progress made through the deployment of these interventions and has required the development of newer, more expensive ITN types. Understanding malaria prevention behaviour, including barriers and facilitators to net access and use, can support effective decision-making for the promotion and distribution of ITNs. METHODS: In-depth interviews and focus group discussions were conducted in 3 to 4 villages per district, in 13 districts across Burkina Faso, Mozambique, Nigeria and Rwanda from 2019 to 2022. Interviews were conducted in the local language, translated and transcribed in English, French or Portuguese. Transcripts were coded and analysed using Nvivo and ATLAS.ti. RESULTS: ITNs were obtained from mass distribution campaigns, antenatal care and immunization visits, and purchased on the private market in some locations. While there were divergent perspectives in whether the number of distributed nets were adequate, participants consistently expressed concerns of bias, discrimination, and a lack of transparency with the distribution process. ITNs were frequently used alongside other malaria prevention methods. The primary motivation for use was malaria prevention. While some participants reported using nets nightly throughout the year, other participants reported seasonal use, both due to the perceived higher density of mosquitoes and discomfort of sleeping under a net in the increased heat. Other barriers to consistent net use included activities that take place away from the home, sleeping patterns and arrangements, and sensitivity to the insecticides on the nets. CONCLUSIONS: ITNs remain an important malaria control intervention. To ensure adequate and increased net access, distribution campaigns should consider family structures, available sleeping spaces, and other bed sharing preferences when identifying the number of nets needed for distribution. In addition, campaigns should allow for multiple options for net distribution points and timing to accommodate households remote to health services. Continuous distribution channels and complimentary distribution through the private sector could help fill gaps in coverage. Solutions are needed for outdoor malaria transmission, including alternative designs for ITNs, and improving access to complementary personal protective measures.

Modelling the impact of human behavior using a two-layer Watts-Strogatz network for transmission and control of Mpox.

PURPOSE: This study aims to evaluate the effectiveness of mitigation strategies and analyze the impact of human behavior on the transmission of Mpox. The results can provide guidance to public health authorities on comprehensive prevention and control for the new Mpox virus strain in the Democratic Republic of Congo as of December 2023. METHODS: We develop a two-layer Watts-Strogatz network model. The basic reproduction number is calculated using the next-generation matrix approach. Markov chain Monte Carlo (MCMC) optimization algorithm is used to fit Mpox cases in Canada into the network model. Numerical simulations are used to assess the impact of mitigation strategies and human behavior on the final epidemic size. RESULTS: Our results show that the contact transmission rate of low-risk groups and susceptible humans increases when the contact transmission rate of high-risk groups and susceptible humans is controlled as the Mpox epidemic spreads. The contact transmission rate of high-risk groups after May 18, 2022, is approximately 20% lower than that before May 18, 2022. Our findings indicate a positive correlation between the basic reproduction number and the level of heterogeneity in human contacts, with the basic reproduction number estimated at 2.3475 (95% CI: 0.0749-6.9084). Reducing the average number of sexual contacts to two per week effectively reduces the reproduction number to below one. CONCLUSION: We need to pay attention to the re-emergence of the epidemics caused by low-risk groups when an outbreak dominated by high-risk groups is under control. Numerical simulations show that reducing the average number of sexual contacts to two per week is effective in slowing down the rapid spread of the epidemic. Our findings offer guidance for the public health authorities of the Democratic Republic of Congo in developing effective mitigation strategies.

SensorNet: An Adaptive Attention Convolutional Neural Network for Sensor Feature Learning.

This work develops a generalizable neural network, SENSORNET, for sensor feature learning across various applications. The primary challenge addressed is the poor portability of pretrained neural networks to new applications with limited sensor data. To solve this challenge, we design SensorNet, which integrates the flexibility of self-attention with multi-scale feature locality of convolution. Moreover, we invent patch-wise self-attention with stacked multi-heads to enrich the sensor feature representation. SensorNet is generalizable to pervasive applications with any number of sensor inputs, and is much smaller than the state-of-the-art self-attention and convolution hybrid baseline (0.83 M vs. 3.87 M parameters) with similar performance. The experimental results show that SensorNet is able to achieve state-of-the-art performance compared with the top five models on a competition activity recognition dataset (SHL'18). Moreover, pretrained SensorNet in a large inertial measurement unit (IMU) dataset can be fine-tuned to achieve the best accuracy on a much smaller IMU dataset (up to 5% improvement in WISDM) and to achieve the state-of-the-art performance on an EEG dataset (SLEEP-EDF-20), showing the strong generalizability of our approach.

Bridging Requirements, Planning, and Evaluation: A Review of Social Robot Navigation.

Navigation lies at the core of social robotics, enabling robots to navigate and interact seamlessly in human environments. The primary focus of human-aware robot navigation is minimizing discomfort among surrounding humans. Our review explores user studies, examining factors that cause human discomfort, to perform the grounding of social robot navigation requirements and to form a taxonomy of elementary necessities that should be implemented by comprehensive algorithms. This survey also discusses human-aware navigation from an algorithmic perspective, reviewing the perception and motion planning methods integral to social navigation. Additionally, the review investigates different types of studies and tools facilitating the evaluation of social robot navigation approaches, namely datasets, simulators, and benchmarks. Our survey also identifies the main challenges of human-aware navigation, highlighting the essential future work perspectives. This work stands out from other review papers, as it not only investigates the variety of methods for implementing human awareness in robot control systems but also classifies the approaches according to the grounded requirements regarded in their objectives.

Meta-analyses of motivational factors of response to natural disaster.

Response behavior of individuals is of critical importance to decrease chances of injury and death as well as ameliorate costs in property and infrastructure damage in natural disasters. Plenty of studies have examined which factors motivate individuals to respond to natural disasters. However, a systematic overview of the key motivating factors of various response behaviors is lacking. This study conducts a series of meta-analyses using data of 53,713 samples from 87 studies (77 papers) conducted in 27 different countries and regions to examine how 17 motivational factors were associated with individuals' response to natural disasters. The results indicate self-efficacy, outcome efficacy, attitudes, subjective norms, and information acquisition show the strongest effects on response behavior. Contrarily, the impact of negative affects like fear, depression, and anxiety on victims is minimal, despite the common assumption that they are significant related to response behaviour. In addition, current studies have disproportionally focused on studying risk perception, experience and information acquisition, earthquake and hurricane, and evacuation and preparation, while attention given to other types of motivational factors, disasters and response behaviors is lacking.

A cultural evolutionary model of the interaction between parental beliefs and behaviors, with applications to vaccine hesitancy.

Health perceptions and health-related behaviors can change at the population level as cultures evolve. In the last decade, despite the proven efficacy of vaccines, the developed world has seen a resurgence of vaccine-preventable diseases (VPDs) such as measles, pertussis, and polio. Vaccine hesitancy, which is influenced by historical, political, and socio-cultural forces, is believed to be a primary factor responsible for decreasing vaccine coverage, thereby increasing the risk and occurrence of VPD outbreaks. Behavior change models have been increasingly employed to understand disease dynamics and intervention effectiveness. However, since health behaviors are culturally influenced, it is valuable to examine them within a cultural evolution context. Here, using a mathematical modeling framework, we explore the effects of cultural evolution on vaccine hesitancy and vaccination behavior. With this model, we shed light on facets of cultural evolution (vertical transmission, community influences, homophily, etc.) that promote the spread of vaccine hesitancy, ultimately affecting levels of vaccination coverage and VPD outbreak risk in a population. In addition, we present our model as a generalizable framework for exploring cultural evolution when humans' beliefs influence, but do not strictly dictate, their behaviors. This model offers a means of exploring how parents' potentially conflicting beliefs and cultural traits could affect their children's health and fitness. We show that vaccine confidence and vaccine-conferred benefits can both be driving forces of vaccine coverage. We also demonstrate that an assortative preference among vaccine-hesitant individuals can lead to increased vaccine hesitancy and lower vaccine coverage.