Introduction: Sudden impact disasters often result in the displacement of large numbers of people. These movements can occur prior to events, due to early warning messages, or take place post-event due to damages to shelters and livelihoods as well as a result of long-term reconstruction efforts. Displaced populations are especially vulnerable and often in need of support. However, timely and accurate data on the numbers and destinations of displaced populations are extremely challenging to collect across temporal and spatial scales, especially in the aftermath of disasters. Mobile phone call detail records were shown to be a valid data source for estimates of population movements after the 2010 Haiti earthquake, but their potential to provide near real-time ongoing measurements of population displacements immediately after a natural disaster has not been demonstrated.Methods: A computational architecture and analytical capacity were rapidly deployed within nine days of the Nepal earthquake of 25th April 2015, to provide spatiotemporally detailed estimates of population displacements from call detail records based on movements of 12 million de-identified mobile phones users.Results: Analysis shows the evolution of population mobility patterns after the earthquake and the patterns of return to affected areas, at a high level of detail. Particularly notable is the movement of an estimated 390,000 people above normal from the Kathmandu valley after the earthquake, with most people moving to surrounding areas and the highly-populated areas in the central southern area of Nepal.Discussion: This analysis provides an unprecedented level of information about human movement after a natural disaster, provided within a very short timeframe after the earthquake occurred. The patterns revealed using this method are almost impossible to find through other methods, and are of great interest to humanitarian agencies.

Converging neuroscientific evidence suggests the existence of close links between language and sensorimotor cognition. Accordingly, during the comprehension of meaningful actions, our brain would recruit semantic-related operations similar to those associated with the processing of language information. Consistent with this view, electrophysiological findings show that the N400 component, traditionally linked to the semantic processing of linguistic material, can also be elicited by action-related material. This review outlines recent data from N400 studies that examine the understanding of action events. We focus on three specific domains, including everyday action comprehension, co-speech gesture integration, and the semantics involved in motor planning and execution. Based on the reviewed findings, we suggest that both negativities (the N400 and the action-N400) reflect a common neurocognitive mechanism involved in the construction of meaning through the expectancies created by previous experiences and current contextual information. To shed light on how this process is instantiated in the brain, a testable contextual fronto-temporo-parietal model is proposed.

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Social learning, defined as the imitation of behaviours performed by others, is recognised as a distinctive characteristic in humans and several other animal species. Previous work has claimed that the evolutionary fixation of social learning requires decision-making cognitive abilities that result in transmission bias (e.g., discriminatory imitation) and/or guided variation (e.g., adaptive modification of behaviours through individual learning). Here, we present and analyse a simple agent-based model which demonstrates that the transition from instinctive actuators (i.e., non-learning agents whose behaviour is hardcoded in their genes) to social learners (i.e., agents that imitate behaviours) can occur without invoking such decision-making abilities. The model shows that the social learning of a trait may evolve and fix in a population if there are many possible behavioural variants of the trait, if it is subject to strong selection pressure for survival (as distinct from reproduction), and if imitation errors occur at a higher rate than genetic mutation. These results demonstrate that the (sometimes implicit) assumption in prior work that decision-making abilities are required is incorrect, thus allowing a more parsimonious explanation for the evolution of social learning that applies to a wider range of organisms. Furthermore, we identify genotype-phenotype disengagement as a signal for the imminent fixation of social learners, and explain the way in which this disengagement leads to the emergence of a basic form of cultural evolution (i.e., a non-genetic evolutionary system).