Measuring Brain Activity Correlates of Behavior: A Methodological Overview

The present article was prepared as an introduction to current approaches to studying brain activity correlates of behavior. Our goals are to (1) acquaint readers with current methods for detecting brain activity correlates of behavior and (2) suggest examples of scientific opportunities for collaborative research with brain scientists

Studies of Brain Activity Correlates of Behavior in Individuals with and without Developmental Disabilities

There is a rich assortment of brain imaging methodologies that permits evaluation of the covert events that are necessary to complete a comprehensive account of behavior. Among the latter methodologies, our laboratories have begun to explore event-related potential (ERP) research to complement traditional behavior analysis

Revisiting consistency conditions for quantum states of systems on closed timelike curves: an epistemic perspective

There has been considerable recent interest in the consequences of closed timelike curves (CTCs) for the dynamics of quantum mechanical systems. A vast majority of research into this area makes use of the dynamical equations developed by Deutsch, which were developed from a consistency condition that assumes that mixed quantum states uniquely describe the physical state of a system. We criticise this choice of consistency condition from an epistemic perspective, i.e., a perspective in which the quantum state represents a state of knowledge about a system. We demonstrate that directly applying Deutsch's condition when mixed states are treated as representing an observer's knowledge of a system can conceal time travel paradoxes from the observer, rather than resolving them. To shed further light on the appropriate dynamics for quantum systems traversing CTCs, we make use of a toy epistemic theory with a strictly classical ontology due to Spekkens and show that, in contrast to the results of Deutsch, many of the traditional paradoxical effects of time travel are present.Comment: 10 pages, 6 figures, comments welcome; v2 added references and clarified some points; v3 published versio

Understanding concurrent earcons: applying auditory scene analysis principles to concurrent earcon recognition

Two investigations into the identification of concurrently presented, structured sounds, called earcons were carried out. One of the experiments investigated how varying the number of concurrently presented earcons affected their identification. It was found that varying the number had a significant effect on the proportion of earcons identified. Reducing the number of concurrently presented earcons lead to a general increase in the proportion of presented earcons successfully identified. The second experiment investigated how modifying the earcons and their presentation, using techniques influenced by auditory scene analysis, affected earcon identification. It was found that both modifying the earcons such that each was presented with a unique timbre, and altering their presentation such that there was a 300 ms onset-to-onset time delay between each earcon were found to significantly increase identification. Guidelines were drawn from this work to assist future interface designers when incorporating concurrently presented earcons

Experimental Implementation of the Deutsch-Jozsa Algorithm for Three-Qubit Functions using Pure Coherent Molecular Superpositions

The Deutsch-Jozsa algorithm is experimentally demonstrated for three-qubit functions using pure coherent superpositions of Li$_{2}$ rovibrational eigenstates. The function's character, either constant or balanced, is evaluated by first imprinting the function, using a phase-shaped femtosecond pulse, on a coherent superposition of the molecular states, and then projecting the superposition onto an ionic final state, using a second femtosecond pulse at a specific time delay

Predicting the Impact of Climate Change on Threatened Species in UK Waters

Global climate change is affecting the distribution of marine species and is thought to represent a threat to biodiversity. Previous studies project expansion of species range for some species and local extinction elsewhere under climate change. Such range shifts raise concern for species whose long-term persistence is already threatened by other human disturbances such as fishing. However, few studies have attempted to assess the effects of future climate change on threatened vertebrate marine species using a multi-model approach. There has also been a recent surge of interest in climate change impacts on protected areas. This study applies three species distribution models and two sets of climate model projections to explore the potential impacts of climate change on marine species by 2050. A set of species in the North Sea, including seven threatened and ten major commercial species were used as a case study. Changes in habitat suitability in selected candidate protected areas around the UK under future climatic scenarios were assessed for these species. Moreover, change in the degree of overlap between commercial and threatened species ranges was calculated as a proxy of the potential threat posed by overfishing through bycatch. The ensemble projections suggest northward shifts in species at an average rate of 27 km per decade, resulting in small average changes in range overlap between threatened and commercially exploited species. Furthermore, the adverse consequences of climate change on the habitat suitability of protected areas were projected to be small. Although the models show large variation in the predicted consequences of climate change, the multi-model approach helps identify the potential risk of increased exposure to human stressors of critically endangered species such as common skate (Dipturus batis) and angelshark (Squatina squatina)

Molecular basis for increased susceptibility of Indigenous North Americans to seropositive rheumatoid arthritis

Objective The pathogenetic mechanisms by which HLA-DRB1 alleles are associated with anticitrullinated peptide antibody (ACPA)-positive rheumatoid arthritis (RA) are incompletely understood. RA high-risk HLA-DRB1 alleles are known to share a common motif, the ‘shared susceptibility epitope (SE)’. Here, the electropositive P4 pocket of HLA-DRB1 accommodates self-peptide residues containing citrulline but not arginine. HLA-DRB1 His/Phe13β stratifies with ACPA-positive RA, while His13βSer polymorphisms stratify with ACPA-negative RA and RA protection. Indigenous North American (INA) populations have high risk of early-onset ACPA-positive RA, whereby HLA-DRB1*04:04 and HLA-DRB1*14:02 are implicated as risk factors for RA in INA. However, HLA-DRB1*14:02 has a His13βSer polymorphism. Therefore, we aimed to verify this association and determine its molecular mechanism. Methods HLA genotype was compared in 344 INA patients with RA and 352 controls. Structures of HLA-DRB1*1402-class II loaded with vimentin-64Arg59-71, vimentin-64Cit59-71 and fibrinogen β−74Cit69-81 were solved using X-ray crystallography. Vimentin-64Cit59-71-specific and vimentin59-71-specific CD4+ T cells were characterised by flow cytometry using peptide-histocompatibility leukocyte antigen (pHLA) tetramers. After sorting of antigen-specific T cells, TCRα and β-chains were analysed using multiplex, nested PCR and sequencing. Results ACPA+ RA in INA was independently associated with HLA-DRB1*14:02. Consequent to the His13βSer polymorphism and altered P4 pocket of HLA-DRB1*14:02, both citrulline and arginine were accommodated in opposite orientations. Oligoclonal autoreactive CD4+ effector T cells reactive with both citrulline and arginine forms of vimentin59-71 were observed in patients with HLA-DRB1*14:02+ RA and at-risk ACPA- first-degree relatives. HLA-DRB1*14:02-vimentin59-71-specific and HLA-DRB1*14:02-vimentin-64Cit59-71-specific CD4+ memory T cells were phenotypically distinct populations. Conclusion HLA-DRB1*14:02 broadens the capacity for citrullinated and native self-peptide presentation and T cell expansion, increasing risk of ACPA+ RA

Highly Diastereo- and Enantioselective CuH-Catalyzed Synthesis of 2,3-Disubstituted Indolines

A diastereo- and enantioselective CuH-catalyzed method for the preparation of highly functionalized indolines is reported. The mild reaction conditions and high degree of functional group compatibility as demonstrated with substrates bearing heterocycles, olefins, and substituted aromatic groups, renders this technique highly valuable for the synthesis of a variety of cis-2,3-disubstituted indolines in high yield and enantioeselectivity.National Institutes of Health (U.S.) (Award GM46059)Danish Council for Independent Research (Postdoctoral Fellowship

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures