Multidimensional Recording (MDR) and Data Sharing: An Ecological Open Research and Educational Platform for Neuroscience

Primate neurophysiology has revealed various neural mechanisms at the single-cell level and population level. However, because recording techniques have not been updated for several decades, the types of experimental design that can be applied in the emerging field of social neuroscience are limited, in particular those involving interactions within a realistic social environment. To address these limitations and allow more freedom in experimental design to understand dynamic adaptive neural functions, multidimensional recording (MDR) was developed. MDR obtains behavioral, neural, eye position, and other biological data simultaneously by using integrated multiple recording systems. MDR gives a wide degree of freedom in experimental design because the level of behavioral restraint is adjustable depending on the experimental requirements while still maintaining the signal quality. The biggest advantage of MDR is that it can provide a stable neural signal at higher temporal resolution at the network level from multiple subjects for months, which no other method can provide. Conventional event-related analysis of MDR data shows results consistent with previous findings, whereas new methods of analysis can reveal network mechanisms that could not have been investigated previously. MDR data are now shared in the public server Neurotycho.org. These recording and sharing methods support an ecological system that is open to everyone and will be a valuable and powerful research/educational platform for understanding the dynamic mechanisms of neural networks

A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability

A Digital Repository and Execution Platform for Interactive Scholarly Publications in Neuroscience

The CARMEN Virtual Laboratory (VL) is a cloud-based platform which allows neuroscientists to store, share, develop, execute, reproduce and publicise their work. This paper describes new functionality in the CARMEN VL: an interactive publications repository. This new facility allows users to link data and software to publications. This enables other users to examine data and software associated with the publication and execute the associated software within the VL using the same data as the authors used in the publication. The cloud-based architecture and SaaS (Software as a Service) framework allows vast data sets to be uploaded and analysed using software services. Thus, this new interactive publications facility allows others to build on research results through reuse. This aligns with recent developments by funding agencies, institutions, and publishers with a move to open access research. Open access provides reproducibility and verification of research resources and results. Publications and their associated data and software will be assured of long-term preservation and curation in the repository. Further, analysing research data and the evaluations described in publications frequently requires a number of execution stages many of which are iterative. The VL provides a scientific workflow environment to combine software services into a processing tree. These workflows can also be associated with publications and executed by users. The VL also provides a secure environment where users can decide the access rights for each resource to ensure copyright and privacy restrictions are met

alpha-decay of excited states in 11C and 11B

Studies of the 16O(9Be,alpha7Be)14C and 7Li(9Be,alpha7Li)5He reactions at E{beam}=70 MeV have been performed using resonant particle spectroscopy techniques. The 11C excited states decaying into alpha+7Be(gs) are observed at 8.65, 9.85, 10.7 and 12.1 MeV as well as possible states at 12.6 and 13.4 MeV. This result is the first observation of alpha-decay for excited states above 9 MeV. The alpha+7Li(gs) decay of 11B excited states at 9.2, 10.3, 10.55, 11.2, (11.4), 11.8, 12.5,(13.0), 13.1, (14.0), 14.35, (17.4) and (18.6) MeV is observed. The decay processes are used to indicate the possible three-centre 2alpha+3He(3H) cluster structure of observed states. Two rotational bands corresponding to very deformed structures are suggested for the positive-parity states. Excitations of some observed T=1/2 resonances coincide with the energies of T=3/2 states which are the isobaric analogs of the lowest 11Be states. Some of these states may have mixed isospin.Comment: accepted for publication in Nuclear Physics

Would the field of cognitive neuroscience be advanced by sharing functional MRI data?

During the past two decades, the advent of functional magnetic resonance imaging (fMRI) has fundamentally changed our understanding of brain-behavior relationships. However, the data from any one study add only incrementally to the big picture. This fact raises important questions about the dominant practice of performing studies in isolation. To what extent are the findings from any single study reproducible? Are researchers who lack the resources to conduct a fMRI study being needlessly excluded? Is pre-existing fMRI data being used effectively to train new students in the field? Here, we will argue that greater sharing and synthesis of raw fMRI data among researchers would make the answers to all of these questions more favorable to scientific discovery than they are today and that such sharing is an important next step for advancing the field of cognitive neuroscience

Why Are Computational Neuroscience and Systems Biology So Separate?

Despite similar computational approaches, there is surprisingly little interaction between the computational neuroscience and the systems biology research communities. In this review I reconstruct the history of the two disciplines and show that this may explain why they grew up apart. The separation is a pity, as both fields can learn quite a bit from each other. Several examples are given, covering sociological, software technical, and methodological aspects. Systems biology is a better organized community which is very effective at sharing resources, while computational neuroscience has more experience in multiscale modeling and the analysis of information processing by biological systems. Finally, I speculate about how the relationship between the two fields may evolve in the near future

Human Factors Analysis of Naval Transport Aircraft Maintenance and Flight Line Related Incidents

The article of record as published may be found at https://www.jstor.org/stable/44729462To study maintainer error, the Naval Safety Center’s Human Factors Accident Classification System (HFACS) was adapted for Maintenance Related Mishaps (MRMs). The HFACS Maintenance Extension (ME) successfully profiled the errors present Naval Aviation Class A MRMs. In order to assess its suitability for studying major and minor airline accidents, a post hoc analysis was conducted on 124 Naval Fleet Logistics Support (VR) Wing maintenance related mishap, hazard, and injury reports. Two judges separately coded the 124 VR Wing incidents; a Cohen’s kappa of .78 was achieved, indicating an “excellent” level of agreement. Generally, HFACS-ME was able to profile maintainer errors found in more minor incidents and the factors that contribute to them. Common factors observed include errors attributed to third party maintenance, inadequate supervision, failed communications, skill-based errors, and procedural violations