Sharing brain mapping statistical results with the neuroimaging data model

Only a tiny fraction of the data and metadata produced by an fMRI study is finally conveyed to the community. This lack of transparency not only hinders the reproducibility of neuroimaging results but also impairs future meta-analyses. In this work we introduce NIDM-Results, a format specification providing a machine-readable description of neuroimaging statistical results along with key image data summarising the experiment. NIDM-Results provides a unified representation of mass univariate analyses including a level of detail consistent with available best practices. This standardized representation allows authors to relay methods and results in a platform-independent regularized format that is not tied to a particular neuroimaging software package. Tools are available to export NIDM-Result graphs and associated files from the widely used SPM and FSL software packages, and the NeuroVault repository can import NIDM-Results archives. The specification is publically available at: http://nidm.nidash.org/specs/nidm-results.html

Neural and physiological data from participants listening to affective music

Music provides a means of communicating affective meaning. However, the neurological mechanisms by which music induces affect are not fully understood. Our project sought to investigate this through a series of experiments into how humans react to affective musical stimuli and how physiological and neurological signals recorded from those participants change in accordance with self-reported changes in affect. In this paper, the datasets recorded over the course of this project are presented, including details of the musical stimuli, participant reports of their felt changes in affective states as they listened to the music, and concomitant recordings of physiological and neurological activity. We also include non-identifying meta data on our participant populations for purposes of further exploratory analysis. This data provides a large and valuable novel resource for researchers investigating emotion, music, and how they affect our neural and physiological activity

Considerations for reducing food system energy demand while scaling up urban agriculture

There is an increasing global interest in scaling up urban agriculture (UA) in its various forms, from private gardens to sophisticated commercial operations. Much of this interest is in the spirit of environmental protection, with reduced waste and transportation energy highlighted as some of the proposed benefits of UA; however, explicit consideration of energy and resource requirements needs to be made in order to realize these anticipated environmental benefits. A literature review is undertaken here to provide new insight into the energy implications of scaling up UA in cities in high-income countries, considering UA classification, direct/indirect energy pressures, and interactions with other components of the food–energy–water nexus. This is followed by an exploration of ways in which these cities can plan for the exploitation of waste flows for resource-efficient UA. Given that it is estimated that the food system contributes nearly 15% of total US energy demand, optimization of resource use in food production, distribution, consumption, and waste systems may have a significant energy impact. There are limited data available that quantify resource demand implications directly associated with UA systems, highlighting that the literature is not yet sufficiently robust to make universal claims on benefits. This letter explores energy demand from conventional resource inputs, various production systems, water/energy trade-offs, alternative irrigation, packaging materials, and transportation/supply chains to shed light on UA-focused research needs. By analyzing data and cases from the existing literature, we propose that gains in energy efficiency could be realized through the co-location of UA operations with waste streams (e.g. heat, CO2, greywater, wastewater, compost), potentially increasing yields and offsetting life cycle energy demands relative to conventional approaches. This begs a number of energy-focused UA research questions that explore the opportunities for integrating the variety of UA structures and technologies, so that they are better able to exploit these urban waste flows and achieve whole-system reductions in energy demand. Any planning approach to implement these must, as always, assess how context will influence the viability and value added from the promotion of UA

Left dorsolateral prefrontal cortex supports context-dependent prioritisation of off-task thought

When environments lack compelling goals, humans often let their minds wander to thoughts with greater personal relevance; however, we currently do not understand how this context-dependent prioritisation process operates. Dorsolateral prefrontal cortex (DLPFC) maintains goal representations in a context-dependent manner. Here, we show this region is involved in prioritising off-task thought in an analogous way. In a whole brain analysis we established that neural activity in DLPFC is high both when ‘on-task’ under demanding conditions and ‘off-task’ in a non-demanding task. Furthermore, individuals who increase off-task thought when external demands decrease, show lower correlation between neural signals linked to external tasks and lateral regions of the DMN within DLPFC, as well as less cortical grey matter in regions sensitive to these external task relevant signals. We conclude humans prioritise daydreaming when environmental demands decrease by aligning cognition with their personal goals using DLPFC

A large-scale study on the effects of sex on gray matter asymmetry

Research on sex-related brain asymmetries has not yielded consistent results. Despite its importance to further understanding of normal brain development and mental disorders, the field remains relatively unexplored. Here we employ a recently developed asymmetry measure, based on the Dice coefficient, to detect sex-related gray matter asymmetries in a sample of 457 healthy participants (266 men and 191 women) obtained from 5 independent databases. Results show that women’s brains are more globally symmetric than men’s (p < 0.001). Although the new measure accounts for asymmetries distributed all over the brain, several specific structures were identified as systematically more symmetric in women, such as the thalamus and the cerebellum, among other structures, some of which are typically involved in language production. These sex-related asymmetry differences may be defined at the neurodevelopmental stage and could be associated with functional and cognitive sex differences, as well as with proneness to develop a mental disorder

Best practices in data analysis and sharing in neuroimaging using MRI

Given concerns about the reproducibility of scientific findings, neuroimaging must define best practices for data analysis, results reporting, and algorithm and data sharing to promote transparency, reliability and collaboration. We describe insights from developing a set of recommendations on behalf of the Organization for Human Brain Mapping, and identify barriers that impede these practices, including how the discipline must change to fully exploit the potential of the world’s neuroimaging data