The challenges of data in future pandemics.

The use of data has been essential throughout the unfolding COVID-19 pandemic. We have needed it to populate our models, inform our understanding, and shape our responses to the disease. However, data has not always been easy to find and access, it has varied in quality and coverage, been difficult to reuse or repurpose. This paper reviews these and other challenges and recommends steps to develop a data ecosystem better able to deal with future pandemics by better supporting preparedness, prevention, detection and response.

Information Quality Challenges of Patient-Generated Data in Clinical Practice.

A characteristic trend of digital health has been the dramatic increase in patient-generated data being presented to clinicians, which follows from the increased ubiquity of self-tracking practices by individuals, driven, in turn, by the proliferation of self-tracking tools and technologies. Such tools not only make self-tracking easier but also potentially more reliable by automating data collection, curation, and storage. While self-tracking practices themselves have been studied extensively in human-computer interaction literature, little work has yet looked at whether these patient-generated data might be able to support clinical processes, such as providing evidence for diagnoses, treatment monitoring, or postprocedure recovery, and how we can define information quality with respect to self-tracked data. In this article, we present the results of a literature review of empirical studies of self-tracking tools, in which we identify how clinicians perceive quality of information from such tools. In the studies, clinicians perceive several characteristics of information quality relating to accuracy and reliability, completeness, context, patient motivation, and representation. We discuss the issues these present in admitting self-tracked data as evidence for clinical decisions.

Adaptation in multisensory neurons: impact on cross-modal enhancement.

Adaptation is a ubiquitous property of sensory neurons. Multisensory neurons, receiving convergent input from different sensory modalities, also likely exhibit adaptation. The responses of multisensory superior colliculus neurons have been extensively studied, but the impact of adaptation on these responses has not been examined. Multisensory neurons in the superior colliculus exhibit cross-modal enhancement, an often non-linear and non-additive increase in response when a stimulus in one modality is paired with a stimulus in a different modality. We examine the possible impact of adaptation on cross-modal enhancement within the framework of a simple model of adaptation for a neuron employing a saturating, logistic response function. We consider how adaptation to an input's mean and standard deviation affects cross-modal enhancement, and also how the statistical correlations between two different modalities influence cross-modal enhancement. We determine the optimal bimodal stimuli to present a bimodal neuron that evoke the largest changes in cross-modal enhancement under adaptation to input statistics. The model requires separate gains for each modality, unless the statistics specific to each modality have been standardised by prior adaptation in earlier, unisensory neurons. The model also predicts that increasing the correlation coefficient between two modalities reduces a multisensory neuron's overall gain.

The evolution of the Web and implications for eResearch.

The hypertext visionaries foresaw the potential of richly interlinked global information systems for advancing human knowledge. The Web provided the infrastructure to enable those ideas to become a reality, and it quickly became a platform for collaborative research and data sharing. As the Web has evolved, new ways of using it for eResearch have emerged, such as the social networking facilities enabled by Web 2.0 technologies. The next generation of the Web-the so-called Semantic Web--is now on the horizon, which will again enable new types of collaborative research to emerge. If we are to understand and anticipate these new modes of collaboration, we need a discipline that studies the Web as a whole. Web science is this discipline.

An invariance principle for maintaining the operating point of a neuron.

Sensory neurons adapt to changes in the natural statistics of their environments through processes such as gain control and firing threshold adjustment. It has been argued that neurons early in sensory pathways adapt according to information-theoretic criteria, perhaps maximising their coding efficiency or information rate. Here, we draw a distinction between how a neuron's preferred operating point is determined and how its preferred operating point is maintained through adaptation. We propose that a neuron's preferred operating point can be characterised by the probability density function (PDF) of its output spike rate, and that adaptation maintains an invariant output PDF, regardless of how this output PDF is initially set. Considering a sigmoidal transfer function for simplicity, we derive simple adaptation rules for a neuron with one sensory input that permit adaptation to the lower-order statistics of the input, independent of how the preferred operating point of the neuron is set. Thus, if the preferred operating point is, in fact, set according to information-theoretic criteria, then these rules nonetheless maintain a neuron at that point. Our approach generalises from the unimodal case to the multimodal case, for a neuron with inputs from distinct sensory channels, and we briefly consider this case too.

Memories for life: a review of the science and technology.

This paper discusses scientific, social and technological aspects of memory. Recent developments in our understanding of memory processes and mechanisms, and their digital implementation, have placed the encoding, storage, management and retrieval of information at the forefront of several fields of research. At the same time, the divisions between the biological, physical and the digital worlds seem to be dissolving. Hence, opportunities for interdisciplinary research into memory are being created, between the life sciences, social sciences and physical sciences. Such research may benefit from immediate application into information management technology as a testbed. The paper describes one initiative, memories for life, as a potential common problem space for the various interested disciplines.

Developmental robotics: manifesto and application.

We argue that all embodied organisms, whether robots or animals, face the same challenge: of adapting to bodies, brains and environments that undergo constant and inevitable change. After highlighting the evidence for the universal role of a class of molecular factors called neurotrophic factors in the response of animals to this challenge, we suggest that implementing models of neurotrophic interactions on robots may confer on them the adaptability and robustness exhibited by animals. We briefly review a mathematical model of neurotrophic interactions and then discuss its application in a robotic context. Finally, we examine the potential, or otherwise, of our approach to developmental robotics.