A roadmap to integrate astrocytes into Systems Neuroscience.

Systems neuroscience is still mainly a neuronal field, despite the plethora of evidence supporting the fact that astrocytes modulate local neural circuits, networks, and complex behaviors. In this article, we sought to identify which types of studies are necessary to establish whether astrocytes, beyond their well-documented homeostatic and metabolic functions, perform computations implementing mathematical algorithms that sub-serve coding and higher-brain functions. First, we reviewed Systems-like studies that include astrocytes in order to identify computational operations that these cells may perform, using Ca2+ transients as their encoding language. The analysis suggests that astrocytes may carry out canonical computations in a time scale of subseconds to seconds in sensory processing, neuromodulation, brain state, memory formation, fear, and complex homeostatic reflexes. Next, we propose a list of actions to gain insight into the outstanding question of which variables are encoded by such computations. The application of statistical analyses based on machine learning, such as dimensionality reduction and decoding in the context of complex behaviors, combined with connectomics of astrocyte-neuronal circuits, is, in our view, fundamental undertakings. We also discuss technical and analytical approaches to study neuronal and astrocytic populations simultaneously, and the inclusion of astrocytes in advanced modeling of neural circuits, as well as in theories currently under exploration such as predictive coding and energy-efficient coding. Clarifying the relationship between astrocytic Ca2+ and brain coding may represent a leap forward toward novel approaches in the study of astrocytes in health and disease

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

The Landscape of Academic Literature in Quantum Technologies

In this study, we investigated the academic literature on quantum technologies (QT) using bibliometric tools. We used a set of 49,823 articles obtained from the Web of Science (WoS) database using a search query constructed through expert opinion. Analysis of this revealed that QT is deeply rooted in physics, and the majority of the articles are published in physics journals. Keyword analysis revealed that the literature could be clustered into three distinct sets, which are (i) quantum communication/cryptography, (ii) quantum computation, and (iii) physical realizations of quantum systems. We performed a burst analysis that showed the emergence and fading away of certain key concepts in the literature. This is followed by co-citation analysis on the highly cited articles provided by the WoS, using these we devised a set of core corpus of 34 publications. Comparing the most highly cited articles in this set with respect to the initial set we found that there is a clear difference in most cited subjects. Finally, we performed co-citation analyses on country and organization levels to find the central nodes in the literature. Overall, the analyses of the datasets allowed us to cluster the literature into three distinct sets, construct the core corpus of the academic literature in QT, and to identify the key players on country and organization levels, thus offering insight into the current state of the field. Search queries and access to figures are provided in the appendix.Comment: 32 pages, 10 figures, draft version of a working pape

The Neuroscience of Moral Judgment: Empirical and Philosophical Developments

We chart how neuroscience and philosophy have together advanced our understanding of moral judgment with implications for when it goes well or poorly. The field initially focused on brain areas associated with reason versus emotion in the moral evaluations of sacrificial dilemmas. But new threads of research have studied a wider range of moral evaluations and how they relate to models of brain development and learning. By weaving these threads together, we are developing a better understanding of the neurobiology of moral judgment in adulthood and to some extent in childhood and adolescence. Combined with rigorous evidence from psychology and careful philosophical analysis, neuroscientific evidence can even help shed light on the extent of moral knowledge and on ways to promote healthy moral development

Towards dynamical network biomarkers in neuromodulation of episodic migraine

Computational methods have complemented experimental and clinical neursciences and led to improvements in our understanding of the nervous systems in health and disease. In parallel, neuromodulation in form of electric and magnetic stimulation is gaining increasing acceptance in chronic and intractable diseases. In this paper, we firstly explore the relevant state of the art in fusion of both developments towards translational computational neuroscience. Then, we propose a strategy to employ the new theoretical concept of dynamical network biomarkers (DNB) in episodic manifestations of chronic disorders. In particular, as a first example, we introduce the use of computational models in migraine and illustrate on the basis of this example the potential of DNB as early-warning signals for neuromodulation in episodic migraine.Comment: 13 pages, 5 figure

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

Rethinking affordance

n/a – Critical survey essay retheorising the concept of 'affordance' in digital media context. Lead article in a special issue on the topic, co-edited by the authors for the journal Media Theory