Literature knows a lot about attention – how it is gained and retained, how it is mastered and manipulated. As such it can contribute significantly to current research in interdisciplinary attention studies, transform debates about attentional crises, and offer deep insight into attention regimes we live by. LitAttention explores this fundamentally under-researched knowledge domain of literature about attention and attention politics by analysing ‘literary attention’ in short fiction. As LitAttention will show, short fiction does not only cater to short(er) attention spans: its development was driven by attention anxieties and struggles for attention control, which responded to technological innovation, new streams of information, the rise of attention studies, changing modes of reading, growing concerns about the limits of human attentional capacities, and intensifying struggles for attention sovereignty. Integrating approaches from educational psychology, computational linguistics, and literary and cultural studies, LitAttention has four key objectives. It will (1) examine the various ways in which short fiction has been shaped by but also shaped discourses on attention and attention management; (2) analyse the poetics and politics of attention in short fiction by identifying syntactic, semantic, and narrative strategies that elicit attention, and assess how these narratives reflect upon, support, or subvert attention regimes of their time; (3) develop (transferable) methodological and conceptual frameworks for examining literary attention; (4) introduce the important role of literary attention for education. The project is the first to conceptualize literary attention and propose a networked approach for its analysis. Its results will reveal the crucial role of short fiction in changing ecosystems of attention, have a deep impact on education, and change the way in which scholars, teachers, and the general public approach the knowledge and value of short fiction.

Being able to decode neural signals that control skeletal muscles with high accuracy will enable scientific breakthroughs in diagnostics and treatment, including early detection of neurodegenerative diseases, optimising personalised treatment or gene therapy, and assistive technologies like neuroprostheses. This breakthrough will require technology that is able to record signals from skeletal muscles in sufficient detail to allow the morpho-functional state of the neuromuscular system to be extracted. No existing technology can do this. Measuring the magnetic field induced by the flow of electrical charges in skeletal muscles, known as Magnetomyography (MMG), is expected to be the game-changing technology because magnetic fields are not attenuated by biological tissue. However, the extremely small magnetic fields involved require extremely sensitive magnetometers. The only promising option is novel quantum sensors, such as optically pumped magnetometers (OPMs), because they are small, modular, and can operate outside of specialised rooms. Our vision is to use this technology and our expertise in computational neuromechanics to decode, for the first time, neuromuscular control of skeletal muscles based on in vivo, high-density MMG data. For this purpose, we will design the first high-density MMG prototypes with up to 96 OPMs and develop custom calibration techniques. We will record magnetic fields induced by contracting skeletal muscles at the highest resolution ever measured. Such data, combined with the advanced computational musculoskeletal system models, will allow us to derive robust and reliable source localisation and separation algorithms. This will provide us with unique input for subject-specific neuromuscular models. We will demonstrate the superiority of the data over existing techniques with two applications; signs of ageing and neuromuscular disorders and show that it is possible to transfer these methodologies to clinical applications.