The aim of my research is to construct theoretical, computational, experimental, and robotic models of the development of brain function, and specifically to develop models of how the brain learns to represent physical spaces, such as that occupied by the body. My current interests are focussed around four overlapping themes, and I am happy to discuss projects with potential collaborators and enthusiastic students interested in either.
Self-organisation is a general theory of how function is assigned to cortical microcircuits. The theory predicts that a balance between cooperative and competitive interactions in local cortical circuits, consolidated by Hebbian learning, results in similar inputs being represented by nearby neurons. Simulations of cortical self-organisation have mainly concerned vision, where 'similar inputs' may translate to 'pixels at similar retinal locations' or 'edges of similar orientation'. My previous work has extended the approach for touch, showing that 'similar inputs' can, for example, translate to 'body parts often touching'. In principle, self-organising models can generate predictions about the functional organisation assigned to any cortical area. In practice, the validity of these models is limited by the accuracy with which model inputs reflect natural developmental experiences. Particularly for 'higher-order' cortical areas that combine information from multiple sources, i.e., multisensory or sensorimotor areas, natural interactions between these sources are difficult to synthesize. The project aims to address this bottleneck, by exploiting natural human and animal behaviours to generate inputs for models of map formation. This should help improve our understanding of the developmental mechanisms that underlie disorders of multisensory and sensorimotor integration.
How do natural experiences shape the functional organisation of the developing brain? To address this question directly, we have been developing a novel robotic technology - the synthetic littermate (or 'surrogate'). The current prototype consists of a biomimetic skin, which encloses camera, microphone, gyroscope, and accelerometer sensors. This allows us to collect naturalistic, multisensory experiences from within a litter of real developing rat pups. Rat pups spend the first two postnatal weeks in large huddles, wriggling closely in a synergy that aids thermoregulation: This primitive, natural 'huddling' behaviour presents a rich and continuous source of sensory input to the developing pups, and so provides a unique opportunity to study self-organisation at the interface between natural and artificial systems. Driven by the rich multisensory experiences of a surrogate, self-organising models can be used to derive important predictions about the functional organisation in multisensory cortical areas, about which modern neuroscience knows relatively little. The approach could be used to predict, for example, the receptive field structure of multisensory neurons that represent combinations of somatosensory, visual, and proprioceptive spaces that interact to provide an agent with a sense of where it is in space (body schema).
The body schema can be loosely defined as the representation of the body in space, i.e., how you know you can reach the pint at the bar but not the bottle behind it; that you can fit through the door but not the cat-flap; that you must dive to kick a ball or duck to avoid a punch. Constructed from proprioceptive, somatosensory, visual, and auditory information, the body schema is like a bubble around the body, which includes bodily extensions such as clothes worn and tools wielded. When it goes awry, patients report a fascinating range of symptoms, for example amputees can experience pain originating in phantom hands. Given the importance of body schema to our everyday experience of the world, it is surprising just how little agreement there is between researchers (from philosophers, to neuroscientists, to roboticists) about the fundamentals: Namely, i) how can body schema be objectively defined, ii) how can body schema be objectively measured? The virtual body schema project aims to address these two challenges. Firstly, by constructing a psychological theory of body schema; through a series of experiments designed to explore the body schema as a representation in a space that is e.g., relative and/or absolute, topological and/or metric, innate and/or learnt? Secondly, by constructing a visualisation and virtual representation of a participant's body schema, based on objective psychophysical measurements that may be rendered in realtime to a virtual avatar. An important aim will be to derive a set of principles for the design of body schema for better and safer artificial agents and robots.
Rapid developments in bioengineering, computer science, psychology, and biomedicine are leading to increasing levels of interaction between humans and emerging biotechnologies in a wide range of settings from the clinic to the classroom. The use of these new technologies takes many forms, including implants, prosthetics, drugs and devices that modify or augment the body, and at the same time create new forms of individual and collective identity. These changes challenge both existing scientific and cultural categories and blur the boundaries between natural, social, and synthetic objects. Bio-hybrid systems are networks of reciprocally interacting units, where one or more of those units are the product of nature, and one or more are designed by people. Bio-hybrid systems can emerge or be created at each of the scales at which natural systems can be defined; at the microscopic scale where biomaterials, drugs, and devices interact with the molecular and cellular processes of the body; at the mesoscopic scale where individual organisms interact with synthetic objects and robots to achieve shared goals; and at the macroscopic scale where smart cities and ecosystems can harbour new forms of society. Projects under this theme will be focussed on identifying common principles underlying research on biohybrid systems, biohybrid humans, and biohybrid societies.