Developing a new generation of neuro-prosthetic interfaces: structure-function correlates of viable retina-CNT biohybrids

PhD ThesisOne of the many challenges in the development of neural prosthetic devices is the choice of electrode material. Electrodes must be biocompatible, and at the same time, they must be able to sustain repetitive current injections in a highly corrosive physiological environment. We investigated the suitability of carbon nanotube (CNT) electrodes for retinal prosthetics by studying prolonged exposure to retinal tissue and repetitive electrical stimulation of retinal ganglion cells (RGCs). Experiments were performed on retinal wholemounts isolated from the Cone rod homeobox (CRX) knockout mouse, a model of Leber congenital amaurosis. Retinas were interfaced at the vitreo-retinal juncture with CNT assemblies and maintained in physiological conditions for up to three days to investigate any anatomical (immunohistochemistry and electron microscopy) and electrophysiological changes (multielectrode array stimulation and recordings; electrodes were made of CNTs or commercial titanium nitride). Anatomical characterisation of the inner retina, including RGCs, astrocytes and Müller cells as well as cellular matrix and inner retinal vasculature, provide strong evidence of a gradual remodelling of the retina to incorporate CNT assemblies, with very little indication of an immune response. Prolonged electrophysiological recordings, performed over the course of three days, demonstrate a gradual increase in signal amplitudes, lowering of stimulation thresholds and an increase in cellular recruitment for RGCs interfaced with CNT electrodes, but not with titanium nitride electrodes. These results provide for the first time electrophysiological, ultrastructural and cellular evidence of the time-dependent formation of strong and viable bio-hybrids between the RGC layer and CNT arrays in intact retinas. We conclude that CNTs are a promising material for inclusion in retinal prosthetic devices

Scalable Logic Defined Static Analysis

Logic languages such as Datalog have been proposed as a method for specifying flexible and customisable static analysers. Using Datalog, various classes of static analyses can be expressed precisely and succinctly, requiring fewer lines of code than hand-crafted analysers. In this paradigm, a static analysis specification is encoded by a set of declarative logic rules and an o -the-shelf solver is used to compute the result of the static analysis. Unfortunately, when large-scale analyses are employed, Datalog-based tools currently fail to scale in comparison to hand-crafted static analysers. As a result, Datalog-based analysers have largely remained an academic curiosity, rather than industrially respectful tools. This thesis outlines our e orts in understanding the sources of performance limitations in Datalog-based tools. We propose a novel evaluation technique that is predicated on the fact that in the case of static analysis, the logical specification is a design time artefact and hence does not change during evaluation. Thus, instead of directly evaluating Datalog rules, our approach leverages partial evaluation to synthesise a specialised static analyser from these rules. This approach enables a novel indexing optimisations that automatically selects an optimal set of indexes to speedup and minimise memory usage in the Datalog computation. Lastly, we explore the case of more expressive logics, namely, constrained Horn clause and their use in proving the correctness of programs. We identify a bottleneck in various symbolic evaluation algorithms that centre around Craig interpolation. We propose a method of improving these evaluation algorithms by a proposing a method of guiding theorem provers to discover relevant interpolants with respect to the input logic specification. The culmination of our work is implemented in a general-purpose and highperformance tool called Souffl´e. We describe Souffl´e and evaluate its performance experimentally, showing significant improvement over alternative techniques and its scalability in real-world industrial use cases

Social context of creativity

This thesis analyses the long-distance control of the environmentally-situated imagination, in both spatial and temporal dimensions. Central to the project is what I call the extended social brain hypothesis. Grounded in the Peircean conception of 'pragmaticism‘, this re-introduces technical intelligence to Dunbar‘s social brain—conceptually, through Clark‘s 'extended mind‘ philosophy, and materially, through Callon‘s 'actor–network theory‘. I claim that: There is no subjectivity without intersubjectivity. That is to say: as an evolutionary matter, it was necessary for the empathic capacities to evolve before the sense of self we identify as human could emerge. Intersubjectivity is critical to human communication, because of its role in interpreting intention. While the idea that human communication requires three levels of intentionality carries analytical weight, I argue that the inflationary trajectory is wrong as an evolutionary matter. The trend is instead towards increasing powers of individuation. The capacity for tool-use is emphasized less under the social brain hypothesis, but the importance of digital manipulation needs to be reasserted as part of a mature ontology. These claims are modulated to substantiate the work-maker, a socially situated (and embodied) creative agent who draws together Peircean notions of epistemology, phenomenology and oral performance