Synaptic rewiring in neuromorphic VLSI for topographic map formation

A generalised model of biological topographic map development is presented which combines both weight plasticity and the formation and elimination of synapses (synaptic rewiring) as well as both activity-dependent and -independent processes. The question of whether an activity-dependent process can refine a mapping created by an activity-independent process is investigated using a statistical approach to analysingmapping quality. The model is then implemented in custom mixed-signal VLSI. Novel aspects of this implementation include: (1) a distributed and locally reprogrammable address-event receiver, with which large axonal fan-out does not reduce channel capacity; (2) an analogue current-mode circuit for Euclidean distance calculation which is suitable for operation across multiple chips; (3) slow probabilistic synaptic rewiring driven by (pseudo-)random noise; (4) the application of a very-low-current design technique to improving the stability of weights stored on capacitors; (5) exploiting transistor non-ideality to implement partially weightdependent spike-timing-dependent plasticity; (6) the use of the non-linear capacitance of MOSCAP devices to compensate for other non-linearities. The performance of the chip is characterised and it is shown that the fabricated chips are capable of implementing the model, resulting in biologically relevant behaviours such as activity-dependent reduction of the spatial variance of receptive fields. Complementing a fast synaptic weight change mechanism with a slow synapse rewiring mechanism is suggested as a method of increasing the stability of learned patterns

Fever, hyperglycaemia and swallowing dysfunction management in acute stroke: A cluster randomised controlled trial of knowledge transfer

Background: Hyperglycaemia, fever, and swallowing dysfunction are poorly managed in the admission phase of acute stroke, and patient outcomes are compromised. Use of evidence-based guidelines could improve care but have not been effectively implemented. Our study aims to develop and trial an intervention based on multidisciplinary team-building to improve management of fever, hyperglycaemia, and swallowing dysfunction in patients following acute stroke. Methods and design: Metropolitan acute stroke units (ASUs) located in New South Wales, Australia will be stratified by service category (A or B) and, within strata, by baseline patient recruitment numbers (high or low) in this prospective, multicentre, single-blind, cluster randomised controlled trial (CRCT). ASUs then will be randomised independently to either intervention or control groups. ASUs allocated to the intervention group will receive: unit-based workshops to identify local barriers and enablers; a standardised core education program; evidence-based clinical treatment protocols; and ongoing engagement of local staff. Control group ASUs will receive only an abridged version of the National Clinical Guidelines for Acute Stroke Management. The following outcome measures will be collected at 90 days post-hospital admission: patient death, disability (modified Rankin Score); dependency (Barthel Index) and Health Status (SF-36). Additional measures include: performance of swallowing screening within 24 hours of admission; glycaemic control and temperature control. Discussion: This is a unique study of research transfer in acute stroke. Providing optimal inpatient care during the admission phase is essential if we are to combat the rising incidence of debilitating stroke. Our CRCT will also allow us to test interventions focussed on multidisciplinary ASU teams rather than individual disciplines, an imperative of modern hospital services

Synaptic rewiring in neuromorphic VLSI for topographic map formation

A generalised model of biological topographic map development is presented which combines both weight plasticity and the formation and elimination of synapses (synaptic rewiring) as well as both activity-dependent and -independent processes. The question of whether an activity-dependent process can refine a mapping created by an activity-independent process is investigated using a statistical approach to analysingmapping quality. The model is then implemented in custom mixed-signal VLSI. Novel aspects of this implementation include: (1) a distributed and locally reprogrammable address-event receiver, with which large axonal fan-out does not reduce channel capacity; (2) an analogue current-mode circuit for Euclidean distance calculation which is suitable for operation across multiple chips; (3) slow probabilistic synaptic rewiring driven by (pseudo-)random noise; (4) the application of a very-low-current design technique to improving the stability of weights stored on capacitors; (5) exploiting transistor non-ideality to implement partially weightdependent spike-timing-dependent plasticity; (6) the use of the non-linear capacitance of MOSCAP devices to compensate for other non-linearities. The performance of the chip is characterised and it is shown that the fabricated chips are capable of implementing the model, resulting in biologically relevant behaviours such as activity-dependent reduction of the spatial variance of receptive fields. Complementing a fast synaptic weight change mechanism with a slow synapse rewiring mechanism is suggested as a method of increasing the stability of learned patterns.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Synaptic Rewiring for Topographic Map Formation

Abstract. A model of topographic map development is presented which combines both weight plasticity and the formation and elimination of synapses as well as both activity-dependent and -independent processes. We statistically address the question of whether an activity-dependent process can refine a mapping created by an activity-independent process. A new method of evaluating the quality of topographic projections is presented which allows independent consideration of the development of a projection's preferred locations and variance. Synapse formation and elimination embed in the network topology changes in the weight distributions of synapses due to the activity-dependent learning rule used (spike-timing-dependent plasticity). In this model, variance of a projection can be reduced by an activity dependent mechanism with or without spatially correlated inputs, but the accuracy of preferred locations will not necessarily improve when synapses are formed based on distributions with on-average perfect topography