Balancing Guidance Range and Strength Optimizes Self-Organization by Silicon Growth Cones

We characterize the first hardware implementation of a self-organizing map algorithm based on axon migration. A population of silicon growth cones automatically wires a topographic mapping by migrating toward sources of a diffusible guidance signal that is released by postsynaptic activity. We varied the diffusion radius of this signal, trading strength for range. Best performance is achieved by balancing signal strength against signal range

Costing the ex situ conservation of genetic resources: maize and wheat at CIMMYT

Worldwide, the number of genebanks and the amount of seed stored in them has increased substantially over the past few decades. Most attention is focused on the likely benefits from conservation, but conserving germplasm involves costs whose nature and magnitude are largely unknown. In this paper we compile and use a set of cost data for wheat and maize stored in the CIMMYT genebank to address a number of questions. What is the cost of storing an accession of either crop for one more year, or, equivalently what is the benefit in terms of cost savings from eliminating duplicate accessions from the genebank? Relatedly, what is the cost from introducing a new accession into the genebank, given the decision to store it is revisited after one year? Does it make economic sense for CIMMYT to discard accessions that may be available elsewhere? As an extension of this line of inquiry it is possible to value the benefits from either consolidating genebanks or at least networking existing banks to reduce or eliminate duplicate holdings not needed for backup safety purposes. We present estimates of the size and scale economies evident in the CIMMYT operation as a basis for assessing the economics of consolidation. Genebanks represent a commitment to conserve seeds for the very long-run. In this study we report on these long-run costs for the CIMMYT genebank costs that are sensitive to the interest rate used and the protocols for periodically replenishing accessions that are shared with others or regenerating accessions whose viability gradually diminishes with age.Germplasm conservation., Gene banks, Plant., Maize Breeding., Wheat Breeding., Rate of return.,

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world

Self -organizing neuromorphic systems with silicon growth cones

Neuromorphic engineers have achieved considerable success in devising silicon implementations of progressively more complex neural architectures. However, the effort required to design a successful neuromorphic system grows dramatically as the scope of these projects expands to encompass multiple neuromorphic subsystems. This design process could be eased by automating difficult design tasks. In this thesis I introduce a novel technique for automatically rewiring connectivity between spiking neurons based on a model of activity-dependent axonal growth cone navigation during neural development, and illustrate its performance with a silicon implementation of a model growth cone population whose migration is driven and directed by patterned neural activity. I develop a stochastic model of silicon growth cone motion to explain and characterize population behavior, and discover that performance is limited by an optimality criterion whose existence is implied by the fundamental physicality of the system

Self -organizing neuromorphic systems with silicon growth cones

Neuromorphic engineers have achieved considerable success in devising silicon implementations of progressively more complex neural architectures. However, the effort required to design a successful neuromorphic system grows dramatically as the scope of these projects expands to encompass multiple neuromorphic subsystems. This design process could be eased by automating difficult design tasks. In this thesis I introduce a novel technique for automatically rewiring connectivity between spiking neurons based on a model of activity-dependent axonal growth cone navigation during neural development, and illustrate its performance with a silicon implementation of a model growth cone population whose migration is driven and directed by patterned neural activity. I develop a stochastic model of silicon growth cone motion to explain and characterize population behavior, and discover that performance is limited by an optimality criterion whose existence is implied by the fundamental physicality of the system

Topographic map formation by silicon growth cones

We describe a self-configuring neuromorphic chip that uses a model of activity-dependent axon remodeling to automatically wire topographic maps based solely on input correlations. Axons are guided by growth cones, which are modeled in analog VLSI for the first time. Growth cones migrate up neurotropin gradients, which are represented by charge diffusing in transistor channels. Virtual axons move by rerouting address-events. We refined an initially gross topographic projection by simulating retinal wave input. 1 Neuromorphic Systems Neuromorphic engineers are attempting to match the computational efficiency of biological systems by morphing neurocircuitry into silicon circuits [1]. One of the most detailed implementations to date is the silicon retina described in [2]. This chip comprises thirteen different cell types, each of which must be individually and painstakingly wired. While this circuit-level approach has been very successful i

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that work radically different from traditional cameras. Instead of capturing images at a fixed rate, they measure per-pixel brightness changes asynchronously. This results in a stream of events, which encode the time, location and sign of the brightness changes. Event cameras posses outstanding properties compared to traditional cameras: very high dynamic range (140 dB vs. 60 dB), high temporal resolution (in the order of microseconds), low power consumption, and do not suffer from motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as high speed and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world

Costing the Ex Situ Conservation of Genetic Resources: Maize and Wheat at CIMMYT

Worldwide, the number of genebanks and the amount of seed stored in them has increased substantially over the past few decades. Most attention is focused on the likely benefits from conservation, but conserving germplasm involves costs whose nature and magnitude are largely unknown. Because more resources spent on conserving germplasm often means less spent on characterizing the collection or using the saved seeds in crop-improvement research, knowledge of the costs of germplasm conservation has important, possibly long run, R&D management, policy, and food-security consequences. Moreover, these costs place a lower bound on the benefits deemed likely to justify the expense of saving this seed. In this paper we compile and use a set of cost data for wheat and maize stored in the CIMMYT genebank to address a number of questions. What is the cost of storing an accession of either crop for one more year, or, equivalently what is the benefit in terms of cost savings from eliminating duplicate accessions from the genebank? Relatedly, what is the cost from introducing a new accession into the genebank, given the decision to store it is revisited after one year? Does it make economic sense for CIMMYT to discard accessions that may be available elsewhere? As an extension of this line of inquiry it is possible to value the benefits from either consolidating genebanks or at least networking existing banks to reduce or eliminate duplicate holdings not needed for backup safety purposes. We present estimates of the size and scale economies evident in the CIMMYT operation as a basis for assessing the economics of consolidation. Genebanks represent a commitment to conserve seeds for the very long-run. In this study we report on these long-run costs for the CIMMYT genebank¾costs that are sensitive to the interest rate used and the protocols for periodically replenishing accessions that are shared with others or regenerating accessions whose viability gradually diminishes with age. We estimate that under baseline assumptions the present value of conserving the existing accessions in perpetuity at CIMMYT is $7.95 million¾$4.42 million for storing the 17,000 maize accessions and $3.53 million for the 123,000 wheat samples. Maintaining the current level of effort to disseminate accessions free-of-charge to those who request them would cost an additional$3.07 million in perpetuity. Contrary to popular perception, conserving seeds (like R&D more generally) is much more of a labor or human-, not physical-capital intensive, undertaking. On an annualized basis, physical capital represents 22 percent of the costs of conservation, labor about 60 percent, with operational costs making up the remaining 18 percent. Much of the labor takes the form of a quasi-fixed input¾the human capital embodied in senior scientific and technical genebank staff is a lumpy labor input that is not especially sensitive to changes in the size of the holding