Biological neurons perform information processing using a model called pulse processing, which is both computationally efficient and scalable, adopting the best features of both analog and digital computing. Implementing pulse processing with photonics can result in bandwidths that are billions of times faster than biological neurons and substantially faster than electronics. Neurons have the ability to learn and adapt their processing based on experience through a change in the strength of synaptic connections in response to spiking activity.
View Article and Find Full Text PDFWe developed an asynchronous spiking photonic neuron that forms the basic building block for hybrid analog/digital lightwave neuromorphic processing. Our approach enables completely asynchronous spiking in response to input signals while maximizing the throughput relative to synchronous approaches. Asynchronous operation is achieved by generating the spike source for the photonic neuron through four-wave mixing.
View Article and Find Full Text PDFIn this paper, we demonstrate for the first time an ultrafast fully functional photonic spiking neuron. Our experimental setup constitutes a complete all-optical implementation of a leaky integrate-and-fire neuron, a computational primitive that provides a basis for general purpose analog optical computation. Unlike purely analog computational models, spiking operation eliminates noise accumulation and results in robust and efficient processing.
View Article and Find Full Text PDFWe developed a hybrid analog/digital lightwave neuromorphic processing device that effectively performs signal feature recognition. The approach, which mimics the neurons in a crayfish responsible for the escape response mechanism, provides a fast and accurate reaction to its inputs. The analog processing portion of the device uses the integration characteristic of an electro-absorption modulator, while the digital processing portion employ optical thresholding in a highly Ge-doped nonlinear loop mirror.
View Article and Find Full Text PDFThis paper presents an all optical fiber based implementation of a hybrid analog-digital computational primitive that provides a basis for complex processing on high bandwidth signals. A natural implementation of a hybrid analog/digital photonic processing primitive is achieved through the integration of new nonlinear fiber, and exploitation of the physics of semiconductor device to process signals in unique ways. Specifically, we describe the use of a semiconductor optical amplifier to implement leaky temporal integration of a signal and a highly Ge-doped nonlinear fiber for thresholding.
View Article and Find Full Text PDFBackground: It is well known that individuals receiving social assistance have more health problems than those with higher incomes. In this paper, we estimate the proportion of social assistance recipients who were on welfare following a drop in health status.
Methods: The study population consisted of Saskatchewan adults who had been continuously off social assistance for 12 consecutive months followed by 6 months on social assistance.
Objectives: To examine the changes in health service use by recipients of Family Health Benefits, a supplementary benefits program that was introduced to lower-income, working families in Saskatchewan beginning in July 1998. These benefits reduced or eliminated fees for prescription drugs and for chiropractic, optometric and dental services.
Methods: The study population included program beneficiaries between July 1998 and January 2000.
What we see depends on where we look. This paper characterizes the modulatory effects of point of regard in three-dimensional space on responsiveness of visual cortical neurons in areas V1, V2, and V4. Such modulatory effects are both common, affecting 85% of cells, and strong, frequently producing changes of mean firing rate by a factor of 10.
View Article and Find Full Text PDF