Convolutional networks for fast, energy-efficient neuromorphic computing.

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning.

Artificial brains. A million spiking-neuron integrated circuit with a scalable communication network and interface.

Inspired by the brain's structure, we have developed an efficient, scalable, and flexible non-von Neumann architecture that leverages contemporary silicon technology. To demonstrate, we built a 5.4-billion-transistor chip with 4096 neurosynaptic cores interconnected via an intrachip network that integrates 1 million programmable spiking neurons and 256 million configurable synapses.

Modeling the GABAergic action of etomidate on the thalamocortical system.

Background: We have used a computational model of the thalamocortical system to investigate the effects of a GABAergic anesthetic (etomidate) on cerebral cortical and thalamic neuronal function. We examined the effects of phasic and tonic inhibition, as well as the relative importance of anesthetic action in the thalamus and cortex.

Methods: The amount of phasic GABAergic inhibition was adjusted in the model to simulate etomidate concentrations of between 0.

Anterior modification of Delorme procedure provides equivalent results to Delorme procedure in treatment of rectal outlet obstruction.

Background: This study was designed to assess the results of the standard Delorme procedure versus an anterior modification of the Delorme procedure in the treatment of patients with rectal outlet obstruction secondary to internal intussusception with or without rectocele.

Study Design: A descriptive retrospective study from October 1997 to May 2001 was undertaken. Twenty-seven patients with symptoms of rectal outlet obstruction assumed to be caused by internal rectal prolapse or a combination of internal rectal prolapse and rectocele underwent surgical repair.

Stapled hemorrhoidectomy with local anesthesia can be performed safely and cost-efficiently.

Purpose: This prospective study was designed to assess the feasibility of performing the procedure for prolapsing hemorrhoids, or stapled hemorrhoidectomy, under local anesthesia supplemented with conscious sedation.

Methods: Seventy consecutive patients (mean age, 56 years; 37 males) with Grade 3 or 4 hemorrhoids underwent the procedure for prolapsing hemorrhoids after perianal infiltration of 0.5 percent lidocaine with 1:200,000 epinephrine and supplemental conscious sedation.