A learning-enabled neuron array IC based upon transistor channel models of biological phenomena.

We present a single-chip array of 100 biologically-based electronic neuron models interconnected to each other and the outside environment through 30,000 synapses. The chip was fabricated in a standard 350 nm CMOS IC process. Our approach used dense circuit models of synaptic behavior, including biological computation and learning, as well as transistor channel models. We use Address-Event Representation (AER) spike communication for inputs and outputs to this IC. We present the IC architecture and infrastructure, including IC chip, configuration tools, and testing platform. We present measurement of small network of neurons, measurement of STDP neuron dynamics, and measurement from a compiled spiking neuron WTA topology, all compiled into this IC.

Computing with networks of spiking neurons on a biophysically motivated floating-gate based neuromorphic integrated circuit.

Results are presented from several spiking network experiments performed on a novel neuromorphic integrated circuit. The networks are discussed in terms of their computational significance, which includes applications such as arbitrary spatiotemporal pattern generation and recognition, winner-take-all competition, stable generation of rhythmic outputs, and volatile memory. Analogies to the behavior of real biological neural systems are also noted. The alternatives for implementing the same computations are discussed and compared from a computational efficiency standpoint, with the conclusion that implementing neural networks on neuromorphic hardware is significantly more power efficient than numerical integration of model equations on traditional digital hardware.

EEG and spectral analysis in acute hyperventilation.

Acute hypocapnia decreases CBF, increases hemoglobin affinity for oxygen and causes cerebral tissue hypoxia. This tissue hypoxia is reversed with inhalation of 100% O2 in dogs. EEG slowing produced by hyperventilation is considered a manifestation of cerebral hypoxia due to decreased CBF and is thought to be reversed with hyperoxia. This study evaluated the effects of 3 gas mixtures (16% O2, 21% O2, 100% O2) on posterior frequencies of the resting and hyperventilatory EEG in normal subjects aged 23-37. Hypocapnia was maintained to an end-tidal pCO2 of 21 mm Hg for 3 min. Respiratory measures, heart rate, saO2, minute ventilation and side effects were recorded. EEG was analyzed by visual inspection and by spectral analysis. Spectral analysis evaluated total amplitude, percentile frequencies, and peak frequencies. There were significant changes from eucapnia to hypocapnia for the group in all physiologic parameters, total amplitude by spectral analysis, and posterior frequencies by visual analysis. There were no significant differences among the gases. We conclude that the EEG changes of hyperventilation are independent of the concentration of inspired oxygen over the range studied in our subjects. Symptoms of hyperventilation are likewise independent of the inspired oxygen concentration for the range studied.