Lawrence G. Brown

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The statistical spiking response of an ensemble of identically prepared stochastic integrate-and-fire neurons to a rectangular input current plus gaussian white noise is analyzed. It is shown that, on average, integrate-and-fire neurons adapt to the root-mean-square noise level of their input. This phenomenon is referred to as noise adaptation. Noise(More)
Under appropriate experimental conditions, the threshold intensity of a visual stimulus varies as the square-root of the background illuminance. This square-root law has been observed in both psychophysical threshold experiments and in measurements of the thresholds of individual ganglion cells. A signal detection theory developed in the 1940s by H. L. de(More)
We present several variations of a model of gain control in the retina of the toad Bufo marinus, and use them to fit the threshold-vs-intensity data of an actual toad ganglion cell [Donner et al. (1990). Journal of General Physiology, 95, 733-753]. Our models are based on a proposal by Donner et al. that the gain (neural spike per photon ratio) of toad(More)
For small, brief targets incremental threshold is known to obey the de Vries-Rose law: threshold rises in direct proportion to the square-root of background intensity. We present data demonstrating a square-root law for brightness matching as well. The square-root law for brightness is obtained over the full range of scotopic vision, and the low intensity(More)
We explore various limit constructions for C *-algebras, such as composition series and inverse limits, in relation to the notions of real rank, stable rank, and extremal richness. We also consider extensions and pullbacks. We identify some conditions under which the constructions preserve low rank for the C *-algebras or their multiplier algebras. We also(More)
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