Yu CP, Page WK, Gaborski R, Duffy CJ. Receptive field dynamics underlying MST neuronal optic flow selectivity. J Neurophysiol 103: 2794 -2807, 2010. First published March 24, 2010 doi:10.1152/jn.01085.2009. Optic flow informs moving observers about their heading direction. Neurons in monkey medial superior temporal (MST) cortex show heading selective responses to optic flow and planar direction selective responses to patches of local motion. We recorded MST neuronal responses to a 90 ϫ 90°optic flow display and to a 3 ϫ 3 array of local motion patches covering the same area. Our goal was to test the hypothesis that the optic flow responses reflect the sum of the local motion responses. The local motion responses of each neuron were modeled as mixtures of Gaussians, combining the effects of two Gaussian response functions derived using a genetic algorithm, and then used to predict that neuron's optic flow responses. Some neurons showed good correspondence between local motion models and optic flow responses, others showed substantial differences. We used the genetic algorithm to modulate the relative strength of each local motion segment's responses to accommodate interactions between segments that might modulate their relative efficacy during co-activation by global patterns of optic flow. These gain modulated models showed uniformly better fits to the optic flow responses, suggesting that coactivation of receptive field segments alters neuronal response properties. We tested this hypothesis by simultaneously presenting local motion stimuli at two different sites. These two-segment stimuli revealed that interactions between response segments have direction and location specific effects that can account for aspects of optic flow selectivity. We conclude that MST's optic flow selectivity reflects dynamic interactions between spatially distributed local planar motion response mechanisms.

The goal of the study was to compare a cathode-ray-tube (CRT) digital display with film by using task-dependent image quality assessment methods. Contrast-detail analysis was utilized. Human observers performed a simple detection task, specifically, detecting a pillbox target in a uniform Poisson field, using either film or a digital display that employed a CRT monitor. Observers performed equally well on both film and CRT when the window settings of the digital display were established subjectively by a radiologist. Changing the window settings of the digital display to match the average background luminance of a film-illuminator combination decreased the luminance contrast of the targets and observer performance was reduced, though these effects were probably not linked. The "gold standard" film had lower luminance contrast than the CRT displayed images, yet observer performance was never lower for film than for the CRT. Therefore we concluded that luminance contrast was not a limiting factor for observer performance in this study. The CRT monitor changed fairly rapidly after it was calibrated. During a period of six months the gamma of the display increased from 1.82 to 2.42 and the maximum luminance decreased from 319 to 228 cd/m2. Low luminance output demonstrated a larger percentage decrease (approximately equal to 85%) than high luminance output (approximately equal to 29%) over the same time period. These observations suggest that standard window settings should be reviewed from time to time to ensure that the display is used optimally. No special look-up table setup such as perceptual linearization was used.

Wavelet-based image compression is receiving significant attention, largely because of its potential for good image quality at low bit rates. In medical applications, low bit rate coding may not be the primary concern, and it is not obvious that wavelet techniques are significantly superior to more established techniques at higher quality levels. In this work we present a straightforward comparison between a wavelet decomposition and the well-known discrete cosine transform decomposition (as used in the JPEG compression standard), using comparable quantization and encoding strategies to isolate fundamental differences between the two methods. Our focus is on the compression of single-frame, monochrome images taken from several common modalities (chest and bone xrays and mammograms).