What distinguishes the locations that we fixate from those that we do not? To answer this question we recorded eye movements while observers viewed natural scenes, and recorded image characteristics centred at the locations that observers fixated. To investigate potential differences in the visual characteristics of fixated versus non-fixated locations, these images were transformed to make intensity, contrast, colour, and edge content explicit. Signal detection and information theoretic techniques were then used to compare fixated regions to those that were not. The presence of contrast and edge information was more strongly discriminatory than luminance or chromaticity. Fixated locations tended to be more distinctive in the high spatial frequencies. Extremes of low frequency luminance information were avoided. With prolonged viewing, consistency in fixation locations between observers decreased. In contrast to [Parkhurst, D. J., Law, K., & Niebur, E. (2002). Modeling the role of salience in the allocation of overt visual attention. Vision Research, 42 (1), 107-123] we found no change in the involvement of image features over time. We attribute this difference in our results to a systematic bias in their metric. We propose that saccade target selection involves an unchanging intermediate level representation of the scene but that the high-level interpretation of this representation changes over time.

The primary visual cortex (V1) is the ¢rst cortical area to receive visual input, and inferior temporal (IT) areas are among the last along the ventral visual pathway. We recorded, in area V1 of anaesthetized cats and area ITof awake macaque monkeys, responses of neurons to videos of natural scenes. Responses were analysed to test various hypotheses concerning the nature of neural coding in these two regions. A variety of spike-train statistics were measured including spike-count distributions, interspike interval distributions, coe¤cients of variation, power spectra, Fano factors and di¡erent sparseness measures. All statistics showed non-Poisson characteristics and several revealed self-similarity of the spike trains. Spike-count distributions were approximately exponential in both visual areas for eight di¡erent videos and for counting windows ranging from 50 ms to 5 seconds. The results suggest that the neurons maximize their information carrying capacity while maintaining a ¢xed long-term-average ¢ring rate, or equivalently, minimize their average ¢ring rate for a ¢xed information carrying capacity. I N T RO DUC T IONIt has been suggested that visual representations are optimized to transmit the maximum information about the images encountered in everyday life (Uttley 1973;Linsker 1987;Barlow 1989). This simple assumption has proven su¤cient to account for the characteristics of large monopolar cells in the £y (Srinivasan et al. 1982;Van Hateren 1992;Laughlin 1981), the temporal characteristics of retinal ganglion cells (Dong & Atick 1995), human spatial frequency thresholds (Atick & Redlich 1992;Van Hateren 1993), and the psychophysics of orientation perception for short presentation times (Baddeley & Hancock 1991).Maximization of information is a powerful theoretical principle that leads to testable predictions about the ¢ring patterns of neurons. However, to generate speci¢c predictions we must make some assumptions about the nature of the neural code and the type of constraint that limits its information carrying capacity. To apply information maximization to neuronal spike trains, we must identify which of their characteristics carry information. In our analysis, we will consider two possibilities: that ¢ring rates, or more precisely, spike counts over discrete intervals of time, are the information carrying elements; or that interspike intervals play this role. Without any constraints on the rate or precision of neuronal spiking, the information carrying capacity of a spike train is in¢nite. Thus, constraints play a crucial role in any information maximization procedure. We will consider three possibilities, constraints on the maximum ¢ring rate, the average ¢ring rate, or a quantity known as the sparseness of the ¢ring-rate distribution. Identifying the nature of the constraint that limits information carrying capacity has important implications for the biophysical mechanisms that underlie neural coding.Assuming the ¢ring rates carry information, Laughlin (1981) proposed a constraint on the maximum ¢...

Recently, it has been proposed that all suppressive phenomena observed in the primary visual cortex (V1) are mediated by a single mechanism, involving inhibition by pools of neurons, which, between them, represent a wide range of stimulus specificities. The strength of such inhibition would depend on the stimulus that produces it (particularly its contrast) rather than on the firing rate of the inhibited cell. We tested this hypothesis by measuring contrast-response functions (CRFs) of neurons in cat V1 for stimulation of the classical receptive field of the dominant eye with an optimal grating alone, and in the presence of inhibition caused by (1) a superimposed orthogonal grating (cross-orientation inhibition); (2) a surrounding iso-oriented grating (surround inhibition); and (3) an orthogonal grating in the other eye (interocular suppression). We fitted hyperbolic ratio functions and found that the effect of cross-orientation inhibition was best described as a rightward shift of the CRF ('contrast-gain control'), while surround inhibition and interocular suppression were primarily characterised as downward shifts of the CRF ('response-gain control'). However, the latter also showed a component of contrast-gain control. The two modes of suppression were differently distributed between the layers of cortex. Response-gain control prevailed in layer 4, whereas cells in layers 2/3, 5 and 6 mainly showed contrast-gain control. As in human observers, surround gratings caused suppression when the central grating was of high contrast, but in over a third of the cells tested, enhanced responses for low-contrast central stimuli, hence actually decreasing threshold contrast.

Sensory-motor integration has frequently been studied using a single-step change in a control variable such as prismatic lens angle and has revealed human visuomotor adaptation to often be partial and inefficient. We propose that the changes occurring in everyday life are better represented as the accumulation of many smaller perturbations contaminated by measurement noise. We have therefore tested human performance to random walk variations in the visual feedback of hand movements during a pointing task. Subjects made discrete targeted pointing movements to a visual target and received terminal feedback via a cursor the position of which was offset from the actual movement endpoint by a random walk element and a random observation element. By applying ideal observer analysis, which for this task compares human performance against that of a Kalman filter, we show that the subjects' performance was highly efficient with Fisher efficiencies reaching 73%. We then used system identification techniques to characterize the control strategy used. A "modified" delta-rule algorithm best modeled the human data, which suggests that they estimated the random walk perturbation of feedback in this task using an exponential weighting of recent errors. The time constant of the exponential weighting of the best-fitting model varied with the rate of random walk drift. Because human efficiency levels were high and did not vary greatly across three levels of observation noise, these results suggest that the algorithm the subjects used exponentially weighted recent errors with a weighting that varied with the level of drift in the task to maintain efficient performance.

We recorded over 90,000 saccades while observers viewed a diverse collection of natural images and measured low level visual features at fixation. The features that discriminated between where observers fixated and where they did not varied considerably with task, and the length of the preceding saccade. Short saccades (<8 degrees) are image feature dependent, long are less so. For free viewing, short saccades target high frequency information, long saccades are scale-invariant. When searching for luminance targets, saccades of all lengths are scale-invariant. We argue that models of saccade behaviour must account not only for task but also for saccade length and that long and short saccades are targeted differently.

A Bayesian system identification technique was used to determine which image characteristics predict where people fixate when viewing natural images. More specifically an estimate was derived for the mapping between image characteristics at a given location and the probability that this location was fixated. Using a large database of eye fixations to natural images, we determined the most probable (a posteriori) model of this mapping. From a set of candidate feature maps consisting of edge, contrast and luminance maps (at two different spatial scales), fixation probability was dominated by high spatial frequency edge information. The best model applied compressive non-linearity to the high frequency edge detecting filters (approximately a square root). Both low spatial frequency edges and contrast had weaker, but inhibitory, effects. The contributions of the other maps were so small as to be behaviourally irrelevant. This Bayesian method identifies not only the relevant weighting of the different maps, but how this weighting varies as a function of distance from the point of fixation. It was found that rather than centre surround inhibition, the weightings simply averaged over an area of about 2 degrees.

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A complete explanation of the diversity of animal colour patterns requires an understanding of both the developmental mechanisms generating them and their adaptive value. However, only two previous studies, which involved computer-generated evolving prey, have attempted to make this link. This study examines variation in the camouflage patterns displayed on the flanks of many felids. After controlling for the effects of shared ancestry using a fully resolved molecular phylogeny, this study shows how phenotypes from plausible felid coat pattern generation mechanisms relate to ecology. We found that likelihood of patterning and pattern attributes, such as complexity and irregularity, were related to felids' habitats, arboreality and nocturnality. Our analysis also indicates that disruptive selection is a likely explanation for the prevalence of melanistic forms in Felidae. Furthermore, we show that there is little phylogenetic signal in the visual appearance of felid patterning, indicating that camouflage adapts to ecology over relatively short time scales. Our method could be applied to any taxon with colour patterns that can reasonably be matched to reaction -diffusion and similar models, where the kinetics of the reaction between two or more initially randomly dispersed morphogens determines the outcome of pattern development.