Rapid sensitivity changes on flickering backgrounds: tests of models of light adaptation

Retinal ganglion cell adaptation to small luminance fluctuations

To accommodate the wide input range over which the visual system operates within the narrow output range of spiking neurons, the retina adjusts its sensitivity to the mean light level so that retinal ganglion cells can faithfully signal contrast, or relative deviations from the mean luminance. Given the large operating range of the visual system, the majority of work on luminance adaptation has involved logarithmic changes in light level. We report that luminance gain controls are recruited for remarkably small fluctuations in luminance as well. Using spike recordings from the rat optic tract, we show that ganglion cell responses to a brief flash of light are modulated in amplitude by local background fluctuations as little as 15% contrast. The time scale of the gain control is rapid (<125 ms), at least for on cells. The retinal locus of adaptation precedes the ganglion cell spike generator because response gain changes of on cells were uncorrelated with firing rate. The mechanism seems to reside within the inner retinal network and not in the photoreceptors, because the adaptation profiles of on and off cells differed markedly. The response gain changes follow Weber's law, suggesting that network mechanisms of luminance adaptation described in previous work modulates retinal ganglion cell sensitivity, not just when we move between different lighting environments, but also as our eyes scan a visual scene. Finally, we show that response amplitude is uniformly reduced for flashes on a modulated background that has spatial contrast, indicating that another gain control that integrates luminance signals nonlinearly over space operates within the receptive field center of rat ganglion cells.

Transient lumanopia at high intensities

Transient lumanopia is the loss of sensitivity to a flicker burst presented in early dark adaptation. We earlier reported that lumanopia with 18 Hz flicker was greatest after turning off 400 td adapting fields and progressively disappeared as the adapting field was intensified. We now report that lumanopia can occur with intense adapting fields, but only with faster flickers (e.g. 40 Hz, 5000 td fields). Dimming the field (but not brightening it) can also produce lumanopia. The results illustrate frequency-dependent attenuation by a temporal filter whose parameters are set by light adaptation and which change abruptly when the field is dimmed or extinguished.

Comparing increment and decrement probes in the probed-sinewave paradigm

Using the probed-sinewave paradigm, we explore the differences between increment and decrement probes across a range of frequencies (approx. 1-19 Hz). In this paradigm, detection threshold is measured for a small test probe presented on a large sinusoidally flickering background (at eight different phases). Probe thresholds are very similar for increment and decrement probes, but there is a very small (and systematic) difference: increment thresholds are usually slightly higher relative to decrement thresholds during the part of the cycle when the background's intensity is increasing. Although Wilson's (1997, Vis. Neuro., 14, 403-423) model substantially underestimates the size of this difference, it predicts some phase dependency. However, the existence of On- and Off-pathways in Wilson's model is not important for these predictions. A recent model by Snippe, Poot, and van Hateren (2000, Vis. Neuro., 17, 449-462) may be able to predict this result by using explicit contrast-gain control rather than separate On- and Off-pathways. Auxiliary experiments measuring the perceived polarity of the probe provide a further argument suggesting that separate On- and Off-pathways are not useful in explaining increment and decrement probe thresholds.

Exploring the dynamics of light adaptation: the effects of varying the flickering background's duration in the probed-sinewave paradigm

In the probed-sinewave paradigm, threshold for detecting a probe is measured at various phases with respect to a sinusoidally-flickering background. Here we vary the duration of the flickering background before (and after) the test probe is presented. The adaptation is rapid; after approximately 10-30 ms of the flickering background, probe threshold is the same as that on a continually-flickering background. It is interesting that this result holds at both low (1. 2 Hz) and middle (9.4 Hz) frequencies because at middle frequencies (but not at low) there is a dc-shift, i.e. probe threshold is elevated at all phases relative to that on a steady background (of the same mean luminance). We compare our results to predictions from Wilson's model [Wilson (1997), Visual Neuroscience, 14, 403-423; Hood & Graham (1998), Visual Neuroscience, 15, 957-967] of light adaptation. The model predicts the rapid adaptation, and the dc-shift, but not the detailed shape of the probe-threshold-versus-phase curve at middle frequencies.

Increment and decrement detection on temporally modulated fields

Increment and decrement probe thresholds were measured during the presentation of two types of temporal masking stimuli. In Experiment 1, we measured thresholds for increment or decrement rectangular probes presented during the presentation of an increment or decrement Gaussian masking stimulus. We find that thresholds are higher when the probe and the Gaussian mask are of the same sign (e. g. both increments). However, both types of Gaussian mask raised increment and decrement probe thresholds above steady state conditions. In Experiment 2, we presented increment or decrement probes at one of eight possible phases of a 1 Hz luminance-modulated sine wave. For both increment and decrement probes, threshold variation with phase is non-sinusoidal in shape, but increment and decrement probe thresholds vary as a function of the sinusoid phase. These experiments show that increment and decrement thresholds vary as a function of the adaptation state of the visual system, and as a function of the direction of change in the adaptation state. Data from both experiments are discussed in terms of a recent neurophysiological model [Hood & Graham (1998). Threshold fluctuations on temporally modulated backgrounds: a possible physiological explanation based upon a recent computational model. Visual Neuroscience, 15 (5), 957-967]. We find that the predicted ON- and OFF-pathway responses do not correlate in a straightforward manner with the psychophysical thresholds, suggesting that detection of increment and decrement probes may not be performed exclusively by one pathway. Our data have implications for modeling visual performance under conditions where visual adaptation is dynamic, such as when scanning complex images or natural scenes.

Equivalence between temporal frequency and modulation depth for flicker response suppression: analysis of a three-process model of visual adaptation

We analyze adaptation processes responsible for eliciting and alleviating flicker response suppression, which is a class of phenomena characterized by the selective reduction of visual response to the ac component of a flickering light. Stimulus conditions were chosen that would allow characteristic features of flicker response suppression to be defined and manipulated systematically. Data are presented to show that reducing the sinusoidal modulation depth of an 11-Hz stimulus can correspond precisely to raising the temporal frequency of a fully modulated stimulus. In each case there is a nonmonotonic relation between flicker response and dc test illuminance. The nonmonotonic relation cannot be explained by adaptation models that postulate multiplicative and subtractive adaptation processes followed by a single static saturating nonlinearity, even when temporal frequency filters are incorporated into such models. A satisfactory explanation requires an additional contrast gain-control process. This process enhances flicker response at progressively lower temporal response contrasts as the illuminance of a surrounding field increases.

Lower-level visual processing and models of light adaptation

Before there was a formal discipline of psychology, there were attempts to understand the relationship between visual perception and retinal physiology. Today, there is still uncertainty about the extent to which even very basic behavioral data (called here candidates for lower-level processing) can be predicted based upon retinal processing. Here, a general framework is proposed for developing models of lower-level processing. It is argued that our knowledge of ganglion cell function and retinal mechanisms has advanced to the point where a model of lower-level processing should include a testable model of ganglion cell function. This model of ganglion cell function, combined with minimal assumptions about the role of the visual cortex, forms a model of lower-level processing. Basic behavioral and physiological descriptions of light adaptation are reviewed, and recent attempts to model lower-level processing are discussed.

Fourier models and the loci of adaptation

First measures of sensitivity and the need for a model to interpret them are addressed. Then modeling in the Fourier domain is promoted by a demonstration of how much an approach explains spatial sensitization and its dependence on luminance. Then the retinal illuminance and receptor absorptions produced by various stimuli are derived to foster interpretation of the neural mechanisms underlying various psychophysical phenomena. Finally, the sequence and the anatomical loci of the processes controlling visual sensitivity are addressed. It is concluded that multiplicative adaptation often has effects identical to response compression followed by subtractive adaptation and that, perhaps as a consequence, there is no evidence of retinal gain changes in human cone vision until light levels are well above those available in natural scenes and in most contemporary psychophysical experiments; that contrast gain control fine tunes sensitivity to patterns at all luminances; and that response compression, modulated by subtractive adaptation, predominates in the control of sensitivity in human cone vision.