Sean F. O'Neil

Adaptation and the perception of facial age

We examined how the perceived age of adult faces is affected by adaptation to younger or older adult faces. Observers viewed images of a synthetic male face simulating ageing over a modelled range from 15 to 65 years. Age was varied by changing shape cues or textural cues. Age level was varied in a staircase to find the observers subjective category boundary between “old” and “young”. These boundaries were strongly biased by adaptation to the young or old face, with significant aftereffects induced by either shape or textural cues. A further experiment demonstrated comparable aftereffects for photorealistic images of average older or younger adult faces, and found that aftereffects showed some selectivity for a change in gender but also strongly transferred across gender. This transfer shows that adaptation can adjust to the attribute of age somewhat independently of other facial attributes. These findings suggest that perceived age, like many other natural facial dimensions, is highly susceptible to adaptation, and that this adaptation can be carried by both the structural and textural changes that normally accompany facial ageing.

Adding Years to Your Life (or at Least Looking Like It): A Simple Normalization Underlies Adaptation to Facial Age

Adaptation has been widely used to probe how experience shapes the visual encoding of faces, but the pattern of perceptual changes produced by adaptation and the neural mechanisms these imply remain poorly characterized. We explored how adaptation alters the perceived age of faces, a fundamental facial attribute which can uniquely and reliably be scaled by observers. This allowed us to measure how adaptation to one age level affected the full continuum of perceived ages. Participants guessed the ages of faces ranging from 18–89, before or after adapting to a different set of faces composed of younger, older, or middle-aged adults. Adapting to young or old faces induced opposite linear shifts in perceived age that were independent of the models age. Specifically, after adapting to younger or older faces, faces of all ages appeared 2 to 3 years older or younger, respectively. In contrast, middle-aged adaptors induced no aftereffects. This pattern suggests that adaptation leads to a simple and uniform renormalization of age perception, and is consistent with a norm-based neural code for the mechanisms mediating the perception of facial age.

Tests of a functional account of the Abney effect

The Abney effect refers to changes in the hue of lights as they are desaturated. Normally the purity is varied by desaturating with a fixed spectrum. Mizokami et al. [J. Vis.6, 996 (2006)] instead varied purity by using Gaussian spectra and increasing their bandwidth. Under these conditions the hues of lights at short and medium wavelengths tended to remain constant and thus were tied to a fixed property of the stimulus such as the spectral peak, possibly reflecting a compensation for the spectral filtering effects of the eye. Here we test this account more completely by comparing constant hue loci across a wide range of wavelengths and between the fovea and periphery. Purity was varied by adding either a fixed spectrum or by varying the spectral bandwidth, using an Agile Light Source capable of generating arbitrary spectra. For both types of spectra, hue loci were approximated by the Gaussian model at short and medium wavelengths, though the model failed to predict the precise form of the hue changes or the differences between the fovea and periphery. Our results suggest that a Gaussian model provides a useful heuristic for predicting constant hue loci and the form of the Abney effect at short and medium wavelengths and may approximate the inferences underlying the representation of hue in the visual system.

Filling in, filling out, or filtering out: processes stabilizing color appearance near the center of gaze.

Spectral sensitivity varies markedly across the center of gaze, in part because of the rapid decline in the density of macular pigment outside the fovea. Yet despite these retinal inhomogeneities, the color appearance of large uniform fields remains very uniform. We explored some of the processes contributing to these stable color percepts by measuring the effects of field size and eccentricity on saturated purples, whose spectra should show the largest biases with macular pigment screening. Small purple fields at 0° and 8° eccentricities differ in appearance but by much less than predicted by the macular screening or by compensation for the average effects of this screening at the two loci. This shows that the compensation is already nearly complete because of local adjustments that filter out the sensitivity variation and confirms that this filtering includes adjustments beyond average gain changes in the cones. In large fields, the appearance is dominated by the local peripheral color. This bias persists when the field edge is fixated or when abrupt edges are removed in Gaussian spots, suggesting that the spreading is not strongly dependent on luminance edges.

Action–effect contingency modulates the readiness potential

&NA; The ability to constantly anticipate events in the world is critical to human survival. It has been suggested that predictive processing originates from the motor system and that incoming sensory inputs can be altered to facilitate sensorimotor integration. In the current study, we investigated the role of the readiness potentials, i.e. the premotor brain activity registered within the fronto‐parietal areas, in sensorimotor integration. We recorded EEG data during three conditions: a motor condition in which a simple action was required, a visual condition in which a visual stimulus was presented on the screen, and a visuomotor condition wherein the visual stimulus appeared in response to a button press. We measured evoked potentials before the motor action and/or after the appearance of the visual stimulus. Anticipating a visual feedback in response to a voluntary action modulated the amplitude of the readiness potentials. We also found an enhancement in the amplitude of the visual N1 and a reduction in the amplitude of the visual P2 when the visual stimulus was induced by the action rather than externally generated. Our results suggest that premotor brain activity might reflect predictive processes in sensory‐motor binding and that the readiness potentials may possibly represent a neural marker of these predictive mechanisms.