Previous studies have shown that face stimuli elicit extremely fast and involuntary saccadic responses toward them, relative to other categories of visual stimuli. In the present study, we further investigated to what extent face stimuli influence the programming and execution of saccades examining their amplitude. We performed two experiments using a saccadic choice task: two images (one with a face, one with a vehicle) were simultaneously displayed in the left and right visual fields of participants who had to initiate a saccade toward the image (Experiment 1) or toward a cross in the image (Experiment 2) containing a target stimulus (a face or a vehicle). Results revealed shorter saccades toward vehicle than face targets, even if participants were explicitly asked to perform their saccades toward a specific location (Experiment 2). Furthermore, error saccades had smaller amplitude than correct saccades. Further analyses showed that error saccades were interrupted in mid-flight to initiate a concurrently-programmed corrective saccade. Overall, these data suggest that the content of visual stimuli can influence the programming of saccade amplitude, and that efficient online correction of saccades can be performed during the saccadic choice task.

Despite the complexity of the visual world, humans rarely confuse variations in illumination, for example shadows, from variations in material properties, such as paint or stain. This ability to distinguish illumination from material edges is crucial for determining the spatial layout of objects and surfaces in natural scenes. In this study, we explore the role that color (chromatic) cues play in edge classification. We conducted a psychophysical experiment that required subjects to classify edges into illumination and material, in patches taken from images of natural scenes that either contained or did not contain color information. The edge images were of various sizes and were pre-classified into illumination and material, based on inspection of the edge in the context of the whole image from which the edge was extracted. Edge classification performance was found to be superior for the color compared to grayscale images, in keeping with color acting as a cue for edge classification. We defined machine observers sensitive to simple image properties and found that they too classified the edges better with color information, although they failed to capture the effect of image size observed in the psychophysical experiment. Our findings are consistent with previous work suggesting that color information facilitates the identification of material properties, transparency, shadows and the perception of shape-from-shading.

Multi-site studies utilizing MRI-derived measures from multiple scanners present an opportunity to increase the power of statistical models by pooling data. This represents the potential of detecting finer and more subtle effects related to pathology and is thus very appealing. It remains however unclear whether or not the potential confound introduced by scanner-related variations will devalue the integrity of any result. Specifically, it is crucial to test whether or not the error introduced into brain morphometry descriptors by image properties variations across scanners can exceed the effect of the disease itself. Moreover, evaluating the influence of the scanner on age-related effects in measurements is essential in the context of developmental disorders such as Autism Spectrum Disorders.In this study, we investigated a data-set of anatomical MRI pooled form three different scanners, representing a total of 186 subjects, 97 patients suffering from ASD and 89 controls. We quantitatively assessed the effects of age, pathology and scanner factors on cortical thickness measurements.