Efficient bubbles for visual categorization tasks

Nonlocal contrast calculated by the second order visual mechanisms and its significance in identifying facial emotions

Background: Previously obtained results indicate that faces are / preattentively/ detected in the visual scene very fast, and information on facial expression is rapidly extracted at the lower levels of the visual system. At the same time different facial attributes make different contributions in facial expression recognition. However, it is known, among the preattentive mechanisms there are none that would be selective for certain facial features, such as eyes or mouth. The aim of our study was to identify a candidate for the role of such a mechanism. Our assumption was that the most informative areas of the image are those characterized by spatial heterogeneity, particularly with nonlocal contrast changes. These areas may be identified / in the human visual system/ by the second-order visual / mechanisms/ filters selective to contrast modulations of brightness gradients. Methods: We developed a software program imitating the operation of these / mechanisms/ filters and finding areas of contrast heterogeneity in the image. Using this program, we extracted areas with maximum, minimum and medium contrast modulation amplitudes from the initial face images, then we used these to make three variants of one and the same face. The faces were demonstrated to the observers along with other objects synthesized the same way. The participants had to identify faces and define facial emotional expressions. Results: It was found that the greater is the contrast modulation amplitude of the areas shaping the face, the more precisely the emotion is identified. Conclusions: The results suggest that areas with a greater increase in nonlocal contrast are more informative in facial images, and the second-order visual / mechanisms/ filters can claim the role of /filters/ elements that detect areas of interest, attract visual attention and are windows through which subsequent levels of visual processing receive valuable information.

Impact of local luminance contrast on facial skin lightness perception: A psychophysical reverse correlation study using sub-band contrast modulation noise

In conventional psychophysical reverse correlation methods using white or pink noise, the luminance noise is added to every pixel. Thus, the image features correlated with perception are often biased toward local mean luminance. Furthermore, spatial frequencies and orientations are represented in the primary visual cortex, which forms the basis of various visual perception. In this study, we proposed a new reverse correlation method using noise that modulated the spatial frequency sub-band contrast and examined its properties in psychophysical experiments on facial skin lightness perception. In the experiment, we asked the observers to compare the perceived skin lightness in a paired comparison manner on face stimuli with increased or decreased spatial frequency sub-band contrasts at random spatial locations. The results showed that the contrasts in the eyes or irises were strongly and positively correlated with the perceived skin lightness in most sub-bands, demonstrating that the proposed method reiterated the findings of previous studies that the sparkle of the irises makes the skin appear lighter. Contrarily, the conventional reverse correlation method using pink noise images was applied to the skin lightness perception. The results indicated that only the local mean luminance in some skin regions, such as the forehead, was correlated with skin lightness perception. In summary, with the proposed method, we found some image features in the facial parts other than the skin mean luminance relevant to skin lightness perception, which are difficult to detect using the conventional method. They are considered complementary given that the proposed method and the conventional method extracted considerably different image features. It depends on the psychophysical tasks and stimuli which one is more appropriate.

Lateral presentation of faces alters overall viewing strategy

Eye tracking has been used during face categorisation and identification tasks to identify perceptually salient facial features and infer underlying cognitive processes. However, viewing patterns are influenced by a variety of gaze biases, drawing fixations to the centre of a screen and horizontally to the left side of face images (left-gaze bias). In order to investigate potential interactions between gaze biases uniquely associated with facial expression processing, and those associated with screen location, face stimuli were presented in three possible screen positions to the left, right and centre. Comparisons of fixations between screen locations highlight a significant impact of the screen centre bias, pulling fixations towards the centre of the screen and modifying gaze biases generally observed during facial categorisation tasks. A left horizontal bias for fixations was found to be independent of screen position but interacting with screen centre bias, drawing fixations to the left hemi-face rather than just to the left of the screen. Implications for eye tracking studies utilising centrally presented faces are discussed.

Brain signatures of perceiving a smile: Time course and source localization

Facial happiness is consistently recognized faster than other expressions of emotion. In this study, to determine when and where in the brain such a recognition advantage develops, EEG activity during an expression categorization task was subjected to temporospatial PCA analysis and LAURA source localizations. Happy, angry, and neutral faces were presented either in whole or bottom-half format (with the mouth region visible). The comparison of part- versus whole-face conditions served to examine the role of the smile. Two neural signatures underlying the happy face advantage emerged. One peaked around 140 ms (left N140) and was source-located at the left IT cortex (MTG), with greater activity for happy versus non-happy faces in both whole and bottom-half face format. This suggests an enhanced perceptual encoding mechanism for salient smiles. The other peaked around 370 ms (P3b and N3) and was located at the right IT (FG) and dorsal cingulate (CC) cortices, with greater activity specifically for bottom-half happy versus non-happy faces. This suggests an enhanced recruitment of face-specific information to categorize (or reconstruct) facial happiness from diagnostic smiling mouths. Additional differential brain responses revealed a specific "anger effect," with greater activity for angry versus non-angry expressions (right N170 and P230; right pSTS and IPL); and a coarse "emotion effect," with greater activity for happy and angry versus neutral expressions (anterior P2 and posterior N170; vmPFC and right IFG).

Modulations of eye movement patterns by spatial filtering during the learning and testing phases of an old/new face recognition task

In two experiments, we examined the effects of varying the spatial frequency (SF) content of face images on eye movements during the learning and testing phases of an old/new recognition task. At both learning and testing, participants were presented with face stimuli band-pass filtered to 11 different SF bands, as well as an unfiltered baseline condition. We found that eye movements varied significantly as a function of SF. Specifically, the frequency of transitions between facial features showed a band-pass pattern, with more transitions for middle-band faces (≈5-20 cycles/face) than for low-band (≈<5 cpf) or high-band (≈>20 cpf) ones. These findings were similar for the learning and testing phases. The distributions of transitions across facial features were similar for the middle-band, high-band, and unfiltered faces, showing a concentration on the eyes and mouth; conversely, low-band faces elicited mostly transitions involving the nose and nasion. The eye movement patterns elicited by low, middle, and high bands are similar to those previous researchers have suggested reflect holistic, configural, and featural processing, respectively. More generally, our results are compatible with the hypotheses that eye movements are functional, and that the visual system makes flexible use of visuospatial information in face processing. Finally, our finding that only middle spatial frequencies yielded the same number and distribution of fixations as unfiltered faces adds more evidence to the idea that these frequencies are especially important for face recognition, and reveals a possible mediator for the superior performance that they elicit.

Developmental changes in face visual scanning in autism spectrum disorder as assessed by data-based analysis

Individuals with autism spectrum disorder (ASD) present reduced visual attention to faces. However, contradictory conclusions have been drawn about the strategies involved in visual face scanning due to the various methodologies implemented in the study of facial screening. Here, we used a data-driven approach to compare children and adults with ASD subjected to the same free viewing task and to address developmental aspects of face scanning, including its temporal patterning, in healthy children, and adults. Four groups (54 subjects) were included in the study: typical adults, typically developing children, and adults and children with ASD. Eye tracking was performed on subjects viewing unfamiliar faces. Fixations were analyzed using a data-driven approach that employed spatial statistics to provide an objective, unbiased definition of the areas of interest. Typical adults expressed a spatial and temporal strategy for visual scanning that differed from the three other groups, involving a sequential fixation of the right eye (RE), left eye (LE), and mouth. Typically developing children, adults and children with autism exhibited similar fixation patterns and they always started by looking at the RE. Children (typical or with ASD) subsequently looked at the LE or the mouth. Based on the present results, the patterns of fixation for static faces that mature from childhood to adulthood in typical subjects are not found in adults with ASD. The atypical patterns found after developmental progression and experience in ASD groups appear to remain blocked in an immature state that cannot be differentiated from typical developmental child patterns of fixation.

Comparing face processing strategies between typically-developed observers and observers with autism using sub-sampled-pixels presentation in response classification technique

In the present study we modified the standard classification image method by subsampling visual stimuli to provide us with a technique capable of examining an individual's face-processing strategy in detail with fewer trials. Experiment 1 confirmed that one testing session (1450 trials) was sufficient to produce classification images that were qualitatively similar to those obtained previously with 10,000 trials (Sekuler et al., 2004). Experiment 2 used this method to compare classification images obtained from observers with autism spectrum disorders (ASD) and typically-developing (TD) observers. As was found in Experiment 1, classification images obtained from TD observers suggested that they all discriminated faces based on information conveyed by pixels in the eyes/brow region. In contrast, classification images obtained from ASD observers suggested that they used different perceptual strategies: three out of five ASD observers used a typical strategy of making use of information in the eye/brow region, but two used an atypical strategy that relied on information in the forehead region. The advantage of using the response classification technique is that there is no restriction to specific theoretical perspectives or a priori hypotheses, which enabled us to see unexpected strategies, like ASD's forehead strategy, and thus showed this technique is particularly useful in the examination of special populations.