Spatial summation of face information

Do all parts of the face contribute equally to face detection or are some parts more detectable than others? To evaluate this issue, we studied detection of the presence of normalized frontal-face images within aperture windows of varying extent. We performed a face summation study using two-alternative forced-choice psychophysics. The face stimuli were scaled to equal eye-to-chin distance, centered on the bridge of the nose, and windowed by fourth-power Gaussian envelopes of various sizes. The faces were intermixed with control stimuli consisting inverted faces to test for configuration effects, split-half inverted faces to perturb the symmetry, and phase-scrambled versions of the faces with equal Fourier energy. Face detectability improved rapidly at first, then at a progressively shallower rate for larger window sizes, in a similar fashion for the three face-based stimulus types. The spectrally equated noise stimuli were less detectable than the face stimuli for all except the smallest apertures. The results were fit with a model incorporating global face-specific and local nonspecific spatial integration mechanisms. Detection of the noise images was consistent with local detection mechanisms accessed through a wide-field attention mechanism. The data for face detection implied detection mechanisms that integrated linearly up to some small size, integrated more slowly up to an intermediate size, and failed to gain any improvement for information beyond some larger size. This performance supports the concept of a specialized face configuration mechanism operating at detection threshold, similar in extent among the observers

Seeing visual word forms: Spatial summation, eccentricity and spatial configuration

AbstractWe investigated observers’ performance in detecting and discriminating visual word forms as a function of target size and retinal eccentricity. The contrast threshold of visual words was measured with a spatial two-alternative forced-choice paradigm and a PSI adaptive method. The observers were to indicate which of two sides contained a stimulus in the detection task, and which contained a real character (as opposed to a pseudo- or non-character) in the discrimination task. When the target size was sufficiently small, the detection threshold of a character decreased as its size increased, with a slope of −1/2 on log–log coordinates, up to a critical size at all eccentricities and for all stimulus types. The discrimination threshold decreased with target size with a slope of −1 up to a critical size that was dependent on stimulus type and eccentricity. Beyond that size, the threshold decreased with a slope of −1/2 on log–log coordinates before leveling out. The data was well fit by a spatial summation model that contains local receptive fields (RFs) and a summation across these filters within an attention window. Our result implies that detection is mediated by local RFs smaller than any tested stimuli and thus detection performance is dominated by summation across receptive fields. On the other hand, discrimination is dominated by a summation within a local RF in the fovea but a cross RF summation in the periphery

Learning motion: Human vs. optimal Bayesian learner

We used the optimal perceptual learning paradigm (Eckstein, Abbey, Pham, & Shimozaki, 2004) to investigate the dynamics of human rapid learning processes in motion discrimination tasks and compare it to an optimal Bayesian learner. This paradigm consists of blocks of few trials defined by a set of target attributes, and it has been shown its ability to detect learning effects appearing as soon as after the first trial. In the present task a sequence consisting of four patches containing random-dot patterns is presented at four separate locations equidistant from a fixation point. On each trial, the random dots in three patches moved with a mean speed and the fourth, target patch, could move either with slower or faster mean speed. Observers' task was to indicate what speed, faster or slower, was present in the display. The mean direction of the target patch was kept invariant along a block of trials. Observers learned the target relevant motion direction through indirect feedback, leading to an improvement in speed identification performance ranging from 15% to 30% which is greater than previously studied contrast defined targets and faces. However, comparison to an ideal learner revealed incomplete or partial learning for the motion task which was lower than previously measured for contrast defined targets and faces. A sub-optimal model that included inefficiencies in the updating of motion direction weights due to memory effects could account for the human learning. Finally, the similarity of the rapid learning effect observed here for motion perception with that found for contrast defined targets for localization and identification tasks could be suggesting a general strategy for learning in the human visual system and some common limitations such as memory.Fil: Trenti, Edgardo Javier. Universidad Nacional de Salta. Facultad de Ciencias Exactas; ArgentinaFil: Barraza, Jose Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Investigación en Luz, Ambiente y Visión. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Instituto de Investigación en Luz, Ambiente y Visión; ArgentinaFil: Eckstein, Miguel P.. University of California; Estados Unido

Area summation in human vision at and above detection threshold

The initial image-processing stages of visual cortex are well suited to a local (patchwise) analysis of the viewed scene. But the world's structures extend over space as textures and surfaces, suggesting the need for spatial integration. Most models of contrast vision fall shy of this process because (i) the weak area summation at detection threshold is attributed to probability summation (PS) and (ii) there is little or no advantage of area well above threshold. Both of these views are challenged here. First, it is shown that results at threshold are consistent with linear summation of contrast following retinal inhomogeneity, spatial filtering, nonlinear contrast transduction and multiple sources of additive Gaussian noise. We suggest that the suprathreshold loss of the area advantage in previous studies is due to a concomitant increase in suppression from the pedestal. To overcome this confound, a novel stimulus class is designed where: (i) the observer operates on a constant retinal area, (ii) the target area is controlled within this summation field, and (iii) the pedestal is fixed in size. Using this arrangement, substantial summation is found along the entire masking function, including the region of facilitation. Our analysis shows that PS and uncertainty cannot account for the results, and that suprathreshold summation of contrast extends over at least seven target cycles of grating

A more featural based processing for the self-face: An eye-tracking study

Studies have suggested that the holistic advantage in face perception is not always reported for the own face. With two eye-tracking experiments, we explored the role of holistic and featural processing in the processing and the recognition of self, personally familiar, and unfamiliar faces. Observers were asked to freely explore (Exp.1) and recognize (Exp.2) their own, a friend's, and an unfamiliar face. In Exp.1, self-face was fixated more and longer and there was a preference for the mouth region when seeing the own face and for the nose region when seeing a friend and unfamiliar faces. In Exp.2, the viewing strategies did not differ across all faces, with eye fixations mostly directed to the nose region. These results suggest that task demands might modulate the way that the own face is perceived and highlights the importance of considering the role of the distinct visual experience people have for the own face in the processing and recognition of the self-face

Exploring cognitive mechanisms involved in self-face recognition

Due to the own face being a significant stimulus that is critical to one’s identity, the own face is suggested to be processed in a quantitatively different (i.e., faster and better recognition) and qualitatively different (i.e., processed in a more featural manner) manner compared to other faces. This thesis further explored the cognitive mechanisms (perceptual and attentional systems) involved in the processing of the own face. Chapter 2 explored the role of holistic and featural processing involved in the processing of self-face (and other faces) with eye-tracking measures in a passive-viewing paradigm and a face identification task. In the passive-viewing paradigm, the own face was sampled in a more featural manner compared to other faces whereas when asked to identify faces, all faces were sampled in a more holistic manner. Chapter 3 further explored the role of holistic and featural processing in the identification of the own face using the three standard measures of holistic face processing: The face inversion task, the composite face task, and the part-whole task. Compared to other faces, individuals showed a smaller “holistic interference” by a task irrelevant bottom half for the own face in the composite face task and a stronger feature advantage for the own face, but inversion impaired the identification of all faces. These findings suggest that self-face is processed in a more featural manner, but the findings do not deny the role of holistic processing. The final experimental chapter, Chapter 4, explored the modulation effects of cultural differences in one’s self-concept (i.e., independent vs. interdependent self-concept) and a negative self-concept (i.e., depressive traits) on the attentional prioritization for the own face with a visual search paradigm. Findings showed that the attentional prioritization for the own face over an unfamiliar face is not modulated by cultural differences of one’s self-concept nor one’s level of depressive traits, and individuals showed no difference in the attentional prioritization for both the own face and friend’s face, demonstrating no processing advantage for the own face over a personally familiar face. These findings suggests that the attentional prioritization for the own face is better explained by a familiar face advantage. Altogether, the findings of this thesis suggest that the own face is processed qualitatively different compared to both personally familiar and unfamiliar face, with the own face being processed in a more featural manner. However, in terms of quantitative differences, the self-face is processed differently compared to an unfamiliar face, but not to a familiar face. Although the specific face processing strategies for the own face may be due to the distinct visual experience that one has with their face, the attentional prioritization of the own face is however, better explained by a familiar face advantage rather than a self-specificity effect

Sailing the ocean of faces: unravelling individual differences in face recognition abilities

Even though it has generally been assumed that humans are experts in face recognition, the ability to learn and recognize faces varies considerably across individuals. However, it is still unclear to what extent the use of facial information and/or underlying processes differs across individuals. This dissertation consists of four empirical chapters that aimed to explore the role of low-level visual processing to higher-level processes in face recognition ability (FRA) at an individual level. In the first empirical chapter (Chapter 2), we examined how the use of different bands of spatial frequency (SF) information influences FRA at different stages of face recognition. While studies have found that low SF information is important for accurate face recognition, whether it facilitates individual differences in FRA remains unexplored. In our study, we found that low and high SF information are equally important and informative in face learning and face recognition. However, no significant association was found between the recognition performance of low and high SF-filtered faces with FRA, this argues that SF processing does not contribute to individual differences in face recognition. In Chapter 3, we aimed to gain further insight into the role of holistic processing in FRA, particularly between Western and Eastern societies. Although it is generally assumed that face recognition relies on holistic processing, whether face recognition ability can be predicted by holistic processing is currently under debate. The mixed findings from past studies could be the consequence of cultural differences across studies, as well as the use of different measures of holistic processing that showed a poor association between each other: the composite task, the part-whole task, and the inversion task. We found that FRA is associated with the part-whole and inversion effect, but not the composite effect. This was true for both Easterners and Westerners. This suggests that FRA is facilitated by similar underlying cognitive mechanisms of holistic processing across different societies. Despite that, our factor analysis revealed cultural differences in the loading patterns of holistic mechanisms into FRA. This argues that holistic face processing is not universal, wherein underlying construct in holistic face processing is culture-specific. Accordingly in Chapter 4, we examined the role of holistic processing in Developmental Prosopagnosics (DPs) and Acquired Prosopagnosics (APs). Similar to the preceding chapter, several tests measuring the holistic processing of faces and non-face objects were used. However, the current chapter recruited groups of DPs (Experiment 1), APs (Experiment 2), and neurotypicals. At a group level, DPs showed diminished inversion and part-whole effects, but comparable magnitudes of the composite effect and global precedence effect. Interestingly, single-case analyses showed that these holistic processing deficits in DPs are heterogeneous, wherein holistic impairments are distinct across individual DPs. On the other hand, our single-case analyses revealed that two APs were both impaired in holistic processing, as measured with the face inversion effect, but not the part-whole or composite effects. This suggest that holistic processing deficits in APs are consistent. Together, the findings challenge the view that the concept of holistic processing is unitary, as well as highlight the importance of single-case analyses in characterizing neurodevelopmental profiles. In Chapter 5, we aimed to further investigate the role of holistic processing, as well as featural processing, in face identification abilities by incorporating the fixed trajectory aperture paradigm (FTAP) during face learning and recognition. While it is generally accepted that holistic processing facilitates face recognition, recent studies suggest that poor recognition might also arise from the imprecise perception of local features in the face. Our results showed that participants recognised faces more accurately in conditions where holistic information was preserved than when it is impaired. We also show that the better use of holistic processing during face learning and face recognition was associated with better FRAs. However, enhanced featural processing during recognition, but not during learning, was related to better FRAs. Together, our findings demonstrate that good face recognition depends on distinct roles played by holistic and featural processing, at different stages of face recognition. Altogether, across four empirical chapters, the results of this thesis showed that individual differences in face recognition abilities can be explained by high-level (i.e., holistic and/or featural processing), but not low-level (i.e., spatial frequency) processes. In the first study, we found that low and high SF processing does not facilitate face learning and face recognition. In contrast, the following studies indicated that higher-level cognitive mechanisms involving holistic and/or featural processing underlie individual differences in face recognition. These associations between holistic face processing and face recognition abilities are also found across both Western and Eastern cultures. However, holistic processing does not seem to predict face recognition deficits in prosopagnosics. Interestingly, the concept of holistic face processing is (1) not unitary, (2) nor is it universal across cultures, and presumably (3) has distinct roles during face learning and face recognition

Exploring cognitive mechanisms involved in self-face recognition

Due to the own face being a significant stimulus that is critical to one’s identity, the own face is suggested to be processed in a quantitatively different (i.e., faster and better recognition) and qualitatively different (i.e., processed in a more featural manner) manner compared to other faces. This thesis further explored the cognitive mechanisms (perceptual and attentional systems) involved in the processing of the own face. Chapter 2 explored the role of holistic and featural processing involved in the processing of self-face (and other faces) with eye-tracking measures in a passive-viewing paradigm and a face identification task. In the passive-viewing paradigm, the own face was sampled in a more featural manner compared to other faces whereas when asked to identify faces, all faces were sampled in a more holistic manner. Chapter 3 further explored the role of holistic and featural processing in the identification of the own face using the three standard measures of holistic face processing: The face inversion task, the composite face task, and the part-whole task. Compared to other faces, individuals showed a smaller “holistic interference” by a task irrelevant bottom half for the own face in the composite face task and a stronger feature advantage for the own face, but inversion impaired the identification of all faces. These findings suggest that self-face is processed in a more featural manner, but the findings do not deny the role of holistic processing. The final experimental chapter, Chapter 4, explored the modulation effects of cultural differences in one’s self-concept (i.e., independent vs. interdependent self-concept) and a negative self-concept (i.e., depressive traits) on the attentional prioritization for the own face with a visual search paradigm. Findings showed that the attentional prioritization for the own face over an unfamiliar face is not modulated by cultural differences of one’s self-concept nor one’s level of depressive traits, and individuals showed no difference in the attentional prioritization for both the own face and friend’s face, demonstrating no processing advantage for the own face over a personally familiar face. These findings suggests that the attentional prioritization for the own face is better explained by a familiar face advantage. Altogether, the findings of this thesis suggest that the own face is processed qualitatively different compared to both personally familiar and unfamiliar face, with the own face being processed in a more featural manner. However, in terms of quantitative differences, the self-face is processed differently compared to an unfamiliar face, but not to a familiar face. Although the specific face processing strategies for the own face may be due to the distinct visual experience that one has with their face, the attentional prioritization of the own face is however, better explained by a familiar face advantage rather than a self-specificity effect

Sailing the ocean of faces: unravelling individual differences in face recognition abilities

Even though it has generally been assumed that humans are experts in face recognition, the ability to learn and recognize faces varies considerably across individuals. However, it is still unclear to what extent the use of facial information and/or underlying processes differs across individuals. This dissertation consists of four empirical chapters that aimed to explore the role of low-level visual processing to higher-level processes in face recognition ability (FRA) at an individual level. In the first empirical chapter (Chapter 2), we examined how the use of different bands of spatial frequency (SF) information influences FRA at different stages of face recognition. While studies have found that low SF information is important for accurate face recognition, whether it facilitates individual differences in FRA remains unexplored. In our study, we found that low and high SF information are equally important and informative in face learning and face recognition. However, no significant association was found between the recognition performance of low and high SF-filtered faces with FRA, this argues that SF processing does not contribute to individual differences in face recognition. In Chapter 3, we aimed to gain further insight into the role of holistic processing in FRA, particularly between Western and Eastern societies. Although it is generally assumed that face recognition relies on holistic processing, whether face recognition ability can be predicted by holistic processing is currently under debate. The mixed findings from past studies could be the consequence of cultural differences across studies, as well as the use of different measures of holistic processing that showed a poor association between each other: the composite task, the part-whole task, and the inversion task. We found that FRA is associated with the part-whole and inversion effect, but not the composite effect. This was true for both Easterners and Westerners. This suggests that FRA is facilitated by similar underlying cognitive mechanisms of holistic processing across different societies. Despite that, our factor analysis revealed cultural differences in the loading patterns of holistic mechanisms into FRA. This argues that holistic face processing is not universal, wherein underlying construct in holistic face processing is culture-specific. Accordingly in Chapter 4, we examined the role of holistic processing in Developmental Prosopagnosics (DPs) and Acquired Prosopagnosics (APs). Similar to the preceding chapter, several tests measuring the holistic processing of faces and non-face objects were used. However, the current chapter recruited groups of DPs (Experiment 1), APs (Experiment 2), and neurotypicals. At a group level, DPs showed diminished inversion and part-whole effects, but comparable magnitudes of the composite effect and global precedence effect. Interestingly, single-case analyses showed that these holistic processing deficits in DPs are heterogeneous, wherein holistic impairments are distinct across individual DPs. On the other hand, our single-case analyses revealed that two APs were both impaired in holistic processing, as measured with the face inversion effect, but not the part-whole or composite effects. This suggest that holistic processing deficits in APs are consistent. Together, the findings challenge the view that the concept of holistic processing is unitary, as well as highlight the importance of single-case analyses in characterizing neurodevelopmental profiles. In Chapter 5, we aimed to further investigate the role of holistic processing, as well as featural processing, in face identification abilities by incorporating the fixed trajectory aperture paradigm (FTAP) during face learning and recognition. While it is generally accepted that holistic processing facilitates face recognition, recent studies suggest that poor recognition might also arise from the imprecise perception of local features in the face. Our results showed that participants recognised faces more accurately in conditions where holistic information was preserved than when it is impaired. We also show that the better use of holistic processing during face learning and face recognition was associated with better FRAs. However, enhanced featural processing during recognition, but not during learning, was related to better FRAs. Together, our findings demonstrate that good face recognition depends on distinct roles played by holistic and featural processing, at different stages of face recognition. Altogether, across four empirical chapters, the results of this thesis showed that individual differences in face recognition abilities can be explained by high-level (i.e., holistic and/or featural processing), but not low-level (i.e., spatial frequency) processes. In the first study, we found that low and high SF processing does not facilitate face learning and face recognition. In contrast, the following studies indicated that higher-level cognitive mechanisms involving holistic and/or featural processing underlie individual differences in face recognition. These associations between holistic face processing and face recognition abilities are also found across both Western and Eastern cultures. However, holistic processing does not seem to predict face recognition deficits in prosopagnosics. Interestingly, the concept of holistic face processing is (1) not unitary, (2) nor is it universal across cultures, and presumably (3) has distinct roles during face learning and face recognition