Serial dependence in perception across naturalistic generative adversarial network-generated mammogram.

Purpose: Human perception and decisions are biased toward previously seen stimuli. This phenomenon is known as serial dependence and has been extensively studied for the last decade. Recent evidence suggests that clinicians' judgments of mammograms might also be impacted by serial dependence. However, the stimuli used in previous psychophysical experiments on this question, consisting of artificial geometric shapes and healthy tissue backgrounds, were unrealistic. We utilized realistic and controlled generative adversarial network (GAN)-generated radiographs to mimic images that clinicians typically encounter. Approach: Mammograms from the digital database for screening mammography (DDSM) were utilized to train a GAN. This pretrained GAN was then adopted to generate a large set of authentic-looking simulated mammograms: 20 circular morph continuums, each with 147 images, for a total of 2940 images. Using these stimuli in a standard serial dependence experiment, participants viewed a random GAN-generated mammogram on each trial and subsequently matched the GAN-generated mammogram encountered using a continuous report. The characteristics of serial dependence from each continuum were analyzed. Results: We found that serial dependence affected the perception of all naturalistic GAN-generated mammogram morph continuums. In all cases, the perceptual judgments of GAN-generated mammograms were biased toward previously encountered GAN-generated mammograms. On average, perceptual decisions had 7% categorization errors that were pulled in the direction of serial dependence. Conclusions: Serial dependence was found even in the perception of naturalistic GAN-generated mammograms created by a GAN. This supports the idea that serial dependence could, in principle, contribute to decision errors in medical image perception tasks.

Individual differences in classification images of Mooney faces.

Human face recognition is robust even under conditions of extreme lighting and in situations where there is high noise and uncertainty. Mooney faces are a canonical example of this: Mooney faces are two-tone shadow-defined images that are readily and holistically recognized despite lacking easily segmented face features. Face perception in such impoverished situations-and Mooney face perception in particular-is often thought to be supported by comparing encountered faces to stored templates. Here, we used a classification image approach to measure the templates that observers use to recognize Mooney faces. Visualizing these templates reveals the regions and structures of the image that best predict individual observer recognition, and they reflect the underlying internal representation of faces. Using this approach, we tested whether there are classification images that are consistent from session to session, whether the classification images are observer-specific, and whether they allow for pattern completion of holistic representations even in the absence of an underlying signal. We found that classification images of Mooney faces were indeed non-random (i.e., consistent session from session) within each observer, but they were different between observers. This result is in line with previously proposed existence of face templates that support face recognition, and further suggests that these templates may be unique to each observer and could drive idiosyncratic individual differences in holistic face recognition. Moreover, we found classification images that reflected information within the blank regions of the original Mooney faces, suggesting that observers may fill in missing information using idiosyncratic internal information about faces.

Relative tuning of holistic face processing towards the fovea.

Humans quickly detect and gaze at faces in the world, which reflects their importance in cognition and may lead to tuning of face recognition toward the central visual field. Although sometimes reported, foveal selectivity in face processing is debated: brain imaging studies have found evidence for a central field bias specific to faces, but behavioral studies have found little foveal selectivity in face recognition. These conflicting results are difficult to reconcile, but they could arise from stimulus-specific differences. Recent studies, for example, suggest that individual faces vary in the degree to which they require holistic processing. Holistic processing is the perception of faces as a whole rather than as a set of separate features. We hypothesized that the dissociation between behavioral and neuroimaging studies arises because of this stimulus-specific dependence on holistic processing. Specifically, the central bias found in neuroimaging studies may be specific to holistic processing. Here, we tested whether the eccentricity-dependence of face perception is determined by the degree to which faces require holistic processing. We first measured the holistic-ness of individual Mooney faces (two-tone shadow images readily perceived as faces). In a group of independent observers, we then used a gender discrimination task to measured recognition of these Mooney faces as a function of their eccentricity. Face gender was recognized across the visual field, even at substantial eccentricities, replicating prior work. Importantly, however, holistic face gender recognition was relatively tuned-slightly, but reliably stronger in the central visual field. Our results may reconcile the debate on the eccentricity-dependance of face perception and reveal a spatial inhomogeneity specifically in the holistic representations of faces.

Visual search in naturalistic scenes from foveal to peripheral vision: A comparison between dynamic and static displays.

How important foveal, parafoveal, and peripheral vision are depends on the task. For object search and letter search in static images of real-world scenes, peripheral vision is crucial for efficient search guidance, whereas foveal vision is relatively unimportant. Extending this research, we used gaze-contingent Blindspots and Spotlights to investigate visual search in complex dynamic and static naturalistic scenes. In Experiment 1, we used dynamic scenes only, whereas in Experiments 2 and 3, we directly compared dynamic and static scenes. Each scene contained a static, contextually irrelevant target (i.e., a gray annulus). Scene motion was not predictive of target location. For dynamic scenes, the search-time results from all three experiments converge on the novel finding that neither foveal nor central vision was necessary to attain normal search proficiency. Since motion is known to attract attention and gaze, we explored whether guidance to the target was equally efficient in dynamic as compared to static scenes. We found that the very first saccade was guided by motion in the scene. This was not the case for subsequent saccades made during the scanning epoch, representing the actual search process. Thus, effects of task-irrelevant motion were fast-acting and short-lived. Furthermore, when motion was potentially present (Spotlights) or absent (Blindspots) in foveal or central vision only, we observed differences in verification times for dynamic and static scenes (Experiment 2). When using scenes with greater visual complexity and more motion (Experiment 3), however, the differences between dynamic and static scenes were much reduced.

Idiosyncratic biases in the perception of medical images.

Introduction: Radiologists routinely make life-altering decisions. Optimizing these decisions has been an important goal for many years and has prompted a great deal of research on the basic perceptual mechanisms that underlie radiologists' decisions. Previous studies have found that there are substantial individual differences in radiologists' diagnostic performance (e.g., sensitivity) due to experience, training, or search strategies. In addition to variations in sensitivity, however, another possibility is that radiologists might have perceptual biases-systematic misperceptions of visual stimuli. Although a great deal of research has investigated radiologist sensitivity, very little has explored the presence of perceptual biases or the individual differences in these. Methods: Here, we test whether radiologists' have perceptual biases using controlled artificial and Generative Adversarial Networks-generated realistic medical images. In Experiment 1, observers adjusted the appearance of simulated tumors to match the previously shown targets. In Experiment 2, observers were shown with a mix of real and GAN-generated CT lesion images and they rated the realness of each image. Results: We show that every tested individual radiologist was characterized by unique and systematic perceptual biases; these perceptual biases cannot be simply explained by attentional differences, and they can be observed in different imaging modalities and task settings, suggesting that idiosyncratic biases in medical image perception may widely exist. Discussion: Characterizing and understanding these biases could be important for many practical settings such as training, pairing readers, and career selection for radiologists. These results may have consequential implications for many other fields as well, where individual observers are the linchpins for life-altering perceptual decisions.

Serial dependence in the perceptual judgments of radiologists.

In radiological screening, clinicians scan myriads of radiographs with the intent of recognizing and differentiating lesions. Even though they are trained experts, radiologists' human search engines are not perfect: average daily error rates are estimated around 3-5%. A main underlying assumption in radiological screening is that visual search on a current radiograph occurs independently of previously seen radiographs. However, recent studies have shown that human perception is biased by previously seen stimuli; the bias in our visual system to misperceive current stimuli towards previous stimuli is called serial dependence. Here, we tested whether serial dependence impacts radiologists' recognition of simulated lesions embedded in actual radiographs. We found that serial dependence affected radiologists' recognition of simulated lesions; perception on an average trial was pulled 13% toward the 1-back stimulus. Simulated lesions were perceived as biased towards the those seen in the previous 1 or 2 radiographs. Similar results were found when testing lesion recognition in a group of untrained observers. Taken together, these results suggest that perceptual judgements of radiologists are affected by previous visual experience, and thus some of the diagnostic errors exhibited by radiologists may be caused by serial dependence from previously seen radiographs.

Stimulus-Specific Individual Differences in Holistic Perception of Mooney Faces.

Humans perceive faces holistically rather than as a set of separate features. Previous work demonstrates that some individuals are better at this holistic type of processing than others. Here, we show that there are unique individual differences in holistic processing of specific Mooney faces. We operationalized the increased difficulty of recognizing a face when inverted compared to upright as a measure of the degree to which individual Mooney faces were processed holistically by individual observers. Our results show that Mooney faces vary considerably in the extent to which they tap into holistic processing; some Mooney faces require holistic processing more than others. Importantly, there is little between-subject agreement about which faces are processed holistically; specific faces that are processed holistically by one observer are not by other observers. Essentially, what counts as holistic for one person is unique to that particular observer. Interestingly, we found that the per-face, per-observer differences in face discrimination only occurred for harder Mooney faces that required relatively more holistic processing. These findings suggest that holistic processing of hard Mooney faces depends on a particular observer's experience whereas processing of easier, cartoon-like Mooney faces can proceed universally for everyone. Future work using Mooney faces in perception research should take these stimulus-specific individual differences into account to best isolate holistic processing.