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Trübutschek D, Melloni L. Stable perceptual phenotype of the magnitude of history biases even in the face of global task complexity. J Vis 2023; 23:4. [PMID: 37531102 PMCID: PMC10405861 DOI: 10.1167/jov.23.8.4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 06/25/2023] [Indexed: 08/03/2023] Open
Abstract
According to a Bayesian framework, visual perception requires active interpretation of noisy sensory signals in light of prior information. One such mechanism, serial dependence, is thought to promote perceptual stability by assimilating current percepts with recent stimulus history. Combining a delayed orientation-adjustment paradigm with predictable (study 1) or unpredictable (study 2) task structure, we test two key predictions of this account in a novel context: first, that serial dependence should persist even in variable environments, and, second, that, within a given observer and context, this behavioral bias should be stable from one occasion to the next. Relying on data of 41 human volunteers and two separate experimental sessions, we confirm both hypotheses. Group-level, attractive serial dependence remained strong even in the face of volatile settings with multiple, unpredictable types of tasks, and, despite considerable interindividual variability, within-subject patterns of attractive and repulsive stimulus-history biases were highly stable from one experimental session to the next. In line with the hypothesized functional role of serial dependence, we propose that, together with previous work, our findings suggest the existence of a more general individual-specific fingerprint with which the past shapes current perception. Congruent with the Bayesian account, interindividual differences may then result from differential weighting of sensory evidence and prior information.
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Affiliation(s)
- Darinka Trübutschek
- Research Group Neural Circuits, Consciousness and Cognition, Max Planck Institute for Empirical Aesthetics, Frankfurt/Main, Germany
| | - Lucia Melloni
- Research Group Neural Circuits, Consciousness and Cognition, Max Planck Institute for Empirical Aesthetics, Frankfurt/Main, Germany
- Department of Neurology, NYU Grossman School of Medicine, New York, New York, USA
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Ren Z, Li X, Pietralla D, Manassi M, Whitney D. Serial Dependence in Dermatological Judgments. Diagnostics (Basel) 2023; 13:diagnostics13101775. [PMID: 37238260 DOI: 10.3390/diagnostics13101775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/09/2023] [Accepted: 05/13/2023] [Indexed: 05/28/2023] Open
Abstract
Serial Dependence is a ubiquitous visual phenomenon in which sequentially viewed images appear more similar than they actually are, thus facilitating an efficient and stable perceptual experience in human observers. Although serial dependence is adaptive and beneficial in the naturally autocorrelated visual world, a smoothing perceptual experience, it might turn maladaptive in artificial circumstances, such as medical image perception tasks, where visual stimuli are randomly sequenced. Here, we analyzed 758,139 skin cancer diagnostic records from an online app, and we quantified the semantic similarity between sequential dermatology images using a computer vision model as well as human raters. We then tested whether serial dependence in perception occurs in dermatological judgments as a function of image similarity. We found significant serial dependence in perceptual discrimination judgments of lesion malignancy. Moreover, the serial dependence was tuned to the similarity in the images, and it decayed over time. The results indicate that relatively realistic store-and-forward dermatology judgments may be biased by serial dependence. These findings help in understanding one potential source of systematic bias and errors in medical image perception tasks and hint at useful approaches that could alleviate the errors due to serial dependence.
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Affiliation(s)
- Zhihang Ren
- Vision Science Graduate Group, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Xinyu Li
- Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Dana Pietralla
- Institute of Sociology and Social Psychology, University of Cologne, Albertus-Magnus-Platz, D-50923 Cologne, Germany
| | - Mauro Manassi
- School of Psychology, King's College, University of Aberdeen, Aberdeen AB24 3FX, UK
| | - David Whitney
- Vision Science Graduate Group, University of California, Berkeley, Berkeley, CA 94720, USA
- Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
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Parthasarathy MK, Zuley ML, Bandos AI, Abbey CK, Webster MA. Visual adaptation to medical images: a comparison of digital mammography and tomosynthesis. J Med Imaging (Bellingham) 2023; 10:S11909. [PMID: 37114188 PMCID: PMC10128168 DOI: 10.1117/1.jmi.10.s1.s11909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 03/31/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Purpose Radiologists and other image readers spend prolonged periods inspecting medical images. The visual system can rapidly adapt or adjust sensitivity to the images that an observer is currently viewing, and previous studies have demonstrated that this can lead to pronounced changes in the perception of mammogram images. We compared these adaptation effects for images from different imaging modalities to explore both general and modality-specific consequences of adaptation in medical image perception. Approach We measured perceptual changes induced by adaptation to images acquired by digital mammography (DM) or digital breast tomosynthesis (DBT), which have both similar and distinct textural properties. Participants (nonradiologists) adapted to images from the same patient acquired from each modality or for different patients with American College of Radiology-Breast Imaging Reporting and Data System (BI-RADS) classification of dense or fatty tissue. The participants then judged the appearance of composite images formed by blending the two adapting images (i.e., DM versus DBT or dense versus fatty in each modality). Results Adaptation to either modality produced similar significant shifts in the perception of dense and fatty textures, reducing the salience of the adapted component in the test images. In side-by-side judgments, a modality-specific adaptation effect was not observed. However, when the images were directly fixated during adaptation and testing, so that the textural differences between the modalities were more visible, significantly different changes in the sensitivity to the noise in the images were observed. Conclusions These results confirm that observers can readily adapt to the visual properties or spatial textures of medical images in ways that can bias their perception of the images, and that adaptation can also be selective for the distinctive visual features of images acquired by different modalities.
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Affiliation(s)
| | - Margarita L. Zuley
- University of Pittsburgh, Department of Radiology, Pittsburgh, Pennsylvania, United States
| | - Andriy I. Bandos
- University of Pittsburgh, School of Public health, Pittsburgh, Pennsylvania, United States
| | - Craig K. Abbey
- University of California, Santa Barbara, Department of Psychological and Brain Sciences, Santa Barbara, California, United States
| | - Michael A. Webster
- University of Nevada, Reno, Department of Psychology, Reno, Nevada, United States
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Wang Z, Manassi M, Ren Z, Ghirardo C, Canas-Bajo T, Murai Y, Zhou M, Whitney D. Idiosyncratic biases in the perception of medical images. Front Psychol 2022; 13:1049831. [PMID: 36600706 PMCID: PMC9806180 DOI: 10.3389/fpsyg.2022.1049831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 11/29/2022] [Indexed: 12/23/2022] Open
Abstract
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.
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Affiliation(s)
- Zixuan Wang
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States,*Correspondence: Zixuan Wang,
| | - Mauro Manassi
- School of Psychology, University of Aberdeen, King’s College, Aberdeen, United Kingdom
| | - Zhihang Ren
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States,Vision Science Group, University of California, Berkeley, Berkeley, CA, United States
| | - Cristina Ghirardo
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States
| | - Teresa Canas-Bajo
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States,Vision Science Group, University of California, Berkeley, Berkeley, CA, United States
| | - Yuki Murai
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Koganei, Japan
| | - Min Zhou
- Department of Pediatrics, The First People's Hospital of Shuangliu District, Chengdu, Sichuan, China
| | - David Whitney
- Department of Psychology, University of California, Berkeley, Berkeley, CA, United States,Vision Science Group, University of California, Berkeley, Berkeley, CA, United States,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
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Wolfe JM. How one block of trials influences the next: persistent effects of disease prevalence and feedback on decisions about images of skin lesions in a large online study. Cogn Res Princ Implic 2022; 7:10. [PMID: 35107667 PMCID: PMC8811054 DOI: 10.1186/s41235-022-00362-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 01/15/2022] [Indexed: 11/16/2022] Open
Abstract
Using an online, medical image labeling app, 803 individuals rated images of skin lesions as either "melanoma" (skin cancer) or "nevus" (a skin mole). Each block consisted of 80 images. Blocks could have high (50%) or low (20%) target prevalence and could provide full, accurate feedback or no feedback. As in prior work, with feedback, decision criteria were more conservative at low prevalence than at high prevalence and resulted in more miss errors. Without feedback, this low prevalence effect was reversed (albeit, not significantly). Participants could participate in up to four different conditions a day on each of 6 days. Our main interest was in the effect of Block N on Block N + 1. Low prevalence with feedback made participants more conservative on a subsequent block. High prevalence with feedback made participants more liberal on a subsequent block. Conditions with no feedback had no significant impact on the subsequent block. The delay between Blocks 1 and 2 had no significant effect. The effect on the second half of Block 2 was just as large as on the first half. Medical expertise (over the range available in the study) had no impact on these effects, though medical students were better at the task than other groups. Overall, these seem to be robust effects where feedback may be 'teaching' participants how to respond in the future. This might have application in, for example, training or re-training situations.
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Affiliation(s)
- Jeremy M Wolfe
- Visual Attention Lab, Department of Surgery, Brigham and Women's Hospital, 900 Commonwealth Ave, 3rd Floor, Boston, MA, 02215, USA. .,Harvard Medical School, Boston, USA.
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