Reviews in Perception Science will publish high-quality scholarly review papers on key topics in Perception Science. It aims to highlight recent advances in the field, whilst emphasizing important directions and new possibilities for future inquiries. We anticipate the research presented will promote discussion in the community of Perception Science that will translate to best practice applications in Perception Science settings. The Reviews in Perception Science collection welcomes full-length, mini, or systematic review papers. New articles will be added to this collection as they are published.

University of Padua

Sapienza University of Rome

University of Central Florida

Frontiers in Psychology

Perception Science

Frontiers in Neuroscience

Reviews In Perception Science

In our society interaction with robots is becoming more and more frequent since robots are not only used in the industry, but increasingly often in assistance and in health system. Perception of robots and their movements is crucial for their acceptance. Here we shortly review basic mechanisms of perception of actions, and then of perception of robotic and human movements. The literature demonstrates that there are commonalities, but also differences in the perception of human and robotic movements. Especially interesting are biologic gender differences in the perception of robotic movements. The results show that males seem to be more sensitive to the differences between robotic and anthropomorphic movements, whereas females seem not to perceive such differences. However, females transfer more anthropomorphic features to robotic movements. While looking at the brain activation during perception of humanoid and robotic movements in different genders one can conclude that different strategies are used; female seem to analyse robotic movements online, while male seem to use previous knowledge from interaction with robots. Further research is needed to specify more such gender differences.

In our society interaction with robots is becoming more and more frequent since robots are not only used in the industry, but increasingly often in assistance and in health system. Perception of robots and their movements is crucial for their acceptance. Here we shortly review basic mechanisms of perception of actions, and then of perception of robotic and human movements. The literature demonstrates that there are commonalities, but also differences in the perception of human and robotic movements. Especially interesting are biologic gender differences in the perception of robotic movements. The results show that males seem to be more sensitive to the differences between robotic and anthropomorphic movements, whereas females seem not to perceive such differences. However, females transfer more anthropomorphic features to robotic movements. While looking at the brain activation during perception of humanoid and robotic movements in different genders one can conclude that different strategies are used; female seem to analyse robotic movements online, while male seem to use previous knowledge from interaction with robots. Further research is needed to specify more such gender differences.

Perception of robotic actions and the influence of gender

The human visual system rapidly recognizes the categories and global properties of complex natural scenes. The present study investigated the spatiotemporal dynamics of neural signals involved in visual scene processing using electroencephalography (EEG) decoding. We recorded visual evoked potentials from 11 human observers for 232 natural scenes, each of which belonged to one of 13 natural scene categories (e.g., a bedroom or open country) and had three global properties (naturalness, openness, and roughness). We trained a deep convolutional classification model of the natural scene categories and global properties using EEGNet. Having confirmed that the model successfully classified natural scene categories and the three global properties, we applied Grad-CAM to the EEGNet model to visualize the EEG channels and time points that contributed to the classification. The analysis showed that EEG signals in the occipital electrodes at short latencies (approximately 80 ~ ms) contributed to the classifications, whereas those in the frontal electrodes at relatively long latencies (200 ~ ms) contributed to the classification of naturalness and the individual scene category. These results suggest that different global properties are encoded in different cortical areas and with different timings, and that the combination of the EEGNet model and Grad-CAM can be a tool to investigate both temporal and spatial distribution of natural scene processing in the human brain.

The human visual system rapidly recognizes the categories and global properties of complex natural scenes. The present study investigated the spatiotemporal dynamics of neural signals involved in visual scene processing using electroencephalography (EEG) decoding. We recorded visual evoked potentials from 11 human observers for 232 natural scenes, each of which belonged to one of 13 natural scene categories (e.g., a bedroom or open country) and had three global properties (naturalness, openness, and roughness). We trained a deep convolutional classification model of the natural scene categories and global properties using EEGNet. Having confirmed that the model successfully classified natural scene categories and the three global properties, we applied Grad-CAM to the EEGNet model to visualize the EEG channels and time points that contributed to the classification. The analysis showed that EEG signals in the occipital electrodes at short latencies (approximately 80&#x2009;~&#x2009;ms) contributed to the classifications, whereas those in the frontal electrodes at relatively long latencies (200&#x2009;~&#x2009;ms) contributed to the classification of naturalness and the individual scene category. These results suggest that different global properties are encoded in different cortical areas and with different timings, and that the combination of the EEGNet model and Grad-CAM can be a tool to investigate both temporal and spatial distribution of natural scene processing in the human brain.

Spatiotemporal cortical dynamics for visual scene processing as revealed by EEG decoding

BackgroundDepression is a serious psychological disorder that college students are experiencing. College students’ depression problems, which can be caused by various factors, have been easily ignored and untreated. In recent years, exercise, as a low-cost and easily accessible method for treating depression, has attracted widespread attention. The purpose of this study is to use bibliometrics to explore the hotspots and trends in the field of exercise therapy of college students in depression from 2002 to 2022.</sec>MethodsWe retrieved relevant literature from the Web of Science (WoS), PubMed, and Scopus databases, and generated a ranking table to describe the core productivity in the field. We used VOSViewer software to generate network maps of authors, countries, co-cited journals, and co-occurring keywords to help us better understand the scientific collaboration patterns, potential disciplinary foundations, as well as research hotspots and trends in this field.</sec>ResultsFrom 2002 to 2022, a total of 1,397 articles related to exercise therapy of college students in depression were selected. The key findings of this study are as follows: (1) the number of publications has gradually increased, especially after 2019; (2) United States and its affiliated higher education institutions have made significant contributions to the development of this field; (3) there are multiple research groups in this field, but their connections are relatively limited; (4) the field is relatively interdisciplinary, primarily a convergence of behavioral science, public health, and psychology; (5) based on co-occurring keyword analysis, six main themes were summarized: health-promoting factors, body image, negative behaviors, increased stress, depression coping strategies, and diet.</sec>ConclusionOur study illustrates the research hotspots and trends for the research of exercise therapy of college students in depression, presents some challenges and new insights, and provides valuable information for further research.</sec>

Background: Depression is a serious psychological disorder that college students are experiencing. College students’ depression problems, which can be caused by various factors, have been easily ignored and untreated. In recent years, exercise, as a low-cost and easily accessible method for treating depression, has attracted widespread attention. The purpose of this study is to use bibliometrics to explore the hotspots and trends in the field of exercise therapy of college students in depression from 2002 to 2022.Methods: We retrieved relevant literature from the Web of Science (WoS), PubMed, and Scopus databases, and generated a ranking table to describe the core productivity in the field. We used VOSViewer software to generate network maps of authors, countries, co-cited journals, and co-occurring keywords to help us better understand the scientific collaboration patterns, potential disciplinary foundations, as well as research hotspots and trends in this field.Results: From 2002 to 2022, a total of 1,397 articles related to exercise therapy of college students in depression were selected. The key findings of this study are as follows: (1) the number of publications has gradually increased, especially after 2019; (2) United States and its affiliated higher education institutions have made significant contributions to the development of this field; (3) there are multiple research groups in this field, but their connections are relatively limited; (4) the field is relatively interdisciplinary, primarily a convergence of behavioral science, public health, and psychology; (5) based on co-occurring keyword analysis, six main themes were summarized: health-promoting factors, body image, negative behaviors, increased stress, depression coping strategies, and diet.Conclusion: Our study illustrates the research hotspots and trends for the research of exercise therapy of college students in depression, presents some challenges and new insights, and provides valuable information for further research.

Research trends of exercise therapy of college students in depression from 2002 to 2022: a bibliometric analysis

While approaching celebrations for the 150 years of “The Expression of the Emotions in Man and Animals”, scientists’ conclusions on emotion expression are still debated. Emotion expression has been traditionally anchored to prototypical and mutually exclusive facial expressions (e.g., anger, disgust, fear, happiness, sadness, and surprise). However, people express emotions in nuanced patterns and – crucially – not everything is in the face. In recent decades considerable work has critiqued this classical view, calling for a more fluid and flexible approach that considers how humans dynamically perform genuine expressions with their bodies in context. A growing body of evidence suggests that each emotional display is a complex, multi-component, motoric event. The human face is never static, but continuously acts and reacts to internal and environmental stimuli, with the coordinated action of muscles throughout the body. Moreover, two anatomically and functionally different neural pathways sub-serve voluntary and involuntary expressions. An interesting implication is that we have distinct and independent pathways for genuine and posed facial expressions, and different combinations may occur across the vertical facial axis. Investigating the time course of these facial blends, which can be controlled consciously only in part, is recently providing a useful operational test for comparing the different predictions of various models on the lateralization of emotions. This concise review will identify shortcomings and new challenges regarding the study of emotion expressions at face, body, and contextual levels, eventually resulting in a theoretical and methodological shift in the study of emotions. We contend that the most feasible solution to address the complex world of emotion expression is defining a completely new and more complete approach to emotional investigation. This approach can potentially lead us to the roots of emotional display, and to the individual mechanisms underlying their expression (i.e., individual emotional signatures).

While approaching celebrations for the 150 years of &#x201c;The Expression of the Emotions in Man and Animals&#x201d;, scientists&#x2019; conclusions on emotion expression are still debated. Emotion expression has been traditionally anchored to prototypical and mutually exclusive facial expressions (e.g., anger, disgust, fear, happiness, sadness, and surprise). However, people express emotions in nuanced patterns and &#x2013; crucially &#x2013; not everything is in the face. In recent decades considerable work has critiqued this classical view, calling for a more fluid and flexible approach that considers how humans dynamically perform genuine expressions with their bodies in context. A growing body of evidence suggests that each emotional display is a complex, multi-component, motoric event. The human face is never static, but continuously acts and reacts to internal and environmental stimuli, with the coordinated action of muscles throughout the body. Moreover, two anatomically and functionally different neural pathways sub-serve voluntary and involuntary expressions. An interesting implication is that we have distinct and independent pathways for genuine and posed facial expressions, and different combinations may occur across the vertical facial axis. Investigating the time course of these facial blends, which can be controlled consciously only in part, is recently providing a useful operational test for comparing the different predictions of various models on the lateralization of emotions. This concise review will identify shortcomings and new challenges regarding the study of emotion expressions at face, body, and contextual levels, eventually resulting in a theoretical and methodological shift in the study of emotions. We contend that the most feasible solution to address the complex world of emotion expression is defining a completely new and more complete approach to emotional investigation. This approach can potentially lead us to the roots of emotional display, and to the individual mechanisms underlying their expression (i.e., individual emotional signatures).