{"title":"局部轮廓特征有助于猴子 V4 神经群和人类感知中的图形-地面分离。","authors":"Motofumi Shishikura , Itsuki Machida , Hiroshi Tamura , Ko Sakai","doi":"10.1016/j.neunet.2024.106821","DOIUrl":null,"url":null,"abstract":"<div><div>Figure-ground (FG) segregation is a crucial step towards the recognition of objects in natural scenes. Gestalt psychologists have emphasized the importance of contour features in perception of FG. Recent electrophysiological studies have identified a neural population in V4 that shows FG-dependent modulation (FG neurons). However, whether the contour features contribute to the modulation of the response patterns of the neural population remains unclear. In the present study, we quantified the contour features associated with Gestalt factors in local natural stimuli and examined whether salient contour-features evoked reliable perceptual and neural responses by analyzing response consistency (stability) across trials. The results showed the tendency that the more salient contour-features evoked the greater consistencies in the perceptual FG judgments and population-based neural responses in FG determination; a greater partial correlation for curvature and weaker correlations for closure and parallelism. Multiple linear regression analyses demonstrated that the perceptual consistency depended similarly on curvature and closure, and the neural consistency depended significantly on curvature but weakly on closure. We further observed a strong correlation between the consistencies in the perceptual and neural responses, <em>i.e</em>., stimuli that evoked more stable percepts tended to evoke more stable neural responses. These results indicate that local contour-features modulate the responses of the neural population in V4 and contribute to the perception of FG organization.</div></div>","PeriodicalId":49763,"journal":{"name":"Neural Networks","volume":"181 ","pages":"Article 106821"},"PeriodicalIF":6.0000,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Local contour features contribute to figure-ground segregation in monkey V4 neural populations and human perception\",\"authors\":\"Motofumi Shishikura , Itsuki Machida , Hiroshi Tamura , Ko Sakai\",\"doi\":\"10.1016/j.neunet.2024.106821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Figure-ground (FG) segregation is a crucial step towards the recognition of objects in natural scenes. Gestalt psychologists have emphasized the importance of contour features in perception of FG. Recent electrophysiological studies have identified a neural population in V4 that shows FG-dependent modulation (FG neurons). However, whether the contour features contribute to the modulation of the response patterns of the neural population remains unclear. In the present study, we quantified the contour features associated with Gestalt factors in local natural stimuli and examined whether salient contour-features evoked reliable perceptual and neural responses by analyzing response consistency (stability) across trials. The results showed the tendency that the more salient contour-features evoked the greater consistencies in the perceptual FG judgments and population-based neural responses in FG determination; a greater partial correlation for curvature and weaker correlations for closure and parallelism. Multiple linear regression analyses demonstrated that the perceptual consistency depended similarly on curvature and closure, and the neural consistency depended significantly on curvature but weakly on closure. We further observed a strong correlation between the consistencies in the perceptual and neural responses, <em>i.e</em>., stimuli that evoked more stable percepts tended to evoke more stable neural responses. These results indicate that local contour-features modulate the responses of the neural population in V4 and contribute to the perception of FG organization.</div></div>\",\"PeriodicalId\":49763,\"journal\":{\"name\":\"Neural Networks\",\"volume\":\"181 \",\"pages\":\"Article 106821\"},\"PeriodicalIF\":6.0000,\"publicationDate\":\"2024-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neural Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0893608024007457\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neural Networks","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0893608024007457","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Local contour features contribute to figure-ground segregation in monkey V4 neural populations and human perception
Figure-ground (FG) segregation is a crucial step towards the recognition of objects in natural scenes. Gestalt psychologists have emphasized the importance of contour features in perception of FG. Recent electrophysiological studies have identified a neural population in V4 that shows FG-dependent modulation (FG neurons). However, whether the contour features contribute to the modulation of the response patterns of the neural population remains unclear. In the present study, we quantified the contour features associated with Gestalt factors in local natural stimuli and examined whether salient contour-features evoked reliable perceptual and neural responses by analyzing response consistency (stability) across trials. The results showed the tendency that the more salient contour-features evoked the greater consistencies in the perceptual FG judgments and population-based neural responses in FG determination; a greater partial correlation for curvature and weaker correlations for closure and parallelism. Multiple linear regression analyses demonstrated that the perceptual consistency depended similarly on curvature and closure, and the neural consistency depended significantly on curvature but weakly on closure. We further observed a strong correlation between the consistencies in the perceptual and neural responses, i.e., stimuli that evoked more stable percepts tended to evoke more stable neural responses. These results indicate that local contour-features modulate the responses of the neural population in V4 and contribute to the perception of FG organization.
期刊介绍:
Neural Networks is a platform that aims to foster an international community of scholars and practitioners interested in neural networks, deep learning, and other approaches to artificial intelligence and machine learning. Our journal invites submissions covering various aspects of neural networks research, from computational neuroscience and cognitive modeling to mathematical analyses and engineering applications. By providing a forum for interdisciplinary discussions between biology and technology, we aim to encourage the development of biologically-inspired artificial intelligence.