The influence of stimuli valence, extraversion, and emotion regulation on visual search within real-world scenes.
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ABSTRACT:
SUBMITTER: Bendall RCA
PROVIDER: S-EPMC8766590 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Research shows that emotional stimuli can capture attention, and this can benefit or impair performance, depending on the characteristics of a task. Additionally, whilst some findings show that attention expands under positive conditions, others show that emotion has no influence on the broadening of attention. The current study investigated whether emotional real-world scenes influence attention in a visual search task. Participants were asked to identify a target letter embedded in the centre or periphery of emotional images. Identification accuracy was lower in positive images compared to neutral images, and response times were slower in negative images. This suggests that real-world emotional stimuli have a distracting effect on visual attention and search. There was no evidence that emotional images influenced the spatial spread of attention. Instead, it is suggested that findings may provide support for the argument that positive emotion encourages a global processing style and negative emotion promotes local processing.
| S-EPMC6647383 | biostudies-literature
Project description:IntroductionEmotion has been shown to influence selective visual attention. However, studies in this field have revealed contradictory findings regarding the nature of this influence. One possible explanation for the variation in findings is that affective inter-individual differences impact both attention and emotion and may therefore moderate any influence of emotion on attention. The current work is a novel investigation of the effects of induced emotional states and the traits of extraversion and neuroticism on visual attention. This allowed a direct investigation of any impact of extraversion and neuroticism on the way in which emotion influences attention.MethodsParticipants were induced into positive, neutral, and negative emotional states before completing a change detection flicker task in which they were required to locate a change to a real-world scene as quickly and accurately as possible.ResultsParticipants scoring higher in extraversion were more accurate but slower at detecting changes. Importantly, this was particularly evident when induced into a negative emotional state compared to a neutral emotional state. Neuroticism had no impact on attention.ConclusionsThe current study provides evidence that extraversion can moderate the influence of negative emotion upon visual attention and may help to explain some of the contradictory findings in this research area. When considered independently, increased trait levels of extraversion were associated with improved change detection. Individuals higher in extraversion appear better equipped to regulate negative emotion compared to individuals lower in extraversion, supporting research linking extraversion to affective reactivity and models of psychopathology.
| S-EPMC8613417 | biostudies-literature
Project description:Categorization performance is a popular metric of scene recognition and understanding in behavioral and computational research. However, categorical constructs and their labels can be somewhat arbitrary. Derived from exhaustive vocabularies of place names (e.g., Deng et al., 2009), or the judgements of small groups of researchers (e.g., Fei-Fei, Iyer, Koch, & Perona, 2007), these categories may not correspond with human-preferred taxonomies. Here, we propose clustering by increasing the rand index via coordinate ascent (CIRCA): an unsupervised, data-driven clustering method for deriving ground-truth scene categories. In Experiment 1, human participants organized 80 stereoscopic images of outdoor scenes from the Southampton-York Natural Scenes (SYNS) dataset (Adams et al., 2016) into discrete categories. In separate tasks, images were grouped according to i) semantic content, ii) three-dimensional spatial structure, or iii) two-dimensional image appearance. Participants provided text labels for each group. Using the CIRCA method, we determined the most representative category structure and then derived category labels for each task/dimension. In Experiment 2, we found that these categories generalized well to a larger set of SYNS images, and new observers. In Experiment 3, we tested the relationship between our category systems and the spatial envelope model (Oliva & Torralba, 2001). Finally, in Experiment 4, we validated CIRCA on a larger, independent dataset of same-different category judgements. The derived category systems outperformed the SUN taxonomy (Xiao, Hays, Ehinger, Oliva, & Torralba, 2010) and an alternative clustering method (Greene, 2019). In summary, we believe this novel categorization method can be applied to a wide range of datasets to derive optimal categorical groupings and labels from psychophysical judgements of stimulus similarity.
| S-EPMC7900870 | biostudies-literature
Project description:Mammals are highly skilled in rapidly detecting objects in cluttered natural environments, a skill necessary for survival. What are the neural mechanisms mediating detection of objects in natural scenes? Here, we use human brain imaging to address the role of top-down preparatory processes in the detection of familiar object categories in real-world environments. Brain activity was measured while participants were preparing to detect highly variable depictions of people or cars in natural scenes that were new to the participants. The preparation to detect objects of the target category, in the absence of visual input, evoked activity patterns in visual cortex that resembled the response to actual exemplars of the target category. Importantly, the selectivity of multivoxel preparatory activity patterns in object-selective cortex (OSC) predicted target detection performance. By contrast, preparatory activity in early visual cortex (V1) was negatively related to search performance. Additional behavioral results suggested that the dissociation between OSC and V1 reflected the use of different search strategies, linking OSC preparatory activity to relatively abstract search preparation and V1 to more specific imagery-like preparation. Finally, whole-brain searchlight analyses revealed that, in addition to OSC, response patterns in medial prefrontal cortex distinguished the target categories based on the search cues alone, suggesting that this region may constitute a top-down source of preparatory activity observed in visual cortex. These results indicate that in naturalistic situations, when the precise visual characteristics of target objects are not known in advance, preparatory activity at higher levels of the visual hierarchy selectively mediates visual search.
| S-EPMC3141945 | biostudies-literature
Project description:When studying how people search for objects in scenes, the inhomogeneity of the visual field is often ignored. Due to physiological limitations, peripheral vision is blurred and mainly uses coarse-grained information (i.e., low spatial frequencies) for selecting saccade targets, whereas high-acuity central vision uses fine-grained information (i.e., high spatial frequencies) for analysis of details. Here we investigated how spatial frequencies and color affect object search in real-world scenes. Using gaze-contingent filters, we attenuated high or low frequencies in central or peripheral vision while viewers searched color or grayscale scenes. Results showed that peripheral filters and central high-pass filters hardly affected search accuracy, whereas accuracy dropped drastically with central low-pass filters. Peripheral filtering increased the time to localize the target by decreasing saccade amplitudes and increasing number and duration of fixations. The use of coarse-grained information in the periphery was limited to color scenes. Central filtering increased the time to verify target identity instead, especially with low-pass filters. We conclude that peripheral vision is critical for object localization and central vision is critical for object identification. Visual guidance during peripheral object localization is dominated by low-frequency color information, whereas high-frequency information, relatively independent of color, is most important for object identification in central vision.
| S-EPMC7424126 | biostudies-literature
Project description:Real-world events do not only provide temporally and spatially correlated information across the senses, but also semantic correspondences about object identity. Prior research has shown that object sounds can enhance detection, identification, and search performance of semantically consistent visual targets. However, these effects are always demonstrated in simple and stereotyped displays that lack ecological validity. In order to address identity-based cross-modal relationships in real-world scenarios, we designed a visual search task using complex, dynamic scenes. Participants searched for objects in video clips recorded from real-life scenes. Auditory cues, embedded in the background sounds, could be target-consistent, distracter-consistent, neutral, or just absent. We found that, in these naturalistic scenes, characteristic sounds improve visual search for task-relevant objects but fail to increase the salience of irrelevant distracters. Our findings generalize previous results on object-based cross-modal interactions with simple stimuli and shed light upon how audio-visual semantically congruent relationships play out in real-life contexts.
| S-EPMC6848886 | biostudies-literature
Project description:Perceptual load is a well-established determinant of attentional engagement in a task. So far, perceptual load has typically been manipulated by increasing either the number of task-relevant items or the perceptual processing demand (e.g. conjunction versus feature tasks). The tasks used often involved rather simple visual displays (e.g. letters or single objects). How can perceptual load be operationalized for richer, real-world images? A promising proxy is the visual complexity of an image. However, current predictive models for visual complexity have limited applicability to diverse real-world images. Here we modelled visual complexity using a deep convolutional neural network (CNN) trained to learn perceived ratings of visual complexity. We presented 53 observers with 4000 images from the PASCAL VOC dataset, obtaining 75 020 2-alternative forced choice paired comparisons across observers. Image visual complexity scores were obtained using the TrueSkill algorithm. A CNN with weights pre-trained on an object recognition task predicted complexity ratings with r = 0.83. By contrast, feature-based models used in the literature, working on image statistics such as entropy, edge density and JPEG compression ratio, only achieved r = 0.70. Thus, our model offers a promising method to quantify the perceptual load of real-world scenes through visual complexity.
| S-EPMC7277246 | biostudies-literature
Project description:In performing search tasks, the visual system encodes information across the visual field at a resolution inversely related to eccentricity and deploys saccades to place visually interesting targets upon the fovea, where resolution is highest. The serial process of fixation, punctuated by saccadic eye movements, continues until the desired target has been located. Loss of central vision restricts the ability to resolve the high spatial information of a target, interfering with this visual search process. We investigate oculomotor adaptations to central visual field loss with gaze-contingent artificial scotomas.Spatial distortions were placed at random locations in 25° square natural scenes. Gaze-contingent artificial central scotomas were updated at the screen rate (75 Hz) based on a 250 Hz eye tracker. Eight subjects searched the natural scene for the spatial distortion and indicated its location using a mouse-controlled cursor.As the central scotoma size increased, the mean search time increased [F(3,28) = 5.27, p = 0.05], and the spatial distribution of gaze points during fixation increased significantly along the x [F(3,28) = 6.33, p = 0.002] and y [F(3,28) = 3.32, p = 0.034] axes. Oculomotor patterns of fixation duration, saccade size, and saccade duration did not change significantly, regardless of scotoma size.There is limited automatic adaptation of the oculomotor system after simulated central vision loss.
| S-EPMC3432450 | biostudies-literature
Project description:Upward and downward motor actions influence subsequent and ongoing emotional processing in accordance with a space-valence metaphor: positive is up/negative is down. In this study, we examined whether upward and downward motor actions could also affect previous emotional processing. Participants were shown an emotional image on a touch screen. After the image disappeared, they were required to drag a centrally located dot towards a cued area, which was either in the upper or lower portion of the screen. They were then asked to rate the emotional valence of the image using a 7-point scale. We found that the emotional valence of the image was more positive when the cued area was located in the upper portion of the screen. However, this was the case only when the dragging action was required immediately after the image had disappeared. Our findings suggest that when somatic information that is metaphorically associated with an emotion is linked temporally with a visual event, retrospective emotional integration between the visual and somatic events occurs.
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Project description:Advances in digital technology mean that the creation of visually compelling photographic fakes is growing at an incredible speed. The prevalence of manipulated photos in our everyday lives invites an important, yet largely unanswered, question: Can people detect photo forgeries? Previous research using simple computer-generated stimuli suggests people are poor at detecting geometrical inconsistencies within a scene. We do not know, however, whether such limitations also apply to real-world scenes that contain common properties that the human visual system is attuned to processing. In two experiments we asked people to detect and locate manipulations within images of real-world scenes. Subjects demonstrated a limited ability to detect original and manipulated images. Furthermore, across both experiments, even when subjects correctly detected manipulated images, they were often unable to locate the manipulation. People's ability to detect manipulated images was positively correlated with the extent of disruption to the underlying structure of the pixels in the photo. We also explored whether manipulation type and individual differences were associated with people's ability to identify manipulations. Taken together, our findings show, for the first time, that people have poor ability to identify whether a real-world image is original or has been manipulated. The results have implications for professionals working with digital images in legal, media, and other domains.
| S-EPMC5514174 | biostudies-literature