The Experts below are selected from a list of 49152 Experts worldwide ranked by ideXlab platform
Gregor Schöner - One of the best experts on this subject based on the ideXlab platform.
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Scene memory and spatial inhibition in visual search : A neural dynamic process model and new Experimental evidence.
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
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Scene memory and spatial inhibition in visual search
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
Raul Grieben - One of the best experts on this subject based on the ideXlab platform.
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Scene memory and spatial inhibition in visual search : A neural dynamic process model and new Experimental evidence.
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
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Scene memory and spatial inhibition in visual search
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
Harald M Mohr - One of the best experts on this subject based on the ideXlab platform.
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neural adaptation to thin and fat bodies in the fusiform body area and middle occipital gyrus an fmri adaptation study
Human Brain Mapping, 2013Co-Authors: Dennis Hummel, Anne K Rudolf, Marieluise Brandi, Karlheinz Untch, Ralph Grabhorn, Harald Hampel, Harald M MohrAbstract:Visual perception can be strongly biased due to exposure to specific stimuli in the environment, often causing neural adaptation and visual aftereffects. In this study, we investigated whether adaptation to certain body shapes biases the perception of the own body shape. Furthermore, we aimed to evoke neural adaptation to certain body shapes. Participants completed a Behavioral Experiment (n = 14) to rate manipulated pictures of their own bodies after adaptation to demonstratively thin or fat pictures of their own bodies. The same stimuli were used in a second Experiment (n = 16) using functional magnetic resonance imaging (fMRI) adaptation. In the Behavioral Experiment, after adapting to a thin picture of the own body participants also judged a thinner than actual body picture to be the most realistic and vice versa, resembling a typical aftereffect. The fusiform body area (FBA) and the right middle occipital gyrus (rMOG) show neural adaptation to specific body shapes while the extrastriate body area (EBA) bilaterally does not. The rMOG cluster is highly selective for bodies and perhaps body parts. The findings of the Behavioral Experiment support the existence of a perceptual body shape aftereffect, resulting from a specific adaptation to thin and fat pictures of one's own body. The fMRI results imply that body shape adaptation occurs in the FBA and the rMOG. The role of the EBA in body shape processing remains unclear. The results are also discussed in the light of clinical body image disturbances.
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neural adaptation to thin and fat bodies in the fusiform body area and middle occipital gyrus an fmri adaptation study
Human Brain Mapping, 2013Co-Authors: Dennis Hummel, Anne K Rudolf, Marieluise Brandi, Karlheinz Untch, Ralph Grabhorn, Harald Hampel, Harald M MohrAbstract:Visual perception can be strongly biased due to exposure to specific stimuli in the environment, often causing neural adaptation and visual aftereffects. In this study, we investigated whether adaptation to certain body shapes biases the perception of the own body shape. Furthermore, we aimed to evoke neural adaptation to certain body shapes. Participants completed a Behavioral Experiment (n = 14) to rate manipulated pictures of their own bodies after adaptation to demonstratively thin or fat pictures of their own bodies. The same stimuli were used in a second Experiment (n = 16) using functional magnetic resonance imaging (fMRI) adaptation. In the Behavioral Experiment, after adapting to a thin picture of the own body participants also judged a thinner than actual body picture to be the most realistic and vice versa, resembling a typical aftereffect. The fusiform body area (FBA) and the right middle occipital gyrus (rMOG) show neural adaptation to specific body shapes while the extrastriate body area (EBA) bilaterally does not. The rMOG cluster is highly selective for bodies and perhaps body parts. The findings of the Behavioral Experiment support the existence of a perceptual body shape aftereffect, resulting from a specific adaptation to thin and fat pictures of one's own body. The fMRI results imply that body shape adaptation occurs in the FBA and the rMOG. The role of the EBA in body shape processing remains unclear. The results are also discussed in the light of clinical body image disturbances. Hum Brain Mapp 34:3233–3246, 2013. © 2012 Wiley Periodicals, Inc.
Jan Tekulve - One of the best experts on this subject based on the ideXlab platform.
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Scene memory and spatial inhibition in visual search : A neural dynamic process model and new Experimental evidence.
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
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Scene memory and spatial inhibition in visual search
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
Sebastian Schneegans - One of the best experts on this subject based on the ideXlab platform.
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Scene memory and spatial inhibition in visual search : A neural dynamic process model and new Experimental evidence.
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.
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Scene memory and spatial inhibition in visual search
Attention Perception & Psychophysics, 2020Co-Authors: Raul Grieben, Jonas Lins, Sebastian Schneegans, Jan Tekulve, Stephan K. U. Zibner, Gregor SchönerAbstract:Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a Behavioral Experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the Behavioral results. In a second Experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.