Interactions between attention and visual working memory - Dr. Blaire Dube, Ohio State University
Published at : March 14, 2022
Interactions between attention and visual working memory: How their circuit supports behaviour, and what happens when it fails.
Dr. Blaire Dube, Ohio State University (08/03/2022)
Our visual environments are too complex to process in their entirety at one time. How do our minds extract the information we need to appropriately interact with these environments? Cognitive mechanisms like attention—our mechanism for selecting relevant visual information—and visual working memory (VWM)—our short-term visual storage system—interact with each other to prioritize the aspects of a visual scene that are most consistent with a behavioural goal. When crossing a busy street, for instance, attention prioritizes goal-relevant information (such as the locations of nearby vehicles and the colour of the traffic signal) for visual selection and, in turn, serves as a filter to VWM to ensure that only the most relevant information is encoded and used to guide subsequent behaviour (such as the decision to wait before crossing the street).
Across two themes in my talk, I will first discuss how attention and VWM interact flexibly to support behaviour, and then describe the consequences to behaviour when their interaction is interrupted. Specifically, in theme 1 I expand on the extant theory of how attention filters access to VWM, providing evidence that attention not only serves as a filter to VWM, but also flexibly and dynamically regulates how resources in VWM are distributed such that the most relevant information is remembered with the highest quality. That is, when trying to cross a busy street, not only are goal-relevant aspects of the scene prioritized for VWM encoding, but the most relevant aspects (the locations of the vehicles that are closest to you, for instance) are best remembered. While trying to cross this street, what happens if something particularly unexpected or salient, such as an ambulance, suddenly appears in view? We know a great deal about the consequences of distraction for spatial attention and response times: distractors capture spatial attention and increase the time it takes to make a behavioural response. We know very little, however, about its broader consequences. How does distraction affect control over the filters that support behaviour? I address this question in Theme 2, describing evidence that distraction causes attentional filters to break. Following attentional capture, not only is irrelevant information (such as the colour of a nearby pedestrian’s shirt, for instance) errantly selected and attended, but irrelevant distractor features also intrude into memory and can drive subsequent behaviour. I propose a novel Filter Disruption Theory to account for these findings and describe ideas for future related work.
Dr. Blaire Dube, Ohio State University (08/03/2022)
Our visual environments are too complex to process in their entirety at one time. How do our minds extract the information we need to appropriately interact with these environments? Cognitive mechanisms like attention—our mechanism for selecting relevant visual information—and visual working memory (VWM)—our short-term visual storage system—interact with each other to prioritize the aspects of a visual scene that are most consistent with a behavioural goal. When crossing a busy street, for instance, attention prioritizes goal-relevant information (such as the locations of nearby vehicles and the colour of the traffic signal) for visual selection and, in turn, serves as a filter to VWM to ensure that only the most relevant information is encoded and used to guide subsequent behaviour (such as the decision to wait before crossing the street).
Across two themes in my talk, I will first discuss how attention and VWM interact flexibly to support behaviour, and then describe the consequences to behaviour when their interaction is interrupted. Specifically, in theme 1 I expand on the extant theory of how attention filters access to VWM, providing evidence that attention not only serves as a filter to VWM, but also flexibly and dynamically regulates how resources in VWM are distributed such that the most relevant information is remembered with the highest quality. That is, when trying to cross a busy street, not only are goal-relevant aspects of the scene prioritized for VWM encoding, but the most relevant aspects (the locations of the vehicles that are closest to you, for instance) are best remembered. While trying to cross this street, what happens if something particularly unexpected or salient, such as an ambulance, suddenly appears in view? We know a great deal about the consequences of distraction for spatial attention and response times: distractors capture spatial attention and increase the time it takes to make a behavioural response. We know very little, however, about its broader consequences. How does distraction affect control over the filters that support behaviour? I address this question in Theme 2, describing evidence that distraction causes attentional filters to break. Following attentional capture, not only is irrelevant information (such as the colour of a nearby pedestrian’s shirt, for instance) errantly selected and attended, but irrelevant distractor features also intrude into memory and can drive subsequent behaviour. I propose a novel Filter Disruption Theory to account for these findings and describe ideas for future related work.
Interactionsbetweenattention