Parallel specification of competing sensorimotor control policies for alternative action options

Gallivan, Jason P.; Logan, Lindsey; Wolpert, Daniel M.; Flanagan, J. Randall

doi:10.1038/nn.4214

Cited by 114 publications

(100 citation statements)

References 58 publications

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“…Results from the co-optimization experiments support this claim since individuals exhibited faster reaction and movement times on trials in which the co-optimized wrist posture was selected versus trials in which it was not selected. 95,96 Action-based models are also consistent with many experiments regarding how motor-related costs factor into decision making. Cos et al 97,98 provide compelling support for action-based models by showing that when individuals make free choices between two potential reaching movements, which vary in motor-related costs (e.g., energy, stability, distance, etc.…”

Section: Behaviorsupporting

confidence: 67%

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Models, movements, and minds: bridging the gap between decision making and action

Wispinski

Gallivan

Chapman

2018

Annals of the New York Academy of Sciences

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Decision making is a fundamental cognitive function, which not only determines our day‐to‐day choices but also shapes the trajectories of our movements, our lives, and our societies. While immense progress has been made in recent years on our understanding of the mechanisms underlying decision making, research on this topic is still largely split into two halves. Good‐based models largely state that decisions are made between representations of abstract value associated with available options; while action‐based models largely state that decisions are made at the level of action representations. These models are further divided between those that state that a decision is made before an action is specified, and those that regard decision making as an evolving process that continues until movement completion. Here, we review computational models, behavioral findings, and results from neural recordings associated with these frameworks. In synthesizing this literature, we submit that decision making is best understood as a continuous, graded, and distributed process that traverses a landscape of behaviorally relevant options, from their presentation until movement completion. Identifying and understanding the intimate links between decision making and action processing has important implications for the study of complex, goal‐directed behaviors such as social communication, and for elucidating the underlying mechanisms by which decisions are formed.

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Section: Behaviorsupporting

confidence: 67%

“…). Results from the co‐optimization experiments support this claim since individuals exhibited faster reaction and movement times on trials in which the co‐optimized wrist posture was selected versus trials in which it was not selected …”

Section: Action‐based Models: From Reaction Time To End Of Movementmentioning

confidence: 76%

Models, movements, and minds: bridging the gap between decision making and action

Wispinski

Gallivan

Chapman

2018

Annals of the New York Academy of Sciences

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“…In particular, the findings underscore that the goal of attention is to ensure we act upon the right object at any given moment, and that capacity limits in attention reflect physical constraints imposed by the number of actions that can be performed coherently on an object at a time (Humphreys et al, 2013). Whether real objects trigger a greater number of competing action plans than images, or whether these plans and their associated feedback gains are stronger, more highly elaborated (Gallivan, Logan, Wolpert, & Flanagan, 2016), or temporally distinct, awaits further investigation. Our data from adults align with studies showing that children habituate differently (Gerhard, Culham, & Schwarzer, 2016) and maintain fixation longer (Mustafar, De Luna, & Rainer, 2015) upon real objects versus matched 2D images, and add to an emerging literature showing that cognitive processes such as object recognition (Chainay & Humphreys, 2001; Humphrey et al, 1994), memory (Snow et al, 2014) and decision-making (Bushong et al, 2010; Mischel & Moore, 1973), as well as neural responses (Snow et al, 2014), differ between real objects versus 2D images.…”

Section: Discussionmentioning

confidence: 99%

Graspable Objects Grab Attention More Than Images Do

2017

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The opportunity an object presents for action is known as an ‘affordance’. A basic assumption in previous research is that images of objects, which do not afford physical action, elicit effects on attention and behavior comparable to that of real-world tangible objects. Using a flanker task, we compared interference effects between real graspable objects versus matched two-dimensional (2D) or three-dimensional (3D) images of the items. Compared to both 2D and 3D images, real objects slowed response times overall and elicited greater flanker interference effects. When the real objects were positioned out of reach, or behind a transparent barrier, the pattern of RTs and interference effects was comparable to 2D images. Graspable objects exert a more powerful influence on attention and manual responses than images due to the affordances they offer for manual interaction. These results raise questions about whether images are suitable proxies for real objects in psychological research.

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“…This perspective has gained renewed support from recent work on action planning, which suggests that the action system continually prepares multiple, parallel plans that are appropriate for the environment (3,4). If this view is correct, then sensory systems should be routinely engaged in identifying the potential of the environment for action, and they should explicitly and automatically encode these action affordances.…”

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confidence: 99%

Coding of navigational affordances in the human visual system

Bonner

Epstein

2017

Proc. Natl. Acad. Sci. U.S.A.

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A central component of spatial navigation is determining where one can and cannot go in the immediate environment. We used fMRI to test the hypothesis that the human visual system solves this problem by automatically identifying the navigational affordances of the local scene. Multivoxel pattern analyses showed that a scene-selective region of dorsal occipitoparietal cortex, known as the occipital place area, represents pathways for movement in scenes in a manner that is tolerant to variability in other visual features. These effects were found in two experiments: One using tightly controlled artificial environments as stimuli, the other using a diverse set of complex, natural scenes. A reconstruction analysis demonstrated that the population codes of the occipital place area could be used to predict the affordances of novel scenes. Taken together, these results reveal a previously unknown mechanism for perceiving the affordance structure of navigable space.scene-selective visual cortex | occipital place area | affordances | navigation | dorsal stream I t has long been hypothesized that perceptual systems are optimized for the processing of features that afford ecologically important behaviors (1, 2). This perspective has gained renewed support from recent work on action planning, which suggests that the action system continually prepares multiple, parallel plans that are appropriate for the environment (3, 4). If this view is correct, then sensory systems should be routinely engaged in identifying the potential of the environment for action, and they should explicitly and automatically encode these action affordances. Here we explore this idea for spatial navigation, a behavior that is essential for survival and ubiquitous among mobile organisms.A critical component of spatial navigation is the ability to understand where one can and cannot go in the local environment: for example, knowing that one can exit a room through a corridor or a doorway but not through a window or a painting on the wall. We reasoned that if perceptual systems routinely extract the parameters of the environment that delimit potential actions, then these navigational affordances should be automatically encoded during scene perception, even when subjects are not engaged in a navigational task.Previous work has shown that observers can determine the overall navigability of a scene-for example, whether it is possible to move through the scene or not-from a brief glance (5). However, no study has examined the coding of fine-grained navigational affordances, such as whether the direction one can move in the scene is to the left or to the right. Furthermore, only recently have investigators begun to characterize the affordance properties of scenes, and this work has focused not on navigational affordances but on more abstract behavioral events that can be used to define scene categories, such as cooking and sleeping (6). It therefore remains unknown whether navigational affordances play a fundamental role in the perception of visual scenes, an...

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Parallel specification of competing sensorimotor control policies for alternative action options

Cited by 114 publications

References 58 publications

Models, movements, and minds: bridging the gap between decision making and action

Models, movements, and minds: bridging the gap between decision making and action

Graspable Objects Grab Attention More Than Images Do

Coding of navigational affordances in the human visual system

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