The cone method: Inferring decision times from single-trial 3D movement trajectories in choice behavior

Ulbrich, Philipp; Gail, Alexander

doi:10.3758/s13428-021-01579-5

Cited by 3 publications

(3 citation statements)

References 30 publications

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“…Consequently, the animal shows a regular outward positioning to react to screens, limiting the visibility of face and limbs during the task epochs. As such, this task structure is not optimized for assessing reach and eye movements, therefore other design strategies could be added for tasks designed to study reaching and facial movements (Womelsdorf et al, 2021; Ulbrich and Gail, 2021; Möller et al, 2020; Hayden et al, 2022) Our use of touches on the screen, however, was effective at ensuring spatiotemporal and physical (vision and reach) points of alignment, each funneling into lower degrees of freedom than the full continuous behaviors would offer. This suggests that for predictable goals, the range of movements and poses has far fewer degrees of freedom and is therefore more tractable to analyze than random foraging and exploration.…”

Section: Discussionmentioning

confidence: 99%

Learning of object-in-context sequences in freely-moving macaques

Abbaspoor,

Rahman,

Zinke

et al. 2023

Preprint

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Flexible learning is a hallmark of primate cognition, which arises through interactions with changing environments. Studies of the neural basis for this flexibility are typically limited by laboratory settings that use minimal environmental cues and restrict interactions with the environment, including active sensing and exploration. To address this, we constructed a 3-D enclosure containing touchscreens on its walls, for studying cognition in freely moving macaques. To test flexible learning, two monkeys completed trials consisting of a regular sequence of object selections across four touchscreens. On each screen, the monkeys had to select by touching the sole correct object item (‘target’) among a set of four items, irrespective of their positions on the screen. Each item was the target on exactly one screen of the sequence, making correct performance conditioned on the spatiotemporal sequence rule across screens. Both monkeys successfully learned multiple 4-item sets (N=14 and 22 sets), totaling over 50 and 80 unique, conditional item-context memoranda, with no indication of capacity limits. The enclosure allowed freedom of movements leading up to and following the touchscreen interactions. To determine whether movement economy changed with learning, we reconstructed 3D position and movement dynamics using markerless tracking software and gyroscopic inertial measurements. Whereas general body positions remained consistent across repeated sequences, fine head movements varied as monkeys learned, within and across sequence sets, demonstrating learning set or “learning to learn”. These results demonstrate monkeys’ rapid, capacious, and flexible learning within an integrated, multisensory 3-D space. Furthermore, this approach enables the measurement of continuous behavior while ensuring precise experimental control and behavioral repetition of sequences over time. Overall, this approach harmonizes the design features that are needed for electrophysiological studies with tasks that showcase fully situated, flexible cognition.

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Section: Discussionmentioning

confidence: 99%

Learning of object-in-context sequences in freely-moving macaques

Abbaspoor,

Rahman,

Zinke

et al. 2023

Preprint

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“…Response times can be as fast as 100 ms for a pre-planned motor response (Scott, 2016) or as long as 700 ms when identifying emotions from a person's face (Nook et al, 2015). This "decide-then-act" paradigm has supplied a number of experiments used to study decision-making during motor actions, including motor lotteries (Adkins et al, 2021;Jarvstad et al, 2013;Nagengast et al, 2011;Neyedli & LeBlanc, 2017;Neyedli & Welsh, 2013, 2015Trommershäuser et al, 2008;Wu et al, 2009), reaching tasks (Cos et al, 2014;Enachescu et al, 2021;Gallivan et al, 2015;Gallivan et al, 2011;Ulbrich & Gail, 2021), foraging tasks (Diamond et al, 2017), and intercept tasks (Barany et al, 2020;Fooken & Spering, 2020;Michalski et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…We ask the question, at what point do the brain's time-sensitive processing capabilities limit the performance of rapid motor behaviours? One important consideration is that perceptual, decision-making, and motor processes interact and interfere with one another (Carroll et al, 2019;Künstler et al, 2018;Passingham, 1996;Raßbach et al, 2021;Scherbaum et al, 2015;Thura, 2020;Ulbrich & Gail, 2021). This interference effect has been explained by models that posit either a structural bottleneck or a shared pool of central resources that restrict the brain's processing capacity (Navon & Miller, 2002).…”

Section: Introductionmentioning

confidence: 99%

Capacity Limits Lead to Information Bottlenecks in Ongoing Rapid Motor Behaviors

Moulton

Rudie

Dukelow

et al. 2023

eNeuro

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Studies of ongoing, rapid motor behaviours have often focused on the decision-making implicit in the task. Here, we instead study how decision-making integrates with the perceptual and motor systems and propose a framework of limited-capacity, pipelined processing with flexible resources to understand rapid motor behaviours. Results from three experiments show that human performance is consistent with our framework: participants perform objectively worse as task difficulty increases and, surprisingly, this drop in performance is largest for the most skilled performers. As well, our analysis shows that the worst-performing participants can perform equally well under increased task demands, which is consistent with flexible neural resources being allocated to reduce bottleneck effects and improve overall performance. We conclude that capacity limits lead to information bottlenecks and that processes like attention help reduce the effects that these bottlenecks have on maximal performance.Significance StatementBehaviour results from perception, decision-making, and motor control. These processes can be modelled serially, but we must often decide about future actions in parallel with ongoing actions. We use computational models to demonstrate that simply perceiving, deciding, and moving in parallel inevitably produces performance-limiting interference. We see that the best performers in rapid motor behaviour tasks are counter-intuitively the most affected by increasing task demands, which is consistent with sharing attention between pipelined processes.

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Deciding While Acting—Mid-Movement Decisions Are More Strongly Affected by Action Probability than Reward Amount

Ulbrich

Gail

2023

eNeuro

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When deciding while acting, such as sequentially selecting targets during naturalistic foraging, movement trajectories reveal the dynamics of the unfolding decision process. Ongoing and planned actions may impact decisions in these situations in addition to expected reward outcomes. Here, we test how strongly humans weigh and how fast they integrate individual constituents of expected value, namely the prior probability of an action (PROB) and the prior expected reward amount associated with an action (AMNT), when deciding based on the combination of both together during an ongoing movement. Unlike other decision-making studies, we focus on PROB and AMNT priors, and not final evidence, in that correct actions were either instructed or could be chosen freely. This means, there was no decision-making under risk. We show that both priors gradually influence movement trajectories already before mid-movement instructions of the correct target and bias free-choice behavior. These effects were consistently stronger for PROB compared to AMNT priors. Participants biased their movements towards a high-PROB target, committed to it faster when instructed or freely chosen, and chose it more frequently even when it was associated with a lower AMNT prior than the alternative option. Despite these differences in effect magnitude, the time course of both priors’ effect on movement direction was highly similar. We conclude that prior action probability, and hence the associated possibility to plan actions accordingly, has higher behavioral relevance than prior action value for decisions that are expressed by adjusting already ongoing movements.Significance StatementNatural behavior, like foraging or hunting prey, requires animals and humans to select their next action during ongoing movements, thereby updating movements as the decision process unfolds. Here, we study the magnitude and time course with which prior action probability and prior expectancy of reward amount influence the selection between two competing movements in humans. By simultaneously but independently manipulating both priors in individual decisions, and by avoiding confounds of reward probability, we show that both priors affect the decision process with different magnitude yet comparable time courses. Our results emphasize the prioritized relevance of action probabilities over action values on mid-movement decisions.

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The cone method: Inferring decision times from single-trial 3D movement trajectories in choice behavior

Cited by 3 publications

References 30 publications

Learning of object-in-context sequences in freely-moving macaques

Learning of object-in-context sequences in freely-moving macaques

Capacity Limits Lead to Information Bottlenecks in Ongoing Rapid Motor Behaviors

Deciding While Acting—Mid-Movement Decisions Are More Strongly Affected by Action Probability than Reward Amount

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