State anticipation and task serialization attenuate embodied decision biases when deciding while moving.

We examined whether and how embodied decision biases-related to motor costs (MC) as well as cognitive crosstalk (CC) due to the body state-are influenced by extended deliberation time. Participants performed a tracking task while concurrently making reward-based decisions, with rewards being presented with varying preview time. In Experiment 1 (N = 58), we observed a reduced CC bias with extended preview time. Partially, this was due to participants slightly adapting tracking to serialize it in relation to decision making. However, the influence of MC was only marginal and not subject to anticipatory state adjustments. In Experiment 2 (N = 67), we examined whether participants integrated the immediate state at reward presentation or anticipated state when a decision could be implemented when adapting their tracking and decision behavior. Results were most compatible with the anticipated state being integrated. We conclude that humans anticipate the body state when a decision must be implemented and consider the corresponding motor and cognitive demands when adapting their decision behavior. However, anticipatory state adaptations targeting the influence of MC with extended preview time were absent, suggesting that anticipatory adaptations are starkly limited in low-practice tasks compared to more overlearned behavior like walking. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Where scrollbars are clicked, and why.

Scrolling is a widely used mean to interact with visual displays, usually to move content to a certain target location on the display. Understanding how user scroll might identify potentially suboptimal use and allows to infer users' intentions. In the present study, we examined where users click on a scrollbar depending on the intended scrolling action. In two online experiments, click positions were systematically adapted to the intended scrolling action. Click position selection could not be explained as strict optimization of the distance traveled with the cursor, memory load, or motor-cognitive factors. By contrast, for identical scrolling actions click positions strongly depended on the context and on previous scrolls. The behavior of our participants closely resembled behavior observed for manipulation of other physical devices and suggested a simple heuristic of movement planning. The results have implications for modeling human-computer interaction and may contribute to predicting user behavior.

Dual-tasking modulates movement speed but not value-based choices during walking.

Value-based decision-making often occurs in multitasking scenarios relying on both cognitive and motor processes. Yet, laboratory experiments often isolate these processes, thereby neglecting potential interactions. This isolated approach reveals a dichotomy: the cognitive process by which reward influences decision-making is capacity-limited, whereas the influence of motor cost is free of such constraints. If true, dual-tasking should predominantly impair reward processing but not affect the impact of motor costs. To test this hypothesis, we designed a decision-making task in which participants made choices to walk toward targets for rewards while navigating past an obstacle. The motor cost to reach these rewards varied in real-time. Participants either solely performed the decision-making task, or additionally performed a secondary pitch-recall task. Results revealed that while both reward and motor costs influenced decision-making, the secondary task did not affect these factors. Instead, dual-tasking slowed down participants' walking, thereby reducing the overall reward rate. Hence, contrary to the prediction that the added cognitive demand would affect the weighing of reward or motor cost differentially, these processes seem to be maintained at the expense of slowing down the motor system. This slowdown may be indicative of interference at the locomotor level, thereby underpinning motor-cognitive interactions during decision-making.

Embodied decision biases: individually stable across different tasks?

In everyday life, action and decision-making often run in parallel. Action-based models argue that action and decision-making strongly interact and, more specifically, that action can bias decision-making. This embodied decision bias is thought to originate from changes in motor costs and/or cognitive crosstalk. Recent research confirmed embodied decision biases for different tasks including walking and manual movements. Yet, whether such biases generalize within individuals across different tasks remains to be determined. To test this, we used two different decision-making tasks that have independently been shown to reliably produce embodied decision biases. In a within-participant design, participants performed two tasks in a counterbalanced fashion: (i) a walking paradigm for which it is known that motor costs systematically influence reward decisions, and (ii) a manual movement task in which motor costs and cognitive crosstalk have been shown to impact reward decisions. In both tasks, we successfully replicated the predicted embodied decision biases. However, there was no evidence that the strength of the biases correlated between tasks. Hence, our findings do not confirm that embodied decision biases transfer between tasks. Future research is needed to examine whether this lack of transfer may be due to different causes underlying the impact of motor costs on decisions and the impact of cognitive crosstalk or task-specific differences.

Embodied decisions during walking.

Research on embodied decision-making only recently started to examine whether and how concurrent actions influence value-based decisions. For instance, during walking humans preferably make decisions that align with a turn toward the side of their current swing leg, sometimes resulting in unfavorable choices (e.g., less reward). It is suggested that concurrent movements influence decision-making by coincidental changes in motor costs. If this is true, systematic manipulations of motor costs should bias decisions. To test this, participants had to accumulate rewards (i.e., points) by walking and turning toward left and right targets displaying rewards across three experiments. In experiments 1a and 1b, we manipulated the turning cost based on the current swing leg by applying different symmetric turning magnitudes (i.e., same angles for left and right targets). In experiment 2, we manipulated the turning cost by administering asymmetric turning magnitudes (i.e., different angles for left and right targets). Finally, in experiment 3, we increased the cost of walking by adding ankle weights. Altogether, the experiments support the claim that differences in motor costs influenced participants' decisions: experiments 1a and 1b revealed that the swing leg effect and stepping behavior were moderated by turning magnitude. In experiment 2, participants showed a preference for less costly, smaller turning magnitudes. Experiment 3 replicated the swing leg effect when motor costs were increased by means of ankle weights. In conclusion, these findings provide further evidence that value-based decisions during ongoing actions seem to be influenced by dynamically changing motor costs, thereby supporting the concept of "embodied decision-making."NEW & NOTEWORTHY Motor processes of concurrent movements have been shown to influence embodied decision-making. It is hypothesized that this is driven by coincidental changes in motor costs. We tested this claim by systematically manipulating motor costs of choice options during walking. In three experiments we show how variations in motor cost (e.g., turning angle or stepping constraints) bias decision-making, thereby supporting the concept of "embodied decision-making."

Deciding while moving: Cognitive interference biases value-based decisions.

When people act, they repeatedly have to make value-based decisions about the further course of actions. For example, when driving on the highway, they must decide whether to overtake other cars by changing lanes to arrive at their destination quicker; concurrently, they are required to stay on their momentary lane by controlling the steering wheel. Embodied choice models predict that concurrent action execution modulates value-based decisions. Here, we examined whether value-based decisions are influenced by a change of action costs and/or cognitive interference between concurrent actions and decision making. In a novel, computerized multilane tracking task paradigm, participants (N = 50) controlled a cursor moving on one of three horizontal lanes. During tracking (concurrent action), participants had to switch to other lanes to avoid obstacles or collect rewards (value-based decisions). The action costs associated with a lane switch depended on the cursor position relative to the currently tracked lane, and this relationship varied between conditions. Results showed that value-based lane switching decisions were biased by the cursor state. While this influence was partly attributed to minimizing action costs, a considerable part of the influence could be attributed to cognitive interference. Our findings provide further evidence for embodied choice models, showing that both cognitive interference as well as action costs bias value-based decisions.