What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control (original) (raw)
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Perceived effort for motor control and decision-making
PLoS biology, 2017
How effort is internally quantified and how it influences both movement generation and decisions between potential movements are 2 difficult questions to answer. Physical costs are known to influence motor control and decision-making, yet we lack a general, principled characterization of how the perception of effort operates across tasks and conditions. Morel and colleagues introduce an insightful approach to that end, assessing effort indifference points and presenting a quadratic law between perceived effort and force production.
Vigor of reaching movements: reward discounts the cost of effort
Journal of neurophysiology, 2018
Making a movement may be thought of as an economic decision in which one spends effort in order to acquire reward. Time discounts reward, which predicts that the magnitude of reward should affect movement vigor: we should move faster, spending greater effort, when there is greater reward at stake. Indeed, saccade peak velocities are greater and reaction-times are shorter when a target is paired with reward. Here, we focused on human reaching and asked whether movement kinematics were affected by expectation of reward. Participants made out-and-back reaching movements to one of four quadrants of a 14cm circle. During various periods of the experiment only one of the four quadrants was paired with reward, and the transition from reward to non-reward status of a quadrant occurred randomly. Our experiment design minimized dependence of reward on accuracy, granting the subjects wide latitude in self-selecting their movement speed, amplitude, and variability. When a quadrant was paired wi...
Rapid prediction of biomechanical costs during action decisions
Journal of Neurophysiology, 2014
228 words) 35 When given a choice between actions that yield the same reward, we tend to prefer the one that 36 requires the least effort. Recent studies have shown that humans are remarkably accurate at 37 evaluating the effort of potential reaching actions, and can predict the subtle energetic demand 38 caused by the non-isotropic biomechanical properties of the arm. Here, we investigated the 39 time course over which such information is computed and comes to influence decisions. Two 40 independent approaches were used. First, subjects performed a reach decision task in which the 41 time interval for deciding between two candidate reaching actions was varied from 200 to 42 800ms. Second, we measured motor-evoked potential (MEPs) to single pulse transcranial 43 magnetic stimulation (TMS) over the primary motor cortex (M1) to probe the evolving 44 decision at different times after stimulus presentation. Both studies yielded a consistent 45 conclusion: That a prediction of the effort associated with candidate movements is computed 46 very quickly and influences decisions within 200ms after presentation of the candidate actions. 47 Furthermore, while the MEPs measured 150ms after stimulus presentation were well correlated 48 with the choices that subjects ultimately made, later in the trial the MEP amplitudes were 49 primarily related to the muscular requirements of the chosen movement. This suggests that 50 corticospinal excitability (CSE) initially reflects a competition between candidate actions, and 51 later changes to reflect the processes of preparing to implement the winning action choice. 52 53
eneuro, 2021
It is widely assumed that we select actions we value the most. While the influence of rewards on decisionmaking has been extensively studied, evidence regarding the influence of motor costs is scarce. Specifically, how and when motor costs are integrated in the decision process is unclear. Twenty-two right-handed human participants performed a reward-based target selection task by reaching with their right arm toward one of two visual targets. Targets were positioned in different directions according to biomechanical preference, such that one target was systematically associated with a lower motor cost than the other. Only one of the two targets was rewarded, either in a congruent or incongruent manner with respect to the associated motor cost. A timed-response paradigm was used to manipulate participants' reaction times (RT). Results showed that when the rewarded target carried the highest motor cost, movements produced at short RT (,350 ms) were deviated toward the other (i.e., non-rewarded, low-cost (LC) target). In this context participants needed an additional 150-ms delay to reach the same percentage of rewarded trials as when the LC target was rewarded. Crucially, motor costs affected the total earnings of participants. These results demonstrate a robust interference of motor costs in a simple reward-based decision-making task. They point to the rapid and automatic integration of motor costs at an early stage of processing, potentially through the direct modulation of competing action representations in parieto-frontal regions. The progressive overcoming of this bias with increasing RT is likely achieved through top-down signaling pertaining to expected rewards.
Perception of effort reflects central motor command during movement execution
It is thought that perception of effort during physical tasks is the conscious awareness of the central motor command sent to the active muscles. The aim of this study was to directly test this hypothesis by experimentally varying perception of effort and measuring movement-related cortical potential (MRCP). Sixteen healthy, recreationally active men made unilateral dynamic elbow flexions to lift a light (20% one repetition maximum, 1RM) and a heavier (35% 1RM) weight with a fatigued arm and a nonfatigued arm while rating of perceived effort (RPE), biceps brachii electromyogram (EMG), and MRCP were recorded. RPE, EMG amplitude, and MRCP amplitude at Cz during weight raising increased with weight and with muscle fatigue. There was a significant correlation between RPE and MRCP amplitude at the vertex during the weight raising epoch. This study provides direct neurophysiological evidence that perception of effort correlates with central motor command during movement execution.
How do reaching and walking costs affect movement path selection?
Experimental Brain Research, 2018
Although reaching and walking are commonly coordinated, their coordination has been little studied. We investigated decision-making related to reaching and walking in connection with a recently discovered phenomenon called pre-crastination-the tendency to expend extra effort in the service of hastening goal or sub-goal completion. In the earlier studies where pre-crastination was discovered, participants decided which of two buckets to carry to the end of a walkway, picking the bucket they thought was easier. Surprisingly, the majority of participants chose to carry the bucket that was closer to the start position, which meant that the bucket they chose had to be carried farther than the bucket they did not choose. Here we inquired into participants' sensitivity to reaching effort and walking effort by varying how far participants had to reach to pick up a bucket, how heavy the bucket was, and how far participants had to walk with the bucket they chose. We found that participants were willing to lean and reach far to pick up an empty bucket that was a shorter walk from the start position. However, as reaching costs and carrying costs increased, participants prioritized shorter reaches over shorter walking distances. The results show that although pre-crastination is a robust tendency, there are limits to the kinds of costs people are willing to incur to complete sub-goals as soon as possible.
Motor Effort Alters Changes of Mind in Sensorimotor Decision Making
PLoS ONE, 2014
After committing to an action, a decision-maker can change their mind to revise the action. Such changes of mind can even occur when the stream of information that led to the action is curtailed at movement onset. This is explained by the time delays in sensory processing and motor planning which lead to a component at the end of the sensory stream that can only be processed after initiation. Such post-initiation processing can explain the pattern of changes of mind by asserting an accumulation of additional evidence to a criterion level, termed change-of-mind bound. Here we test the hypothesis that physical effort associated with the movement required to change one's mind affects the level of the change-of-mind bound and the time for post-initiation deliberation. We varied the effort required to change from one choice target to another in a reaching movement by varying the geometry of the choice targets or by applying a force field between the targets. We show that there is a reduction in the frequency of change of mind when the separation of the choice targets would require a larger excursion of the hand from the initial to the opposite choice. The reduction is best explained by an increase in the evidence required for changes of mind and a reduced time period of integration after the initial decision. Thus the criteria to revise an initial choice is sensitive to energetic costs.
2021
PURPOSE: The perception of effort (PE) is widely used to prescribe and monitor exercise during locomotor and resistance tasks. The present study examines the validity of PE to prescribe and monitor exercise during upper-limb motor tasks under various loads and speed requirements.METHODS: Forty participants volunteered in two experiments. In experiment 1, we used four PE intensities to prescribe exercise on a modified version of the box and block test (BBT) and a pointing task. We investigated the possibility of monitoring the exercise intensity by tracking changes in PE rating in response to three different tempos or additional weights. Experiment 2 replicated the possibility of prescribing the exercise with the PE intensity during the BBT and explored the impact of additional weights on performance and PE during the standardized version of the BBT. Muscle activation, heart rate and respiratory frequencies were recorded.RESULTS: In experiment 1, increasing the PE intensity to prescr...
Choosing the fastest movement: perceiving speed-accuracy tradeoffs
Experimental Brain Research, 2007
Several studies have shown that humans exhibit an intimate knowledge of prospective motor actions when imagining and planning movements. To probe this knowledge, we used a 2alternative forced-choice task to determine whether people are consistent with Fitts's law when choosing the movement they perceive to require the least movement time. We hypothesized that participants would choose the target with the lower Index of Difficulty with a probability greater than 0.5 in all situations. Participants performed almost perfectly when one of the targets was closer, wider, or both. Contrary to expectations, however, participants showed biases for close targets when one of the targets was closer and narrower. We argue that this pattern of behavior may result from a subjective representation of movement time that is based on both Fitts's law and the distance to the target, suggesting a preference for movements that are less effortful.
The cost of moving optimally: kinematic path selection
Journal of Neurophysiology, 2014
It is currently unclear whether the brain plans movement kinematics explicitly or whether movement paths arise implicitly through optimization of a cost function that takes into account control and/or dynamic variables. Several cost functions are proposed in the literature that are very different in nature (e.g., control effort, torque change, and jerk), yet each can predict common movement characteristics. We set out to disentangle predictions of the different variables using a combination of modeling and empirical studies. Subjects performed goal-directed arm movements in a force field (FF) in combination with visual perturbations of seen hand position. This FF was designed to have distinct optimal movements for muscle-input and dynamic costs while leaving kinematic cost unchanged. Visual perturbations in turn changed the kinematic cost but left the dynamic and muscle-input costs unchanged. An optimally controlled, physiologically realistic arm model was used to predict movements ...