Society for NeuroScience - 2016

Abstract

Intro

A decision-making framework suggests that the goal of movement is to maximize utility, represented as the sum of the rewards obtained during movement minus the costs of the movement (i.e. effort). This framework would predict that movement characteristics, such as speed, are influenced by rewards obtained from movement as well as the effort required to complete it. Previous research shows that humans move faster towards more rewarding targets[1,2], but it is unknown how movement effort affects preferred speed. We examined the effect of increasing effort on reaching speed and metabolic cost. We added mass to the hand to test the hypothesis that movement speed decreases and metabolic cost increases with added mass.

Methods

In two experiments, we quantified the effect of mass on movement kinematics and metabolic cost. Seated subjects made horizontal reaching movements using a robotic handle. For the first experiment we recorded hand position as a function of time as subjects performed 10cm reaching movements from a central starting circle to one of four targets. Each subject performed reaches under four mass conditions (0, 3, 5, and 8 lbs) in a randomized order. For the second experiment we trained subjects to move at a given speed and measured metabolic cost for 10cm reaching movements to similar targets. Each subject performed reaches under four mass conditions (0, 5, 10, and 20 lbs) across 6 different speeds in a randomized order. We assessed the effect of added mass on movement kinematics and on metabolic cost using a linear mixed model.

Results

Mass decreased reaching speed (p$«$0.01) and increased reaction time (p«0.01). Increasing mass and increasing speed both increased metabolic cost of the reach (p«0.01). The increase in metabolic cost due to increasing effective mass was found to be sublinear (m^0.507). We computed optimal movement duration under increased effort using multiple models including a utility model \cite{shadmehr_representation_2016}. We find that metabolic cost alone cannot predict the preferred movement duration, but the utility model can. Maximizing utility as a function of movement duration allows us to further probe how reaching speed should change with added mass. The mass-based decrease in reaching speed results in longer movement durations on the outward reach which is predicted by our utility model. The model additionally predicts a diminishing return on movement duration as the effective mass of the arm increases. Our findings demonstrate that increased effort slows reaching movement, and this can be explained using a framework in which effort is represented as metabolic cost and discounted by time.

References

1. Xu-Wilson et al. (2009). The intrinsic value of visual information affects saccade velocities. Exp Brain Res 196: 475-481.
2. Summerside and Ahmed (2016). Reward feedback accelerates motor learning. Rocky Mountain American Society of Biomechanics.
3. Shadmehr et al. (2015). Effort, reward, and vigor in decision-making and motor control. Translational and Computational Motor Control.