Characterization of reward and effort mechanisms in apathy

Abstract

Apathy is a common but poorly understood condition with a wide societal impact observed in several brain disorders as well as, to some extent, in the normal population. Hence the need for better characterization of the underlying mechanisms. The processes by which individuals decide to attribute physical effort to obtain rewards might be particularly relevant to relate to apathy traits. Here, we designed two paradigms to assess individual differences in physical effort production and effort-based decision-making and their relation to apathy in healthy people. Apathy scores were measured using a modified version of the Lille Apathy Rating Scale, suitable for use in a non-clinical population. In the first study, apathy scores were correlated with the degree to which stake (reward on offer) and difficulty level impacts on physical effort production. Individuals with relatively high apathy traits showed an increased modulation of effort while more motivated individuals generally exerted greater force across different levels of stake. To clarify the underlying mechanisms for this behavior, we designed a second task that allows independent titration of stake and effort levels for which subjects are willing to engage in an effortful response to obtain a reward. Our results suggest that apathy traits in the normal population are related to the way reward subjectively affects the estimation of effort costs, and more particularly manifest as decreased willingness to exert effort when rewards are small, or below threshold. The tasks we introduce here may provide useful tools to further investigate apathy in clinical populations.

Keywords: Action Initiation; Apathy; Decision-making; Effort discounting; Motivation.

Supplementary Fig. S1

Cued and reactive effects of difficulty level on motivation. A. Force exerted, expressed as percentage of MVC for difficult and easy trials when the difficulty cue is presented or not, and when response feedback is provided or not. B. Difficulty effect expressed as percentage change of force from difficult to easy trials. Cued difficulty effect (orange) was computed by comparing the force exerted on easy and difficult trials when cues were presented but no response feedback was provided. Reactive difficulty effect (yellow) was computed by comparing the force exerted on easy and difficult trials when cues were not presented but response feedback was on. C. Effects of difficult cue (red) and easy cue (green) expressed as percentage change of force relative to no cue conditions for trials with no response feedback (±SE).

Supplementary Fig. S2

Relation between apathy traits and task performance. A. Correlation between Action Initiation subscale of LARS-e and predictive difficulty effect (percentage force change from difficult to easy cue when no response feedback provided), B. reactive difficulty effect, and C. effect of difficult cue relative to when no cue is presented.

Fig. 1

Schematic representation of effort and reward-based decision-making. Objective external information on reward level offered and effort requirement are weighed against each other to produce subjective values, which vary across individuals. The output of this weighing process leads to the decision about whether the reward is worth the effort cost, or not.

Fig. 2

Experimental task used in Study 1. Participants were presented with a monetary reward cue (£1 or 10 pence – £0.1 – coin) and on two third of trials a difficulty level cue (Easy or Difficult) was presented. (A) Trial in which difficulty cue is presented with visual feedback of response (level of red bar). (B) Trial where only stake value is presented with no visual feedback of response (red bar full throughout). The order of stake and difficulty cues was counterbalanced across trials. The response period started with the presentation of a vertical bar on one side of the screen and participants had to squeeze the corresponding handgrip (C) to win a percentage of the money at stake. On half of the trials, response feedback was provided, in the form of a red level indicating the percentage of the stake that can be won with the current force exerted.

Fig. 3

Effect of stake, difficulty and response feedback on force exerted (index of motivation). Average response force, expressed as percentage of Maximum Voluntary Contraction (MVC) are plotted for the different stakes (£0.1 and £1) and the different difficulty levels (easy in green, difficult in red), for trials were response feedback was provided (solid lines) or not (dotted lines). Error bars represent standard errors.

Fig. 4

Relation between LARS-e scores and task performance. Relationship between LARS-e scores (higher scores = more motivated individuals) and mean of overall response force, expressed as percentage of MVC, across all trials.

Fig. 5

Relation between behavioral apathy and task performance. (A) Correlation between Action Initiation subscale of the LARS-e and effect of stake on change of response force (percentage change from £0.1 to £1) and (B) effect of difficulty on change of response force (percentage change from difficult to easy trials).

Fig. 6

High and low behavioral apathy group comparison Average response force, expressed as percentage of Maximum Voluntary Contraction (MVC) are plotted for the different stakes (£0.1 and £1) and the different difficulty levels (easy: solid line, difficult: dotted line), for participants with high (orange) and low (cyan) Action Initiation scores (lower scores mean more behavioral apathy). Error bars represent standard errors.

Fig. 7

Adaptive effort discounting task. Trials start with the presentation of an apple tree for 1.5 s. The number of apples in the tree represents the stake while the effort level is indicated by the trunk size and the level highlighted in yellow on the scale. This is followed by the presentation of the yes/no option at the bottom of the screen. Subjects can select the option corresponding to their choice by gently squeezing the correct response device. If the yes option is selected, the same tree reappears on the right or the left of the screen and participants have 3 s to squeeze using the corresponding hand. Subjects only win a percentage of the stake if they manage to reach or go beyond the top of the trunk. If the no option is selected, the next trial starts with the presentation of another tree (i.e. another offer with a different combination of stake and effort required to obtain it).

Fig. 8

Estimation of stake and effort Indifference Points A. Probability of agreeing to engage in an effortful response (‘yes’ choice) averaged across all participants plotted as a function of stake level for each different effort levels, represented in different colors (60–110% of Maximum Voluntary Contraction (MVC) shown in different colors). (B) Probability of making a ‘yes’ choice as a function of effort levels for each different stake, represented in different colors (1–15 apples) across all participants. Panels C and D show an example from one participant of the probabilities of ‘yes’ choices, fitted with logistic functions. E. For each Effort level, plot of Stake Indifference Points corresponding to the points for which the choice probability function is equal to 0.5 (i.e. 50% chance to respond yes). (F) Similarly, Effort Indifference Points are plotted for each stake levels based on choice probability functions for the different stakes. Note that some Indifference Points cannot be estimated, as the corresponding choice probability function never reaches 0.5.

Fig. 9

Correlations between Action Initiation scores and Effort Indifference Line characteristics. (A) Correlation with the intercept: more apathetic individuals (low AI scores) have lower intercept, which reflects a higher subjective estimation of effort cost for small rewards. (B) Correlation with the slope: more apathetic individuals have a steeper slope, which reflects a higher impact of reward on subjective effort costs.