Impaired effort allocation in schizophrenia

Abstract

Background and hypothesis: Effort allocation is a crucial component of amotivation in schizophrenia. This study investigates the hypothesis that schizophrenia is associated with impairments in dynamic cost/benefit decision-making processes.

Study design: We employed a modified version of the effort allocation task developed by Meyniel et al. (2013). Participants were asked to allocate effort during 30-s intervals to maximize their gains. We examined the effects of task difficulty and incentive levels on participants' effort allocation on a trial-by-trial basis.

Study results: Individuals with schizophrenia (N = 25) showed decreased capacity to adapt dynamically to task parameters, as compared to healthy controls (N = 25). (1) Both populations increased the duration of each effort based on difficulty. Only healthy controls decreased rest duration based on incentive. The magnitude of these adaptations was significantly decreased in people with schizophrenia (difficulty: d = 1.25, incentive: d = 0.91). (2) Both groups decreased effort re-initiations with increasing difficulty with significant differences in the magnitude of adaptation between groups. (3) Participants with schizophrenia spent less time exerting effort above the required threshold, resulting in lower overall gains compared to healthy controls (η² = 0.17).

Conclusions: Individuals with schizophrenia exhibit a selective impairment in effort-cost decision-making. This deficit may contribute to maladaptive behavior patterns characterized by suboptimal effort allocation and reduced goal-direct activities.

Keywords: Amotivation; Decision-making; Dynamic effort allocation; Negative symptoms; Schizophrenia.

Fig. 1

Description of the dynamic effort allocation task. A. Experimental Paradigm: Each trial began with a 2-s instruction screen displaying the incentive (a coin) and the difficulty level (as a percentage of maximal force). Participants had 30 s to accumulate as much money as possible by exerting effort using a manual dynamometer. A visual scale represented force levels, with the current trial's difficulty indicated on both sides and as a blue horizontal bar (70 % in the example). Gains were displayed and updated in real time (green text). When the subject exerted effort above the difficulty level, gains accumulated proportionally to the incentive level. The orange gauge represented the subject's real-time force. Between trials, participants had a break of 0 to 30 s. B. Data Analysis: The dynamometer force signal was extracted and epoched into effort/rest periods. The start and end of efforts were determined by sudden increases and decreases in the signal (see methods). The number of re-initiations was calculated by subtracting one from the total number of efforts. The duration of the signal above the difficulty level (circled part) corresponded to the rewarded effort duration.

Fig. 2

Single effort duration across difficulty and incentive conditions. A: Data are averaged per incentive levels. B: Data are averaged per difficulty levels. C. Plot of the interaction effect between group and difficulty on effort duration. Bars represent the effort duration difference between the highest difficulty (70 % of maximal force) and the lowest difficulty (60 % of the maximal force). D. Plot of the interaction effect between group and incentive on effort duration. Bars represent the effort duration difference between the highest incentive (2€) and the lowest incentive (20cts). The stars represent the p-value of the group difference between levels of difficulty and incentive. The intervals on the bars represent the standard error of the mean. ****: p < 0.0001; ***: p < 0.001; **: p < 0.01; *: p < 0.05; •: p < 0.1; ns: non-significant.

Fig. 3

Single rest duration and number of effort re-initiations across incentive and difficulty conditions. A. Data averaged per difficulty level. B. Interaction effect between group and incentive on rest duration. Bars represent the difference in rest duration between the highest (2€) and lowest (0.2€) incentive levels. Stars represent the p-value of the group difference between levels of difficulty and incentive. Error bars indicate the standard error of the mean. ****: p < 0.0001; ***: p < 0.001; *: p < 0.05; ns: non-significant. C: Data averaged per incentive level. D: Interaction effect between group and difficulty on the number of effort re-initiations. Bars represent the difference in the number of re-initiations between the highest (70 %) and lowest (60 %) difficulty levels. Stars represent the p-value of the group difference between levels of difficulty and incentive. Error bars indicate the standard error of the mean. ****: p < 0.0001; ***: p < 0.001; **: p < 0.01; *: p < 0.05; •: p < 0.1; ns: non-significant.

Fig. 4

Rewarded effort duration across difficulty and incentive conditions A: Data aggregated across difficulty and incentive levels. B. Interaction effect between group and difficulty on rewarded effort duration. Bars represent the difference in rewarded effort duration between the highest (70 %) and lowest (60 %) difficulty levels. C. Interaction effect between group and incentive on rewarded effort duration. Bars represent the difference in rewarded effort duration between the highest (2€) and lowest (0.2€) incentive levels. Stars represent the p-value of the group difference between levels of difficulty and incentive. Error bars indicate the standard error of the mean. ****: p < 0.0001; ***: p < 0.001; *: p < 0.05; ns: non-significant.