Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia, 2009, Treadway et al

Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia

Abstract
Background
Of the putative psychopathological endophenotypes in major depressive disorder (MDD), the anhedonic subtype is particularly well supported. Anhedonia is generally assumed to reflect aberrant motivation and reward responsivity. However, research has been limited by a lack of objective measures of reward motivation. We present the Effort-Expenditure for Rewards Task (EEfRT or “effort”), a novel behavioral paradigm as a means of exploring effort-based decision-making in humans. Using the EEfRT, we test the hypothesis that effort-based decision-making is related to trait anhedonia.

Methods/Results
61 undergraduate students participated in the experiment. Subjects completed self-report measures of mood and trait anhedonia, and completed the EEfRT. Across multiple analyses, we found a significant inverse relationship between anhedonia and willingness to expend effort for rewards.

Conclusions
These findings suggest that anhedonia is specifically associated with decreased motivation for rewards, and provide initial validation for the EEfRT as a laboratory-based behavioral measure of reward motivation and effort-based decision-making in humans.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2720457/

 

Posted this since this is the paper on which the "effort test" in the Intramural study is based on and an own thread seems sensible to me.

 

Following studies have also used the ‘EEfRT’ (the first study listed here by Ohmann et al should be of particular interest and @bobbler has already highlighted some interesting quotes from that study in the intramural study thread)

Analysing the EEfRT:
Examining the reliability and validity of two versions of the Effort-Expenditure for Rewards Task (EEfRT) (Ohmann et al, 2022)

General studies:
Parabolic discounting of monetary rewards by physical effort (Hartmann et al, 2013) (uses a modified approach)
Effect of failure/success feedback and the moderating influence of personality on reward motivation (Treadway et al, 2014)
Asymmetric frontal cortical activity predicts effort expenditure for reward (Hughes et al, 2014)
Trait Anticipatory Pleasure Predicts Effort Expenditure for Reward (Treadway et al, 2015)
Effort valuation and psychopathology in children and adults (Nguyen et al, 2019)
Exploring approach motivation: Correlating self-report, frontal asymmetry, and performance in the Effort Expenditure for Rewards Task (Hillmann et al, 2020)

Schizophrenia:
Incentive motivation deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making (Ferhava et al, 2013)
Effort, anhedonia, and function in schizophrenia: Reduced effort allocation predicts amotivation and functional impairment (Treadway et al, 2014)
Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: Part 1—Psychometric Characteristics of 5 Paradigms (Treadway et al, 2015)
Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: Part 2—External Validity and Correlates
(Treadway et al, 2015)
Apathy But Not Diminished Expression in Schizophrenia Is Associated With Discounting of Monetary Rewards by Physical Effort (Hartmann et al, 2015)
Inefficient effort allocation and negative symptoms in individuals with schizophrenia (Treadway et al, 2016)
Neural substrates of the impaired effort expenditure decision making in schizophrenia (Jia et al, 2016)

Psychosis:
Effort-based decision-making impairment in patients with clinically-stabilized first-episode psychosis and its relationship with amotivation and psychosocial functioning (Treadway et al, 2019)

Depression:
Effort-based decision-making in major depressive disorder: A translational model of motivational anhedonia (Treadway et al, 2012)
Motivational deficits in effort-based decision making in individuals with subsyndromal depression, first-episode and remitted depression patients (Yang et al, 2014)

Autism:
Adults with autism spectrum disorders exhibit decreased sensitivity to reward parameters when making effort-based decisions (Treadway et al, 2012)

Treatment/Drug trials:
Amping Up Effort: Effects of d-Amphetamine on Human Effort-Based Decision-Making (Treadway et al, 2011)
Left frontal anodal tDCS increases approach motivation depending on reward attributes (Ohmann et al, 2018)
A low dosage of the dopamine D2-receptor antagonist sulpiride affects effort allocation for reward regardless of trait extraversion (Ohmann et al, 2020)


This list is divided into different focal points and the papers are listed chronologically within each category. I will update this list if other studies show to be relevant.

 

To have a very rough overview and a comparison of the sample size Walitt uses to that of other studies, below is some very brief information of the various publications (HCs=Healthy Controls).

The original study:

Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia
Sample size: 61 HCs

Analysing the EEfRT:

Examining the reliability and validity of two versions of the Effort-Expenditure for Rewards Task (EEfRT) (Ohmann et al, 2022)
Sample size: 120 HCs for one experiment, 394 HCs for one experiment

“In Study 1, we tested 120 healthy participants to directly compare two versions of the EEfRT. In Study 2, we tested a larger sample of 394 healthy participants to further examine the original EEfRT…Our results indicate complex and sometimes inconsistent relations between different personality traits, task properties, and reward attributes.”

General studies:

Parabolic discounting of monetary rewards by physical effort (Hartmann et al, 2013) (uses a modified approach)
Sample size: 24 HCs

"Three different models in a binary choice task in which human participants had to squeeze a handgrip to earn monetary rewards: a linear, a hyperbolic, and a parabolic model. Participants repeatedly chose between a no effort/low reward and a high effort/high reward option. Consider the example of adding weight during a weight-lifting competition: The hyperbolic model predicts that adding 1 kg has a stronger impact on subjective experience at the beginning of the competition, when the lifters are well below their individual maximum. By contrast, the parabolic model predicts that the impact of adding 1 kg is larger toward the end of the competition, when lifters are close to their individual maximum and the linear model predicts the impact to be the same in both cases."

“The parabolic model clearly outperformed the other models on both the group and the individual level.”

This discussion might be of interest to people with ME/CFS and it isn’t a priori clear to me which model would be best suited for a fatiguing disease in which people pace. Other studies have suggested that “Hand fatigue is suggested to occur across the 20-min EEfRT, as HE choice selection statistically decreases with trial number across the session (Hughes et al., 2015; Ohmann et al., 2018; Treadway et al., 2009).”



Effect of failure/success feedback and the moderating influence of personality on reward motivation (Treadway et al, 2014)
Sample size: 131 HCs

“Results indicate that participants who received failure feedback relied more strongly on the reward magnitude when choosing whether to exert greater effort to obtain larger rewards, though this effect only held under conditions of significant uncertainty about whether the effort would be rewarded.”

In the intramural study more pwME receive failure feedback on the hard task. It might be worth looking at the above study.



Asymmetric frontal cortical activity predicts effort expenditure for reward (Hughes et al, 2014)
Sample size: 55 HCs

Interestingly the equipment failed here for one participant and they still included this person “The task ran for 20 min in which participants completed as many trials as possible, and the minimum number of trials completed by all participants during this time (46) was included in analyses. One participant completed only 23 trials due to equipment failure; however, their data were included in final analyses because preliminary investigation revealed that it did not significantly impact results.”

In this study gender didn’t affect results “Gender, age and experimenter were all non-significant predictors of task choice.” The also used a GEE model “A preliminary GEE model examined the effects of reward magnitude, reward probability, expected value (the magnitude × probability interaction), trial number (i.e. position of the trial in the sequence of 46 trials), gender, age and experimenter on task difficulty choice (see Model 1 in Table 1). Experimenter was included as a covariate because data collection was split between three researchers. Reward magnitude was converted to a categorical variable with three levels: low (<$2.30), medium ($2.31–$3.29) and high (>$3.30).”



Trait Anticipatory Pleasure Predicts Effort Expenditure for Reward (Treadway et al, 2015)
Sample size: 97 HCs

It seems that in this trial, to reduce the risk of certain strategies participants were given wrong information of the setup before starting to play “During verbal instruction, participants were informed that the EEfRT would run for 20 min and they would be paid 10% of their total winnings at the end of the experiment (M = $5.86, SD = 0.47). We modeled the likelihood of choosing the hard-task (vs. the easy-task) using generalized estimating equations (GEE) [55].”

They also performed an “EEfRT—manipulation check.”

Three people had invalid data “Valid EEfRT data were not obtained from three participants due to two instances of computer failure and one of noncompliance.” I’m not sure what noncompliance means but they do specify that “All remaining participants (n = 94) chose a mixture of easy- and hard-tasks throughout the EEfRT (hard-task proportion M = .53, SD = .14), at a high completion rate (M = 99.4%).”

Another thing that was done was “The total number of completed trials varied because participants performed the EEfRT for the same length of time (20 min) but differed in their profile of choices (range = 43 to 68, M = 54.79). For consistency, we analyzed only the first 43 trials completed by all participants.”

They clearly state “There was also a significant negative effect of trial number, which is routinely observed in studies using the EEfRT [47,48], potentially reflecting a fatigue effect.”



Effort valuation and psychopathology in children and adults (Nguyen et al, 2019)
Sample size: 1215 children, 1044 adults (their parents)

“In children, significant interactions between reward sensitivity and sex were observed in association with anxiety and thought problems, specifically at low reward sensitivity levels. In adults, main effects of effort expenditure were seen in drug and alcohol abuse, where higher effort was associated with higher degrees of abuse.”

Since this is a large trial the population level averages might be more accurate.

“For the adult participant population, average proportion of hard task choices was 36.76%, and the average reward sensitivity beta- weight was 0.765. Mean percent completion rate among adults was 93.47%. On average, adult participants timed out in their choice of the hard v. easy task in 5.90% of trials. For the child participant population, average proportion of hard task choices was 58.34%, and the average reward sensitivity betaweight was 0.118. Mean percent completion rate among children was 87.27%. On average, child participants timed out in their choice of the hard v. easy task in 1.38% of trials.”

“For the adult participant population, average proportion of hard task choices was 36.76%, and the average reward sensitivity beta- weight was 0.765. Mean percent completion rate among adults was 93.47%. On average, adult participants timed out in their choice of the hard v. easy task in 5.90% of trials. For the child participant population, average proportion of hard task choices was 58.34%, and the average reward sensitivity betaweight was 0.118. Mean percent completion rate among children was 87.27%. On average, child participants timed out in their choice of the hard v. easy task in 1.38% of trials. “

“These results suggest that dysfunction in effort valuation may be a contributing factor rather than a driving force for a range of psychopathology and impairment in children and adults.”

They also have data on “Somatic Problems” if this is what Walitt proposes one may want to look into this data.



Exploring approach motivation: Correlating self-report, frontal asymmetry, and performance in the Effort Expenditure for Rewards Task (Hillmann et al, 2020)
Sample size: 49 HCs

This study tries to build upon the earlier study Asymmetric frontal cortical activity predicts effort expenditure for reward (Hughes et al, 2014) et al from this list. They seem to not be able to reproduce those results from what I’ve gathered which once again shows the fragility of this method “Our third prediction was that higher LFA would correlate to higher trial completion rates and higher % HE trial selection in the EEfRT. As shown in Table 5, resting-state LFA did not correlate to performance variables in the 20-min EEfRT. There were, however, significant correlations between task-state LFA and EEfRT performance.”

 

Above list continued...

Schizophrenia:

Incentive motivation deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making (Ferhava et al, 2013)
Sample size: 16 SCZ patients, 16 matched HCs

“Patients opted to expend greater effort significantly less than controls for trials of high, but uncertain (i.e. 50% and 88% probability) incentive value, which was related to amotivation and neuro- cognitive deficits. Other abnormalities were also noted but were related to different clinical variables such as impulsivity (low reward and 12% probability). These motivational deficits were not due to group differences in reward learning, reward valuation or hedonic capacity.”

This trial has a very similar sample size as the intramural study. They however modified their setup as follows “Importantly, the maximum number of button presses for both the easy and hard trials was individually determined before the task. For this, subjects completed 4 trials with each hand where they were instructed to press the respective key as many times as possible. The trial with the lowest number of button presses was discarded, and the maximum button press rate was calculated as the mean from the remaining 3 trials. The button press criterion used in the actual task was individually set at 90% of the subject’s calculated maximum rate. This manipulation was done to control for non-specific differences in motoric ability between groups, and to assure that each individual had the capacity to complete the trials.“ They also decided on “To rule out potential fatigue effects, analyses were repeated including only the first 30 trials completed, and the findings were unchanged (data not shown). “

One will have to look at the actual data, but that might have been a better setup (of course it still doesn’t account for fatiguability).

On excluding participants the authors note “Three SCZ and one control participant failed to meet the reward learning criterion. The significant group differences of willingness to expend effort remained so, even when these individuals were excluded from the analysis for both 50% (F1,26 1⁄4 12.47, p 1⁄4 0.002), and 88% high-reward trials (F1,26 1⁄4 5.40, p 1⁄4 0.03). The group difference during low-reward 12% trials also remained (F1,26 1⁄4 4.33, p 1⁄4 0.05).”



Effort, anhedonia, and function in schizophrenia: Reduced effort allocation predicts amotivation and functional impairment (Treadway et al, 2014)
Sample size: 59 SCZ patients, 39 matched HCs (referred to as CON)

“In controls, the frequency of choosing the hard task in high reward magnitude and probability conditions was negatively correlated with depression severity and anhedonia. In schizophrenia, fewer hard task choices were associated with more severe negative symptoms and worse community and work function as assessed by a caretaker. “

“We eliminated the 12% probability level used in the original version of this task because it elicited a relatively low level of hard task choice even in healthy individuals (Treadway et al., 2009). “

They also estimated whether participants were able to complete tasks “It is possible that an individual's ability to complete the 100 finger presses within the requisite time might influence their willingness to choose the hard task option. Thus, each participant also completed an assessment of the number of presses tbey could make with their nondominant pinky within 15 s. Each person completed three trials, with the average used as an estimate of finger tapping speed.”

They also looked at the effects that your abilities on completing tasks had on the results “The SCZ (M = 92.4, SD = 11.8) were significantly less likely than CON (M = 98.7, SD = 2.4) to successfully complete trials, t(96) = 3.30, p < .001, though the rate of completion was above 90% for both groups. There was no significant correlation between the number of successfully completed trials and the likelihood of choosing the hard task among CON (r = -.09, p = .60) or SCZ (r = - . 0 5 , p = .70).” They also found that the finger tapping rate had no effect on choosing a hard task “no significant correlafion between finger tapping and the likelihood of choosing the hard task among CON (r = .12, p = .45) or SCZ (/- = .07, p = .59). “

So here both groups complete trials at a rate of above 90%, it would be interesting to see what the differences are for only the hard trials.




Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: Part 1—Psychometric Characteristics of 5 Paradigms (Treadway et al, 2015)
Sample size: 94 SCZ patients, 40 HCs; the EEfRT was applied twice to the SCZ group (baseline, 4-week retest)

They once again removed the 12% probability level and included an individual calibration phase to try to control for the effort required to complete the task “The individual calibration phase precedes the practice rounds and choice trials.”.

“We conducted all analyses with the entire sample included, and then reanalyzed the data with the all-hard inflexible responders excluded. The focus on the all-hard responses was because they are more problematic for clinical trials: if they are performing at the maximum level of motivation at baseline there is no room for improvement. The results remained largely unchanged after excluding the all-hard inflexible responders, thus the entire sample was retained for the primary analyses.”



Effort-Based Decision-Making Paradigms for Clinical Trials in Schizophrenia: Part 2—External Validity and Correlates (Treadway et al, 2015)
Provides a further analyses to the study described above (Part 1).



Apathy But Not Diminished Expression in Schizophrenia Is Associated With Discounting of Monetary Rewards by Physical Effort (Hartmann et al, 2015)
Sample size: 31 SCZ patients, 20 HCs

Doesn’t use the EEfRT but uses a handgrip test. This actually seems like a good approach to me in ME/CFS because one could appropriately reduce the necessary strength required as the test goes on according to the fatiguability of patients.



Inefficient effort allocation and negative symptoms in individuals with schizophrenia (Treadway et al, 2016)
Sample size: 48 SCZ patients, 27 HCs

Once again it seems the results are not consistent with previous literature.

“Contrary to expectations, in individuals with schizophrenia, greater negative symptoms were associated with making more effortful choices“. “Our results are consistent with prior findings that revealed a pattern of inefficient decision making in individuals with schizophrenia relative to healthy controls. However the results did not support the hypothesized association of negative symptoms and reduced effort in schizophrenia and highlight prior inconsistencies in this literature.”

“The main effect of group was significant in that the control group displayed greater effort (proportion of hard tasks chosen) than the schizophrenia group on the EEfRT, χ2(1) = 21.05, p b .001.”

The interpretation is quite interesting. Essentially as they argue that HCs had a better strategy which indicates something is wrong in SCZ . “Thus, individuals with schizophrenia displayed inefficient effort allocation for trials in which it would be most advantageous to put forth more effort, as well as trials when it would appear strategic to conserve effort.”

From what I’ve seen this is an opposite argument than in the intramural study. Furthermore the person that was excluded in the intramural study would serve as a “better HC” in this study.



Neural substrates of the impaired effort expenditure decision making in schizophrenia (Jia et al, 2016)
Sample size: 23 SCZ patients and 23 matched HCs

This study includes an fMRI during EEfRT, to make it more compatible with an fMRI they modified the EEfRT. The also modified the approach to reduce fatigueing effects "We reduced the effects of fatigue by reducing the number of button presses".


“SCZ patients were significantly less likely to expend high level of effort in the medium (50%) and high (80%) probability conditions than healthy controls. The neural response in the NAcc, the posterior cingulate gyrus and the left medial frontal gyrus in SCZ patients were weaker than healthy controls and did not linearly increase with an increase in reward magnitude and probability. Moreover, NAcc activity was positively correlated with the willingness to expend high-level effort and concrete consummatory pleasure experience. Conclusion: NAcc and posterior cingulate dysfunctions in SCZ patients may be involved in their impaired effort expenditure decision-making. “

 

Psychosis:

Effort-based decision-making impairment in patients with clinically-stabilized first-episode psychosis and its relationship with amotivation and psychosocial functioning (Treadway et al, 2019)
Sample size: 45 first-episode psychosis (FEP) patients and 45 matched HCs

It seems Walitt et al might have taken some inspiration from this study.

“Previous research has identified altered effort allocation in chronic schizophrenia, but produced mixed results regarding its relationship with amotivation. No study has investigated effort allocation in first-episode psychosis (FEP)”…”Our results showed that FEP patients did not demonstrate overall reduction in effort expenditure but displayed reduced willingness to expend effort for high-value/high- probability reward as compared to controls. In particular, such selective effort-related impairment was most pronounced in patients with high levels of amotivation. Furthermore, reduced allocation of greater effort for higher probability reward was related to poorer psychosocial functioning. Decreased effort exertion was generally unrelated to other symptom dimensions, self-report anhedonia, antipsychotic dose and cognitive deficits. This study thus provides the first evidence of effort-based decision-making impairment in FEP, and indicates that first-episode patients were not generally effort-averse but exhibited inefficient effort allocation by failing to make high-effort choices to maximize reward receipt. Our findings affirm the critical role of amotivation on aberrant effort allocation, and support the link between laboratory-based effort-cost measures and real-world psychosocial functioning in medicated FEP. Further longitudinal research is required to clarify trajectory of suboptimal effort allocation and its potential utility in predicting amotivation and functional outcomes in the early course of illness.”

It seems patients didn’t have problems completing high-effort trials “Patients completed fewer trials (FEP: 43.5; HC: 48.2; t88 =2.89, p = 0.01) than controls, but the proportion of completed trials did not significantly correlate with the percentage of high-effort trials selected in both patient (p=0.23) and control (p=0.16) groups.”



Depression:
Effort-based decision-making in major depressive disorder: A translational model of motivational anhedonia (Treadway et al, 2012)
Sample size: 20 MDD patients and 15 HCs

Looks like a sort of follow-up study of the original work including a control group.

“Here, we provide data from a study in MDD patients and healthy controls using a translational measure of reward motivation, the Effort Expenditure for Rewards Task (EEfRT or “effort”). This task offers subjects a series of trials where they may choose to expend more or less effort for the opportunity to win varying amounts of monetary rewards. We found that MDD patients were less willing to expend effort for rewards than controls. Additionally, we observed that patients were less able to effectively use information about magnitude and probability of rewards to guide their choice behavior. Finally, within the MDD patient group, duration of the current episode was a significant negative predictor of EEfRT task performance.”



Motivational deficits in effort-based decision making in individuals with subsyndromal depression, first-episode and remitted depression patients (Yang et al, 2014)
Sample size: Study 1: 43 people in the subsyndromally depressed group and 56 HCs; Study 2: 46 first episode MDD patients, 41 patients with remitted depression

"We tested the hypothesis that anhedonia in MDD may reflect specific impairments in motivation on reward-based decision-making and the deficits might be associated with depressive symptoms severity. In study 1, individuals with and without depressive symptoms performed the modified version of the Effort Expenditure for Rewards Task (EEfRT), a behavioral measure of cost/benefit decision-making. In study 2, MDD patients, remitted MDD patients and healthy controls were recruited for the same procedures. We found evidence for decreased willingness to make effort for rewards among individuals with subsyndromal depression; the effect was amplified in MDD patients, but dissipated in patients with remitted depression. We also found that reduced anticipatory and consummatory pleasure predicted decreased willingness to expend efforts to obtain rewards in MDD patients. For individuals with subsyndromal depression, the impairments were correlated with anticipatory anhedonia but not consummatory anhedonia."

The EEfRT was slightly modified.

“For both the subsyndromally depressed and non-depressed group, all participants chose a mixture of HC/HR trials and LC/LR trials, and there was no difference in the percentage of trials successfully completed between the subsyndromally depressed group (M 1⁄4 89.54%, S.D. 1⁄4 12.88%) and the non-depressed group (M1⁄493.19%, S.D.1⁄46.84%) (t971⁄41.81, p1⁄40.09). This suggested that all participants were able to complete both the hard and easy tasks throughout the experiment.”


Autism:
Adults with autism spectrum disorders exhibit decreased sensitivity to reward parameters when making effort-based decisions (Treadway et al, 2012)
Sample size: 20 adults with autism spectrum disorder (ASD) and 38 HCs

They adjusted the EEfRT to make up for possible ASD related issues “The EEfRT was modified so that participants had an unlimited amount of time to make choices to accommodate potential slower processing speeds in the ASD group [40, 41].”

The results are quite interesting here or at least the opposite of many other studies.

“Participants with ASD chose the hard task more frequently than did the control group, yet were less influenced by differences in reward value and probability than the control group. Additionally, effort-based decision-making was related to repetitive behavior symptoms across both groups.”

“These results suggest that individuals with ASD may be more willing to expend effort to obtain a monetary reward regardless of the reward contingencies. More broadly, results suggest that behavioral choices may be less influenced by information about reward contingencies in individuals with ASD. This atypical pattern of effort-based decision-making may be relevant for understanding the heightened reward motivation for circumscribed interests in ASD.”



Treatment/Drug trials:
Amping Up Effort: Effects of d-Amphetamine on Human Effort-Based Decision-Making (Treadway et al, 2011)
Sample size: 17 HCs

“Over three sessions, 17 healthy normal adults received placebo, d-amphetamine 10 mg, and 20 mg under counterbalanced double-blind conditions and completed the Effort Expenditure for Rewards Task. Consistent with predictions, amphetamine enhanced willingness to exert effort, particularly when reward probability was lower. Amphetamine did not alter effects of reward magnitude on willingness to exert effort. Amphetamine sped task performance, but its psychomotor effects were not strongly related to its effects on decision-making. This is the first demonstration in humans that dopaminergic manipulations alter willingness to exert effort for rewards.”



Left frontal anodal tDCS increases approach motivation depending on reward attributes (Ohmann et al, 2018)
Sample size: 60 HCs

“Participants were invited to the lab twice with at least 7 days between both sessions. Before starting, participants were randomly assigned to one of 4 study conditions. Between the 4 study conditions, the order of tDCS stimulation (sham / anodal) and the order of hand (left / right) used in the first and second block per session varied systematically.”

“No main effect of stimulation condition was found, however the interactions of stimulation condition and both probability of reward attainment and reward magnitude reached significance. These interactions indicated that left frontal anodal tDCS specifically increased the percentage of hard task choices (HTC) in trials with low probability of reward attainment and in trials with high reward magnitude.”

“Anodal tDCS stimulation over the left dlPFC increases approach motivation; Stimulation effects show when large rewards are at stake or rewards are unlikely; Results hint at a causal role of asymmetric frontal brain activity in motivation.”

Once again success rates of hard trials are much higher then in pwME “Participants completed easy trials with a success rate of 99.13% (sd = 2.43) and hard trials with a success rate of 96.95% (sd = 4.81), success rates of both conditions differed significantly (t(58) = 4.45, p > .001).” I think it makes sense to look at this closer to look at the lowest success rate of hard trials and see if it is anywhere close to that of pwME (it most likely isn't).

There’s also interesting observations about the effort required.

“In line with previous research, we expected the reward attributes (reward magnitude and probability of reward attainment) to be positive predictors of the number of HTC, whereas we expected trial number within task blocks (i.e., an indicator of fatigue) to be a negative predictor of HTC. We only tested right-handed participants, who typically show worse motoric performance with their left hand on finger tapping tests (Hervé et al., 2005). Therefore, we expected the factor hand to be a significant predictor of HTC, as participants should make fewer HTC with their left hand due to the increased effort requirements. “



A low dosage of the dopamine D2-receptor antagonist sulpiride affects effort allocation for reward regardless of trait extraversion (Ohmann et al, 2020)
Sample size: 203 HCs (102 in sulpiride group and 101 in placebo group)

They got unexpected and mixed results.

“Based on its presumably DA increasing action, we expected the low dose of sulpiride to increase participants’ willingness to allocate effort during the modified EEfRT relative to placebo, especially in trials with low probability of reward attainment. Further, we expected a moderating effect of trait extraversion on the effects of sulpiride. Two hundred and three healthy male participants were tested in a randomized, double-blind between-subjects design. Contrary to our expectations, sulpiride reduced the average number of clicks within the modified EEfRT and did not interact with reward attributes, suggesting a more global and not reward-specific effect of sulpiride. Furthermore, trait extraversion did not moderate the effect of sulpiride. Our results provide initial support for the validity of the modified version of the EEfRT, suggesting a possible inhibiting effect of a low dose of sulpiride on approach motivation regardless of trait extraversion. However, given the mixed pattern of findings and the possible confounding role of motoric abilities, further studies examining these effects are clearly warranted.”