The Effort Expenditure for Rewards Task
The Effort-Expenditure for Reward Task (EEfRT Task) is a behavioral paradigm that offers researchers and clinicians a means to explore effort-based decision-making in humans. Based on a concurrent choice paradigm developed by Salamone et al.,1994 to explore effort-based decision making in rodents, the EEfRT task presents subjects with a series of repeated trials in which they are able to choose between performing a “hard-task” or an “easy-task” in order to earn varying amounts of monetary reward.
For all trials, participants will make repeated manual button presses over a short period of time which each press raising the level of a virtual “bar” viewed onscreen by the participant. In addition to varying reward magnitude, trials are presented with different probability levels for reward receipt, allowing us to examine the extent to which the relationship between motivation levels and effort-based decision-making is modulated by perceived reward magnitude.
The EEfRT has been used in 100+ laboratories in over a dozen countries, and has been translated into five languages. Dr. Michael Treadway has collaborated on projects with other research groups to explore motivational deficits using this task, in a wide-range of psychiatric and neurological disorders. Examples of applications of the task include assessing reward motivation as a moderator of treatment response and reward anticipation and consumption using the EEfRT, EEG, and fMRI. Dr. Treadway has conducted examinations of the task’s sensitivity, validity, and reliability in studies of healthy controls and patient populations and continues to investigate correlations of the EEfRT with other measures of motivation and establish the task’s test-retest reliability.
COI Disclosures for the EEfRT: Michael Treadway is a co-inventor of the EEfRT. Emory University and Vanderbilt University licensed this software to BlackThorn Therapeutics. Under the IP Policies of both universities, Dr. Treadway has previously received licensing fees and royalties from Neumora (formerly BlackThorn Therapeutics). Additionally, Dr. Treadway has previously been a paid consulting relationship with Neumora. While he does not currently receive royalties or consulting fees related to the EEfRT, he is potentially eligible to receive royalties in the future. The terms of these arrangements have been reviewed and approved by Emory University in accordance with its conflict of interest policies. For more information on the EEfRT Task, click here.
For researchers at academic or non-profit institutions there is no cost to using the EEfRT and we are happy to provide the code for administering the EEfRT using the Matlab Psychtoolbox. For commercial or for-profit entities interested in using the task, please contact Justin Burns in the Emory Office of Technology Transfer.
Please note that some aspects of the code and instructions may need to be adjusted to meet the needs of your specific study. Please be aware that we have limited resources to troubleshoot/advise on the use of the EEfRT, and we recommend that individuals interested in using the EEfRT have prior experience using computerized decision-making tasks.
To access the EEfRT Task, complete the form below.
The Staggered Effort-Based Decision-Making Task
The Staggered Effort-Based Decision-Making Task is a fMRI paradigm that offers researchers and clinicians a means to explore the neural circuitry of effort-based decision-making in humans. Based on the EEfRT task, this task presents subjects with a series of repeated trials in which they are able to choose between performing a “hard-task” or an “easy-task” in order to earn varying amounts of monetary reward. This task involves three parts: Training Phase, fMRI Phase, Post-fMRI Phase.
For more information on the Staggered Effort-Based Decision-Making Task, click here
Please note that some aspects of the code and instructions may need to be adjusted to meet the needs of your specific study. Please be aware that we have limited resources to troubleshoot/advise on the use of the Staggered Effort-Based Decision-Making Task, and we recommend that individuals interested in using the task have prior experience using computerized decision-making tasks and Matlab.