Kennedy Krieger Institute
Baltimore, Maryland, 21209, United States
Location status: Recruiting
NCT Number: NCT04041154
The goal of this proposal is to understand the common and distinct behavioral and neural representations of subjective effort valuation, and how these representations are influenced by fatigue and changes in motivation. It is hypothesized that the brain will use overlapping and distinct neural circuits to represent cognitive and physical effort value, and that fatigue and enhanced motivation will influence the subjective value of effort.
Interested in participating?
Request Info18 year–35 year
All sexes
Interventional
Not applicable
Baltimore, Maryland, 21209, United States
Location status: Recruiting
How effortful a task feels is an integral aspect of human decision-making that shapes motivation. If a task feels very effortful one may be unwilling to perform the work required, whereas if a task feels less effortful one may be more likely to persevere. Despite the importance of these perceptions for decision-making, the behavioral and neural mechanisms of subjective effort valuation are not well understood. Furthermore, the National Institutes of Mental Health (NIMH) Research Domain Criteria (RDoC) has identified "Effort Valuation / Willingness to Work" as a key subconstruct for understanding deficits in motivated performance in mental disorders. The goal of this proposal is to understand the mechanisms of subjective valuation of physical and cognitive effort, and the common and distinct systems that underlie these representations. To this end, a combination of experiments in healthy human participants, computational modeling of behavior, and functional magnetic resonance imaging (fMRI) will be used. Aim 1 will identify common and distinct physical and cognitive effort valuation mechanisms. Computational models will be used to characterize participants' subjective valuation of physical and cognitive effort, and to test if there are similarities in subjective preferences for these different types of effort. Model-based fMRI will be used to examine the common and distinct brain regions that encode the subjective valuation of physical and cognitive effort, and the network of brain regions that incorporate such preferences to motivate effortful engagement. Aim 2 will investigate the behavioral and neural mechanisms by which physical and cognitive fatigue effect effort valuation. Participants will be fatigued with sustained physical or cognitive exertion to examine how being in a fatigued state influences subjective valuation of physical and cognitive effort; and associated signals in the brain's valuation network. Aim 3 will explore how motivational state modulates decisions to exert physical and cognitive effort. Choices for physical and cognitive effort will be paired with motivational cues (i.e., cues that formerly predicted reward) in order to modulate participants' motivational state. This manipulation will allow for behavioral and neural dissociations between motivation and effort valuation in order to understand how these processes interact to give rise to motivated physical and cognitive engagement. In sum, the proposed studies will have a broad impact on the field of decision-making by dissecting the behavioral and neural mechanisms responsible for physical and cognitive effort valuation. In the long term, these studies may reveal novel behavioral and neural markers to aid in the study, classification, and treatment of amotivation.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Individuals with a history of any of the following will be excluded from the study:
Participants will perform a cognitively demanding task (spatial attention task), repeatedly, to induce cognitive fatigue.
Participants will perform a physically demanding task (grip force exertion task), repeatedly, to induce cognitive fatigue.
Reward-associated stimuli will be used to study how reward-induced changes in motivational state influence effort choices.
Time frame: 1 day
Choice data will be fit to a model of the form u(x) = x^rho. The parameter rho is indicative of individuals' subjective preferences for effort. We will test if participants cognitive subjective effort parameters will be significantly different than zero. Effort levels will be expressed as a percentage of each individual's maximum exertion capacity. This will ensure that comparisons can be made between participants.
Time frame: 1 day
Choice data will be fit to a model of the form u(x) = x^rho. The parameter rho is indicative of individuals' subjective preferences for effort. We will test if participants cognitive subjective effort parameters will be significantly different when comparing parameters extracted from pre-fatigue and post-fatigue choices. Effort levels will be expressed as a percentage of each individual's maximum exertion capacity. This will ensure that comparisons can be made between participants.
Time frame: 1 days
Choice data will be fit to a model of the form u(x) = x^rho. The parameter rho is indicative of individuals' subjective preferences for effort. We will test if participants physical subjective effort parameters will be significantly different than zero. Effort levels will be expressed as a percentage of each individual's maximum exertion capacity. This will ensure that comparisons can be made between participants.
Time frame: 1 day
Choice data will be fit to a model of the form u(x) = x^rho. The parameter rho is indicative of individuals' subjective preferences for effort. We will test if participants physical subjective effort parameters will be significantly different when comparing parameters extracted from pre-fatigue and post-fatigue choices. Effort levels will be expressed as a percentage of each individual's maximum exertion capacity. This will ensure that comparisons can be made between participants.
Time frame: 1 day
Choice data will be fit to a model of the form u(x) = x^rho. The parameter rho is indicative of individuals' subjective preferences for effort. We will test if participants subjective effort parameters will be significantly different when comparing parameters extracted from low and high reward stimuli trials. Effort levels will be expressed as a percentage of each individual's maximum exertion capacity. This will ensure that comparisons can be made between participants.
Time frame: 1 day
Choice data will be fit to a model of the form u(x) = x^rho. The parameter rho is indicative of individuals' subjective preferences for effort. We will test if participants subjective effort parameters will be significantly different when comparing parameters extracted from low and high reward stimuli trials. Effort levels will be expressed as a percentage of each individual's maximum exertion capacity. This will ensure that comparisons can be made between participants.
Time frame: 1 day
We will use a general linear model to examine brain activity that is positively and negatively correlated with chosen cognitive effort value.
Time frame: 1 day
We will use a general linear model to examine brain activity that is positively and negatively correlated with chosen physical effort value.
Time frame: 1 day
We will use a general linear model to examine brain activity that is positively and negatively correlated with fatigue-induced changes in cognitive effort value.
Time frame: 1 day
We will use a general linear model to examine brain activity that is positively and negatively correlated with fatigue-induced changes in physical effort value.
Time frame: 1 day
We will use a general linear model to examine brain activity that is positively and negatively correlated with motivation-induced changes in cognitive effort value.
Time frame: 1 day
We will use a general linear model to examine brain activity that is positively and negatively correlated with motivation-induced changes in physical effort value.
Contact information is provided by the study sponsor or research team.
Hugo W. Moser Research Institute at Kennedy Krieger, Inc.
Other
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