Behavioral and Neural Representations of Subjective Effort Cost

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.

Study Overview

• Status: Recruiting
• Conditions: Fatigue
• Intervention / Treatment: Behavioral: Cognitive Fatigue; Behavioral: Physical Fatigue; Behavioral: Rewarding Stimuli

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Estimated): 185
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Anthony Gonzalez; Phone Number: 443-923-2716; Email: gonzalezan@kennedykrieger.org

Study Locations

• United States
  • Maryland
    • Baltimore, Maryland, United States, 21209
      • Recruiting
      • Kennedy Krieger Institute
      • Contact: Anthony Gonzalez; Phone Number: 443-923-2716; Email: gonzalezan@kennedykrieger.org

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 35 years (Adult)
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:

• Right-handed
• Age between 18 and 35 years old - Male or female
• Any ethnicity

Exclusion Criteria:

Individuals with a history of any of the following will be excluded from the study:

• Neurological problems such as stroke, head injury, epilepsy, seizures, brain tumors, brain surgery, Parkinson's Disease (self- report)
• Diagnosed history of severe psychiatric disease such as depression, schizophrenia (self-report)
• Metal in the head or eyes
• If they are pregnant or suspect that you may be pregnant
• If they experience discomfort from the MRI scan, such as severe claustrophobia or excessive heating of tattoos

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Basic Science
• Allocation: Non-Randomized
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Cognitive Fatigue; We will use a behavioral intervention. Participants will perform a cognitively demanding task, repeatedly, to induce cognitive fatigue.	Behavioral: Cognitive Fatigue; Participants will perform a cognitively demanding task (spatial attention task), repeatedly, to induce cognitive fatigue.
Experimental: Physical Fatigue; We will use a behavioral intervention. Participants will perform a physically demanding task (grip force exertion task), repeatedly, to induce cognitive fatigue.	Behavioral: Physical Fatigue; Participants will perform a physically demanding task (grip force exertion task), repeatedly, to induce cognitive fatigue.
Experimental: Rewarding Stimuli; We will use a behavioral intervention. Reward-associated stimuli will be used to study how reward-induced changes in motivational state influence effort choices.	Behavioral: Rewarding Stimuli; Reward-associated stimuli will be used to study how reward-induced changes in motivational state influence effort choices.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Mean of cognitive subjective effort parameters (from behavioral choice data)	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.	1 day
Differences between cognitive subjective effort parameters before and after fatigue (from behavioral choice data)	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.	1 day
Mean of physical subjective effort parameters (from behavioral choice data)	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.	1 days
Differences between physical subjective effort parameters before and after fatigue (from behavioral choice data)	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.	1 day
Difference between cognitive effort cost parameters between the low and high reward stimuli	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.	1 day
Difference between physical effort cost parameters between the low and high reward stimuli	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.	1 day
Regions of the brain encoding cognitive effort	We will use a general linear model to examine brain activity that is positively and negatively correlated with chosen cognitive effort value.	1 day
Regions of the brain encoding physical effort	We will use a general linear model to examine brain activity that is positively and negatively correlated with chosen physical effort value.	1 day
Regions of the brain encoding changes cognitive effort value following cognitive fatigue	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.	1 day
Regions of the brain encoding changes physical effort value following physical fatigue	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.	1 day
Regions of the brain encoding differences in cognitive effort value resulting from reward-induced changes in motivation	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.	1 day
Regions of the brain encoding differences in physical effort value resulting from reward-induced changes in motivation	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.	1 day

Collaborators and Investigators

• Sponsor: Hugo W. Moser Research Institute at Kennedy Krieger, Inc.
• Collaborators: National Institute of Mental Health (NIMH)
• Investigators: Principal Investigator: Vikram S. Chib, PhD, Kennedy Krieger Institute and Johns Hopkins School of Medicine

Study record dates

Study Major Dates

• Study Start (Actual): August 1, 2018
• Primary Completion (Estimated): December 31, 2024
• Study Completion (Estimated): December 31, 2024

Study Registration Dates

• First Submitted: July 26, 2019
• First Submitted That Met QC Criteria: July 30, 2019
• First Posted (Actual): August 1, 2019

Study Record Updates

• Last Update Posted (Estimated): April 15, 2024
• Last Update Submitted That Met QC Criteria: April 12, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Fatigue
• Other Study ID Numbers: IRB00034447 & IRB00283000; 1R56MH113627-01A1 (U.S. NIH Grant/Contract)

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No