NCT04041154

Brief Summary

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.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
185

participants targeted

Target at P75+ for not_applicable

Timeline
44mo left

Started Aug 2018

Longer than P75 for not_applicable

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Progress68%
Aug 2018Dec 2029

Study Start

First participant enrolled

August 1, 2018

Completed
12 months until next milestone

First Submitted

Initial submission to the registry

July 26, 2019

Completed
6 days until next milestone

First Posted

Study publicly available on registry

August 1, 2019

Completed
10.4 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

December 31, 2029

Expected
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

December 31, 2029

Last Updated

January 26, 2026

Status Verified

January 1, 2026

Enrollment Period

11.4 years

First QC Date

July 26, 2019

Last Update Submit

January 23, 2026

Conditions

Fatigue

Outcome Measures

Primary Outcomes (12)

  • 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

Study Arms (3)

Cognitive Fatigue

EXPERIMENTAL

We will use a behavioral intervention. Participants will perform a cognitively demanding task, repeatedly, to induce cognitive fatigue.

Behavioral: Cognitive Fatigue

Physical Fatigue

EXPERIMENTAL

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

Rewarding Stimuli

EXPERIMENTAL

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

Interventions

Cognitive FatigueBEHAVIORAL

Participants will perform a cognitively demanding task (spatial attention task), repeatedly, to induce cognitive fatigue.

Cognitive Fatigue
Physical FatigueBEHAVIORAL

Participants will perform a physically demanding task (grip force exertion task), repeatedly, to induce cognitive fatigue.

Physical Fatigue
Rewarding StimuliBEHAVIORAL

Reward-associated stimuli will be used to study how reward-induced changes in motivational state influence effort choices.

Rewarding Stimuli

Eligibility Criteria

Age18 Years - 35 Years
Sexall
Healthy VolunteersYes
Age GroupsAdult (18-64)

You may qualify if:

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

You may not qualify if:

  • 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

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Kennedy Krieger Institute

Baltimore, Maryland, 21209, United States

RECRUITING

MeSH Terms

Conditions

Fatigue

Condition Hierarchy (Ancestors)

Signs and SymptomsPathological Conditions, Signs and Symptoms

Study Officials

  • Vikram S. Chib, PhD

    Kennedy Krieger Institute and Johns Hopkins School of Medicine

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Anthony Gonzalez

CONTACT

443-923-2716gonzalezan@kennedykrieger.org

Study Design

Study Type
interventional
Phase
not applicable
Allocation
NON RANDOMIZED
Masking
NONE
Purpose
BASIC SCIENCE
Intervention Model
SINGLE GROUP
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Assistant Professor; Research Scientist

Study Record Dates

First Submitted

July 26, 2019

First Posted

August 1, 2019

Study Start

August 1, 2018

Primary Completion (Estimated)

December 31, 2029

Study Completion (Estimated)

December 31, 2029

Last Updated

January 26, 2026

Record last verified: 2026-01

Locations

US(1)