Control Systems Approach to Predicting Individualized Dynamics of Nicotine Cravings
NCT02643914 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 23
Last updated 2017-07-02
Summary
Nicotine is the most common drug of abuse in the United States, and has addiction strength comparable to cocaine, heroin, and alcohol. It is the primary addictive component of tobacco, and its use markedly increases risk for cancer, heart disease, asthma, miscarriage, and infant mortality. Addiction is thought to be caused primarily by the intersection of two components: 1) the impact of drug pharmacokinetics on the dynamics of dopamine response, and 2) dysregulation of the brain's reward circuit. While the term 'dysregulated' tends to be used qualitatively within the neuroscience literature, regulation has a precise and testable meaning in control systems engineering, which has yet to be addressed in a quantitative manner by current neuroimaging methods or models of addiction. Current approaches to neuroimaging have primarily focused on identifying nodes and causal connections within the meso-circuit of interest, but have yet to take the next step in treating these nodes and connection as a self-interacting dynamical system evolving over time. Such an approach is critical for improving our understanding, and therefore prediction, of trajectories for addiction as well as recovery.
Conditions
- Nicotine Addiction
- Cigarette Smoking
Interventions
- DRUG
-
Nicotine
- DEVICE
-
MR Compatible Nicotine Delivery Device
Sponsors & Collaborators
- lead OTHER
Principal Investigators
-
Lilianne Mujica-Parodi, PhD · Stony Brook University
Study Design
- Allocation
- NA
- Purpose
- DIAGNOSTIC
- Masking
- NONE
- Model
- SINGLE_GROUP
Eligibility
- Min Age
- 21 Years
- Max Age
- 65 Years
- Sex
- ALL
- Healthy Volunteers
- Yes
Timeline & Regulatory
- Start
- 2015-09-30
- Primary Completion
- 2017-06-30
- Completion
- 2017-12-31
Countries
- United States
Study Locations
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