Control Systems Approach to Predicting Individualized Dynamics of Nicotine Cravings

Status unconfirmed · Not applicable

Conditions studied: Nicotine Addiction, Cigarette Smoking

In brief

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.

Key facts

Study ID
NCT02643914
Run by
Stony Brook University
People needed
23
Starts
2015-09-01
Expected to finish
2017-12-01
Last updated by the study team
2017-07-02

Who can join

Age: 21 and older, up to 65. Sex: any. Healthy volunteers: accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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