Control Systems Approach to Predicting Individualized Dynamics of Nicotine Cravings
Status:
Unknown status
Trial end date:
2017-12-01
Target enrollment:
Participant gender:
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.