Our work is focused on understanding the biological and neurodevelopmental mechanisms of addiction and decision making.

We integrate sophisticated behavioral paradigms with computational analyses, neuroimaging approaches, systems-level manipulations, and molecular analyses to generate mechanistic links between genes, signaling mechanisms, and behavior that can help us understand the pathology of addiction. Below is a description of some of the projects that are currently being conducted in the lab.

Although most individuals will use a drug of abuse at least once in their lifetime, only a subset of people will develop an addiction. This suggests that some individuals may more susceptible to developing an addiction and, importantly, if we can identify the neurobiology mediating drug use susceptibility, addiction may one day be a preventable disorder. There is considerable interest in understanding the biological mechanisms that impact addiction susceptibility. Most studies, however, have been done in humans or animals that have been exposed to drugs of abuse, which is known to have profound effects on the brain and is likely to overshadow the pre-existing differences that mediate susceptibility. Identify the mechanisms mediating addiction risk - from the consequence of drug use - has been difficult to do.

Our work has been using a computational approach to delineate the decision-making processes that predict drug-taking behaviors from those that are disrupted by drug use in rats (Groman et al., 2020a; Groman et al., 2020b) in order to identify novel biological targets for preventing as well as treating addiction. Some of our ongoing projects are 1) using proteomics to identify the signaling mechanisms related to specific reinforcement-learning parameters, 2) viral and neuroimaging tools to identify the neural circuits that control decision-making (Groman et al., 2019) and addiction-relevant behaviors, and 3) genomic approaches to identify new biomarkers of addiction susceptibility. Our goal is to generate mechanistic links between proteins, circuits, and behavior that can provide insights into the results obtained in humans.

This work is currently funded by NIDA U01 award (DA051977) between the Groman and DiLeone Lab.

Most prevention-based strategies for addiction (e.g., family or community-based programs) are initiated after an individual begins using drugs of abuse, which for some individuals may be too late to be effective. Behavioral and/or molecular biomarkers of addiction risk could be used for early screenings of individuals so that prevention strategies are implemented before drug use is initiated. It is known that the likelihood of developing an addiction is mediated by both genetic and environmental factors, but the identify of these factors and how they may impact neural functions mediating drug use susceptibility is not known.

Our recently funded work is focused on isolating the signaling mechanisms that co-vary with genetic components of addiction risk from those that co-vary with environmental components of addiction risk. To do this, we will assess decision-making processes in a genetic rat model of addiction susceptibility (developed and established by the Indiana Alcohol Research Center) and in an animal model of early life stress. Proteomic and drug self-administration behaviors will be assessed to isolate the protein mechanisms mediating genetic versus environmental drug use susceptibility. Upon identification of these targets, we will use viral tools to determine how disruptions in these proteins targets impacts behavioral and neural functions .

This work is currently funded by a NIDA K01 award (DA051598).

One of the most profound periods of brain development occurs during adolescence, the period between childhood and adulthood. There is decline in synaptic density, an increase in myelination, and enhanced connectivity between brain regions that is thought to be the mechanism by which decision making improves adolescence. Direct evidence to support this hypothesis, however, has been limited. Because adolescence is a period in which symptoms of mental illness emerge - which are associated with disruptions in decision making - understanding the neurobiological mechanisms that underlie age-related decision-making in normal and abnormal states could provide critical insights into the neurodevelopmental mechanisms that underlie mental illness.

We have recently developed a novel approach for assessing decision-making processes across adolescent development (Moin Afshar, Keip et al., 2020) and have been using proteomics to identify the signaling mechanisms that are associated with changes in select reinforcement-learning processes. These molecular findings will be integrated with neuroimaging approaches to identify the proteins that mediate changes in synaptic density, myelination, and connectivity. We are also examining how decision-making trajectories during adolescence predict maladaptive behavior in adulthood, including drug self-administration and compulsive patterns of drug use.