PROJECT SUMMARY
Developing a new generation of interventions for cocaine use disorder (CUD) constitutes an important scientific
gap and, if addressed, will open innovation opportunities. To address this gap, we employ the Experimental
Medicine approach to mechanistically examine Reinforcer Pathology, an emerging novel framework for
addiction, that may provide a principled foundation for intervention development. Reinforcer Pathology specifies
that reinforcers are integrated over a temporal window, and the length of that window determines the relative
value of different reinforcers. When the temporal window is short, reinforcers such as cocaine, which are brief,
intense, and reliable, will have greater value. Conversely, as the temporal window lengthens, other more
temporally extended reinforcers begin to have greater influence and cocaine valuation will decrease. The
concept of Reinforcer Pathology identifies the temporal window, measured with delay discounting (i.e., the
decline in the value of a reinforcer as a function of its delay), as a therapeutic target for CUD, and it permits
target engagement via innovative interventions (e.g., episodic future thinking; EFT) to provide novel insights into
cocaine valuation. This project uses multiple analytical levels (e.g., the behavioral laboratory, neuroimaging, and
computational modeling) to quantify, predict, and modulate cocaine valuation among individuals with CUD. In
Aim 1, we will examine manipulations that increase and decrease the temporal window in parallel to
mechanistically test the Reinforcer Pathology framework. In Aim 1a, we will examine the effects of successive
exposure to an intervention that increases the temporal window (EFT) on concomitant changes in cocaine
valuation (demand and craving). In Aim 1b, we will examine the effects of a manipulation that decreases the
temporal window (stress probes) after exposure to EFT on concomitant changes in cocaine valuation.
Throughout Aim 1, neural activity associated with changes in the temporal window will also be examined. In Aim
2, we will use multi-voxel analyses of fMRI data to explore two independent sub-aims related to Reinforcer
Pathology in CUD. First, in Aim 2a, we will build multivariate group regression models of fMRI delay discounting
data in a subset of participants with CUD to predict discounting in an independent subset of participants. Second,
in Aim 2b, we will use real-time fMRI neurofeedback to enhance participants’ ability to control their temporal
window, and hence their ability to modulate delay discounting and cocaine valuation. In Aim 3, we will model the
temporal window by computationally quantifying results from Aims 1 and 2 (Aim 3a), and connecting subjective
value to brain regions of interest using computational neuroscience (Aim 3b). Together, the findings from this
rigorous and innovative research project will improve our understanding of CUD and highlight potential novel
and efficacious intervention strategies.
