The purpose of this pilot project is to understand how functional neuroimaging measures can be used to improve the predictive validity of psychometric measures relevant to addiction. Comprehensive behavioral and fMRI data related to impulsive choice were collected in paradigms focused on two concepts (one in each year of support): Impulsivity and Identity.

Project 1: Impulsivity is a stable trait that can be broken down into several components, including motor, cognitive, and non-planning factors. Non-planning impulsivity is characterized by insensitivity to delayed consequences-“present orientation” as opposed to “future orientation”, and is characteristic of addictive behaviors. To date, few neuroimaging studies have focused primarily on measuring impulsivity, and most of that deal with motor impulsivity or response inhibition. Prefrontal activation is typically reported in fMRI studies, specifically in OFC, dlPFC, and vmPFC. More commonly, studies have correlated brain activity with impulsivity using self-report measures such as the Barratt Impulsivity Scale (BIS). In the past, neuroscience data has been used to inform how we think about behavioral phenotypes only indirectly, not to directly assess personality traits and behaviors. By designing a task for fMRI that will isolate activation from a particular sub-phenotype (impulsivity), we aim to show that brain data can be directly used to improve the current questionnaire-based method of indexing behavioral phenotypes.

In addition, two assessment instruments were administered to these same subjects: one whose content is informed solely by answers to behavioral questionnaires, and the other whose items are selected based on both behavioral and neural data. The overall goal is to provide the first proof-of-concept that the incorporation of neuroscience data can improve the identification of behavioral phenotypes. Further, such a proof-of-concept will allow for the development of self report instruments that are referent to neurally connected markers of impulsivity. This important step can usher in the possibility of using self-report and behavioral indicators as neural processes, which in turn permits the screening of targeted individuals at probable risk for neural regulatory difficulties. Since performing fMRI on a population-wide sample is not feasible either practically or financially, such an advance in measurement of risk propensity should have an enormous impact on population based epidemiological studies of regulatory risk. This goal mirrors the current interest in bio-markers in population based studies.
Task design, setup and data collection have been completed.  Our sample included 49 subjects between 18 and 35 years of age.  Recruited subjects were healthy volunteers who met the study’s inclusion criteria and were recruited from the Duke-IRB-approved “Functional Neuroimaging Participants Registry” run by our Brain Imaging and Analysis Center. All participants in that pool have been screened for MRI eligibility factors, including implanted metal, non-compatible devices, and claustrophobia. Participants came to Duke for a single visit that combined completing a battery of personality questionnaires and an fMRI scanning session.
Quality assurance and image preprocessing have been completed for all collected functional and anatomical imaging data, and we will be able to use imaging data from approximately 45 subjects (4 excluded due to motion). Analyses of the behavioral data revealed that the two experimental tasks evoked distinct forms of impulsiveness within the sample. We have completed the first round of fMRI analyses and have identified neural markers of the different forms of impulsivity (focusing on medial and lateral prefrontal cortex). We have not yet broken the blind to link the fMRI data to the behavioral data, but will do so as soon as we finalize the fMRI models. Results from this study will be presented at the November, 2011, meeting of the Society for Neuroscience.

Project 2: Identity describes how our self-concept incorporates information about our relationships with others. In our ongoing project, we examine the neural basis of (a) the strength of group affiliation and (b) the balance between in-group fairness and between-group inequity. Our working hypothesis is that successful inhibition of self-identity relies on the interaction between two neural systems: the dmPFC (as above), which contributes to the framing of decision problems in terms of self-interest, and the dorsolateral PFC (dlPFC), which plays a key role in the inhibition of undesired behavior. This project is based on a novel collaboration between a neuroscientist (Scott Huettel) and two economists (Rachel Kranton and Seth Sanders), with input from a social psychologist (Phil Costanzo).

We have created and piloted two approaches to examine the effects of group membership on identity judgments and associated decision making. We have successfully implemented the “minimal group” paradigm to establish in- and out-group effects; in this paradigm, individuals are grouped based on arbitrary perceptual judgments (e.g., their responses to abstract artwork). Because the groups are indeed arbitrary and do not correspond to any real-world categories, any effects can be attributed to abstract “group” status. In the reward allocation task, individuals make decisions to allocate money to themselves, an in-group member, and/or an outgroup member. We have collected behavioral data from approximately 130 individuals, with Kranton and Sanders leading analyses of the choice data and construction of subject-specific utility functions (inclusion enrollment table is attached). Our data indicate that we can indeed group individuals on three factors: in-group bias, preference for overall value of outcomes (efficiency), and preference for fairness. Such groupings will be important for understanding the contributions of social information to judgments about rewards. We collected fMRI data on this task in spring 2011, with a final sample size of ~30 individuals. We are also piloting a real-world group manipulation based on political affiliation. We use this way of dividing individuals because it is highly salient and because it allows study of how people reappraise information based on how they think about others.

We plan to conduct additional analyses on both projects in 2011 and 2012. On the first project, we plan to break the blind on our intersubject measures of impulsivity and then relate those measures to our neural data. On the second project, we plan to link the models of utility associated with in-/out-group effects (as currently studied in our behavioral data) to our imaging data. Those analyses will serve as a bridge between the measures of identity and group that are studied by social scientists and the social cognition mechanisms studied by neuroscientists. We will also make our data available to other Center investigators, as well as colleagues at Duke and elsewhere, subject to IRB approval for such distribution.

With C-StARR support, we have submitted two papers – one accepted for publication (#1), the other under review (#2) – on the theoretical background for this research. We also have a manuscript in preparation (#3) based on the behavioral data from Project 2.

1. Coutlee, C., & Huettel, S.A. (in press). The Functional Neuroanatomy of Decision Making: Prefrontal Control of Thought and Action. Brain Research.
2. Huettel, S.A., & Kranton, R.E. (under review). Identity Economics and the Brain: Uncovering the Mechanisms of Social Conflict.
3. Kranton, R., Pease, M., Sanders, S., & Huettel, S. (in preparation). Redistribution, Ideology, and Identity.