Emily B. Falk - US grants

DESCRIPTION (Provided by the applicant) Abstract: Can neuroscience dramatically improve our ability to design health communications? Modifiable health behaviors including poor diet, physical inactivity, and tobacco and alcohol consumption are leading causes of morbidity and mortaiity, both in the United Statesl and throughout the developed world2; yet changing these behaviors has proved an immensely challenging problem. Classic behavior change theories provide a foundation to develop and understand effective health campaigns and interventions;3 however there is still considerable variability in the effectiveness of such campaigns that we are unable to predict and explain. By improving our ability to understand and predict behavior change, neuroimaging methods such as functional magnetic resonance imaging (fMRl) may aid in the creation of maximally effective health campaigns. There may be important precursors of behavior change that are not easily obtained through self-reports, but that can be assessed with fMRl. In particular, people are notoriously limited in their ability to predict their own future o. behavior and accurately identiy their internal mental processes through verbal and written self-report Our team has found that activity in a prioridefined neural regions of interest can double the proportion of variance explained in individual behavior change following persuasive messaging, beyond self-report measures (e.9. attitudes, intentions, self-efficacy).5'6 The current proposal posits a next leap: neuroimaging technology may also be applied to more accurately forecast population level responses to health communications, and could dramatically improve the way that we design and select health communications. To this end, we propose to: (1) identify the neurocognitive signatures of health communications that are successful at changing behavior at the population level; (2) use these maps to forecast the success of new health messages; and, (3) use the information gained about underlying mechanisms of message success to advance theory and to develop novel strategies for message design. We will employ sophisticated multivariate and machine learning data analysis techniques (e.9. reinforcement learning models and pattern classification) to characterize the neural systems that are involved in processing successful health messages (i.e. messages that ultimately facilitate behavior change in larger, independent groups). Such techniques will provide insight about the mechanisms that lead messages to be optimally effective for populations on average, as well as helping to understand heterogeneity within populations (i.e. for whom are given messages likely to be most effective). These techniques will also allow us to define models that optimally combine neuroimaging data with other available data sources (e.9. self-report). Achievement of our goals (to identify neural patterns that predict message success and to test the psychological meaning of these activations) will facilitate the design and dissemination of more effective health messages, and will allow more efficient translation of core theoretical advances across behavior and disease specific silos. Public Health Relevance: Modifiable health behaviors including poor diet, physical inactivity, and tobacco and alcohol consumption are leading causes of morbidity and mortality, both in the United States1 and throughout the developed world2; yet changing these behaviors has proved an immensely challenging problem. The proposed program of research is designed to (1) identify the neurocognitive signatures of health communications that are successful at changing behavior at the population level; (2) use these maps to forecast the success of novel health messages; and, (3) use the information gained about underlying mechanisms that promote message success to advance theory. Achievement of our goals (to identify neural patterns that predict message success and to test the psychological meaning of these activations) will facilitate the design and dissemination of more effective health messages, and will allow more efficient translation of core theoretical advances across behavior and disease specific silos.

DESCRIPTION (provided by applicant): Motor vehicle crashes are the leading cause of death and a major contributor to non-fatal injury in adolescents 1, 2. Teen drivers' crash risk is especially high in the presence of teen passengers3-6. Peer influences are pervasive, powerful, especially salient during adolescence and associated with health-risk behaviors7, but the variability and mechanisms involved are not well understood8. One factor that may promote risky behavior in adolescence is a possible imbalance in brain development between affective and cognitive control systems8-10, resulting not only in riskier choices overall, but also increased reward activity during risk taking in the presence of peers11, and heightened sensitivity to social rejection12,13. In this investigation, we aim to elucidate neurocognitive predictors of: (1) risky teen driving; (2) susceptibility to peer influence in the context of teen driving; and (3) the ability to overcome risky peer influence. To achieve these aims, we propose to integrate neuroimaging (fMRI) measures into a currently funded study that experimentally manipulates peer influences in a state-of-the-art driving simulator. Main outcomes include behaviors in the simulator that are associated with high rates of injury and fatality in real drivig contexts (a composite of speeding, close following distances, traffic light violations). We hypothesize that: [(1a) increased activity in neural reward systems during a risk- taking task14, and (1b) decreased activity in cognitive control systems during a response inhibition task15, in the fMRI environment will predict higher propensity .toward risky-driving behaviors in the simulator; (2a) increased reward activity during the risk task14, and (2b) increased neural activity in regions associated with distress during exclusion16 in the neuroimaging environment will predict increased susceptibility to risk taking in the presence of peers in the driving simulator; and (3) increased neural activity in cognitive control systems will predict decreased susceptibility to peer influence in the driving simulator], as cognitive control systems could serv to buffer negative affective responses during socially threatening situations, and could also serve to reduce the impact of reward responses induced by taking risks in the presence of peers.11 As such, we hypothesize that [reward and social distress sensitivity, as well as a tendency to recruit cognitive control resources will interact with the social situation to render adolescents differentially susceptible to behaviors that put them at risk for crash in the presence of peers]. Preliminary data collected using key elements of the proposed protocol are consistent with our hypotheses [and suggest that neural measures explain variance in key outcomes that is not explained otherwise]. The proposed research will increase understanding of the mechanisms that lead to variability in risky behavior in adolescents, as well as mechanisms of peer influence and ability to resist such influence. Individual differences in neurocognitive resources may not only interact with the social situation to promote risk, but may also serve to buffer social vulnerability to risk; this work may eventually allow us to develop more effective programs that efficiently reduce risk across multiple domains.

DESCRIPTION (provided by applicant): Promoting physical activity and decreasing sedentary behavior are key goals in the fight against cancers; physical activity is associated with lower risk of several cancers [1-10], and lower overall morbidity and mortality [11-26]. Thus, theory-driven initiatives to change these behaviors are essential [1-10, 26-40]. PQ#3 highlights the necessity for new perspectives on the interplay of cognitive and emotional factors in promoting behavior change. Current theories, which focus primarily on predictors derived from self-report measures, do not fully predict behavior change. For example, recent meta-analyses suggest that on average, variables from the Theory of Planned Behavior account for ~27% of the variance in behavior change [41, 42]. This limits our ability to design optimally effective interventions [43], and invites new methods that may explain additional variance. Our team has shown that neural activation in response to health messages in hypothesized neural regions of interest can double the explained variance in behavior change, above and beyond self-reports of attitudes, intentions, and self-efficacy [44, 45]. We now propose a next leap, inspired by PQ3, to identify how cognitive and affective processes interact in the brain to influence and predict behavior change. Our core hypothesis is that the balance of neural activity in regions associated with self-related processing versus defensive counterarguing is key in producing health behavior change, and that self-affirmation (an innovative approach, relatively new to the health behavior area [46]) can alter this balance. Self-affirmation theory [47] posits that people are motivated to maintain a sense of self-worth, and that threats to self-worth will be met with resistance, often i the form of counterarguing. One common threat to self-worth occurs when people are confronted with self-relevant health messages (e.g. encouraging less sedentary behavior in overweight, sedentary adults). This phenomenon speaks to a classic and problematic paradox: those at highest risk are likely to be most defensive and least open to altering cancer risk behaviors [48]. A substantial, and surprisingly impressive, body of evidence demonstrates that affirmation of core-values (self-affirmation priming) preceding messages can reduce resistance and increase intervention effectiveness [46, 49-53]. Uncovering neural mechanisms of such affirmation effects [46], has transformative potential for intervention design and selection. To test our conceptual assumptions and core hypothesis we will: (1) Identify neural signals associated with processing health messages as self-relevant versus counterarguing; (2) Test whether self-affirmation alters the balance of these signals; (3) Use these neural signals to predict physical activity behavior change, above and beyond what is predicted by self-report measures alone. Our approach is innovative methodologically (using fMRI to understand and predict behavior change), and conceptually (self-affirmation may dramatically increase intervention effectiveness). Benchmarks will include objectively measured decreases in sedentary behavior in affirmed vs. control subjects (using accelerometers), and increases in predictive capacity afforded by neuroimaging methods, compared to self-report alone.

Intellectual Merit:

Various advocacy groups bombard citizens with messages via email, print ads, and television broadcasts. Some of these messages are meant to persuade citizens to perform a political action (e.g., sign petitions, contact their congresspersons, etc.), some are meant to pursuade them to buy certain products or subscribe to various services. Although research has shown that persuasive messages can change people's self-reported attitudes or intentions to perform certain actions, self-reports do not necessarily predict change in behavior-suggesting that some processes are not accessible to self-report measures. This project examines the extent to which neural responses can predict persuasion-induced human behavior beyond what is predicted by self-report measures. This project uses functional Magnetic Resonance Imaging (fMRI) to determine the extent to which brain activity can predict real-world behavior in response to persuasive messages, and to study the underlying mechanisms that lead to effective persuasion. With the cooperation of political advocacy groups, this project conducts a field experiment to validate that messages predicted to be persuasive by brain data in the lab are in fact effective at persuading a large number of citizens in the real world. Ultimately, thee information provides basic scientific knowledge about the mechanisms of persuasion.

This project builds on previous work showing that neural activity in the brain can predict individual and population behavioral change in response to health communications. This project examines the extent to which activity in brain regions implicated in self-related and/or reward relevant processing predicts behavior, and provides basic-science insight about common and divergent mechanisms leading to persuasion in different domains.

Broader Impacts:

In addition to the project's contribution to the basic science of social influence, the study stands to make immediate and broad impacts. Execution of the research will have broad impacts on the training of a next generation of scientists. As a first generation Filipino immigrant and as the first person to receive a doctorate in his family, the PI has a commitment to broadening participation by underrepresented groups in the fields of political science and cognitive neuroscience. During his postdoctoral training, the PI will mentor undergraduate researchers from diverse backgrounds, work with groups that broaden civic participation in underrepresented groups, and present the research findings to a wide range of academic and nonacademic audiences.

Project Summary / Abstract Cigarette smoking is the leading cause of preventable death and illness in the United States and throughout the developed world. Currently, the tobacco industry focuses over 80% of its marketing budget in the retail environment. Recent work suggests detrimental links between exposure to point-of-sale tobacco marketing (POSTM), increases in cigarette cravings, and the failure to quit smoking. Understanding how individuals are influenced by and react to their natural environments when making health decisions is thus critical to cancer control efforts. We propose to use an innovative set of methods to test whether repeated, real-world exposure to POSTM affects smoking behavior, and whether this is mediated by heightened craving and neural responses to POSTM. Our novel multi-method approach to communication research includes mobile-phone based geolocation tracking, ecological momentary assessment (EMA), and functional magnetic resonance imaging (fMRI). By adding the ecological validity of observational field methods to the mechanistic insight of neuroimaging, and causal inferences from an experimental design, we aim to significantly advance actionable insight about POSTM effects in cancer control. Research utilizing geospatial location tracking and survey methods suggests that high levels of POSTM exposure may increase craving; however, correlational studies preclude mechanistic explanations and causal inferences about POSTM effects. Relatedly, laboratory studies have documented neural and behavioral reactivity to standardized visual smoking cues, such as photographs of cigarettes, but the brain?s response to naturalistic POSTM exposure has not been explored. We hypothesize that exposure to POSTM increases brain responses to smoking cues as well as subjective craving, leading to increased smoking behavior. To test this, we will follow 180 daily smokers with geospatial location tracking and EMA to assess whether longitudinal fluctuations in real-world POSTM exposure are associated with moment-to-moment cigarette craving and smoking behavior (Aim 1), and whether these processes are related to differences in neural smoking cue reactivity (Aim 2). Finally, we will conduct an experiment that manipulates naturalistic exposure to POSTM to test whether these effects are causal (Aim 3). In the experimental phase, two groups of participants will enter and make a small purchase (e.g., water) at a retail outlet with or without POSTM displays 5 times per week for 4 weeks, while a third control group will not change their habits. We will measure neural responses and subjective cravings to POSTM exposure in all groups before and after the experimental manipulation. Protocol feasibility and dosage has been established through extensive pilot work. Increases in smoking behavior, craving, and/or neural cue reactivity in response to increased POSTM exposure would strongly implicate causal evidence for POSTM exposure, which is much needed for science-based policy making and could inform cancer control efforts.causal evidence for POSTM exposure, which is much needed for science-based policy making and could inform cancer control efforts.