Emily B. Falk

Predicting Persuasion-Induced Behavior Change From the Brain

Although persuasive messages often alter peoples self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance.

Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report

OBJECTIVE The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report. DESIGN Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. RESULTS A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained (R²self-report = .15, R²self-report + neural activity = .35, R²change = .20). CONCLUSION Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain-behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion.

Impulsivity and inhibitory control deficits are associated with unhealthy eating in young adults.

Heightened impulsivity and inefficient inhibitory control are increasingly recognized as risk factors for unhealthy eating and obesity but the underlying processes are not fully understood. We used structural equation modeling to investigate the relationships between impulsivity, inhibitory control, eating behavior, and body mass index (BMI) in 210 undergraduates who ranged from underweight to obese. We demonstrate that impulsivity and inhibitory control deficits are positively associated with several facets of unhealthy eating, including overeating in response to external food cues and in response to negative emotional states, and making food choices based on taste preferences without consideration of health value. We further show that such unhealthy eating is, for the most part, associated with increased BMI, with the exception of Restraint Eating, which is negatively associated with BMI. These results add to our understanding of the impact of individual differences in impulsivity and inhibitory control on key aspects of unhealthy eating and may have implications for the treatment and prevention of obesity.

From Neural Responses to Population Behavior Neural Focus Group Predicts Population-Level Media Effects

Can neural responses of a small group of individuals predict the behavior of large-scale populations? In this investigation, brain activations were recorded while smokers viewed three different television campaigns promoting the National Cancer Institute’s telephone hotline to help smokers quit (1-800-QUIT-NOW). The smokers also provided self-report predictions of the campaigns’ relative effectiveness. Population measures of the success of each campaign were computed by comparing call volume to 1-800-QUIT-NOW in the month before and the month after the launch of each campaign. This approach allowed us to directly compare the predictive value of self-reports with neural predictors of message effectiveness. Neural activity in a medial prefrontal region of interest, previously associated with individual behavior change, predicted the population response, whereas self-report judgments did not. This finding suggests a novel way of connecting neural signals to population responses that has not been previously demonstrated and provides information that may be difficult to obtain otherwise.

In the Trenches of Real-World Self-Control Neural Correlates of Breaking the Link Between Craving and Smoking

Successful goal pursuit involves repeatedly engaging self-control against temptations or distractions that arise along the way. Laboratory studies have identified the brain systems recruited during isolated instances of self-control, and ecological studies have linked self-control capacity to goal outcomes. However, no study has identified the neural systems of everyday self-control during long-term goal pursuit. The present study integrated neuroimaging and experience-sampling methods to investigate the brain systems of successful self-control among smokers attempting to quit. A sample of 27 cigarette smokers completed a go/no-go task during functional magnetic resonance imaging before they attempted to quit smoking and then reported everyday self-control using experience sampling eight times daily for 3 weeks while they attempted to quit. Increased activation in right inferior frontal gyrus, pre-supplementary motor area, and basal ganglia regions of interest during response inhibition at baseline was associated with an attenuated association between cravings and subsequent smoking. These findings support the ecological validity of neurocognitive tasks as indices of everyday response inhibition.

Beyond Brain Mapping: Using Neural Measures to Predict Real-World Outcomes

One goal of social science in general, and of psychology in particular, is to understand and predict human behavior. Psychologists have traditionally used self-report measures and performance on laboratory tasks to achieve this end. However, these measures are limited in their ability to predict behavior in certain contexts. We argue that current neuroscientific knowledge has reached a point where it can complement other existing psychological measures in predicting behavior and other important outcomes. This brain-as-predictor approach integrates traditional neuroimaging methods with measures of behavioral outcomes that extend beyond the immediate experimental session. Previously, most neuroimaging experiments focused on understanding basic psychological processes that could be directly observed in the laboratory. However, recent experiments have demonstrated that brain measures can predict outcomes (e.g., purchasing decisions, clinical outcomes) over longer timescales in ways that go beyond what was previously possible with self-report data alone. This approach can be used to reveal the connections between neural activity in laboratory contexts and longer-term, ecologically valid outcomes. We describe this approach and discuss its potential theoretical implications. We also review recent examples of studies that have used this approach, discuss methodological considerations, and provide specific guidelines for using it in future research.

Sharing the small moments: ephemeral social interaction on Snapchat

ABSTRACT Ephemeral social media, platforms that display shared content for a limited period of time, have become a prominent component of the social ecosystem. We draw on experience sampling data collected over two weeks (Study 1; N = 154) and in-depth interview data from a subsample of participants (Study 2; N = 28) to understand college students’ social and emotional experiences on Snapchat, a popular ephemeral mobile platform. Our quantitative data demonstrated that Snapchat interactions were perceived as more enjoyable – and associated with more positive mood – than other communication technologies. However, Snapchat interactions were also associated with lower social support than other channels. Our qualitative data highlighted aspects of Snapchat use that may facilitate positive affect (but not social support), including sharing mundane experiences with close ties and reduced self-presentational concerns. In addition, users compared Snapchat to face-to-face interaction and reported attending to Snapchat content more closely than archived content, which may contribute to increased emotional rewards. Overall, participants did not see the application as a platform for sharing or viewing photos; rather, Snapchat was viewed as a lightweight channel for sharing spontaneous experiences with trusted ties. Together, these studies contribute to our evolving understanding of ephemeral social media and their role in social relationships.

Dissociable Neural Systems Support Retrieval of How and Why Action Knowledge

In everyday discourse, people typically represent actions in one of two ways: how they are performed or why they are performed. In the present study, we determined the neural systems that support these natural modes of representing actions. Participants underwent functional magnetic resonance imaging while identifying how and why people perform various familiar actions. Identifying how actions are performed produced activity in premotor areas that support the execution of actions and in higher-order visual areas that support the perception of action-related objects; this finding supports an embodied view of action knowledge. However, identifying why actions are performed preferentially engaged areas of the brain associated with representing and reasoning about mental states; these areas were right temporoparietal junction, precuneus, dorsomedial prefrontal cortex, and posterior superior temporal sulcus. Our results suggest that why action knowledge is not sufficiently constituted by information in motor and visual systems, but requires a system for representing states of mind, which do not have reliable motor correlates or visual appearance.

What is a representative brain? Neuroscience meets population science

The last decades of neuroscience research have produced immense progress in the methods available to understand brain structure and function. Social, cognitive, clinical, affective, economic, communication, and developmental neurosciences have begun to map the relationships between neuro-psychological processes and behavioral outcomes, yielding a new understanding of human behavior and promising interventions. However, a limitation of this fast moving research is that most findings are based on small samples of convenience. Furthermore, our understanding of individual differences may be distorted by unrepresentative samples, undermining findings regarding brain–behavior mechanisms. These limitations are issues that social demographers, epidemiologists, and other population scientists have tackled, with solutions that can be applied to neuroscience. By contrast, nearly all social science disciplines, including social demography, sociology, political science, economics, communication science, and psychology, make assumptions about processes that involve the brain, but have incorporated neural measures to differing, and often limited, degrees; many still treat the brain as a black box. In this article, we describe and promote a perspective—population neuroscience—that leverages interdisciplinary expertise to (i) emphasize the importance of sampling to more clearly define the relevant populations and sampling strategies needed when using neuroscience methods to address such questions; and (ii) deepen understanding of mechanisms within population science by providing insight regarding underlying neural mechanisms. Doing so will increase our confidence in the generalizability of the findings. We provide examples to illustrate the population neuroscience approach for specific types of research questions and discuss the potential for theoretical and applied advances from this approach across areas.

Using SMS Text Messaging to Assess Moderators of Smoking Reduction: Validating a New Tool for Ecological Measurement of Health Behaviors

OBJECTIVE Understanding the psychological processes that contribute to smoking reduction will yield population health benefits. Negative mood may moderate smoking lapse during cessation, but this relationship has been difficult to measure in ongoing daily experience. We used a novel form of ecological momentary assessment to test a self-control model of negative mood and craving leading to smoking lapse. DESIGN We validated short message service (SMS) text as a user-friendly and low-cost option for ecologically measuring real-time health behaviors. We sent text messages to cigarette smokers attempting to quit eight times daily for the first 21 days of cessation (N-obs = 3,811). MAIN OUTCOME MEASURES Approximately every two hours, we assessed cigarette count, mood, and cravings, and examined between- and within-day patterns and time-lagged relationships among these variables. Exhaled carbon monoxide was assessed pre- and posttreatment. RESULTS Negative mood and craving predicted smoking two hours later, but craving mediated the mood-smoking relationship. Also, this mediation relationship predicted smoking over the next two, but not four, hours. CONCLUSION Results clarify conflicting previous findings on the relation between affect and smoking, validate a new low-cost and user-friendly method for collecting fine-grained health behavior assessments, and emphasize the importance of rapid, real-time measurement of smoking moderators.