Dr. Alaina Pearce

Assistant Research Professor

Department: Nutritional Sciences

College:  Health and Human Development

Address: Chandlee 302

Phone: 814-863-2120

E-mail: azp271@psu.edu

Website: https://sites.psu.edu/alainapearce/

 

Study of Brain, Reward, and Kids’ Eating (BRAKE)

Children from rural communities are at greater risk for obesity than children from more urban communities. However, some children are resilient to obesity despite greater exposure to obesogenic influences in rural communities (e.g., fewer community-level physical activity or healthy eating resources). Identifying modifiable behavior factors that promote this resiliency could inform strength-based obesity prevention efforts. Eating habits are learned through reinforcement (e.g., hedonic, familial environment), the process through which environmental food cues become valued and influence behavior. Therefore, understanding individual differences in reinforcement learning is essential to uncovering the causes of obesity. Preclinical models have identified two reinforcement learning phenotypes that may have translational importance for understanding excess consumption in humans: 1) goal-tracking—environmental cues have predictive value; and 2) sign-tracking—environmental cues have predictive and hedonic value (i.e., incentive salience). Sign-tracking is associated with poorer attentional control, greater impulsivity, and lower prefrontal cortex (PFC) engagement in response to reward cues. This pattern parallels neurocognitive deficits observed in pediatric obesity (i.e., worse impulsivity, lower PFC food cue reactivity). We hypothesize that goal-tracking will promote resiliency to obesity due to reduced attribution of incentive salience and greater PFC engagement to food cues. To test this hypothesis, we will use a family-risk design and enroll 76, 8-9-year-old children of varying weight status from rural Pennsylvania. Methods will include reinforcement learning and value-modulated attention tasks, BodPod to assess adiposity, and neural food cue reactivity from functional near-infrared spectroscopy (fNIRS).

Home Observation of Meals and Environment (HOME) Bytes

Increased availability of high-energy dense foods has contributed to increases in pediatric obesity, therefore, it is critical to understand determinants of excess food consumption. An ‘obesogenic’ style of eating characterized by larger bites and faster eating and bite rates has been associated with overconsumption and pediatric obesity. These types of meal behaviors are collectively referred to as meal microstructure and are promising targets for pediatric obesity interventions. However, there are two key barriers to the development of meal microstructure interventions. First, the extent to which findings from controlled, laboratory-based studies correspond to eating behaviors outside the laboratory (e.g., at home) is not known. Second, observational coding of meal eating behaviors is a time and resource intensive process. Therefore, this study aims to build a research platform to support the study of eating behaviors in the home by utilizing smart phones and implementing automatic identification of eating behaviors.