The Influence of Heart Rate Variability on Decision Making

1. The Emotions &Quantitative Psychophysiology Lab The Emotions &Quantitative Psychophysiology Lab The Influence of Heart Rate Variability on Decision Making Ravi R. Bhatt, DeWayne P. Williams, Brandon Gillie, Julian Thayer The Emotions and Quantitative Psychophysiology Laboratory Department of Psychology, The Ohio State University R Introduction • Judgment and decision processes include making predictions, developing preferences, and inhibitory control • Heart rate variability (HRV) can be defined as the time in milliseconds (ms) between R-spikes • The vmPFC has been associated with decision making • Previous research has supported the Neurovisceral Integration Model, suggesting that these same areas are responsible for modulating HRV. • The present study attempts to examine HRV as an individual difference marker to judgment and decision making. Active executive function Greater cognitive flexibility Methods Results Active parasympathetic activity R R R R • Participants • 58 participants from The Ohio State University. • Physiological Data • Resting HRV was measured using an electrocardiogram (EKG) and was analyzed using the Task Force (1996) guidelines. • The participants were divided into low and high HRV groups via median split to analyze differences between low and high HRV groups. • JDM Task • Iowa Gambling Task (IGT) • A Deck = Bad , B = Worst , C = Good , D = Best • Learning contingency over time was measured by splitting 300 trials of the IGT in twelfths (25 trials per time period). Discussion • High HRV individuals may be able to inhibit, predict and develop preferences for decisions in comparison to low HRV individuals. • These results suggest HRV, a biological marker of health, can be used to predict real life judgment and decision making. • Researchers have shown physical and psychological ways to increase HRV and according to our results it will be important in JDM research. • Repeated measures ANOVA, revealed a significant interaction of HRV group and time when examining the best (D) deck (F (6.425, 65) = 2.545, p = .018). • Planned contrasts revealed a significant linear increase in selection of worst (B) deck overtime in the low HRV group (F(1,47) = 6.65, p = .013). In contrast, the high HRV group did not show the same trend, and rather these individuals show a significant quadratic trend selecting of the worst deck (F(1,47) = 4.549, p = .0381) . There were no significant trends with the non – extreme decks. A: (F(3.843, 65) = 1.760, p = .142); C: (F(7.631,65) = 1.937, p = .06)