Methods & Materials Playing with your heart: Investigating the neural, physiological, and cognitive effects of biofeedback training Steven Raaijmakers 1 2 , William Steel 1 2 , & Nelleke van Wouwe 2 1 Universiteit van Amsterdam, 2 TNO Abstract • This study is concerned with the application of biofeedback training in healthy participants and its potential beneficial effects at behavioural, physiological and cognitive levels. • We aim to understand the efficacy of biofeedback training as a tool with which to increase heart rate variability (HRV) – an index of autonomic nervous system adaptability which has been associated with effective deployment of cognitive resources in relation to frontal neural dynamics. • Our design employs a controlled experimental manipulation of HRV which, combined with an acute stress induction paradigm, will allow us to determine the relationship between HRV and cognitive performance in response to allostatic pressures of stress. Abstract • Our results will inform the current understanding of biofeedback and its relationship to emotion and physiological regulation through its ability to modulate HRV activity. • The use of an acute stressor paradigm provides an ecologically valid intervention which will offer results relevant to the use of biofeedback within a therapeutic setting. • We hope to provide evidence supporting the relationship between prefrontal cortex, HRV and cognitive performance in line with the neurovisceral integration model. Conclusion References: 1 | Thayer, J. F. & Lane R. D. (2009) A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders. 61: 201–216. 2 | Thayer, J. F,. Hansen, A. L., Saus-Rose, E., & Johnson, B. H. (2009) Heart Variability, Prefrontal Neural Function, and Cognitive Performance: The Neurovisceral Integration Perspective on Self-Regulation, Adaptation, and Health. Annals of Behavioral Medicine, 37:141-53. 3 | Benarroch, E, E. (1993) The central autonomic network: Functional organization, dysfunction, and perspective. Mayo Clin Proc. 68: 988–1001. 4 | Saul, J.P. (1990) Beat-to-beat variations of heart rate reflect modulation of cardiac autonomic outflow. News in Physiological Sciences. 5: 32–37. 5 | Hansen A. L., Johnsen B. H., & Thayer J. F. (2009) Relationship between heart rate variability and cognitive function during threat of shock. Anxiety Stress Coping. 2009; 22: 77–89. 6 | Johnsen, Hansen, Eid, Sollers, Hugdahl, and Thayer (unpublished manuscript: reported in Thayer & Lane, 2009). 7 | Johnsen, B. H., Hansen, A.L., Sollers, J. J., Murison, R., & Thayer, J. F. (2002) Heart rate variability is inversely related to cortisol reactivity during cognitive stress. Psychosomatic Medicine. 64: 289. 8 | Appelhans, B. M., & Luecken, L. J. (2006) Heart Rate Variability as an Index of Regulated Emotional Responding. Review of General Psychology, 10,3:229-240. 9 | Lane, R.D., McRae, K., Reiman, E, M., Chen, K., Ahern, G, L., & Thayer, J, F. (2009) Neural correlates of heart rate variability during emotion. Neuroimage. 44: 213–222. 10 | Nolan, R. P., Kamath, M. V., Floras, J. S., Stanley, J., Pang, C., Picton, P., & Young, Q. R. (2005) Heart rate variability biofeedback as a behavioral neurocardiac intervention to enhance vagal heart rate control. American Heart Journal. 149:1137. 10 | Cowan, M. J., Kogan, H., Burr, R., Hendershot, S., & Buchanan, L. (1990) Power Spectral Analysis of Heart Rate Variability after Biofeedback Training. Journal of Electrocardiology. 11 | Nolan, R. P., Kamath, M. V., Floras, J. S., Stanley, J., Pang, C., Picton, P., & Young, Q. R. (2005) Heart rate variability biofeedback as a behavioral neurocardiac intervention to enhance vagal heart rate control. American Heart Journal. 149:1137. Acknowledgements: We would like to thank Maartje de Goede, who helped program scripts for the cognitive tasks. We would also like to thank all our participants that have participated so far, as well as our confederates who helped ensure our stress induction was as ecologically valid as possible. Our predictions are based on the presumption that biofeedback training will result in modulation (increase) of heart rate variability (HRV). Heart rate variability | Biofeedback training will enhance cortically mediated parasympathetic (inhibitory) influence over heart rate –increased HRV would provide a marker of greater parasympathetic activity. Frontal neural dynamics | Greater HRV should lead to increased frontal cortical activity – decreased right frontal hemisphere activation as a marker of reduced negative affect. Cortisol | Resulting from increased HRV, we predict reduced peak cortisol responses and faster cortisol recovery-to-baseline. Cognitive performance | We predict an increase in availability of cognitive resources - increasing capacity for working memory and spatial ability processing. Expected Results Heart Rate Variability (HRV) | Calculated as the root mean squared of inter-heartbeat interval differences. Skin Conductance Level (SCL) | A measure of sympathetic nervous system activity and level of emotional or cognitive arousal. EEG frontal asymmetry | The relative difference between inter- hemisphere resting-state cortical dynamics has been related to affective processing. HRV / SCL / EEG measured simultaneously in eyes-open / eyes-closed blocks, once pre- & post-training and four times post-stress induction. Cortisol response | Stress elicits a cortisol response peaking 20 minutes after cessation of an acute stressor. Measured once pre-stress, and six times post-stress induction. Cortisol Awakening Response | The cortisol awakening response provides a measure of individual HPA activity. Measured on two occasions: (1) morning of first training session, and (2) morning of stress-induction. PANAS | A questionnaire that provides a measure of positive and negative affect. Measured on three occasions: pre- & post-training baselines, and post-stress induction. Measures Sinoatrial node Efferent Afferent Neurovisceral integration system Anterior Cingulate Cortex Hypothalamus Nucleus tractus solitarius Amygdala Prefrontal Cortex Pituitary gland Participants 40 males, aged 18-35. Exclusion criteria: people who, (1) smoke; (2) meditate or take part in yoga regularly; (3) have previous experience with biofeedback; (4) are left-handed; (5) have heart/respiratory conditions. Design Baseline sessions | Pre- and post-training participants’ resting physiological and frontal neural activity are recorded during counterbalanced eyes-open/eyes-closed 1 minute epochs - external electrodes measure heart rate and skin conductance level. Participants also perform shortened versions of the N-back (block 1: zero-back; block 2: 2-back) and Mental Rotation (same-different) task. Finally, a PANAS questionnaire was completed at the end of the baseline recording. Biofeedback training | Participants completed 6 x 30 minute training sessions, passing through multiple levels of six scenarios according to their success at the game. A simulated learning curve built into the software supports a double-blind control condition. HRV and SCL provide input and visual output to a series of games. Progression through the game creates a positive feedback loop out of which an increased HRV should result. Stress Induction | Following training, participants took part in the Trier Social Stress Test (TSST) - a robust stress-induction paradigm lasting 20 minutes: preparation (10 min); speech (5 min), mental arithmetic task (5 min); all conducted in front of a panel of two confederates, video and audio recorders. An EEG session was conducted immediately post-TSST, during which six cortisol samples were collected over the subsequent 50 minutes. Methods & Materials Mental Rotation Task EEG / Physiology Biofeedback Trier Social Stress Test Cortisol Experimental design 3 4 5 6 2 1 B T C T J A 7 B T C T J A 8 B T C T J A B T C T J A N-Back Task Session Introduction Neurovisceral integration | A model of neural and autonomic nervous system integration involved in cognitive, affective and autonomic regulation 1 2 . The system is constituted by reciprocal connections between the prefrontal cortex, anterior cingulate cortex, amygdala, hypothalamus and nucleus tractus solitarius 3 . Effective functioning within this network mediates cardiovascular activity to adapt to demands of allostatic load. Heart Rate Variability | A marker of the relative contributions of sympathetic and parasympathetic activity to heart rate 4 . HRV also provides a measure of autonomic nervous system (ANS) flexibility in response to cognitive demands 5 6 7 and emotional regulation 8 9 . Research supports a positive relationship between HRV and working memory and attention (executive processing) 5 6 . As well as a negative relationship between HRV susceptibility to stress, cognitive performance post-stress, and cortisol responses 7. Biofeedback | During biofeedback training, individuals receive feedback related to their physiological activity – the aim is to use this information to guide processes, for instance increasing or lowering heart rate 10 11 . Adrenal gland Cortisol Reciprocal connections Autonomic Nervous System pathways HRV PFC Stress coping HRV PFC Stress coping Predicted effects of biofeedback training Illustration legend