Drive at the rhythm of your own heart: a study on Heart Rate Variability, cognitive functioning and driving performance in Ferrari Driving Academy drivers

Racing driving requires the development of extraordinary sensorimotor skills to deliver high-level peak performances in complex environments characterised by multiple stressors, draining drivers’ physiological and cognitive resources. Although previous research provided evidence in favour of the role played by the Autonomic Nervous System (ANS) and different cognitive and executive functions in supporting the delivery of a high-level driving performance, further research is needed to deepen our understanding of the exact mechanisms linking physiological and psychological resources to the behavioural outcomes of driving. We adopted an evidence-based theoretical model (i.e., the Neurovisceral Integration Perspective; Thayer and Lane, 2000; Thayer et al., 2009; Thayer et al., 2012) and validated techniques and tools, to investigate, in a sample of elite racing drivers mainly scouted for the Ferrari Driver Academy, the relationship between HRV parameters, indexing the individual availability of physiological resources, and a set of measures of cognitive functions thought to be relevant for driving, including non-executive (simple reaction times) and executive (inhibitory control and WM) ones. We also tried to elucidate whether and how these physiological and cognitive variables can be used to predict driving performance, measured using a very ecological task in a realistic driving simulator. Based on previous research, we hypothesised that: (a) time-domain HRV indices of parasympathetic cardiac control would be positively associated with measures of inhibitory control (i.e., the performance at a Go/NoGo task) and WM (i.e., the performance at an N-Back task), but not with those of general readiness (i.e., the performance at an SRT task); (b) that driving performance (as indexed by the best and average lap times recorded) would be predicted by HRV indices, as well as by measures of inhibitory control. The results showed a significant negative correlation between cardiorespiratory coherence and the percentage of commissions at the Go/NoGo task, a negative correlation between coherence and the lap times recorded by the drivers, and a positive correlation between the latter and the mean reaction times (RTs) at the Go trials of the Go/NoGo task. Finally, linear models including coherence, the percentage of commissions at Go/NoGo and the mean RTs at Go trials as independent variables, proved to be able to explain a significant amount of variance in driving performance. Our results replicated some findings previously reported in psychophysiology, cognitive psychology, neuropsychology and sport psychology, extending them to the field of motorsport, and provided further support to the Neurovisceral Integration Perspective. Finally, the linear models developed proved to be able to explain a significant amount of variability in peak driving performance in elite racing drivers, providing a useful tool for their assessment and scouting, as well as for future studies in the field.