Working with professional pianists and experienced piano students from London conservatoires, Dr Maria Herrojo Ruiz and colleagues found that the brain receives crucial information from the heart before an error in playing occurs.
This information helps the brain predict the occurrence of an upcoming error and adapt behaviour accordingly.
For pitch errors, the researchers found that the heart’s inter-beat interval immediately preceding an error was larger than the previous inter-beat interval.
The researchers also looked at how the heart’s natural beating cycle influences how well the brain responds in predicting and processing errors.
The brain was better at predicting errors when the heart was contracting and pumping blood into the arteries (cardiac systole) than when the ventricles were relaxed and filled with blood (cardiac diastole), their study concluded.
Detecting errors during any type of performance is necessary to make corrections and improve our performance next time we try it.
For the first time, this study shows how, in expert musicians, detection of errors relies on integrating information from our environment (body movements used in performing and the sound they produce on a musical instrument) alongside cues from inside our body, such as heart rate activity.
The research suggests that highly skilled musicians might be trained to listen to their whole bodies during performance to minimise or eliminate mistakes.
A report of the research was published online in the journal NeuroImage on Tuesday 30 April.
Prior research had found that simple mistakes trigger changes in autonomous nervous system activity, such as a slowing of the heartbeat or pupil dilation following errors, but the role of the body’s internal signals in error monitoring during trained movements, as in expert musical performance, was not known.
And while we know that the brain can anticipate errors in expert musicians, previous work did not look at the role of other bodily signals in the early error prediction phase.
In this new study, researchers expected to find that the extensive training of musicians would allow their bodily signals (heart rate) to help their brain anticipate errors before they are committed to making them.
In advance of testing, 17 pianists were asked to rehearse and memorise four 25 second excerpts from Preludes V and VI of Bach’s Well-Tempered Clavier – pieces chosen for the steady duration of notes and regular time intervals between consecutive notes.
For the first time, this study shows how, in expert musicians, detection of errors relies on integrating information from our environment (body movements used in performing and the sound they produce on a musical instrument) alongside cues from inside our body, such as heart rate activity.
The image is in the public domain.
While brain and heart activity was monitored and musical output recorded for analysis, participants played the pieces a total of 60 times in randomly selected order from memory, and at a faster than rehearsed tempo.
The pianists were not allowed to look at their hands, instead, they fixated on a point at eye level.
These constraints were aimed at inducing errors in the musical performances, which otherwise would have been difficult to get from expert musicians.
Dr Herrojo Ruiz said: “Being able to detect and evaluate errors is essential to gaining the complex motor skills needed in dance or music performance.
Our findings suggest that successfully predicting the future consequences of our actions, in this case making a mistake, relies on effectively using information from receptors in different parts of the body, such as in the heart – and that is a skill which may be developed through training.”
Source:
Goldsmiths University of London
Media Contacts:
Sarah Cox – Goldsmiths University of London
Image Source:
The image is in the public domain.
Original Research: Closed access
“Cardiac afferent activity modulates early neural signature of error detection during skilled performance”. Gabriela Bury, Marta García Huesca, Joydeep Bhattacharya, María Herrojo Ruiz. NeuroImage. doi:10.1016/j.neuroimage.2019.04.043
