How Can Music Influence the Autonomic Nervous System Response in Patients with Severe Disorder of Consciousness?

Abstract

Activations to pleasant and unpleasant musical stimuli were observed within an extensive neuronal network and different brain structures, as well as in the processing of the syntactic and semantic aspects of the music. Previous studies evidenced a correlation between autonomic activity and emotion evoked by music listening in patients with Disorders of Consciousness (DoC). In this study, we analyzed retrospectively the autonomic response to musical stimuli by mean of normalized units of Low Frequency (nuLF) and Sample Entropy (SampEn) of Heart Rate Variability (HRV) parameters, and their possible correlation to the different complexity of four musical samples (i.e., Mussorgsky, Tchaikovsky, Grieg, and Boccherini) in Healthy subjects and Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) patients. The complexity of musical sample was based on Formal Complexity and General Dynamics parameters defined by Imberty's semiology studies. The results showed a significant difference between the two groups for SampEn during the listening of Mussorgsky's music and for nuLF during the listening of Boccherini and Mussorgsky's music. Moreover, the VS/UWS group showed a reduction of nuLF as well as SampEn comparing music of increasing Formal Complexity and General Dynamics. These results put in evidence how the internal structure of the music can change the autonomic response in patients with DoC. Further investigations are required to better comprehend how musical stimulation can modify the autonomic response in DoC patients, in order to administer the stimuli in a more effective way.

Keywords: autonomic nervous system; central autonomic network; disorder of consciousness; entropy; heart rate variability; music therapy; vegetative state.

Figure 1

Scores and first 60 s of the raw waveform, spectrogram, and melogram of the selected music. In the 1st column the first bars of the musical score. In the 2nd column the raw wave formgraph displays the unprocessed recorded sound. In the 3rd column the spectrogram plot show the intensity of the frequency content of a signal as it changes over the time. The vertical axis indicates frequency, the horizontal axis indicates time, and the color or gray scales indicate the intensity. Magenta is the color of the highest and dark blue of the lowest intensity. In the 4th column the melogram (or magnitude) graph displays the intensity of the melody relative to a reference sound.

Figure 2

Distribution of reported emotional responses of healthy subjects according to the music general dynamic and formal complexity (see Table 1). Numbers indicate the position in summary outline of the music samples used as auditory stimuli in the study (1 = Tchaikovsky; 2 = Boccherini; 3 = Grieg; 4 = Mussorgsky). Figure adapted from Riganello et al. (2010a).

Figure 3

Mean and Standard Error of nuLF and SampEn in healthy (green) and VS/UWS (red) groups. In the axis, from left to right, baseline and musical stimuli with increasing complex structure.