Closed-loop musical stimulation: Current status and prospects for research

Abstract

This narrative review addresses a nascent field in neurophysiology—the closed-loop methods of musical stimulation. The review discusses the therapeutic properties of music, including the role of closed-loop musical stimulation in solving the problem of adequate selection of musical stimuli in order to increase the effectiveness of music therapy. The available experimental data on the conditions, features of application, and achievements of various types of closed-loop musical stimulation are considered. The discussed advantages of closed-loop musical stimulation methods open up broad prospects for their use in the correction of psychogenic and neurological disorders and cognitive rehabilitation. The review also includes a short foray into music psychology.

Keywords

non-invasive brain stimulation adaptive neurostimulation with feedback psychophysiological properties of music closed-loop musical stimulation music perception main morphological principle in music music therapy endogenous rhythms therapy of psychogenic disorders

The creation, improvement, and clinical testing of non-invasive methods of brain stimulation with feedback is one of the most promising and rapidly developing areas of neurophysiology. Unlike traditional stimulation methods, in which the stimulation parameters are set in advance and remain unchanged during stimulation (open-loop stimulation), adaptive neurostimulation methods with feedback (closed-loop stimulation) use non-invasive sensory inputs that adapt to the patient’s parameters of dynamic processes by using feedback control signals from various physiological characteristics of the patient’s body (Lo & Widge, 2017; Oxley & Opie, 2019). The key feature of adaptive neurostimulation methods is the automatic adjustment of the parameters of the therapeutic stimulation, which are controlled continuously by feedback signals from the patient’s physiological indicators and carried without the involvement of the patient consciousness (Tervo et al., 2022; Zhou & Miller, 2019). Therefore, feedback signals automatically modulate or adapt therapeutic interventions in response to physiological changes and thus provide more effective and efficient therapy (Potter et al., 2014; Sun & Morrell, 2014). The principle of feedback closure makes it possible to take into account the current dynamics of microstates of the nervous system (de Bock et al., 2020; Hu et al., 2023). In addition, therapeutic stimulation procedures achieve highly personalized effects and acquire the character of closed-loop brain state-dependent stimulation (Bergmann, 2018; Bradley et al., 2022) and physiologically informed adaptive neuromodulation (Weiss et al., 2023; Wendt et al., 2022).

An inspection of the relevant literature shows that the most popular and actively developed methods of adaptive neurostimulation are those that use feedback from the patient’s endogenous rhythmic processes, such as the rhythms of the cardiovascular and respiratory systems, as well as the brain rhythms as detected by the electroencephalogram (EEG). These rhythmic processes are closely interrelated and form the basis of the natural homeostatic regulation; they demonstrate the phenomena of synchronization and resonance and are characterized by high sensitivity to external factors (Fedotchev, Parin, Polevaya & Zemlyanaya, 2021). Typically, these rhythmic processes are effectively used for feedback control of non-invasive sensory inputs, such as transcranial electrical stimulation (Ketz et al., 2018; Ladenbauer et al., 2022), transcranial magnetic stimulation (Faller et al., 2022; Zrenner et al., 2020) and acoustic stimulation (Debellemanière et al., 2022; Ngo et al., 2019). However, in recent years, another area of non-invasive brain stimulation has emerged and is rapidly developing—musical stimulation with feedback.

The purpose of this review is to summarize the available experimental data on the conditions and features of various types of closed-loop musical stimulation. The review mentions the unique properties of music, which underlie the therapeutic effects of musical stimulation. Also discussed is the usefulness of closed-loop musical stimulation in solving the problem of adequate selection of musical stimuli to increase the effectiveness of music therapy.

The nature of music and music’s healing properties

The language of music is characteristic not only of its sensual nature, but also of its extreme abstractness. Music is devoid of cognitive constant of speech (Solntsev, 1974), and visible images and gestures. Despite the abstractness, music is able to generate complex emotions (Juslin & Sloboda, 2010; Sachs et al., 2016). Music as the “art of combining tones in a manner to please the ear” (de Divitiis, 2010) can improve the well-being and quality of human life (MacDonald, 2013). Listening to music influences the brain neurochemistry (Chanda & Levitin, 2013) and synchronizes biological rhythms (Laffont & Dalla Bella, 2018). Music can distract the listener from negative experiences and sensations such as pain (Nilsson, 2008), anxiety, and sadness (Koelsch, 2009).

The beneficial effect of music has been known since ancient times. Today, music therapy helps patients with Parkinson’s disease (Ashoori et al., 2015), dementia (Lam et al., 2020), and Broca’s aphasia (Norton et al., 2009). Music is effective for the alleviation of pain (Gogoularadja & Bakshi, 2020) and restoring cognitive function after stroke (Särkämö et al., 2008). A new and promising area of musical neurostimulation with feedback shows advantages in the correction of psychogenic disorders and cognitive rehabilitation (Fedotchev & Bondar’, 2022). A more effective use of music in rehabilitation and the development and adjustment of parameters to achieve desired therapeutic effects can benefit from the highlighting the relationship between methods of music therapy and the neuropsychology of music.

One of the problems in studies that use musical stimuli is the uncertainty of definition of “what music is.” This problem corresponds to the uncertainty of definition of “what consciousness is.” Before describing the categories of musical stimuli in studies in music therapy, we offer a short outline of the understanding of music in terms of music psychology.

The main parameters of “conventional” music (for example, a favorite melody) comprise of musical sounds and rhythm. In other words, two main dimensions of music are the space of musical sounds (tonal space) and arrow of time. As soon as the human mind recognizes the presence of music (as compared to speech or industrial sounds), the mind instantly generates a perceptual schema for reading melodic information. This perceptual schema, or system of reference, is known informally as a musical scale (Jordan & Shepard, 1987). Listeners sense the scale intuitively, without any formal training (Dowling & Harwood, 1986). The most important feature of a scale is the hierarchy of tonal attraction (Krumhansl & Kessler, 1982). As soon as the mind senses a given musical sound’s status in the tonal hierarchy, the sound becomes a tone in the tonal space. The phenomenon of the tonal status manifests a transition from the acoustics of sound—when a given sound’s physical characteristics of amplitude, frequency, and duration can be explained with numbers—to a space of music, where all acoustical characteristics acquire their meaning in relation to the logic of musical image and form. In music philosophy, the presence of tonal attraction by way of stable and unstable tones is called the phenomenal tonal gravity (Scruton, 1997). The intuitive sense of tonal space is available to the human mind only.

Melodic fabric of music consists of the consonant and dissonant intervals, which are distinct by the extraordinary simplicity of their psychophysical foundations (Bowling & Purves, 2015; Korsakova-Kreyn, 2019). Studies of the auditory system responses at the brainstem level (Bidelman & Krishnan, 2009, 2011) show that the responses are more coherent for consonances compared to dissonances. The integration of the listener’s reactions to the melodic elements and patterns of tonal relationships, encased in rhythm and delivered with expressive timing, conveys the “logic of emotion” (Langer, 1942). An emotional response to a favorite music (whether in a major or a minor mode) activates the biological reward system (Blood & Zatorre, 2001; Sachs et al., 2016). Listening to music influences skin conductance (Khalfa et al., 2002; Vanderark & Ely, 1993), heart and breathing rate (Bernardi et al., 2009), and causes piloerection (goosebumps) (Grewe et al., 2007; Panksepp & Bernatsky, 2002).

Research into the psychophysics of melodic matter gives us important insights into the source of emotion in music. Namely, studies of brainstem frequency-following response to melodic elements (Bidelman & Krishnan, 2009, 2011) and behavioral studies of the perception of motion in tonal space (Bigand et al., 1996; Korsakova-Kreyn & Dowling, 2014) point to the importance of the gradient of perceived tonal tension (Fredrickson, 1995; Krumhansl, 1997; Lerdahl & Krumhansl, 2007). Tonal tension emerges as the basic morphological principle in music. When listening to music, the perception of tonal-temporal patterns is accompanied by the parallel changes in muscle tone (Madsen & Fredrickson, 1993), which brings music into the realm of embodied cognition (Foglia & Wilson, 2013; Korsakova-Kreyn, 2019; Varela et al., 1991). According to the Archaic Model of Music Perception (Korsakova-Kreyn & Dowling, 2014), emotions in music are closely related to the instantaneous somato- and viscero-motor reactions produced by a tonal-rhythmic program of a given musical composition. The perception of tonal patterns transmutes into emotion by simulating the most primitive and basic reactions of the living organisms—physical tension and release from tension.

Over the past century and a half, the language of music has expanded and acquired new harmonies, as well as new artificial schemas for composing music. Yet, for the vast majority of people, music remains a world of melodies, rhythms, and harmonies shaped in the tonal time-space. The perception of tonal music taps directly into our deepest neurobiology (Virtala & Tervaniemi, 2017), bypassing the intellectual demands required, for example, for understanding complex mathematical equations.

Today, music therapy uses stimuli of three levels of complexity. For the restoration of cognitive function after stroke, pain management, and for patients with Parkinson’s disease, music therapy usually employs musically logical forms, such as entire musical compositions or musically meaningful excerpts. By contrast, rehabilitation of patients with Broca’s aphasia involves prosody on two-three different notes, which does not reach the complexity of a musical form. Closed-loop musical stimulation typically uses music-like signals, which means that these stimuli are devoid of tonal syntax and structure. Nevertheless, closed-loop musical stimulation produces effects that reflect on human consciousness, albeit in a fragmentary way. Despite the detachment of music-like signals from the creative powers of the informed human mind, these signals are within the range of human hearing and incorporate the basic elements of music. Similar to regular music, closed-loop musical stimulation uses the intrinsic potential of sound.

Music therapy and closed-loop musical stimulation

From the point of view of the psychology of music, we can assume that closed-loop musical stimulation excites and makes explicit the ancient layers of proto-music. The reactions that listeners experience during sessions of closed-loop musical stimulation indicate the underlying source of music’s influence on human mind and feelings. Moreover, the flexible variability of music-like signals in response to the resonance-generated requests of the brain and heart (Fedotchev, Parin, et al., 2019) may present an evidence of the archaic layer of interaction between the hearing system and the human mind. Evolutionary, this interaction had led to the bifurcation of animalistic vocalization into the cognitive constants of speech and proto-music, the latter grounded in the emotional component of vocalization.

There is also a special connection between the healing properties of flexibility of heart rhythms, generated by EEG- and heart-controlled adaptive neurostimulation (Cheung et al., 2016; Fedotchev, Parin, et al., 2019; Fedotchev et al., 2023) and the flexibility of tempo and rhythm in music, which is known as expressive timing. The heartbeat responsiveness, produced by adaptive neurostimulation, is associated with the healthy variability of heart rhythms, and this undoubtedly contributes to the healing properties of closed-loop music stimulation. In addition, closed-loop musical stimulation can produce quasi-psychedelic effects (personal experience) indicating possible activation of the endogenous opioid system (Parin, 2022). The mentioned properties of music and the research in closed-loop musical stimulation suggest that the use of musical stimuli as a feedback signal generated by the significant-for-humans EEG components can achieve pronounced therapeutic effects (Blain-Moraes et al., 2013; Fedotchev et al., 2018).

One of interesting aspect of closed-loop musical stimulation is its synesthetic effect (Ramachandran & Hubbard, 2003), when listeners’ brains respond to music-like cues with images of abstract color patterns (Fedotchev, Parin, et al., 2019; Fedotchev, Zemlyanaya, et al., 2019). Music pedagogy commonly uses quasi-synesthetic definitions, such as cold, bright, and warm to describe musical harmonies and general character of music, yet these definitions have been tacitly accepted as metaphors. However, recent studies demonstrated that music perception involves a stable synesthetic component (Korsakova-Kreyn & Dowling, 2014).

By modulating the activity of the emotional sphere, music can play a positive role in the treatment of many psychiatric and neurological disorders (Brancatisano et al., 2020; Koelsch, 2014). The therapeutic effects allow us to classify music as a universal tool for cognitive therapy (Altenmüller & Schlaug, 2015; Gray, 2013; Korsakova-Kreyn, 2019). Important advantages of music therapeutic effects are non-invasiveness, the practical absence of contraindications and focus on the central regulatory mechanisms of the brain. Despite the obvious advantages and widespread use, music therapeutic interventions also have some disadvantages that limit their effectiveness. The main limitation of traditional music therapy interventions concerns the selection of music. Because the music listener’s personal characteristics significantly modulate neuronal responses to emotions expressed by music (Park et al., 2013), this requires individual selection of musical compositions for each patient (Höller et al., 2012; Schroeder et al., 2018; Wakim et al., 2010). An acceptable solution to this problem was experimentally demonstrated by presenting music that is individually adapted to the rhythmic processes of the patient’s brain (Müller et al., 2014). Having shown that musical therapeutic interventions can be more effective if they are organized in strict accordance with the bioelectrical characteristics of the patient’s nervous system, these and other data became the basis of a new progressive direction in neurophysiology—closed-loop musical stimulation.

Achievements and prospects of closed-loop musical stimulation

To date, the advantages of using musical stimulation automatically controlled by feedback signals from human physiological parameters for the effective correction of psychogenic and stress-induced states, as well for elimination the consequences of neurological disorders have been demonstrated in a number of works which are presented in Table 1.

Table 1.

Development of closed-loop methods of musical stimulation.

Condition	Kind of stimulation	Feedback parameter	Reference
Management of anxiety and stress states	“Biomusic”	Electrodermal activity + skin temperature + heart and respiratory rhythms	Cheung et al., 2016
Bioacoustic correction of functional state	Musical-acoustic stimulation	Peak EEG frequencies in 1–30 Hz range	Konstantinov et al., 2016
Elimination of stress consequences	Classical music	Narrow frequency (0.6 Hz) alpha EEG oscillators	Fedotchev et al., 2017
Treatment of movement disorders	Music-like stimulation	Alpha and mu EEG rhythms	Deuel et al., 2017
Functional state correction	Classical music + “Music of the brain”	Narrow frequency (0.6 Hz) alpha EEG oscillators	Fedotchev et al., 2018
Relaxation state induction	Music-like stimulation	Heart rate variability	Yu et al., 2018
Correction of functional disorders	“Music of the brain”	Alpha EEG oscillators + heart rate	Fedotchev, Parin, et al., 2019
Emotional state regulation	Synthesized affective music	Theta, alpha, beta, gamma EEG rhythms	Ehrlich et al., 2019
Elimination of stress consequences	“Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Fedotchev, Zemlyanaya, et al., 2019
Cognitive rehabilitation for stroke	“Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Mukhina et al., 2021
Treatment of post-traumatic stress and burnout	“Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Fedotchev, Parin, Polevaya & Zemlyanaya, 2021
Bioacoustic correction of functional state	Musical-acoustic stimulation	Peak EEG frequencies in 1–30 Hz range	Ivanova & Kormushkina, 2021
Correction of anxiety and depression states	Music-like & photic stimulation	Narrow-frequency EEG components	Pino, 2022
Treatment of post-covid syndrome	“Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Polevaya et al., 2022
Bioacoustic correction of functional state	Musical-acoustic stimulation	Peak EEG frequencies in 1–30 Hz range	Shchegolkov et al., 2022
Correction of stress-induced disorders	“Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Fedotchev et al., 2022
Cognitive rehabilitation of high-tech specialists	“Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Fedotchev, 2022
Correction of stress-induced disorders	Resonance scanning & “Music of the brain” & photic stimulation	Alpha EEG oscillators + heart rate + native EEG	Fedotchev et al., 2023

For example, the “Biomusic” neural interface was developed to translate the listener’s physiological parameters into various music-related attributes; namely, the “Biomusic” translates heart rate into the sounds of a drum, a breathing rhythm into rhythmic whistles reminiscent of exhalation sounds, the electro-cutaneous activity into a melody, and skin temperature into a triad representing a tonality (Cheung et al., 2016). The authors argue that this kind of computerized system holds promise for real time monitoring of the subject’s emotional state (Fedotchev, Parin, & Polevaya, 2021).

Using another neural interface, named “Unwind,” it has been shown that pronounced relaxation states could be effectively achieved through complex musical and acoustic influences automatically controlled by the patient’s ongoing heart rate variability (Yu et al., 2018).

The computer transformations of brain biopotentials into music-like signals has become one of the most important directions for the development of musical stimulation with feedback. For example, a method of bioacoustic correction presents a person with music-like signals obtained through computer transformation of the person’s brain EEG components (Konstantinov et al., 2016); this method allows a person to “hear” his/her brain activity in real time, and it induces the correction of the person’s unfavorable functional states during the disorders of the cognitive and emotional-volitional sphere (Ivanova & Kormushkina, 2021; Shchegolkov et al., 2022).

For the stroke patients, the attributes of cognitive rehabilitation, including the progressive improvement of executive and motor functions, could be achieved by presenting the patients with music-like signals automatically generated by computer transformation of the patients’ occipital alpha rhythm of the EEG or the sensorimotor mu rhythm of the EEG (Deuel et al., 2017). Another musical neural interface technology uses the listener’s EEG to automatically generate a synthesized affective music, which allows the listener to track subconsciously his/her own brain oscillations and induce neuroplasticity, cognitive rehabilitation, and improve brain function (Ehrlich et al., 2019). The alleviation of anxiety and depression is observed when a combination of music-like stimuli and light stimuli are automatically controlled by feedback signals from narrow-frequency spectral components of the EEG (Pino, 2022).

During the development of the “Brain Music” project (Fedotchev et al., 2018), researchers utilized their previous studies in suppression of stress-induced conditions. The project employs two types of musical stimulation. The first type stimulation uses classical music, the volume of which is controlled in real time by the amplitude of the subject’s dominant narrow-frequency (0.6 Hz) oscillator from the alpha range (8–13 Hz) of the EEG (Fedotchev et al., 2017). During the second type musical stimulation, the changing amplitude of the patient’s alpha EEG oscillator is converted by a computer into music-like signals resembling the sounds of a flute and smoothly varying in pitch and intensity (Fedotchev et al., 2018). The final version of the “Brain Music” project uses a composite feedback from the EEG and the heart rhythm, when the smooth variation of flute sounds is complemented by weak clicks corresponding to the patient’s heartbeat; the introduction of rhythm increased the musicality of the stimulation (Fedotchev, Parin, et al., 2019). Due to the involvement of interoceptive signals, the developed method plays an important role in maintaining optimal physical, emotional and mental health in a treatment process of a person (Quadt et al., 2018). It was demonstrated that a single application of the “Brain Music” method to subjects in a state of tension and stress leads to an increase in the power of the EEG alpha rhythm relative to the background; these changes of the EEG parameter were accompanied by an increase in the indicators of well-being and mood and a decrease in the degree of emotional maladaptation and the level of stress. Subsequently, the described method of musical stimulation controlled by the biopotentials of the brain and heart, was improved by adding a second feedback loop of rhythmic light stimulation based on the patient’s EEG, thus creating two simultaneous hetero-modal feedback loops (Fedotchev, Zemlyanaya, et al., 2019). Among the advantages of this method are the high personalization and effectiveness of therapeutic procedures due to the use of feedback from a person’s own bioelectric characteristics, the involvement of the mechanisms of multisensory integration, and the involvement of neuroplasticity and resonance mechanisms of the brain in the processes of normalization of the functional state under stimulation.

Overall, this method of musical stimulation uses the automatic (without the patient’s conscious efforts) management of therapeutic sensory stimulation, which makes it possible to apply adaptive neurostimulation to correct the unfavorable functional states in patients with an altered level of consciousness, elderly people, and children (Fedotchev et al., 2022). Our studies in closed-loop musical stimulation do not require any conscious efforts from the patients. The patients’ task is to sit comfortably with their eyes closed and to passively perceive sensory stimuli. Up to date, about 150 participants in our studies have rated the experimental sessions very positively, indicating that the “original music of the brain” was pleasantly complemented by the shimmering multi-colored background perceived by the closed eyes.

The developed music-light neurointerface was successfully used for cognitive rehabilitation of patients with stroke (Mukhina et al., 2021), the alleviation of post-traumatic stress and professional burnout (Fedotchev, Parin & Polevaya, 2021), the correction of stress-induced disorders (Fedotchev et al., 2022), and in cognitive rehabilitation of high-tech specialists (Fedotchev, 2022).

Recent research suggests a new promising direction toward creating efficient methods of feedback neurostimulation. Since EEG-guided adaptive neurostimulation is based on the automatic modulation of sensory stimulation by a person’s own rhythmic components of the EEG, one of the possible ways to increase the EEG-guided adaptive neurostimulation effectiveness can be the preliminary strengthening of the modulating factor, i.e., a subject’s EEG signal. For this purpose, researchers use the resonance scanning technique. Resonance scanning consists of LED photostimulation with a step-by-step increasing frequency from 4 to 20 Hz by 0.2–0.4 Hz steps, that is, the frequency is slowly increased within the range of theta, alpha and beta EEG rhythms. It has been shown that preliminary resonance scanning significantly increases the effectiveness of EEG-guided adaptive neurostimulation in the treatment of post-Covid syndrome (Polevaya et al., 2022) and in eliminating the effects of exam stress in university students (Polevaya et al., 2023). Even a single therapeutic intervention, using the resonant scanning in combination with EEG-controlled adaptive neurostimulation, produced an increase in the power of the EEG alpha rhythm accompanied by a decrease in stress levels and an improvement in the emotional state and indicators of cognitive activity. These indicators were due to the progressive involvement of the resonance and integration mechanisms of the brain and the mechanisms of neuroplasticity. This suggests that the combination of exogenous (resonance scanning) and endogenous (EEG-controlled light-music stimulation) oscillations presents a promising approach to the development of effective tools for the correction and rehabilitation of the human functional states (Fedotchev et al., 2023).

Conclusion

The review demonstrates that musical neurostimulation with feedback is an actively developing and promising area of neurophysiology. Considering the relative novelty of the therapeutic use of the closed-loop stimulation, the existing studies don’t yet provide the data on the long-term duration of the closed-loop musical stimulation’ effects. Current studies in closed-loop musical stimulation have some other limitations—such as the small number of patients in experimental groups, the absence of control groups of subjects, the lack of dynamic observations, etc. However, this line of research is characterized by a number of advantages, such as its high personalization, independence from the subject’s motivation and the involvement of basic regulatory processes of the brain in therapeutic procedures. Overall, research in closed-loop musical stimulation offers innovative methods in cognitive rehabilitation.

According to the analysis of the presented studies, the greatest effectiveness is shown by those methods that use computer transformations of the body’s endogenous rhythms—such as the breathing rhythm, heartbeat rhythm, and EEG rhythms—into music-like signals. Complex feedback from these endogenous rhythms ensures the participation of interoceptive signals that are significant for the mechanisms of multisensory integration, neuroplasticity, and resonance in the human brain. Thanks to the combination of unique psychophysiological properties of music and the dynamics of brain microstates through the use of control signals from the current values of endogenous rhythms, closed-loop musical stimulation allows to achieve a high degree of personalization and the effectiveness of therapeutic interventions. The automatic modulation of music-like signals by the ongoing EEG parameters appears as a particularly promising line of research. The subconscious control and modulation of therapeutic music-like features allows researchers to use EEG-controlled musical stimulation in conditions that do not require conscious efforts of the subjects, which is especially important when conducting therapeutic sessions with children and patients with altered mental states or when drug therapy is contraindicated.

The discussed advantages of closed-loop musical stimulation methods open up broad prospects for their use in the correction of psychogenic disorders and cognitive rehabilitation. In future research, the most promising areas are optimization of resonance scanning parameters, simultaneous use of several rhythmic processes of the patient as modulating feedback factors, and improvement of the algorithm for converting these rhythmic processes into “brain music.” All this will increase the effectiveness of the developed technologies for their use in a wide range of rehabilitation procedures.

Footnotes

ORCID iD

Marina Korsakova-Kreyn

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work was supported by the Russian Science Foundation, grant No. 22-18-20075.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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