The ability of sound to influence the intensity of physical pain and soothe the nervous system was noticed as far back as ancient Greece. Theoretical references to music therapy can be found in the writings of early philosophers such as Pythagoras, Plato, and Democritus. Thus, Xenocrates of Chalcedon, a student of Plato, used playing musical instruments to relieve his patients from hysteria (now this diagnosis is not used, so it is difficult to say exactly what symptoms the melodies helped with).
Over the years, music therapy has evolved from an intuitive practice into a formalized discipline with recognized therapeutic effects. The foundation of modern sound therapy was laid by Alfonso X of Castile and Eva Wesselius: after the First and Second World Wars, doctors noticed that instrumental music—both played by musicians and reproduced in recordings—had a positive effect on the mental health of soldiers and helped to alleviate the symptoms of PTSD until they disappeared completely.
These observations initiated active clinical research into the effects of sound on the human body. With the expansion of the scientific base, approaches to therapy have also changed—now, instead of singing bowls and musical instruments, electronic sounds are used, which can be tuned to a certain frequency and adapt their rhythm and pattern.
How Sound Affects the Body
The main role in music therapy is played by the frequencies with which sound interacts with the human body. These are the so-called alpha (8–13 Hz) and theta waves (4–8 Hz), which affect certain parts of the brain.
- Limbic system – this includes the hippocampus, amygdala, and prefrontal cortex. These areas are associated with the regulation of emotions, memory, and the ability to cope with stress.
- The vagus nerve is the tenth pair of cranial nerves, which regulates the body's involuntary actions: heart rate, respiration, and digestion. Its stimulation, depending on frequency and intensity, triggers a "be-run" reaction when heart rate and breathing increase or a relaxation reaction when they, on the contrary, slow down. This nerve plays an important role in maintaining the overall physical balance of the body, and research shows that it affects the intensity of pain sensations.
- The insula is a brain structure that is responsible for sensing internal body signals (interoception) from the vagus nerve. These include heart rate, breathing, temperature, and muscle tension. The insula translates these signals into subjective sensations, such as feelings of anxiety, relaxation, or discomfort. For example, its hyperactivity is linked to anxiety and depression, and proper stimulation helps it relax and reduce the production of cortisol, the hormone responsible for stress.
During sound therapy, the patient is usually in a special room isolated from external noises and listens to a given set of sounds of different frequencies and durations in headphones for a certain period of time. To visualize how such soundscapes work, you can go to special sections of the Headspace or Brainwaves apps.
Sound therapy uses binaural rhythms, an auditory phenomenon that occurs when a sound is played at a slightly different frequency for each ear, to affect different parts of the brain. When the brain perceives these tones, it finds a third frequency, the binaural rhythm, which affects the activity of the different lobes.
For example, if the left ear plays a sound with a frequency of 20 Hz and the right ear plays a sound with a frequency of 15 Hz, the brain will synchronize them with each other, adjust to the difference, and perceive it at a frequency of 5 Hz, which corresponds to the theta wave.
Practical Limitations
While music therapy is already being used to alleviate symptoms of chronic pain, recovery from surgery, autism spectrum disorders, depression, PTSD, and other conditions, it remains a treatment method available to a limited number of patients. And the problem is not just a shortage of healthcare providers.
The effectiveness of sound therapy depends on many factors: the physiological and psychological state of the individual patient, the duration of the sessions, and the context of the treatment. This is where the problem of personalization arises.
Current approaches rely on generic treatment protocols for each specific diagnosis and do not take into account individual patient characteristics and processes that occur during treatment. For example, heart rate variability (HRV), skin-galvanic response (GSR), and the patient's neural patterns.
At the same time, reactions to sound stimuli can vary considerably from person to person, depending on their physiological and mental state—even if they are people with the same diagnosis.
In addition, existing approaches do not take into account the state of the gut microbiome. Current research shows that this factor significantly affects neuroplasticity and anxiety levels. This reduces the effectiveness of therapy.
How AI Is Helping To Personalize Sound Therapy
Artificial intelligence analyzes the patient's psychological and physical state—HRV, GSR, skin temperature, EEG data—and, according to them, adapts the frequency, rhythm, and volume of sound stimulation to the patient's requirements.
The neural network receives this data through wearable devices—bracelets, rings, or pendants that monitor a patient's breathing, heart rate, skin temperature, vagus nerve activity, insula, and other reactions. They sync with a mobile app and transmit the data for analysis by AI, which customizes the soundscape.
For example, AI can monitor amygdala hyperactivity (responsible for anxiety) and stimulate theta rhythms to suppress it. In addition, the neural network can take into account data about the state of the microbiome to tailor therapies. For example, if the microflora is imbalanced, the vagus nerve may be less active, requiring a change in sound parameters.
The integration of sound therapy with artificial intelligence (AI) is opening new horizons for neuroplastic rehabilitation, relying on technologies such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). Advanced deep learning algorithms analyze data in real time, allowing therapy parameters such as frequency, amplitude, and rhythm of sound to be tailored to individual patient characteristics. For example, therapy using gamma rhythms (30–100 Hz) has been shown to improve cognitive function by 20% in Alzheimer's patients, while alpha rhythm stimulation (8–12 Hz) has been shown to reduce depression by 35%.
Moreover, the integration of heart rate variability (HRV) and vagus nerve activity data can predict treatment efficacy with up to 92% accuracy. Such approaches are already being used in university clinics in Europe, the US and Canada, including projects at the Montreal Neurological Institute, where AI is helping to accelerate motor function recovery after stroke. These advances underscore the potential of sound therapy as a tool for personalized medicine that can change approaches to treating complex neurological and psychosomatic conditions, creating more accurate and effective therapeutic models.
- Researchers at the Montreal Neurological Institute and Hospital are using neural networks to help patients recover from stroke.
- Doctors at Boston University School of Medicine are using AI to generate customized playlists to fight Alzheimer's disease.
- Oslo University is using AI to alleviate symptoms and predict patient responses in therapies for people with autism spectrum disorder.
Endel, an app in which a neural network adapts the music landscape based on data from a fitness tracker to the user's state, time of day, noise level, and other factors and helps them focus, relax, or fall asleep, works in a similar way.
In addition, some companies use sound therapy techniques to increase employee productivity and reduce stress levels in a remote work environment.
Ethics and Risks
Although integrating AI with sound therapy increases its effectiveness and allows its methods to be customized to individual patients, it carries risks that are worth considering.
- Data Privacy. Handling of patient data that is collected from wearable devices must be well-protected and compliant with GDPR and HIPAA protocols.
- Risk of hyperstimulation. Incorrectly selected frequencies can overload certain areas of the brain, so it is important to follow treatment protocols strictly.
- Human supervised therapy. AI should complement, not replace, specialists—neural networks can make mistakes, so it is imperative that a competent worker is involved in the treatment process. Training therapists to work with AI will provide balance and efficiency.
Modern advances in neuroscience and technology offer unique opportunities to integrate sound therapy and artificial intelligence (AI), which allows for more precise investigation of the mechanisms of the effects of acoustic stimuli on the central and autonomous nervous systems. Clinical studies show that adapting sound frequencies using machine learning algorithms can reduce cortisol levels by 30% after the first session, and regular therapy reduces the frequency of anxiety episodes by 40%. The use of heart rate variability (HRV) analysis, skin-galvanic response (GSR), and electrocorticography (ECoG) allows AI to model individual neurophysiological patterns, improving the accuracy of sound stimulation tuning by up to 95%. For example, the use of binaural rhythms in the theta-wave range (4–8 Hz) improves neuroplasticity, which accelerates stroke recovery by 25–30% compared to traditional methods.
In addition, applying these approaches within a neuromodulation paradigm allows for effective treatment of limbic system dysfunctions such as amygdala hyperactivity associated with anxiety and PTSD. These therapies are integrated with the use of wearable devices that collect real-time patient data, minimizing the risks of hyperstimulation and improving treatment outcomes. These innovations represent not only a significant breakthrough in regenerative medicine but also provide the basis for the standardization of personalized therapies, which could significantly improve the quality of life for millions of patients worldwide.
AI integration is helping regenerative medicine become more effective and accessible to a wider range of patients. Technology is changing approaches to treatment and enabling personalized programs that help patients not just get well but take care of their long-term health.
