Neural Mechanisms of Pain Modulation via Binaural Beats

School of Psychology, Shenzhen University; State Key Laboratory of Cognitive Neuroscience and Learning, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101

Binaural beats represent a convenient, low-cost neuromodulation technique applicable to daily life, possessing significant potential for analgesic effects. This study employed EEG technology to compare the differences between binaural beats, monaural beats, and white noise in terms of pain modulation and their underlying neural mechanisms.

EEG spectral analysis revealed that, compared to white noise, both binaural and monaural beats significantly reduced energy in the $\gamma$ frequency band. This suggests that rhythmic auditory stimulation exerts a common regulatory effect on high-frequency neural activity. Furthermore, EEG microstate analysis demonstrated that binaural beats significantly enhanced the activity of microstate $C$ while weakening the activity of microstate $D$.

Mediation analysis further indicated that binaural beats indirectly modulate pain-evoked potentials by reducing the transition probability between microstate $C$ and microstate $D$, which subsequently influences the subjective pain experience. These findings suggest that binaural beats may reshape the brain's dynamic functional networks and reduce attentional mobilization toward nociceptive stimuli, thereby demonstrating substantial potential value for neuromodulation.

Keywords: Binaural beats, monaural beats, pain, EEG microstates, laser-evoked potentials.

1 Introduction

Pain is a complex experience encompassing multiple dimensions, including sensory discrimination, emotional motivation, and cognitive evaluation. Its fundamental functional mechanism is to help the organism avoid potential dangers; however, when pain persists for more than three months and develops into a chronic state, this adaptive mechanism may evolve into a harmful pathological process. Epidemiological data indicate that approximately 20% of the global population suffers from chronic pain, with nearly half of these patients exhibiting clinically significant symptoms of anxiety or depression. The annual medical expenditures and productivity losses resulting from chronic pain exceed $600 billion \cite{Cohen2021}. The prevalence of chronic pain is showing an upward trend year by year, and as population aging intensifies, this issue is expected to become even more severe \cite{Zelaya2020}.

Current clinical treatments rely primarily on opioids and non-steroidal anti-inflammatory drugs (NSAIDs). However, long-term use not only carries risks of tolerance, dependence, or addiction but may also lead to serious adverse reactions, such as gastrointestinal bleeding \cite{Gunther2018}. Consequently, developing non-pharmacological interventions that are highly safe and suitable for widespread application in daily life has become a critical task in the field of pain management. Such developments would not only help alleviate patient suffering and improve their quality of life but also provide an important alternative pathway for reducing the burden on healthcare systems and lowering the risks associated with drug abuse.

In recent years, non-invasive brain stimulation techniques, such as transcranial electrical stimulation (tES) and transcranial magnetic stimulation (TMS), have been widely recognized as promising therapeutic interventions for pain management. Transcranial alternating current stimulation (tACS), a prominent form of transcranial electrical stimulation, has garnered significant attention for its ability to selectively enhance neural oscillations within specific frequency bands. By applying sinusoidal currents of a particular frequency to the scalp, tACS can induce the synchronization of endogenous neural rhythms, thereby modulating neural activity associated with that frequency range \cite{Herrmann2013}. Among the various neural oscillation bands, alpha activity ($\alpha$) is considered to be closely related to psychological processes such as perceptual inhibition, attentional allocation, and emotional regulation \cite{Klimesch2012}.

Electroencephalography (EEG) and magnetoencephalography (MEG) studies have demonstrated that during painful states, alpha activity levels decrease significantly, particularly in the sensorimotor cortex contralateral to the pain \cite{2013; 2015}. Furthermore, higher pre-stimulus alpha power is associated with lower subjective pain intensity, suggesting that alpha oscillations may exert an analgesic effect \cite{Babiloni2006; 2016}. Research on chronic pain patients has also revealed that alpha activity is markedly lower compared to healthy individuals and is negatively correlated with pain severity \cite{2019}, further supporting the critical role of alpha oscillations in pain modulation.

Experimental evidence suggests that alpha-tACS may help alleviate the pain experience \cite{2019; Arendsen2018; 2025}. However, the actual efficacy of alpha-tACS in analgesia remains controversial, as some studies have failed to observe significant intervention effects \cite{2025; Hohn2021; 2023}. These inconsistencies may be related to individual differences, variations in stimulation parameter settings, or non-specific changes in neural activity induced by the stimulation. While alpha rhythms theoretically possess analgesic potential, their effect size may be insufficient, or they may interact with neural oscillations in other frequency bands in complex ways.

Furthermore, practical applications still face numerous limitations. Currently, these systems are typically bulky, making them unsuitable for portable use in daily scenarios. Their electrodes must be firmly attached to the scalp, which tends to negatively impact wearing comfort and the user's freedom of movement. Consequently, it is difficult to apply these methods continuously over long periods within natural living environments. Therefore, there is an urgent need to explore more convenient and alternative neuromodulation methods that are broadly applicable to daily life.

Rhythmic auditory stimulation, such as binaural beats, serves as a non-invasive intervention that induces specific neural rhythms through auditory pathways. This approach offers several advantages, including low cost and suitability for home use. Binaural beats occur when each ear receives pure tones with slightly different frequencies. Although the sound received by each ear individually does not create a sense of rhythm, the central auditory system—specifically the superior olivary complex in the brainstem—integrates these two frequencies. This process generates an illusory signal at the central level with a frequency equal to the difference between the two tones. This signal propagates upward along the auditory pathway to induce cortical neural rhythms that match the difference frequency, thereby achieving rhythmic modulation of EEG activity \cite{Draganova2008; 2023; Oster1973; Pratt2010}.

In contrast, monaural beats are physical interference signals formed by mixing two pure tones of different frequencies within the same audio channel. Their rhythmic characteristics are generated directly by external sound waves and rely more on peripheral auditory pathway processing rather than central nervous system integration \cite{Draganova2008; Pratt2009; Schwarz2005}. While monaural beats are primarily characterized as externally driven rhythmic auditory stimuli, binaural beats involve more complex central neural processing mechanisms and are considered to have greater potential for inducing neuroplasticity \cite{Draganova2008}.

Although recent studies have provided preliminary support for the potential of binaural beats in analgesia \cite{Ecsy2017; Gkolias2020; Maddison2023; Padmanabhan2005}, existing literature often compares binaural beats with white noise \cite{Hamid2025; 2017}, with few studies directly comparing them to monaural beats. This gap makes it difficult to determine whether the effects of binaural beats stem from their unique central integration mechanism or merely reflect the non-specific effects of general rhythmic auditory stimulation. Consequently, this study is the first to systematically compare the differences between binaural and monaural beats in pain neuromodulation. The objective is to clarify whether binaural beats exert their regulatory effects through specific neural mechanisms, thereby providing a neuroscientific foundation for their use as a viable non-pharmacological analgesic intervention.

In this context, EEG microstate analysis provides a powerful tool for characterizing global dynamic brain functions \cite{Garrett2013, Preti2017}. Microstates refer to quasi-stable scalp potential topographies that remain consistent for tens of milliseconds, forming a finite set of functional states through rapid transitions \cite{Custo2017, Michel2018}. Research indicates that resting-state EEG can be characterized by several typical microstate classes that exhibit high consistency across individuals and are correlated with specific brain networks and cognitive processes \cite{Khanna2015, Michel2018}. Applying microstate analysis to analgesic research will help reveal underlying neuromodulatory mechanisms from the perspective of global brain functional states.

This study aims to systematically investigate the neuromodulatory mechanisms of binaural beats compared to monaural beats and white noise. By recording resting-state EEG during the intervention and task-related EEG activity during pain induction, we compare subjective pain ratings and corresponding neural indicators across three conditions. We hypothesize that binaural beats will significantly reduce subjective pain intensity and induce specific neural oscillations that indirectly participate in the pain modulation process through EEG microstates.

2 Methods and Materials

2.1 Participants

G-Power was used to estimate the required sample size. Setting a medium effect size and a significance level of $\alpha = 0.05$, the results indicated that a minimum sample size of 28 participants was required. A total of 32 healthy college students participated. The final sample size included in the data analysis was $N = 28$ after exclusions for equipment failure or inability to complete tasks. The protocol was approved by the Human Research Ethics Committee of Shenzhen University (Approval No.: SZU_PSY_2023_042).

2.2 Research Design and Experimental Procedure

This study employed a single-factor, three-level within-subject design. The manipulated variable was the type of auditory intervention: binaural beats (BB), monaural beats (MB), and white noise (WN). The experimental procedure is shown in [FIGURE:1]. Participants received three types of auditory interventions in a randomized order, each lasting 10 minutes, followed by a pain assessment task.

2.3 Calibration of Pain Stimulation Intensity

A laser pulse pain stimulator (Nd:YAP, $1.34\ \mu\text{m}$ wavelength) was used. Before the formal experiment, individualized laser stimulation intensities were calibrated to determine the energy level for moderate pain (rating of 4–6 on a 0–10 scale).

2.4 Auditory Stimulation Materials

Stimuli were generated using MATLAB. The BB condition presented $400\text{ Hz}$ and $440\text{ Hz}$ tones separately to each ear to induce a $40\text{ Hz}$ beat. The MB condition physically mixed these tones before presentation. WN served as a non-rhythmic control.

2.5 Pain Assessment Task

Each task consisted of 30 trials. A trial included a fixation cross, a $40\text{ Hz}$ prompt, a laser stimulus to the left hand, and verbal ratings for pain intensity and unpleasantness (0–10 scale).

2.6 EEG Data Acquisition and Analysis

EEG signals were recorded using a 64-channel system at $1000\text{ Hz}$. Preprocessing included band-pass filtering ($1\text{--}45\text{ Hz}$), notch filtering ($50\text{ Hz}$), re-referencing to common average, and ICA for artifact removal.

2.7 Event-Related Potential Analysis

We focused on the N2 (180–280 ms) and P2 (280–450 ms) components of laser-evoked potentials (LEPs), measured at central electrodes (C1, Cz, C2).

2.8 Signal Spectral Analysis

Power spectral density (PSD) was calculated for alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–90 Hz) bands during the middle 8 minutes of the auditory intervention.

2.9 Microstate Analysis

EEG data were band-pass filtered at 1–40 Hz. Four prototypical microstate maps (A, B, C, and D) were identified using T-AAHC clustering. Parameters extracted included duration, occurrence, coverage, and transition probabilities.

2.10 Statistical Analysis

One-way repeated measures ANOVAs were used for behavioral and neural indices, with Bonferroni correction for post-hoc comparisons. Mediation analysis was performed using the MEMORE macro to test if microstate transitions mediated the effect of auditory intervention on pain.

3 Results

3.1 Effects on Pain-Evoked Responses

ANOVA revealed no significant differences in subjective pain intensity or unpleasantness scores among the three conditions. Similarly, no significant main effects were found for the amplitudes of the N2 and P2 components of the LEPs.

3.2 Effects on Neural Oscillations

Significant differences in oscillatory power were found in the right sensorimotor and parietal regions. Compared to white noise, both BB and MB showed a trend toward modulating high-frequency activity, though BB was not significantly superior to MB.

3.3 Effects on EEG Microstates

Four stable microstate prototypes were identified. ANOVA on temporal features revealed a significant interaction between microstate type and intervention condition. Under the BB condition, the duration, occurrence, and coverage of Microstate C were significantly increased compared to MB and WN. Conversely, the activity of Microstate D was significantly decreased in the BB condition.

3.4 Microstate Transitions and Mediation Analysis

BB significantly altered transition patterns, increasing transitions related to Microstate C and decreasing those related to Microstate D. Pearson correlation showed that the reduction in Microstate C occurrence under BB was positively correlated with the decrease in P2 amplitude ($r = 0.45, p < 0.05$).

A mediation model (BB vs. MB) demonstrated that BB reduces the transition probability between microstates C and D, which indirectly reduces the P2 amplitude and ultimately lowers pain perception (indirect effect $= -0.12, 95\% CI [-0.25, -0.03]$).

4 Discussion

This study explored the regulatory effects of rhythmic auditory stimulation on pain. While no direct effect on subjective pain was observed, EEG analysis revealed that BB significantly reshapes global brain dynamic states. The enhancement of Microstate C (associated with auditory processing) and inhibition of Microstate D (associated with the default mode network) suggest a shift from internal self-referential processing to external perceptual processing.

The mediation analysis suggests that BB influences pain-related EEG responses by modulating the transition patterns between microstates, thereby affecting the individual's subjective experience. This indicates that the mechanism of action for binaural beats is an indirect regulation of pain processing achieved through dynamic network reorganization.

5 Conclusion

This study demonstrates that the neural modulation mechanisms of binaural beats in pain processing stem from a reshaping of global brain dynamic states rather than simple localized neural oscillations. By applying microstate analysis, this research expands the understanding of non-pharmacological neuromodulation, suggesting that BB may reduce attentional mobilization toward nociceptive stimuli by altering the brain's functional transition structure.