Music has been the subject of extensive research due to its influence on the modulation of affective and cognitive processes, as well as various neurophysiological reactions in the human brain [1, 2]. Music engages multiple brain structures, including the amygdala, anterior hippocampus, auditory cortex, and even the reward network [3]. Listening to familiar music has been shown to induce stronger synchronization of brain activity, which is associated with enhanced engagement of neural networks and facilitates the execution of nervous system functions [4].

This neural activity can be observed using tools such as electroencephalography (EEG), which detects changes in subcortical emotional response networks triggered by musical stimuli [5]. Functional magnetic resonance imaging (fMRI) also allows for visualization of brain activation and connectivity in response to music [6]. EEG reveals neuronal oscillations that synchronize with the frequency of musical rhythms both simple and complex. Remarkably, this synchronization can persist even after the music stops [7]. Studies comparing musical stimulus frequencies with EEG patterns have demonstrated that brain activity aligns with musical pulses and beats, serving as an objective marker of time perception [8]. On the other hand, fMRI shows how musical stimuli activate interconnected brain structures. These include regions associated with intense pleasure responses, such as the nucleus accumbens, frontal cortex, and auditory cortex. The strength of connectivity between these areas predicts the intensity of the emotional response to music [9, 10]. EEG and fMRI thus provide complementary perspectives on how the brain responds to music.

Importantly, individual responses to music vary depending on musical features and the listener's experience or preference. Musicians exhibit greater functional integration between sensorimotor and action networks, while non-musicians rely more heavily on perceptual networks. This results in increased activation of specific areas in the temporal lobe among musicians, which further intensifies with experience [11, 12]. Additionally, music interpretation is subjective and may trigger different emotional responses in different people, depending on which brain areas are activated such as the hippocampus, parahippocampus, or amygdala [13, 14]. Understanding how music affects brain activity is essential to its clinical and therapeutic applications. Experimental music has been shown to influence activation patterns in brain areas like the prefrontal cortex, limbic system, and thalamus, as well as modulate or inhibit neural oscillations as recorded by EEG and other neuroimaging techniques [15, 16].

The aim of this review is to systematically map and describe the existing literature on how music exposure is associated with changes in brain activity among adults, regardless of the type of music, study setting, or population characteristics. Specifically, we focus on reported neurophysiological responses observed across studies using techniques such as EEG and fMRI, without necessarily comparing music exposure to control conditions. We also consider how these brain activity changes relate to broader cognitive and emotional processes, including neuroplasticity and emotional regulation.

No filters were applied for study design, population, or publication year. Eligible studies were limited to those published in English or Spanish. Additionally, the reference lists of included articles and relevant reviews were hand-searched to identify further eligible studies.

An example of the Boolean logic used (adapted for PubMed) is as follows:

(“Music”[MeSH] OR music OR musical OR song OR melody OR sound stimulation) AND (“Brain”[MeSH] OR brain OR neurolog* OR “brain activity” OR “cerebral cortex” OR “central nervous system”) AND (EEG OR “electroencephalography” OR fMRI OR “functional magnetic resonance imaging” OR neuroimaging OR “brain response”)

Study Selection All retrieved references were imported into a reference management tool (Zotero), and duplicates were removed. The screening process was conducted using the Rayyan web application. Two independent reviewers screened titles and abstracts based on predefined eligibility criteria. Full texts of potentially relevant articles were assessed for inclusion. Discrepancies were resolved through discussion, with the involvement of a third reviewer if necessary..

Data Extraction and Charting: A data-charting form was created in order to extract key information from each included study, including: author and year, study design, population characteristics (including any health conditions and musical training background), details of the musical stimulus (genre, duration, delivery method), the brain activity measurement technique(s) used, and the main outcomes related to brain activity changes. For review articles, we extracted the scope and main conclusions of the review. One reviewer extracted data which was then verified by a second reviewer for accuracy.

A qualitative synthesis was performed, identifying patterns such as common findings and discrepancies between studies. Correlations between brain activity changes and emotional/cognitive outcomes were noted when reported. We also examined differences by subpopulation (e.g., comparisons of younger vs. older adults, musicians vs. non-musicians) and any context-specific effects (such as studies in clinical populations). The review process and reporting followed the PRISMA-ScR checklist [76] (The PRISMA-ScR checklist is provided as Supplementary Material (Tricco et al., 2018), ensuring comprehensive and transparent methods. A PRISMA flow diagram (Fig. 1) illustrates the study selection process.

The search yielded a total of 265 unique records (PubMed: 11; EMBASE: 92; Web of Science: 176). After removing duplicates, 239 titles/abstracts were screened. From these, 60 articles were deemed potentially relevant and were examined in full text. Ultimately, 57 studies met all inclusion criteria and were included in this scoping review (Fig. 1). All included studies were published between 2004 and 2025, with an increase in the number of publications in recent years (notably 2021–2024). Figure 2 below displays the distribution of included studies by year of publication, showing a marked rise in research output on this topic in the last few years. The majority of included articles (72%) were literature reviews (systematic, scoping, or narrative), reflecting the presence of many secondary analyses of music-brain research. The remainder comprised primary studies: 10 were experimental studies (e.g., randomized or quasi-experiments) and 6 were observational studies (such as cross-sectional or cohort designs). The high proportion of reviews indicates that this scoping effort captures multiple layers of evidence (both direct experimental findings and synthesized knowledge).

All included studies were published in English, except for two Spanish-language articles from Latin American journals. The research was global in scope, with contributions from North America, Europe, Asia, and the Middle East, indicating a widespread interest in neuromusicology. The settings of primary studies ranged from laboratory experiments with healthy volunteers to clinical trials in hospital or therapy settings.

Across the 57 studies, the population characteristics varied. Many studies did not focus on a narrowly defined age group, and in 31.6% of the studies the participants were described only in general terms (e.g., “healthy adults” or “human participants”) without specific age classification. This “unclear/combined” adult category was the largest single group, highlighting that numerous studies included mixed adult age ranges or did not report detailed demographics. About 28.1% of studies targeted general adult populations (often simply stating “adults” with broad age inclusion). A subset of the literature did stratify by age: 19.3% of studies focused specifically on young adults (commonly ages 18–30), and 12.3% focused on older adults (typically 60 years and above). A small minority of the included studies (approximately 7.0%) involved children or adolescents, but those were usually broader reviews that also included some pediatric data rather than dedicated pediatric studies. Figure 3 summarizes the age-group distribution of study populations. Notably, the lack of age-specific reporting in one-third of studies suggests a gap in the literature: future research could better differentiate age-related effects of music on the brain.

Figure 2. An upward trend is observed, particularly from 2021 onward, reflecting growing research interest in music’s effects on the brain.

In terms of health status, most studies involved healthy participants, although some targeted specific groups. A number of included studies (especially reviews) considered patients with neurological or psychiatric conditions – for example, epilepsy, dementia (Alzheimer’s disease), or disorders of consciousness – to examine how music might modulate brain activity in those contexts. A few studies examined stress or anxiety in medical settings: notably, two references in the set dealt with patients affected by COVID-19 and how music therapy influenced autonomic and brain responses. Additionally, several studies compared individuals with musical training (musicians) to non-musicians, to explore how expertise alters the brain’s reaction to music. Overall, while healthy listeners were the primary focus, the evidence base also encompasses older adults, clinical populations, and the influence of musical expertise.

Figure 3. “Unclear/Combined” refers to studies that did not specify an age range or combined multiple age groups in analyses. Percentages indicate the proportion of studies (out of 57) focusing on each category.

The types of musical exposure used across studies were extremely varied. About 15.8% of the studies specifically examined classical music, often using well-known pieces such as Mozart’s Sonata K.448 (a piece famously linked to the “Mozart effect”) or Beethoven’s “Für Elise” as stimuli. These classical selections were common choices for investigating structured, melodic music effects on the brain. A small proportion of studies (7.0%) focused on other particular forms of music such as instrumental music without vocals, rhythmic percussion-based stimuli, or personalized music selections chosen by participants. For example, some experiments used simple rhythmic tone sequences to isolate the effect of beat and tempo, while others allowed participants to choose a favorite song to assess personally salient music. However, the majority of studies fell into a broad “other” category (56.1%) in terms of musical exposure. These included a wide variety of auditory stimuli: from affective music (pieces chosen for their emotional content), to environmental/natural sounds and complex soundscapes, to therapeutic music interventions in clinical settings (e.g., music therapy protocols for infants or patients). In some cases, studies even looked at traditional music (such as Indian ragas) or contrasts between consonant and dissonant musical harmonies, though these were less commonly isolated ( < ~ 20% combined) and often discussed within broader reviews. The heterogeneity in musical stimuli underscores a lack of standardization – many studies created their own musical paradigms, making direct comparisons challenging. With respect to comparators, the most common approach was to measure brain activity before and after music exposure within the same individuals (each person serving as their own control). In these pre-post designs, baseline (silence or rest) brain activity was compared to during or after listening to music. Some studies employed non-musical auditory controls – for instance, using white noise, tone pips, or environmental sounds to contrast against musical stimuli. A few experiments explicitly compared different genres or types of music (e.g., relaxing versus stimulating music, consonant versus dissonant) to see how brain responses diverged. In clinical contexts, comparators sometimes involved no intervention or standard care versus a music intervention. For example, studies in neonatal intensive care units compared infants who received music exposure to those who did not. Overall, while virtually all studies ensured some form of comparison (silence, noise, or alternate condition), the strategies varied. This variety again highlights the exploratory nature of this field and the absence of a single agreed-upon control condition across studies. Figure 4 presents an overview of the categories of musical stimuli used. It is evident that “music” in the literature ranges from specific classical pieces to personalized playlists, and this variety must be kept in mind when interpreting the breadth of results.

Figure 4. “Classical Music” refers to studies using standard classical pieces; “Instrumental/Personalized” refers to those using instrumental, rhythmic, or participant-selected music; “Traditional/Consonant” includes studies focusing on traditional cultural music or musical consonance vs. dissonance; “Other Varied” encompasses diverse or composite musical stimuli (e.g., ambient soundscapes, multi-genre mixes, therapeutic music interventions). Percentages indicate approximate proportions of studies employing each type (sums to 100% of studies).

The included studies utilized a range of brain monitoring techniques to assess neural responses to music. By far the most common modality was electroencephalography (EEG), which was used in about 51% of the studies. EEG’s popularity can be attributed to its practicality and sensitivity to music-related brain dynamics: it directly captures electrical oscillations and has excellent temporal resolution, allowing researchers to track real-time changes in brain wave patterns as participants listen to music. Many EEG studies examined spectral power changes (e.g., increases in alpha or theta waves during music), and some employed event-related potentials (ERPs) to specific musical events (though in this classification a ERP analysis was considered as a subset of EEG methodology rather than a wholly separate technique). Functional MRI (fMRI) was the second most common method, used in roughly 35.1% of studies. fMRI provides complementary information to EEG by localizing brain activation associated with music processing. Studies using fMRI often reported which brain regions “light up” in response to music, such as limbic regions for emotional music or auditory and motor areas for rhythm processing. The spatial maps from fMRI have revealed consistent involvement of areas like the bilateral auditory cortices, prefrontal cortex, and subcortical reward centers (e.g., nucleus accumbens) during pleasurable music listening. Notably, about one third of the included studies were review articles that summarized findings from multiple fMRI experiments, underscoring fMRI’s importance in this field. A smaller proportion of studies employed combined or advanced neuroimaging approaches. For example, a few studies (~ 3.5% of the total) explicitly combined EEG and fMRI simultaneously, integrating the high temporal resolution of EEG with fMRI’s spatial insights. Another 3.5% of studies used EEG with ERP analysis as a technique (these were counted separately in some reports, although ERP results are derived from EEG recordings). One study (1.8%) was noted to incorporate MEG (magnetoencephalography) alongside EEG and fMRI, reflecting a truly multimodal approach. Additionally, a handful of studies (collectively ~ 5%) utilized other techniques such as PET (positron emission tomography) or functional near-infrared spectroscopy (fNIRS), or focused on MEG alone to examine magnetic brain responses to music. These were less frequent but provided unique contributions (for instance, PET can measure dopamine release during music listening). Figure 5 summarizes the distribution of methods across studies.

Figure 5. EEG = electroencephalography; fMRI = functional magnetic resonance imaging; EEG + fMRI = concurrent EEG-fMRI imaging; EEG + ERP = electroencephalography with event-related potential analysis; EEG + fMRI + MEG = an example of a multimodal approach combining EEG, fMRI, and/or MEG; “Other” includes PET, fNIRS, or standalone MEG. Bars show the number of studies employing each method (out of 57), with percentages annotated above.

The prevalence of EEG in this literature highlights a focus on capturing neural oscillations and immediate electrical responses to music. Many EEG studies reported that music listening leads to power increases in lower-frequency bands (alpha, theta) associated with relaxation or memory, or synchronization in frequency bands corresponding to the beat frequency of the music. On the other hand, fMRI-based studies enriched the findings by showing network-level effects – for example, increased connectivity between auditory and reward regions when listening to preferred music, or activation of the hippocampus during familiar music that evokes autobiographical memories. The use of multiple methods in some studies suggests that combining EEG and fMRI can provide a more holistic understanding (some authors merged EEG and fMRI data to show how transient electrical changes correspond with BOLD signal fluctuations). Overall, the diversity of neuroimaging techniques employed reflects both the complexity of music’s effects on the brain and the interdisciplinary nature of this research field.

The included studies reported a wide array of outcomes, but certain key domains emerged, reflecting the most common research interests. Figure 6 presents the major categories of outcomes that were frequently assessed or highlighted:

Figure 6. “Emotion Processes” includes studies of music-evoked emotions and mood changes; “Emotional Regulation” focuses on using music to manage or change emotional state; “Neural Entrainment” refers to synchronization of neural oscillations with music’s rhythm; “Neuroplasticity” covers long-term changes in brain structure/function from music; “Seizure Modulation” denotes effects of music on pathological brain activity such as epilepsy. Bars indicate the number of studies emphasizing each outcome (some studies addressed multiple domains), and percentages (of 57)

In addition to the above domains, many studies also touched on cognitive outcomes (though not always as the primary focus). For instance, some investigated memory improvement with music (e.g., the impact of playing music during sleep to enhance memory consolidation), or attention and working memory changes due to background music. Others examined motor coordination and gait in Parkinson’s or stroke patients using rhythm to cue movements (often linked with entrainment). These outcomes were mentioned across various studies but were less frequently the central theme compared to emotion and neural dynamics, so they do not appear as separate categories in Fig. 6. Nonetheless, it is worth noting that cognitive processing (attention, memory, executive function) did appear in several research questions – for example, whether listening to music while performing tasks improves or hinders cognitive performance. The results in that area were mixed, suggesting moderation by factors like the type of music and the nature of the task.

Despite the diversity of methods and outcomes, a convergent picture emerges from this scoping review: Music exposure reliably induces measurable changes in brain activity see Table 1 for a summary of the included studies and their key findings). A recurrent finding is that music – especially listening to preferred or pleasant music – engages a network of brain regions associated with emotion, reward, memory, and attention. For example, numerous studies reported activation of the limbic system, including the amygdala and hippocampus, during emotionally engaging music. The prefrontal cortex – involved in higher-order processing and emotional regulation – was also frequently activated or showed connectivity changes with auditory regions. These brain regions are thought to underlie the integrative processing of a song’s emotional meaning, the memories it triggers, and the cognitive appraisal of the music.

On the EEG side, the spectral profile of brain activity often shifts with music. Alpha waves (8–13 Hz) tend to increase in power when individuals listen to calming or enjoyable music, which has been interpreted as a state of relaxed wakefulness or mental imagery triggered by music. Theta waves (4–7 Hz), associated with memory and emotional processing, also increase during immersive music listening, reflecting engagement of hippocampal–frontal networks. Some studies noted decreases in beta power or other changes indicating reduced cortical arousal when soothing music is played, versus increases in high-frequency activity with more stimulating music.

Crucially, functional connectivity analyses (from fMRI and EEG coherence studies) suggest that music can transiently reconfigure brain networks. Listening to music has been shown to enhance connectivity between auditory regions and mesolimbic reward circuits (e.g., ventral striatum), correlating with the pleasure experienced. In older adults, a music-based intervention increased connectivity in temporal and frontal networks related to auditory and reward processing. Such findings hint at music’s potential to prime or strengthen certain neural pathways – for instance, connecting emotional and cognitive centers, which might be beneficial in aging or disease. Another important theme is music’s effect on the autonomic nervous system and stress responses. Though not directly a “brain activity” measure, several studies in this review linked neural outcomes with physiological indices like heart rate, blood pressure, or hormonal changes. For example, in studies of patients with chronic stress or anxiety, music listening led to both EEG changes (increase in alpha power indicating relaxation) and reduced cortisol levels or sympathetic activity. These complementary measures reinforce the idea that music’s impact on the brain also translates to peripheral responses – engaging the brain’s emotion-regulation circuitry can down-regulate stress systems in the body.

In summary, the literature supports that music is a potent modulator of brain function. Consistent patterns include: enhanced activity in emotion/reward circuits during pleasurable music; synchronization of neural rhythms to musical rhythms (entrainment); and improved connectivity across brain regions that can persist beyond the listening period (in interventions). However, it is also clear that findings vary with context – not all music has the same effect, and not all individuals respond identically. Factors such as musical preference, familiarity, training, age, and mental state influence the outcomes. For instance, what calms one person (e.g., classical music) might bore another, leading to different neural responses. This variability points to both the richness of the subject and the challenge in drawing universal conclusions.

The aim of this review is to systematically map and describe the existing literature on how music exposure is associated with changes in brain activity among adults, regardless of the type of music, study setting, or population characteristics. Specifically, the focus is placed on reported neurophysiological responses observed across studies using techniques such as EEG and fMRI, without necessarily comparing music exposure to control conditions. The review also considers how these brain activity changes relate to broader cognitive and emotional processes, including neuroplasticity and emotional regulation.

The reviewed evidence indicates that music exposure elicits measurable changes in brain activity, with consistent patterns observed across diverse experimental settings and populations. Among the most frequently reported effects are increases in alpha and theta oscillatory activity, enhanced functional connectivity, and activation in regions such as the prefrontal cortex, auditory cortex, and limbic structures (e.g., amygdala, hippocampus). These changes are associated with attentional modulation, memory encoding, and emotional regulation, suggesting that music engages both cognitive and affective neural circuits.

Despite methodological variability—particularly in terms of musical genre, exposure duration, and neuroimaging parameters—the findings collectively support the role of music as a multisensory stimulus capable of modulating large-scale brain networks. This effect appears robust across different physiological and emotional contexts, including under conditions of psychological or physical stress.

Notably, Piñeros et al. [74] demonstrated in a crossover clinical trial that patients with active COVID-19 exhibited physiological responses to music exposure. Although the results did not reach conventional statistical thresholds (sympathetic nervous system stimulation, p = 0.078; increase in stress index, p = 0.089), the observed trends suggest autonomic modulation even under acute systemic stress. In a complementary review, Botero et al. [75] examined studies involving populations exposed to high physiological stress, concluding that music consistently influences stress-related physiological responses. These findings align with the broader evidence synthesized in this review, reinforcing the potential of music as a non-pharmacological strategy for modulating brain function under both normal and adverse conditions.

The inclusion of both experimental and observational studies allowed for a broad mapping of current knowledge, while also highlighting critical gaps. Many studies lack standardization in musical stimuli and intervention protocols, limiting the ability to compare results across contexts. Additionally, the absence of detailed participant data in several reports—such as musical background or psychological status—hinders understanding of individual variability in neural responses to music.

Taken together, the available evidence supports the hypothesis that music exposure induces neurophysiological changes in adults with potential relevance for emotional and cognitive regulation. The documented effects extend beyond aesthetic or cultural appreciation, pointing to music's capacity to engage functional networks with implications for health, well-being, and neurorehabilitation. Future research should prioritize standardized designs, diverse populations, and longitudinal assessments to clarify causal pathways and enhance the translational potential of music-based interventions.

This scoping review has some important limitations. The heterogeneity of study designs, neuroimaging methods (e.g., EEG, fMRI), musical stimuli, and participant profiles limited direct comparisons and made quantitative synthesis unfeasible. Additionally, the review did not include a formal assessment of risk of bias, which is common in scoping reviews. Although the search strategy was comprehensive, studies published in non-indexed sources or other languages might have been missed. Finally, most studies focused on healthy adults, which may limit the applicability of findings to clinical or more diverse populations.

Future research should prioritize longitudinal and intervention-based studies to determine the causal effects of music exposure on adult brain function across diverse populations. Expanding investigations to include understudied groups, such as those with neurological or psychiatric conditions, may uncover therapeutic applications. Moreover, integrating multimodal imaging techniques and standardized music protocols can improve comparability across studies and clarify underlying neural mechanisms. Enhancing methodological rigor and exploring culturally diverse musical stimuli will further enrich understanding of how music shapes the adult brain.

This scoping review highlights consistent evidence that music exposure modulates brain activity in adults, as demonstrated through various neuroimaging and electrophysiological methods. Findings reveal patterns of activation in emotional, cognitive, and sensorimotor networks, supporting music’s potential as a non-invasive tool for enhancing neuroplasticity, emotional regulation, and cognitive functioning. These insights contribute to a growing understanding of the neurophysiological underpinnings of music and underscore the relevance of incorporating music-based approaches in both clinical and non-clinical contexts.