Why do we like the music we do? Research has shown that musical preferences and personality are linked, yet little is known about other influences on preferences such as cognitive styles. To address this gap, we investigated how individual differences in musical preferences are explained by the empathizing-systemizing (E-S) theory. Study 1 examined the links between empathy and musical preferences across four samples. By reporting their preferential reactions to musical stimuli, samples 1 and 2 (Ns = 2,178 and 891) indicated their preferences for music from 26 different genres, and samples 3 and 4 (Ns = 747 and 320) indicated their preferences for music from only a single genre (rock or jazz). Results across samples showed that empathy levels are linked to preferences even within genres and account for significant proportions of variance in preferences over and above personality traits for various music-preference dimensions. Study 2 (N = 353) replicated and extended these findings by investigating how musical preferences are differentiated by E-S cognitive styles (i.e., ‘brain types’). Those who are type E (bias towards empathizing) preferred music on the Mellow dimension (R&B/soul, adult contemporary, soft rock genres) compared to type S (bias towards systemizing) who preferred music on the Intense dimension (punk, heavy metal, and hard rock). Analyses of fine-grained psychological and sonic attributes in the music revealed that type E individuals preferred music that featured low arousal (gentle, warm, and sensual attributes), negative valence (depressing and sad), and emotional depth (poetic, relaxing, and thoughtful), while type S preferred music that featured high arousal (strong, tense, and thrilling), and aspects of positive valence (animated) and cerebral depth (complexity). The application of these findings for clinicians, interventions, and those on the autism spectrum (largely type S or extreme type S) are discussed.

Funding: DMG was supported by the Cambridge Commonwealth, European and International Trust. SBC was funded by the UK Medical Research Council and the Autism Research Trust during the period of this work. DJS was supported by a grant from the Richard Benjamin Trust. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability: Studies one and two present results from different datasets. Study one used data from a third party (myPersonality Facebook application) and study two used data that we collected from Amazon’s Mechanical Turk. Thus, the data underlying study one is made available upon request to myPersonality ( www.mypersonality.org ) to full-time academics for the purpose of non-commercial research. The data underlying study two are available in the Supporting Information.

Introduction

Music is a prominent feature of everyday life and a cultural universal [1, 2]. Each day we come across music of varying styles and characteristics, and we continually make judgments about whether or not we like the music we hear. When listening to a new song, it takes us just a few seconds to decide whether to press repeat, change to the next tune, or to buy it. However, little is known about what determines our taste in music. We address this gap in the literature by examining the cognitive and affective underpinnings of musical preferences.

Research over the past decade has argued that musical preferences reflect explicit characteristics such as age, personality, and values [3–6]. Indeed, findings across studies and geographic regions have converged to show that the Big Five personality traits are consistently linked to preferences [6–12]. For example, people who are open to new experiences tend to prefer music from the blues, jazz, classical, and folk genres, and people who are extraverted and agreeable tend to prefer music from the pop, soundtrack, religious, soul, funk, electronic, and dance genres [13].

Though these findings are consistent across studies, what is also consistent is that the results have small effect sizes (r < .30) when compared to benchmarks used in other psychological research [14]. This raises the question of whether there are additional psychological mechanisms that might account for individual differences in musical preferences. In this article we build on previous research by examining two dimensions that may be linked musical preferences: empathy and systemizing.

Empathizing-Systemizing (E-S) Theory and Music Research Music listening involves a range of abilities. These include: perceptual processing: taking in and making sense of audio and visual content in music [15, 16]; affective reactivity: reacting emotionally and physiologically to it [17–19]; intellectual interpretation: interpreting how the detailed emotional and sonic elements in the music relate to the whole [20]; and prediction: anticipating the expected direction of the music (e.g. the melody or narrative) and predicting the thoughts and feelings of the musician [21–24]. These musical abilities may overlap with the drives to empathize and systemize. Empathy is the ability to identify, predict, and respond appropriately to the mental states of others [25, 26]. People use empathy when perceiving musical content, reacting emotionally and physiologically to it, and while performing [27–32]. Systemizing is the ability to identify, predict, and respond to the behavior of systems by analyzing the rules that govern them [33]. These include systems that are natural (e.g. the weather), abstract (e.g. mathematics), organizational (e.g. classifications), and technical (e.g. a mechanical motor) [34, 35]. People are likely to systemize when perceiving and interpreting musical content, particularly when analyzing and deconstructing its sonic features and interpreting how the detailed elements in a musical piece relate to the whole [36]. Even though research into music and empathy has increased, there remains very little empirical research into systemizing and music [37]. This is surprising given that there is evidence that empathy and systemizing are not entirely independent of each other [33, 38–40]. Individual differences in empathy can be measured by the Empathy Quotient (EQ) [26] and systemizing can be measured by the Systemizing Quotient-Revised (SQ-R) [41], and both have contributed to the empathizing-systemizing (E-S) theory [38–39]. Measurements on these two dimensions reveal a person’s cognitive style (or ‘brain type’). Those who score higher on the EQ than the SQ are classified as ‘type E’ (empathizing), and those who score higher on the SQ than the EQ are classified as ‘type S’ (systemizing). Individuals with relatively equal scores on both are classified as ‘type B’ (balanced). Research has provided evidence that these two dimensions explain psychological sex differences. More females are classified as type E and more males are classified as type S [40]. Furthermore, scores on the EQ and SQ predict autistic traits as measured by the Autism Spectrum Quotient (AQ) [41, 42]. Those on the autism spectrum are typically classified as type S or ‘extreme type S’ [41, 43, 44]. These brain types have a neurobiological basis [45, 46]. In males for example, systemizing is positively linked to the size of the hypothalamic and ventral basal ganglia brain regions [47]. There have only been a few studies that have explored how empathy links to musical preferences, and there have been no studies on systemizing. Vuoskoski and colleagues [32] asked participants (N = 148) to indicate their liking for 16 musical excerpts from film music. The 16 excerpts were categorized into four groups: sad, happy, scary, and tender. Results showed that empathy was positively correlated to preferences for sad and tender music, and there were no significant correlations for happy or scary music. However, because the excerpts were exclusive to film music, the extent to which these findings generalize beyond the soundtrack genre is not yet known. In another study, Egermann & McAdams [48] found that preferences moderated the relationship between empathy and emotion contagion in music, however, they did not examine the direct links between empathy and individual differences in musical preferences. Therefore, we extend this previous research by using a music-preference model that examines preferences with stimuli representative of the musical variety that people listen to in everyday life, and which also overcomes critical limitations in previous research in the area of musical preferences.

Methodological Issues Research into musical preferences has long been hindered by constraints posed by genre-based methodologies. Researchers frequently measure preferences by asking participants to indicate their self-ratings of preferences for a list of genres [6]. However, genres are artificial labels that have been developed over a period of decades by the record industry, and which contain illusive definitions and social connotations. They can hold different definitions depending on the time period that is in reference. For example, the ‘jazz’ label can refer to the swing era of the 1930’s and 40’s and the music of Louis Armstrong and Count Basie, but it can also refer to the post-bop and avant-garde era of the 1960’s and 70’s, which featured the music of John Coltrane and Sun Ra. Genres are also umbrella terms that cover a variety of sub-styles. For example, the ‘rock’ label can refer to ‘soft rock’, such as music by Billy Joel and Elton John, but also ‘hard rock’, such as music by AC/DC and Guns N’ Roses. Therefore, genre-based methodologies that ask participants to indicate their liking for genre labels make it difficult for researchers to accurately capture information about an individual’s preferences. To address this issue, Rentfrow, Goldberg, & Levitin [49] measured musical preferences across four independent samples by asking participants to report their preferential reactions to musical stimuli that were representative of a variety of genres and subgenres. Separately, judges rated these excerpts based on their perceptions of various sonic (e.g. instrumentation, timbre, and tempo) and psychological (e.g. joyful, sad, deep, and sophisticated) attributes in the music. Findings across all of the samples converged to suggest that a robust five-factor structure underlies musical preferences, and that each of the five dimensions are defined and differentiated by configurations of their perceived musical attributes. These dimensions (coined the MUSIC model after the first letter of each dimension label) are: Mellow (featuring romantic, relaxing, unaggressive, sad, slow, and quiet attributes; such as in the soft rock, R&B, and adult contemporary genres); Unpretentious (featuring uncomplicated, relaxing, unaggressive, soft, and acoustic attributes; such as in the country, folk, and singer/songwriter genres); Sophisticated (featuring inspiring, intelligent, complex, and dynamic attributes; such as in the classical, operatic, avant-garde, world beat, and traditional jazz genres); Intense (featuring distorted, loud, aggressive, and not relaxing, romantic, nor inspiring attributes; such as in the classic rock, punk, heavy metal, and power pop genres); and Contemporary (featuring percussive, electric, and not sad; such as in the rap, electronica, Latin, acid jazz, and Euro pop genres). We employ the MUSIC model in the current investigation because of four notable advantages. First, the five factors are recoverable not only across genres but also within. In two independent studies, the MUSIC model was replicated within preferences using music from only a single genre [50]. It was first replicated among preferences for jazz music, and second within preferences for rock music. Second, the model has ecological validity because the excerpts administered were of studio recorded music, as opposed computer-generated or manipulated music for the purposes of an experiment. Third, by consulting experts in the field, the musical excerpts were selected via a systematic procedure that aimed to generate a stimulus set that was representative of the large spectrum of musical characteristics and styles that people are exposed to in their everyday lives. Fourth, because each of the excerpts was coded for their sonic and psychological attributes, fine-grained observations about an individual’s musical preferences are able to be made.