The (Co)Evolution of Language and Music Under Human Self-Domestication

Human Nature (2023) 34:229–275 https://doi.org/10.1007/s12110-023-09447-1 Abstract Together with language, music is perhaps the most distinctive behavioral trait of the human species. Different hypotheses have been proposed to explain why only humans perform music and how this ability might have evolved in our species. In this paper, we advance a new model of music evolution that builds on the selfdomestication view of human evolution, according to which the human phenotype is, at least in part, the outcome of a process similar to domestication in other mammals, triggered by the reduction in reactive aggression responses to environmental changes. We specifically argue that self-domestication can account for some of the cognitive changes, and particularly for the behaviors conducive to the complexification of music through a cultural mechanism. We hypothesize four stages in the evolution of music under self-domestication forces: (1) collective protomusic; (2) private, timbre-oriented music; (3) small-group, pitch-oriented music; and (4) collective, tonally organized music. This line of development encompasses the worldwide diversity of music types and genres and parallels what has been hypothesized for languages. Overall, music diversity might have emerged in a gradual fashion under the effects of the enhanced cultural niche construction as shaped by the progressive decrease in reactive (i.e., impulsive, triggered by fear or anger) aggression and the increase in proactive (i.e., premeditated, goal-directed) aggression. Keywords Music evolution · Language evolution · Self-domestication · Cultural niche construction · Music transmission Accepted: 27 March 2023 / Published online: 25 April 2023 © The Author(s) 2023 The (Co)Evolution of Language and Music Under Human Self-Domestication AntonioBenítez-Burraco1,3 · AlekseyNikolsky2 Antonio Benítez-Burraco [email protected] 1 Department of Spanish Language, Linguistics and Literary Theory (Linguistics), Faculty of Philology, University of Seville, Seville, Spain 2 Independent Researcher, Austin, TX, USA 3 Departamento de Lengua Española, Facultad de Filología, Área de Lingüística General, Lingüística y Teoría de la Literatura, Universidad de Sevilla, C/ Palos de la Frontera s/n, Sevilla 41007, España 1 3 Human Nature (2023) 34:229–275 Just like language, music constitutes a distinctive behavioral trait of humans. However, current understanding of the role of music in shaping human evolution, as well as the matter of origins of music, remain far from clear—in contrast to what is known about the contribution of language (but see Honing, 2019; Perlovsky, 2017; Schulkin, 2013; Tomlinson, 2015; Wallin et al., 2000, for some hypotheses). At the same time, notable parallels exist between the structural and functional properties of music and language (see Jackendoff, 2009, for a useful review)—to the extent that some authors have argued in favor of their common evolutionary origins (Brown, 2000; Harvey, 2017; see de Boer & Ravignani, 2021, for a recent critical view). In this paper, we wish to substantiate this view with a new model that heavily builds on current findings and methodologies of evolutionary linguistics. Just like the language types that emerged throughout human history as humans became more tolerant and prosocial, following a steady reduction in reactive aggression (Benítez-Burraco & Progovac, 2020), music acquired diverse typology, complexity, and functionality that accompanied its global spread. We start this paper by overviewing the commonalities between music and language—one of the very few available sources to establish the evolutionary prehistory of music and language. Next we outline the self-domestication hypothesis of human evolution and explain its benefits for modeling the evolution of music and language. Finally we discuss possible ways for music’s interaction with language in their parallel development. Music and Language: Common Evolutionary Roots Overall, existing hypotheses about the origins of music fall into two general classes. The first one regards music as a by-product of the extended use of some preexisting biologically important capacity, such as vocal signaling, sound imitation, auditory analysis, motor coordination, problem solving, and linguistic communication. The second class of theories claims that music was selected for some evolutionary advantage(s). Music shares many commonalities with language. Both feature numerous functions, typologies of complexity, and a pronounced evolutionary continuity of the cognitive and communicative abilities of other species. In other words, many characteristic traits of human musical and linguistic communication can be traced in animal communication (see Corballis, 2020; Cowley & Kuhle, 2020; Pereira et al., 2020 for recent views). We shall list the most important similarities between language and music. First, a number of structural parameters of music—pitch, rhythm, meter, tempo, dynamics, articulation, and timbre—are also exploited by language (Besson & Schön, 2001; Filippi et al., 2019; Heffner & Slevc, 2015; Patel, 2003; Rohrmeier et al., 2015; Slevc, 2012). For example, pitch changes are used to distinguish different words in tonal languages, or different sentence types, as in prosodic intonation (see Nikolsky & Benítez-Burraco, 2022, for ample discussion). Second, music equals language in many of its common functions: 1 3 230 Human Nature (2023) 34:229–275 1. the expressive function—especially, conveying emotions (Altenmüller et al., 2013; Cook, 2002; Eerola & Vuoskoski, 2013; Gabrielsson & Juslin, 2003; Johnson-Laird & Oatley, 2010; Juslin, 2005, 2011, 2013; Krumhansl, 2002; Mohn et al., 2010; Nikolsky, 2015a; Panksepp & Trevarthen, 2009; Peretz, 2013; Perlovsky, 2012; Schiavio et al., 2017; Trainor, 2010; van Goethem & Sloboda, 2011), 2. the phatic function—in other words, reinforcing interpersonal and social bonding (Boer & Fischer, 2012; Clarke et al., 2015; Clayton, 2016; Cross, 2009; Dunbar, 2012a, b; Harvey, 2017, 2020; Mehr et al., 2021; Savage et al., 2020; Trevarthen, 2002), 3. the conative function—in other words, calling to action (Karl & Robinson, 2015; Kühl, 2011; Leman, 2009; Liszkowski et al., 2012; Mehr et al., 2021; Monelle, 2006; Nazaikinsky, 2013; Rodman & Rodman, 2010; Tagg, 2012; Tarasti, 1998; Vuust & Roepstorff, 2008), and 4. the mnemonic function—memory conservation (Belfi et al., 2015; Boer & Fischer, 2012; Janata et al., 2007; Levitin, 2019; Nikolsky, 2016b; Tamm, 2019; van Dijck, 2006; Will, 2004). Third, as with languages, all human cultures have developed different music systems to support important musical behaviors that fulfill specific social and psychological roles. The form-function links between language and music remain quite stable across various cultures and societies. Although during the past 40 years, Western ethnomusicologists have tended to deny the global universality of specific structural patterns of pitch and rhythm organization, their stance seems to be driven by political reasons—mainly, fear of a Eurocentric bias in conducting scientific comparative study of the world’s music traditions (Blacking, 1977; Gourlay, 1984; Hood, 1977; List, 1971, 1984; Nattiez, 2012; Supičič, 1983).1 The arguments for the nonexistence of musical universalities are all limited to the absence of specific higher-order combinatorial patterns in certain music cultures rather than to the omnipresence of certain basic principles of music-making (Brown & Jordania, 2013; Fitch, 2017; Grauer, 1996; Justus & Hutsler, 2005; Kolinski, 1978; Lomax, 1977; McAdams, 1989; Nketia, 1984; Savage et al., 2015; Tagg, 2012; Verhoef & Ravignani, 2021).2 A number of common elementary “surface-level” music constructs are virtually omnipresent across the globe and rely on the perceptory mechanisms that are already active immediately after birth: 1. In practically every music culture, listeners recognize musical sounds as more pleasant than other types of sounds and are eager to listen to them for a long time, over and over again (Alworth & Buerkle, 2013; Fitch, 2006; Granot, 2017; Hefer 1 A striking example can be found in the shift in perspective of Bruno Nettl, a prominent Western ethnomusicologist. In 2000 he advocated the need for the comparative study of cross-cultural universalities in the world’s music cultures (Nettl, 2000) and then just ten years later he denied the validity and possibility of such studies (Nettl, 2010). 2 A serious miss in Western ethnomusicological publications that claim fundamental non-universality of music is that their analyses of cultural diversity zooms into the between-culture variations without much consideration for the within-culture variations that can significantly exceed the between-culture variations—quite similar to genetic diversity (Rzeszutek et al., 2012). 1 3 231 Human Nature (2023) 34:229–275 et al., 2009; Lots & Stone, 2008; Nieminen et al., 2011; Salimpoor & Zatorre, 2013; Schubert, 2009; Snowdon, 2021; Watanabe, 2008). 2. Listeners distinguish pleasant (consonant) from unpleasant (dissonant)3 simultaneous combinations of musical sounds and only vary in judging which specific combinations are considered “consonant” versus “dissonant” (Bidelman & Krishnan, 2009; Brandl, 2008; Cazden, 1959, 1972, 1980; Lots & Stone, 2008; McPherson et al., 2020; Messner, 2006, 2013; Schellenberg & Trehub, 1996; Tenney, 1988; Terhardt, 1974b). 3. Listeners distinguish melodic steps from leaps (Alekseyev, 1986; Bendixen et al., 2015; Bregman, 1994; Larson, 1997; Nazaikinsky, 1977; Rags, 1980; Sievers et al., 2013; Stefanics et al., 2009; Tiulin, 1937; van Noorden, 1975). 4. Listeners distinguish regular integer-ratio rhythms from irregular rhythms (Arom, 2006; Brown & Jordania, 2013; Drake, 1998; Drake & Bertrand, 2001; Fitch, 2012; Fraisse, 1982; Jacoby et al., 2021; Monahan, 1993; Pressing, 1983; Ravignani et al., 2016). 5. Listeners distinguish binary metric groups from ternary (Abecasis et al., 2005; Bergeson & Trehub, 2006; Clayton, 2000; Fraisse, 1982; Iyer, 1998; Jacoby et al., 2021; London, 2004; Monahan, 1993; Potter et al., 2009; Temperley, 2009). 6. Listeners distinguish fast tempi from slow (Baruch & Drake, 1997; Collier & Collier, 2007; Dalla Bella et al., 2001; Ellis, 1992; Fraisse, 1982; Levitin & Cook, 1996; McAuley, 2010; Trainor et al., 2004; van Noorden & Moelants, 1999). 7. Listeners experience music as virtual movement of a certain character, analogous to physical motion, but in imaginary space, formed by the alternation of tensioninducing and relaxation-inducing structures (Fraisse, 1982; Friberg & Sundberg, 1999; Iyer, 1998; Jackendoff & Lerdahl, 2006; Larson, 2012; Larson & McAdams, 2004; Larson & Vanhandel, 2005; Nazaikinsky, 1988; Nikolsky, 2015b; Rothfarb, 1988). 8. Listeners use no more than 12 pitch-classes (most commonly 5–7 of different sizes) and employ logarithmic incrementation to distinguish between them within a pitch-set (Balzano, 1980; Beliayev, 1990; Brown & Jordania, 2013; Gill & Purves, 2009; Honingh & Bod, 2011; Jacoby et al., 2019; Korsakova-Kreyn, 2013; Mazel, 1952; McAdams, 1989; McBride et al., 2022; Sethares, 2005; Shepard, 2010) that possibly shares roots with the linguistic prosody (Fenk- Oczlon, 2017; Kolinsky et al., 2009; Schwartz et al., 2003; Terhardt, 1984). Numerous experimental studies suggest the existence of universal cross-cultural patterns of musical communication (Argstatter, 2016; Balkwill & Thompson, 1999; 3 Here we briefly address the controversy on this issue between cognitive scientists and Western ethnomusicologists. Although the concepts of consonance and dissonance have been forged within the Western civilization, their dichotomy is based on the biologically rooted mechanisms of auditory perception, present among not only humans but at least some animal species (Chiandetti & Vallortigara, 2011; Hulse et al., 1995; Izumi, 2000; Koda et al., 2013; Tramo et al., 2001; Watanabe et al., 2005). Consonant and dissonant combinations of tones are distinguished by means of detection of acoustic roughness and fusion of tones (Terhardt, 1974a, b)—detectable soon after birth (Trainor et al., 2002; Zentner & Kagan, 1998), even for children of deaf parents (Masataka, 2006). See Nikolsky, 2022, for discussion. 1 3 232 Human Nature (2023) 34:229–275 Egermann et al., 2015; Fritz et al., 2006, 2009; Juslin & Laukka, 2003; Kwoun, 2009; Laukka et al., 2013; Sievers et al., 2013; Smith & Williams, 1999; Stevens & Byron, 2009; Trehub et al., 1993; Yurdum et al., 2022). This line of research is extremely important in validating claims of Western ethnomusicologists and identifying the common biomusicological foundation that underlies world’s music cultures. Fourth, newborns show innate predisposition to acquire music no less than language. Hence, there is evidence that fetuses distinguish music from environmental sounds during the last months of gestation, and newborn infants even remember music they were exposed to during gestation (Parncutt, 2016). Acquisition of music occurs implicitly, even in the absence of formal training (Rohrmeier & Rebuschat, 2012). Infants routinely learn multiple music systems just as they learn multiple languages used by their caretakers (Wong et al., 2009). The development of musical skills in childhood seems to proceed in the direction of building new culture-specific skills of identifying culturally important conventional patterns of musical sounds (e.g., “chords” and “keys”), based on the biologically ingrained foundation of synesthetic perception of musical pitch, rhythm, timbre, and dynamics (see the discussion in Nikolsky, 2022). Ontogenetically, this line of development from implicit “natural” (onomatopoeic) and, therefore, cross-cultural and general to explicit “cultural” (convention-based) learning is not that different from linguistic acquisition (Berry et al., 2002; Dasen, 2012; Greenfield et al., 2003; Johnson & White, 2020; Kidd et al., 2018; Monaghan et al., 2014). This emergence of “cultural” forms of musicking from “natural” forms must be responsible for the significant correlation between the geographic distribution of specific genetic variations and specific folk music traditions, as revealed by recent studies (Brown et al., 2013; Le Bomin et al., 2016; Pamjav et al., 2012). Finally, music perception and production rely on specific brain circuits, the impairment of which leads to distinctive, music-specific damage (i.e., amusia) (Perrone-Capano et al., 2017; Reybrouck et al., 2018; Stewart et al., 2006; Tillmann et al., 2015; Vuust et al., 2022). This substrate shows extensive overlapping with the substrate of language impairments, specifically in syntax processing (Asano, 2022; Brown et al., 2006; Harvey, 2017; Sun et al., 2018; but see Chen et al., 2021, for an opposing view). Overall, just as one can argue for a human linguisticality—the set of capacities that enable humans to learn and use languages in all their diverse forms (after Haspelmath 2020)—one can argue for a human musicality, understood as an innate predisposition to perceive and create music, encompassing all the perceptual, cognitive, and behavioral aspects of music. Our contention here is that these parallels can also be extended to the evolutionary domain. Retaining the parallel with language(s) again, in no way should music be regarded as a recent cultural invention.4 Musicality must be an ancient capacity that has manifested in different types of music along the long pathway of Homo sapiens, reflecting the milestones in the cultural evolution of our species, as well as important cognitive and behavioral changes. 4 By cultural invention we mean a new set of behavior adopted by a group of people and passed on to others within that group as well as outside of it. 1 3 233 Human Nature (2023) 34:229–275 In view of the similarities reviewed above, some scholars (most notably, Brown 2000) have suggested that language and music might share common evolutionary roots. However, as noted by Cross and colleagues (2013), even were this the case, there are several likely scenarios of their emergence: music developing from language (Spencer’s view), language emerging from music (Darwin’s view), or language and music splitting up from a common musilanguage (Brown’s view) and afterwards following different, but still related (and perhaps interacting), trajectories (Harvey, 2020). In this paper, we propose a new model of the evolution of music that adheres to the latter possibility. What Music Functions Can Tell About the Evolution of Music Pretty much as for language, one can think of diverse functions for which music might have been selected—and even estimate a timeline for the selection of each type of function. Most of the functions of music mentioned in the previous section can be characterized as “external” to the subject and thus execute some social role: for example, (1) the establishment and consolidation of social bonds within human groups (Dunbar, 2012a, b; Harvey, 2017, 2018; Savage et al., 2020) and (2) the conveyance of credible information to others either for signaling mate quality (e.g., Merker 2000; Miller, 2000) or for coping with progressively complex social conflicts of interest (Mehr et al., 2021). Nonetheless, an “internal” role for music has been hypothesized as well, such as Perlovsky’s (2017) view of music as a tool for overcoming unpleasant emotions, resulting from our interaction with the environment. Often, “external” functions of music, most notably those related to social bonding, impact the “internal” state of a subject by influencing the stress-response systems or the rewards systems (see Dunbar 2012a, b; Harvey, 2020; Savage et al., 2020, for discussion). Accordingly, it is not an easy task to infer an evolutionary path for these functions. One promising approach is to cross-examine the codependencies between the most common music functions, based on the music skills required to process those music structures that characterize each of these functions.5 Like language, music is structurally determined by the functions it regularly performs (listed below). Once forged, such structures, in turn, start supporting and conserving a function that shaped them.6 5 This approach follows the “central neoformation” model, proposed by Vygotsky to describe and explain the general cognitive development (ontogenetic and phylogenetic) and further elaborated by his school: Alexander Luria, Aleksey Leontyev, Piotr Galperin, Daniil Elkonin, and Aleksander Zaporozhets, who headed a lab that researched music perception (Zaporozhets, 1985) (see the discussion in Nikolsky, 2022). According to this model (van der Veer & Valsiner, 1991; Vygotsky, 1987, 2013), each developmental period is forged by the necessity to master a new cognitive function that is imperative for handling critical environmental challenges. Vygotsky called it “central function” because, once established, it remains stable throughout the entire period, laying the foundation for the neoformation of the next stage. This way, the entire line of development becomes cumulative and modular. Each progressive period is characterized by the increase of cultural diversity in implementation of each central neoformation. 6 Thus, the “physical aid” function relies on the presence of rhythmic idioms embedded in a metric grid and sustained in a tempo range suitable for accompanying specific physical activities (e.g., walking for marches or lulling for lullabies). Once forged, such idioms start conserving the compositional arrange- 1 3 234 Human Nature (2023) 34:229–275 As a result, these formative functions form complex dependencies whereby one function cannot operate without another function being accessible.7 More importantly, some functions build the foundation for others, supporting new modes of interaction with the physical and, particularly, the cultural environment. In a recent paper (Nikolsky & Benítez-Burraco, 2022) we present a thorough reconstruction of the entire chain of dependencies of the most common formative music functions, tracking them down to the primordial hedonistic function that underlies all others. We identified 14 operational functions in the recent research literature (Bispham, 2018; Boer & Fischer, 2012; Brown, 2005; Clayton, 2016; Dissanayake, 2005; Levitin, 2019; Perlovsky, 2014; Savage et al., 2015; Schäfer et al., 2012; Schäfer & Sedlmeier, 2009; Stefanija, 2007; Trevarthen, 2009; van Goethem & Sloboda, 2011):8 ●hedonistic stimulation (make music or listen to it to experience pleasure), ●emotional communication (make or listen to music that expresses one’s current emotional state or characterizes a state of a third party), ●emotional regulation (make or listen to a selected type of music to maintain a desired emotional state or to change an undesired one), ●compliance to norms (ritualizing one’s behavior and organizing one’s feelings and goals in accordance with some ideal, collective task, or belief), ●recreation (entertain an individual or a social group by doing something not totally predictable, such as improvising, exploring a new instrument, or playing some singing/vocalization games), ●interpersonal bonding (secure close relations with another individual or a social group by sharing a musical experience with them), ●coalition status display (publicly display one’s membership in a specific social group or project and affirm a wish-to-be social identity), ●physical aid (support a specific pattern of physical motion in one’s daily work, play, or workout, collective or solitary), ●learning aid (stimulate the discovery of new things and help remember important information, as in children’s learning songs), ment of music that supports the same character of movement—e.g., all march-like music within the same musical culture shares the same metro-rhythmic design within the same tempo range, whether this music belongs to a genre of march or is a part of some other genre, such as symphony, opera, ballet, suite, song, sonata, or concerto. 7 For example, “emotional regulation” requires the functions of “emotional communication,” “interpersonal bonding,” and “physical aid” to be already established. To successfully choose music to change or “lock in” a specific emotional state, one must know that music can communicate musical emotions, that these emotions can bring participants to share the same emotional state and thereby bond together, and that the presence of specific structural patterns in music can match or mismatch certain activities. In turn, the “emotional regulation” function must be available in order for “compliance to norms” to emerge. 8 Many more functions have been identified in the literature on music. However, we were interested only in those functions whose existence was experimentally confirmed, reported in numerous music cultures, secured by a well-established tradition of production and/or consumption, and characterized by objectively recognizable structural features. We did our best to get rid of redundancies and minor variations in functionality by grouping similar functions into a single type according to the common mental operation(s) they require. So, our list presents 14 basic operational types to illustrate this novel method of inquiry into the evolution of music. Other researchers are welcome to improve it. 1 3 235 Human Nature (2023) 34:229–275 ●contemplating an event (evoke the imagery of an important occasion, holiday, season, sporting event, place of interest, landmark, or monument), ●calling to action (music signaling, as in military bugle signals or herding calls— i.e., supporting language-like commands—and the creative use of such semiosis to entertain the audience, as in “program music”), ●conservation of memories (preserve a valuable memory for an individual and their close family/friends, usually nostalgic, and maintain one’s mental integrity under pressure), ●self-promotion (exhibit one’s music faculties to increase confidence, self-esteem, and/or earn respect or show superiority), ●personal profiting (earn money and/or fame by making music as a professional occupation). We cannot dedicate much space to the discussion of these functions here and will only cover those points that directly relate to the evolution of music and language. Figure 1 summarizes the codependencies that we have established in our 2022 paper (see Nikolsky & Benítez-Burraco 2022 for details). “Hedonistic stimulation” does not depend on any other function and is not only cross-cultural but cross-specific for a number of nonhuman species. Therefore, it is placed at the root. “Personal profiting” and “calling to action” do not support other functions. Therefore, they go to the top. Other functions are distributed in-between according to their dependencies.9 Note that the lower-order functions form the succession that fits the pattern of acquisition of musical skills throughout childhood (see the discussion in Nikolsky, 2022). “Hedonistic stimulation” by music seems to be inborn and universal. It supports and enables the acquisition of every other music function. “Learning aid” capitalizes on the capacity of music to bring pleasure, connecting it to the disposition to learn new things and the mnemonic power of music (evident in the earworm phenomenon and the efficacy of music therapy in treating dementia). Multimodal interaction with the mothering figure, whose singing, motherese, touch, movements, and gestures altogether shape this “learning” function, teaches an infant the principles of communication. “Interpersonal bonding” emerges from the ongoing communication with caretakers, usually set by the mother and thereafter expanded to other close relatives. Based on the observed patterns of vocal communication, by the second year of life, infants engage in active musicking—in the form of solitary musical babbling, which introduces the “recreation” function. However, musical babbling remains very similar to verbal babbling. All four of these basic functions are engaged in verbal acquisition too. Hours of dedicated exercising self-initiated vocalizations, accompanied by spontaneous physical movements, lead to discovery of the expressive capacities of melodic leaps, steps, directionality, dynamics, and, eventually, rhythm and tempo. Infants 9 It is difficult to define the operational dependencies for each of the musical functions established in the literature. Arguments for their tentative order in Fig. 1 are presented in Nikolsky & Benítez-Burraco 2022. The ultimate ordering requires thorough experimental research. The connection of operational functions with specific musical genres, outlined in the above-mentioned paper, and with those musical structures that characterize such genres will enable researchers to test exactly how various types of listeners perceive music that specializes in each of the musical functions. 1 3 236 Human Nature (2023) 34:229–275 learn melodic movement as they learn physical movement. Mastering melodic leaps and steps accompanies learning to walk. Thereby, music evolves into the “physical aid” function. Through solitary exploration of singing while moving, playing with toys, drawing, and so on, children discover that certain types of melodic motion suit certain types of physical motion. Specific musical patterns become associated with the affective characteristics of the accompanying locomotion and with the imaginary characters of toys and protagonists of drawings. From this point on, musical expres- Fig. 1 Evolutionary development of operational functions of music. Fourteen operational functions are placed along two axes: temporal (vertical) and social (horizontal). The former (on the left, in pink) reflects the operational dependencies between all functions, which is generally representative of the ontogenetic pattern of acquisition of music skills throughout childhood. On the right (in purple), the corresponding phylogenetic line of development is outlined. The horizontal axis shows the gradual social expansion in the use of functions throughout childhood. The ellipsis after the name of a function indicates that this function keeps developing toward engaging a greater number of participants, the extent of which is reflected by the relative length of the surrounding box after the ellipsis. Black arrows show the derivative relations between functions. A blue rectangle at the bottom encloses functions that are undifferentiated from verbal communication and characteristic for the “musilanguage.” A green rectangle marks the functions that are differentiated from verbal communication but are not autonomous from it, representative of protomusic and earliest forms of “personal music.” Darker green distinguishes more biologically dependent functions from more culturally varied ones. A yellow rectangle encloses functions specific to music. Darker yellow distinguishes functions based on informal, orally transmitted, and implicit musical grammars from formally learned, notation-based, and explicit grammars 1 3 237 Human Nature (2023) 34:229–275 Morphologically, music closely follows language in employing both combinatoriality and compositionality, although, as noted above, there is some controversy as to whether music syntax is processed in the same cortical regions as language syntax. Music combines many meaningless elementary units—pitch-, rhythm- and timbre-classes, metric beats, and voices in texture—to generate meaningful morphosyntactic units, such as motifs, chords, rhythmic figures, metric groups, and textural components (e.g., accompaniment, counter-melody, pedal tone) that carry certain semantic values (sighing motif, sad chord, bouncing rhythmic figure, leisurely swaying ternary meter, stiffening pedal tone, etc.). These morpho-syntactic units are conjoined according to a set of rules that distinguish each musical tradition, enabling listeners to identify a tradition by ear (Nazaikinsky, 1982). For instance, in Gregorian plainchant, melodic leaps, regular meters, the so-called dotted (or “punctured”) rhythms, chords, and chromatic alterations are to be avoided altogether (Ferreira, 1997), whereas in Western military march music they are encouraged (Monelle, 2006). Mastering such traditions requires apprenticeship so a layperson can learn their compositional principles. Historic ethnomusicology testifies to the fundamentality of compositional organization of music. Western, Arabic, Persian, Indian, and Chinese classical music traditions each feature hundreds if not thousands of treatises on music composition.18 Western compositional music theory is rooted in the ancient Greek theory of rhetoric, understood as the craft and science of bringing the audience into a specific emotional disposition (Bartel, 1997; Bonds, 1991; Harrison, 1990; Kallberg, 1988; Keller, 1973; Mabbett, 1990; Meier, 1990; Vickers, 1984; Zakharova, 1983).19 The musical implementation of rhetoric occurred initially through the liturgic practice of composing sermons and supporting the verses required for liturgy with music (Murphy, 1981), but by the eighteenth century the theory of musical rhetoric firmly held its ground in purely instrumental and secular forms of music (see Mattheson & Harriss, tion. Many forms of poetry, including traditional folk epic and lyric genres, also feature what can be called “creative play” with phonetic (i.e., timbral), rhythmo-metric, dynamic, and prosodic aspects of linguistic expression, all of which are shared with music. Furthermore, if poetry can be argued to constitute an intentionally “musicalized” use of language, some sounds that by design clearly have nothing to do with music satisfy its definition as creative play. At the extreme, car manufacturers design engine noises to excite or please the driver while distinguishing between different operational modes (starting the engine, speeding up, changing gears, etc.). For example, see: https://www.volkswagenag.com/en/news/stories/2019/03/ volkswagen-sound-design.html. Despite clearly falling off the scope of music (according to the public convention), such sound engineering also satisfies the “creative play” definition of music. 18 The compositionality of music becomes evident whenever the same tune is used in different musical traditions—the very same motifs and rhythms receive different arrangements according to different compositional principles. Such are the compositions by a Polish prisoner of war, Wojciech Bobowski (1610– 1675), also known as Ali Ufki, from his treatise Mecmua-yi saz ü söz [Collection of Instrumental and Vocal Pieces], rearranged according to the homophonic principles by Dimitrius Cantemir (1683–1723), a Moldavian prince, in his treatise Kitāb-i ‘ilmu ‘l mūzīkī ‘ala Vechi’l-Hurufat [Book on the Science of Music]. 19 All standard music forms commonly used today in one way or another descend from the theory of music rhetoric as it has been elaborated in the sixteenth to eighteenth centuries, before Adolf Marx standardized the most common schemes of arranging themes and their development in the beginning of the nineteenth century. Thus, the treatment of rhetorical canons—prooemium, divisio, confirmatio, confutatio, peroratio—in the domain of music became embedded in the so-called sonata form (Bonds, 1991; Marx & Burnham, 1997; Moyer, 1969). 1 3 244 Human Nature (2023) 34:229–275 1981). Other musical cultures featured their own pathways of developing musical rhetoric (see Dorchak 2016; López-Cano, 2020; Powers, 1980; Rink, 1989; Smith, 1971; Theodosopoulou, 2019), including such a recent development as composing music for advertising (Scott, 1990). Chain transmissions inherently introduce and magnify cultural biases in music structures and combinatorial and compositional rules since different cultures favor different structural features in response to culturally dependent factors, such as popularity and social prestige. The same applies to the domain of speech (Verhoef et al., 2014). More generally, experiments involving artificial languages suggest that the cultural transmission of linguistic structures promotes compressible regularities, combinatorial rules, and compositionality (Kirby et al., 2015; Tamariz & Kirby, 2016). The analysis of sign languages spontaneously developed by isolated deaf populations also suggests that some basic properties of language (such as duality of pattern) are lacking at the beginning of transmission and emerge gradually as a result of increased interactions between signers (Dachkovsky et al., 2018; Sandler et al., 2005). In the case of music, it is more difficult to identify “idiomatic” structures (i.e., music lexicons of specific music-user communities) and combinatorial rules (i.e., conventional music grammars). The reason for this might be the growing prevalence of “tree-like” transmission—in other words, chain-like passing of a music work from a person to a group (Nettl, 2005).20 “Tree-like” transmission tends to replace folkstyle “linear,” person-to-person transmission as notation, formal music theory, and professional forms of public performance begin to obtain a greater share in a musical culture. Notation and theory substantially aid learning, thereby reducing the formative power of simplification in learning on the part of the listeners throughout the transmission chain. The presence of an audience, in turn, incentivizes performers to intuitively amplify their expression in order to increase rhetorical control over the listeners. As a result, the innovation rate in exploring newer expressive means grows—structural patterns are modified more at each new act of transmission. Subsequently, the diversity of the emerging variants increases since each of the multiple listeners inevitably introduces slight variations in the learned music when they pass it on to new listeners. The compound effect of the tree-like transmission greatly exceeds that of linear transmission. Prevalence of linear transmission makes music cultures that remain primarily “personal” (e.g., Nenets or Nganasan) in their music usage to stand out as amazingly conservative in comparison to music cultures that primarily employ collective forms of performance and listening. The larger the number of the ensemble performers typical for a given tradition (e.g., orchestral music) and the size of its audience (e.g., concert hall, radio), the higher the innovation rate (Alekseyev, 1976, 1986, 1988). Naturally, the greater the discrepancy between synchronic and diachronic invariants of the same musical structure, the vaguer its structural and semantic characteristics and the weaker the combinatorial rules of its use. Language does not have this problem because, in everyday use, “person-to-person” distribution remains prevalent over 20 Here we note the similarity between the transmission of specific music structures and genetic transmission in light of the general similarity between variation in genetics and variations in music styles (Brown et al., 2013; Le Bomin et al., 2016; Pamjav et al., 2012). 1 3 245 Human Nature (2023) 34:229–275 “person-to-group” (for the discussion of harmonization versus individualization, see Harvey, 2017). Music is more oriented to the expression, transmission, and prolonged experience of emotions, whereas language is more optimized for delivering prompt referential information. Therefore, oral verbal encoding is designed for quick peer-to-peer streaming, where information has to be constantly chunked by parsing the stream of sounds, identifying words in it, retrieving their meanings, interpreting phrases, and constructing the meaning in a cumulative way. All of this relies on clarity of phonemic and morphological contrasts, while prioritizing the processing speed and robust error-correction. Conversely, music prioritizes continuity and homogeneity of the sounds within the same musical phrase. Music is designed to elicit particular affective states in the listener, allowing them to immerse themselves in the music and fully engage with the experience of those states. This requirement causes music to: ● slow down music’s transmission rates, giving music a meditative appearance, ● cause music to simultaneously engage multiple aspects of expression, each with its own proprietary “idiomatic” patterns (rhythmic, metric, melodic, harmonic, etc.), and ● ground music to iconic semiosis and synesthetic correspondences between the musical meaning and the acoustic attributes of music sounds. This distinction between music and language is far from being clear-cut. Language also conveys emotional contents and is partially iconic—especially poetic speech, in which iconicity facilitates word learning and communication while systematicity facilitates category learning. Linguistic arbitrariness, iconicity, and systematicity interact in complex ways under the effects of cultural selection to reshape not only a language’s vocabulary but also its grammar, promoting compositionality and regularity (Dingemanse et al., 2015). Nevertheless, the differences between musical and linguistic oral transmissions are sufficient to make music functions form operational relations quite different from language functions. Notably, music functions rely on each other to such an extent that higher-order functions can hardly be fully operational without lower-order functions being effectively engaged. Subsequently, the study of the evolution of music requires the consideration of all music functions in their systemic relations. Most disagreements between extant theories of the evolution of music seem to originate from the limitation of study to only a few functions, specific to the earliest or latest stages of evolutionary development, while ignoring the other functions. Moreover, both biological and cultural factors need to be considered on par and in their interaction. Human Self-Domestication and Language Evolution In the next two sections we present a model of music evolution to account for musical functions and for biological and cultural factors formative for music structure and function. Our model is based on a recent account of human evolution, namely, 1 3 246 Human Nature (2023) 34:229–275 the hypothesis of “human self-domestication” (HSD), which has been successfully applied to the characterization of the evolution of language in our species (Benítez- Burraco & Progovac, 2020; Thomas & Kirby, 2018). Because of the parallels between music and language discussed above, we expect this evolutionary model to be applicable to music. The HSD hypothesis supports the view that the human phenotype is, to a large extent, the outcome of an evolutionary process similar to that of animal domestication. In nonhuman mammals, domestication initially involved selection for tameness and resulted in a set of distinctive traits—physical, cognitive, and behavioral—that usually co-occurred, forming the domestication syndrome (Wilkins et al., 2014; see Lord et al., 2020, and Sanchez-Villagra et al., 2019, for critical views). This might be due to the fact that tameness reduces the input to the neural crest, an embryonic structure that supports the ontogenetic development of numerous body parts (Wilkins et al., 2014; see Lord et al., 2020; Sánchez-Villagra et al., 2016). The HSD hypothesis builds on the findings of many domestication traits in humans, including smaller skulls/brains (compared with archaic humans), reduced hair, neotenic features (e.g., extended childhood and increased playing behavior), and, particularly, reduced levels of reactive aggression (Fukase et al., 2015; Leach, 2003; Plavcan, 2012; Shea, 1989; Somel et al., 2009; Stringer, 2016; Zollikofer & Ponce de León, 2010). Diverse factors have been hypothesized to trigger HSD, including the rise of coparenting, the advent of community living, changes in our foraging ecology, climate deterioration, and the colonization of new environments (Brooks & Yamamoto, 2021; Pisor & Surbeck, 2019; Spikins et al., 2021). All in all, these factors might have promoted a selection toward less reactive and more prosocial behaviors, thereby instilling in humans a constellation of physical, behavioral, and cognitive changes characteristic of domestication. Many human-specific traits, such as our enhanced social cognition, increased cooperation, and finally, advanced technology and sophisticated culture, are the products of domesticate-like adaptation (see Hare, 2017, for an overview). This collective cooperativity that extends beyond the familial gene pool does not necessarily equate to domestication, but it quite closely resembles its principal traits. It seems to us that HSD presents a useful evolutionary framework for linguistic studies, especially for capturing those aspects of languages that are thought to emerge through a cultural mechanism. It is worth remembering that the earliest hominids, who had high levels of reactive aggression, practiced musilanguage rather than “language” and must have cultivated signals similar to animal communication. The latter simply could not support the “duality of patterning” (Hockett, 1960) and combinatoriality. Therefore, the “linguistic” component in musilanguage is harder to see than the “musical” component, although there is evidence that animal communication uses referential as well as motivational information, each coded differently (Manser, 2010). Indeed, animal communication comes much closer to human music than to human language due to its dedication to showing the signaller’s affective state (Fitch, 2006). There is neurophysiological evidence that “full language” must have crystallized later than “full music” because the acoustic characteristics of primate vocalizations are mainly determined by music-like features that serve as the foundation of verbal acquisition for human infants (Koelsch, 2009). 1 3 247 Human Nature (2023) 34:229–275 However, concluding from this that language evolved from music, as argued by Fitch (2010), seems a far stretch. The principal arguments against this scenario were summarized by Tallerman (2013): 1. Phonological systems do not evolve in isolation from semantics, as if they were “bare vocal sounds.” Consonants and vowels are linguistic entities, and phonological expansion derives from a growing vocabulary of words—not the other way around. It is the developing lexical system that brings to life phonological gestures (de Boer & Zuidema, 2010; Lindblom, 1998; Studdert-Kennedy, 2011; Zuidema & de Boer, 2009). 2. Despite greater similarity to animal vocalizations than human language, human song remains fundamentally different from animal vocalization. Animal-learned vocalizations lack transposability of intentions (i.e., repeated use of the same signal in different circumstances) and abstraction of the representation of an affective state, which are the landmarks of musical emotions. A single animal call is the basic unit of animal communication—produced instinctively in response to the actual stimulus present in the environment (Zuberbühler, 2017). And animallearned vocalizations are limited to display of fitness (Naguib & Riebel, 2014), are season- and gender-specific (Slater, 2011), and relate to mating or territorydefending situations (Slater, 2001)—unlike human music. 3. Animal learned vocalizations (some ethologists and researchers of animal communication call them “animal songs”) have a critical period of acquisition, are learned holistically, and take months before an animal can deliver them (Hurford, 2012). In contrast, humans can learn songs at any life-stage, doing it incrementally and rather quickly. Evidently, human song-learning engages very different neuro-physiological mechanisms and constitutes not an extension but a parallel evolutionary development to animal song—as Fitch himself recognizes (Fitch, 2010:184).21 4. Finally, it is hard to explain how and why music-like aspects of hominin vocalizations would have reduced their musicality and given rise to consonants that are fundamentally “unmusical” and notably absent in animal communication (Kolinsky et al., 2009). The musicality of speech comes from prosody, and prosody comes from joining words into phrases. Musical phrases have nothing in common with linguistic phrases other than the misleading term “phrase” (Benjamin et al., 2015)—linguistic phrases are built around words and their categorical relations, whereas musical phrases are determined primarily by the breathing rate that characterizes different emotional states (greater excitement transpires in 21 For this reason, the distinction between animal calls and songs has nothing to do with the distinction between human calls (e.g., the genre of forest-calls) and songs. Both distinctions emerged at different times, determined by different factors, and followed different evolutionary trajectories. A fundamental reorganization of expressive means in human musical communication in comparison with animal communication probably took place during the Paleolithic, resulting in the complete reversal of semantic values for a number of acoustic attributes of typical animal vocalizations (see Nikolsky, 2020b). 1 3 248 Human Nature (2023) 34:229–275 shorter phrases) and general release of tension (harmonic and melodic) toward the end of a phrase, which accompanies expiration (Alekseyev 1976).22 As we see it, the evolutionary continuity of animal communication and human music is superficial—human song and animal song constitute independent developments— and there is no reason to trace the origins of language from music. Under closer scrutiny, animal communication combines the semiotic characteristics of both human music and language (Manser, 2010): ●Animals use referential calls (i.e., they refer to specific attributes of the eliciting external stimuli to enable the receivers of these signals to react to these external stimuli) when encountering predators, discovering a food resource, and in agonistic social interactions, ●Animals use motivational calls (i.e., calls that display the emotional state of a caller, so the receivers react to this emotional state) in all other situations. Ontogenetically, acquisition of motivational calls precedes acquisition of referential calls and appears to be simpler in structure. Musilanguage must have just inherited referential and motivational specialization from animal communication and advanced it to the next evolutionary stage—building the repertories of calls of both types and introducing some transposability of their use. In this process, each type obtained a set of characteristic structural features that allowed listeners to distinguish both types upon hearing them. Motivational calls probably resembled the repertory of infantile vocalizations during the first few months of life, categorized into negative cries of various sorts and positive cooing—all characterized by prolonged use, as with music (typically, as long as the emotional state lasts). Referential musilanguage calls likely resembled the earliest attempts of an infant to point to specific things in a dialogic communication with a caretaker with the aid of gestures—shorter and more of turn-taking than the “monologic” motivational vocalizations. Such a “wordless” linguistic component is what Brown outlined in his 2017 amendment of the musilanguage theory with his new “prosodic scaffold” model (Brown, 2017). According to it, musilanguage conveyed primarily affect-related information in two principal ways: 1. through “affective prosody” (music-like) by means of anatomically available and innate impulse-driven modulations of pitch, loudness, and tempo—which remain global and holistic for the entirety of a call; 22 Although some researchers equate musical and linguistic syntax, the parallels between pitch and interval classes and sets, chordal typology, and key structure of music on the one hand and, correspondingly, phonological, morphological, and morphonological organizations of language are limited to only the latest stage of evolution of music, specifically as it is implemented in the Western classical music tradition (see Nikolsky & Benitez-Burraco, 2022). The majority of known non-Western traditional musical systems do not subscribe to the principles of Western tonality. For such musical systems, similarities between musical and linguistic syntax are confined to the elementary, “surface” level of tonal organization—what music theorists qualify as “motivic” rather than “phrasal” level of compositionality. 1 3 249 Human Nature (2023) 34:229–275 2. through “intonational prosody” (speech-like) by filling a prosodic scaffold with phoneme-like deictic utterances—employing both global and local mechanisms for conveying linguistic modality (e.g., question versus statement) and emphasis (stress, prominence, focus). The speech-like way must have evolved from the music-like way through an ongoing adaptation of the reflex-based vocalizations in response to the most common environmental situations. Such vocalizations were probably reshaped by their chain transmission and natural selection for the most effective patterns of communication under the pressure of time—in other words, to successfully deliver signals as soon as possible, enabling live updates on critical changes in the environment. The demand of urgency probably pushed “intonational prosody” toward language, in contrast to “affective prosody,” focused on the caller’s expression rather than the task of keeping listeners up-to-date. Supported with hominin’s capacity for accumulation of knowledge, the newly forged intonational patterns were memorized and preserved (in contrast to animal communication), leading to the invention of consonants, formation of syllables, and eventual adoption of basic conventional words for the most common objects.23 With regard to HSD, musilanguage, protomusic, and protolanguage all fall out of its scope, since currently available data do not indicate the presence of a domesticated phenotype among extinct hominins, and the data coming from developmental psychology and ethnomusicology is applicable to Homo sapiens only. Extrapolating our conclusions on the factors at play (see Nikolsky & Benítez-Burraco, 2022, for details), it is plausible to expect that hominins who practiced protomusic and protolanguage, perhaps even musilanguage, had lower levels of reactive aggression than nonhuman primates. Some traits established for Homo erectus might be interpreted as promoting cooperative behaviors between closely related partners: hunting and gathering in groups, caring for injured and sick group members (Leroy et al., 2011), need for helpers during delivery due to large cranial size, caretaking assistance due to longer altriciality (Boaz & Ciochon, 2004), and migration to colder climates, where hardship of survival was likely to encourage mutual support in such activities as communally planned big game hunting, maintaining fire, and making clothes and huts— all suggestive of some form of communication between the participants (Mania & Mania, 2004). However, such arguments remain speculative until more conclusive archaeological evidence is uncovered. 23 It is not a trivial task to explain the brain divergence of processing architectures for music and language. Recently, Dehaene and colleagues (2022) have argued that music and language, as well as several other human-distinctive abilities, such as mathematics, might depend on parallel circuits endowed with similar computational principles, which the authors construed as internal languages of thought, akin to computer languages. These languages are claimed to recursively compute small sets of symbols—the authors call them “primitives”—whose nature varies from one domain to another (merge and antisymmetry for language, but pitch and rhythm for music). These mental programs which encode nested repetitions with variations contrast with the simpler computational models that can capture nonhuman primate data. Interestingly for our concerns here, Dehaene and colleagues have hypothesized that some mutation(s) in the human lineage might have granted compositionality to many, possibly all, human cortical circuits. This circumstance would account for the fact that although these circuits process different types of “primitives” and differ in their styles (e.g., pitch and rhythm for music, merge and antisymmetry for language), they exhibit similar computational properties (particularly, the ability to process symbolic items recursively). 1 3 250 Human Nature (2023) 34:229–275 For humans, HSD can account for the evolution of abilities and behaviors that enable the cumulative growth of linguistic complexity through already ongoing, multigenerational learning and use. This involves language teaching and practicing, promoted by a more prosocial and neotenic phenotype. In a series of related papers, Progovac and Benítez-Burraco (2019; Benítez-Burraco & Progovac, 2020, 2021) have developed a detailed model of how HSD might have contributed to the evolution of language (and of languages). At the time of the emergence of early humans, reactive aggression was still high, and consequently, communication through language must have been limited to single-word commands, threats, and exclamations, mostly aimed at conveying emotions. Patient and cooperative turn-taking, using long utterances, and conveying referential meanings, frequently observed in present-day interactions, were simply unattainable back then. Increasing HSD supported stronger in-group networks, involving more diverse, frequent, and prolonged contacts between their members. Cooperative turn-taking must have become more common and elaborated, enabling the development of linguistic structures via cultural transmission. It is plausible to expect that single-word utterances were replaced by rudimentary two-slot grammars made of nouns and verbs to express predications. These earliest grammars might have been primarily used for creating colorful derogatory expressions (since emotional reactivity was still quite high), contributing to further increase in HSD, as these derogatory utterances helped replace physical reactive aggression with less-harmful verbal aggression. The main reason for the positive feedback loop between reactive aggression and grammar is the functional connection and partial overlap of the brain mechanisms that support combinatoriality and control of reactive aggressivity. To give just one example, in learned aggressive actions (a form of controlled aggression), the prefrontal cortex regulates the activity of the hypothalamus (a component of the “core aggression circuit”) and the striatum (part of the “learned aggression circuit”; Lischinsky & Lin, 2020). But the striatum plays a key role in grammar processing as part of the procedural memory and, more generally, of the cortico-subcortical networks responsible for hierarchical processing (Teichmann et al., 2015). Evidence of this functional connection/partial overlap is the concurrence of the difficulties in processing structural aspects of language with the aggressive outbursts in clinical conditions, caused by striatal dysfunction (Rosenblatt & Leroi, 2000; Savage, 1997; Zgaljardic et al., 2003). Accordingly, from an evolutionary point of view, one can expect that reduced reactive aggression, resulting from increased HSD, demanded additional control of subcortical structures by the cortex, which also promoted cross-modality. In other words, the ability to combine information from different cognitive domains was pivotal for merging linguistic items (see Benítez-Burraco & Progovac, 2021, for a more detailed discussion). Once HSD reached its peak at the end of the Upper Paleolithic (Cieri et al., 2014), behaviors conducive to the advance in linguistic complexity via cultural mechanisms proliferated: more frequent and diverse social contacts, longer learning periods, more frequent practicing, and so on. Such changes likely put in place the first hierarchical grammars that expressed transitivity. Languages with such grammars are called esoteric. These languages typically exhibit larger sound inventories and complex phonotactics, opaque morphologies (with more irregularities and morphophonological 1 3 251 Human Nature (2023) 34:229–275 constraints), limited semantic transparency (abundant idioms and idiosyncratic speech), reduced compositionality, and less sophisticated syntactic devices. These features are common for languages spoken by isolated human groups, living in small, close-knit communities with high proportions of native speakers—a rough proxy for languages spoken by present-day hunter-gatherer societies. The transition from the Upper Paleolithic to the Neolithic was accompanied by cardinal changes in social organization as a result of steady demographic growth and climatic changes. Growing social interactions brought to life extensive social networks, promoting trading and mating, while also unleashing intergroup hostilities over competition for limited natural resources. The necessity to regulate conflicts, convey decontextualized meanings, and exchange technological know-how with unrelated individuals favored the emergence of another type of language—exoteric. These languages typically feature expanded vocabularies and increased syntactic complexity (including greater reliance on recursion), as well as greater compositionality and enhanced semantic transparency—all advanced at the cost of simpler phonological inventories and sound combinations, and more regular morphologies. A proxy of such languages are those spoken by present-day agriculturalist societies, particularly state-governed autochthonous ones. Since these languages are also suitable for conscious planning, establishing alliances, conducting warfare, and, ultimately, supporting the emergence of cultural institutions related to war and peace, their emergence can be linked to the advent of proactive aggression that became more widespread during the transition from the Neolithic to the rise of first civilizations. Our model of evolution of human languages under the effects of HSD can also explain modern pragmatics and linguistic modes of interaction. A reduction in reactive aggression is beneficial for cognitive and behavioral changes necessary for the emergence of rules of turn-taking and complex inferential abilities, both of which are cornerstones of our conversational abilities. On the cognitive side, the expansion of pair-bonding to nonreproductive relationships marked a crucial achievement in social organization. The potentiating of cross-modal thinking, instrumental for linguistic chunking, enabled conventions of figurative uses of language (e.g., metaphors and metonyms) and pragmatic inferencing. On the behavioral side, increased HSD favored prolonged face-to-face interactions, long-term cooperation, and consideration for others’ needs. Overall, these cognitive and behavioral changes enabled communication of more complex meanings by indirect means (see Benítez-Burraco et al., 2021 for a detailed view). In general, this HSD model ties the evolution of language to changes in aggression management, both reactive and proactive, ultimately connecting specific linguistic structural features with the HSD-related behavioral and cognitive changes, based on their shared neurobiological substrate. At the same time, this model establishes a strong continuity between communication and cognitive abilities exhibited by other species, while also supporting cultural niche construction, cultural evolution, and gene-culture coevolution as key factors that accounted for the exclusiveness of language to human communication. Our contention here is that the same model can be also applied to human musicality, music types, and functions of music—not only because of the common origins of music and language, but mostly because of the common effects of changing levels of reactive and proactive aggression. 1 3 252 Human Nature (2023) 34:229–275 Human Self-Domestication and the Evolution of Music As noted, we find our HSD model of coevolution more parsimonious than those accounts that hypothesize different rationales and mechanisms for the evolution of music and of language. Our approach reconciles hypotheses about music evolution that have been presented as irreconcilable, such as the “social bonding hypothesis” (Savage et al., 2020) and “the credible signal hypothesis” (Mehr et al., 2021). Moreover, this model explains better than other models how different types of music diachronically emerged through a cultural mechanism—which was previously examinable mostly through memetic approaches (see Jan, 2018). Overall, we hypothesize that the gradual changes in the subtle balance between reactive and proactive aggression could help us understand the steady complexification of music, the emergence of its new functions, and the transformation of the old ones, as well as the past and present distribution of musical types and genres as reported by ethnomusicologists. Our model is summarized in Fig. 2, which presents music evolution vis-à-vis language evolution to highlight their common origins and their parallel evolutionary pathways under the effects of HSD, changes in paleoclimatic conditions, demo- Fig. 2 The timeline of the coevolution of music and language. The figure reflects the evolution of types of music vis-à-vis the evolution of types of languages in regard to the changes in human socialization patterns under the effects of increased HSD (reproduced from Nikolsky & Benítez-Burraco, 2022, Fig. 7) 1 3 253 Human Nature (2023) 34:229–275 Acknowledgements The authors wish to thank Ms. Sheila Bazleh for her assistance during the proofreading of the manuscript. Author Contributions ABB and AN conceived the paper, reviewed the available literature, analyzed the data, and wrote the paper. Both authors approved the final version of the manuscript. Funding Sources Funding for open access publishing: Universidad de Sevilla/CBUA Data Availability Not applicable. Declarations Conflict of Interest Disclosure The authors have no conflicts of interest to declare. Statement of Ethics The research conducted for the paper relied on previously published data by others, hence no ethics approval was required. Publication History A previous, less-elaborate version of this manuscript has been posted as a preprint to PsyArXiv: https://psyarxiv.com/xfbqn/. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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