Groove—defined as the pleasurable urge to move to a rhythm—depends on a fine-tuned interplay between predictability arising from repetitive rhythmic patterns, and surprise arising from rhythmic deviations, for example in the form of syncopation. The perfect balance between predictability and surprise is commonly found in rhythmic patterns with a moderate level of rhythmic complexity and represents the sweet spot of the groove experience. In contrast, rhythms with low or high complexity are usually associated with a weaker experience of groove because (...) they are too boring to be engaging or too complex to be interpreted, respectively. Consequently, the relationship between rhythmic complexity and groove experience can be described by an inverted U-shaped function. We interpret this inverted U shape in light of the theory of predictive processing and provide perspectives on how rhythmic complexity and groove can help us to understand the underlying neural mechanisms linking temporal predictions, movement, and reward. A better understanding of these mechanisms can guide future approaches to improve treatments for patients with motor impairments, such as Parkinson’s disease, and to investigate prosocial aspects of interpersonal interactions that feature music, such as dancing. Finally, we present some open questions and ideas for future research. (shrink)

The two target articles agree that processes of cultural evolution generate richness and diversity in music, but neither address this question in a focused way. We sketch one way to proceed – and hence suggest how the target articles differ not only in empirical claims, but also in their tacit, prior assumptions about the relationship between cognition and culture.

Why do humans make music? Theories of the evolution of musicality have focused mainly on the value of music for specific adaptive contexts such as mate selection, parental care, coalition signaling, and group cohesion. Synthesizing and extending previous proposals, we argue that social bonding is an overarching function that unifies all of these theories, and that musicality enabled social bonding at larger scales than grooming and other bonding mechanisms available in ancestral primate societies. We combine cross-disciplinary evidence from archeology, anthropology, (...) biology, musicology, psychology, and neuroscience into a unified framework that accounts for the biological and cultural evolution of music. We argue that the evolution of musicality involves gene–culture coevolution, through which proto-musical behaviors that initially arose and spread as cultural inventions had feedback effects on biological evolution because of their impact on social bonding. We emphasize the deep links between production, perception, prediction, and social reward arising from repetition, synchronization, and harmonization of rhythms and pitches, and summarize empirical evidence for these links at the levels of brain networks, physiological mechanisms, and behaviors across cultures and across species. Finally, we address potential criticisms and make testable predictions for future research, including neurobiological bases of musicality and relationships between human music, language, animal song, and other domains. The music and social bonding hypothesis provides the most comprehensive theory to date of the biological and cultural evolution of music. (shrink)

The aim of this contribution is to broaden the concept of musical meaning from an abstract and emotionally neutral cognitive representation to an emotion-integrating description that is related to the evolutionary approach to music. Starting from the dispositional machinery for dealing with music as a temporal and sounding phenomenon, musical emotions are considered as adaptive responses to be aroused in human beings as the product of neural structures that are specialized for their processing. A theoretical and empirical background is provided (...) in order to bring together the findings of music and emotion studies and the evolutionary approach to musical meaning. The theoretical grounding elaborates on the transition from referential to affective semantics, the distinction between expression and induction of emotions, and the tension between discrete-digital and analog-continuous processing of the sounds. The empirical background provides evidence from several findings such as infant-directed speech, referential emotive vocalizations and separation calls in lower mammals, the distinction between the acoustic and vehicle mode of sound perception, and the bodily and physiological reactions to the sounds. It is argued, finally, that early affective processing reflects the way emotions make our bodies feel, which in turn reflects on the emotions expressed and decoded. As such, there is a dynamic tension between nature and nurture, which is reflected in the nature-nurture-nature cycle of musical sense-making. (shrink)

The online processing of both music and language involves making predictions about upcoming material, but the relationship between prediction in these two domains is not well understood. Electrophysiological methods for studying individual differences in prediction in language processing have opened the door to new questions. Specifically, we ask whether individuals with musical training predict upcoming linguistic material more strongly and/or more accurately than non-musicians. We propose two reasons why prediction in these two domains might be linked: Musicians may have greater (...) verbal short-term/working memory; music may specifically reward predictions based on hierarchical structure. We provide suggestions as to how to expand upon recent work on individual differences in language processing to test these hypotheses. (shrink)

Worldwide, children face adverse childhood experiences, being exposed to risks ranging from, exposure to political violence and forced migration over the deleterious effects of climate change, to unsafe cultural practices. As a consequence, children that seek refuge or migrate to European countries are extremely vulnerable, often struggling with integration in school, peer community, and their broader social circle. This multifaceted struggle can derive from external factors, such as the adaptation process and contact with other children, or internal factors such as (...) the fears and trauma that every child carries within them since they departed from their homeland. To bounce, grow, connect, and create in both adversity and opportunity, children need to build resilience, i.e., the capacity of an individual to maintain stable psychological functioning throughout the course of adversity. On the one hand, building resilience requires developing a set of individual skills, such as self-control, emotion regulation, self-esteem, and agency. On the other hand, building resilience involves developing social skills, connection, and close relationships. In this theoretical contribution, we review and map existing research to argue that activities based on the combination of music and movement has a strong potential to intensively build resilience. First, we connect the concepts of resilience and eudaimonia, based on the protective factors and key components of resilience. Then we discuss how music and movement, separately, may contribute to building resilience. Next, drawing on the basic mechanisms of musical sense-making, we argue that through combining music and movement, children engage in empowering musical sense-making processes that support building resilience, and in this way, support them to grow together and deeply experience eudaimonic values such as self-awareness, confidence and self-esteem, personal autonomy, connection, belonging, and bonding. Finally, we connect theory to practice. Based on the presented theoretical elaborations and on the authors’ experience as practitioners, we propose a set of guiding principles for the design of movement-based musical activities that foster the internal and external factors necessary to build resilience. (shrink)

The predictive processing framework posits that people continuously use predictive principles when interacting with, learning from, and interpreting their surroundings. Here, we suggest that the same framework may help explain how people process self-relevant knowledge and maintain a stable and positive self-concept. Specifically, we recast two prominent self-relevant motivations, self-verification and self-enhancement, in predictive processing (PP) terms. We suggest that these self-relevant motivations interact with the self-concept (i.e., priors) to create strong predictions. These predictions, in turn, influence how people interpret (...) information about themselves. In particular, we argue that these strong self-relevant predictions dictate how prediction error, the deviation from the original prediction, is processed. In contrast to many implementations of the PP framework, we suggest that predictions and priors emanating from stable constructs (such as the self-concept) cultivate belief-maintaining, rather than belief-updating, dynamics. Based on recent findings, we also postulate that evidence supporting a predicted model of the self (or interpreted as such) triggers subjective reward responses, potentially reinforcing existing beliefs. Characterizing the role of rewards in self-belief maintenance and reframing self-relevant motivations and rewards in predictive processing terms offers novel insights into how the self is maintained in neurotypical adults, as well as in pathological populations, potentially pointing to therapeutic implications. (shrink)

We argue that music can serve as a time-sensitive lens into the interplay between instrumental and ritual stances in cultural evolution. Over various timescales, music can switch between pursuing an end goal or not, and between presenting a causal opacity that is resolvable, or not. With these fluctuations come changes in the motivational structures that drive innovation versus copying.

Savage et al. argue for musicality as having evolved for the overarching purpose of social bonding. By way of contrast, we highlight contemporary predictive processing models of human cognitive functioning in which the production and enjoyment of music follows directly from the principle of prediction error minimization.