Cumulative cultural evolution, population structure and the origin of combinatoriality in human language

Population turnover, behavioral conservatism, and rates of cultural evolution

Cultural evolution facilitates behavioral adaptation in many species. The pace of cultural evolution can be accelerated by population turnover, where newcomers (immigrants or juvenile recruits) introduce adaptive cultural traits into their new group. However, where newcomers are naïve to the challenges of their new group, population turnover could potentially slow the rate of cultural evolution. Here, we model cultural evolution with population turnover and show that even if turnover results in the replacement of experienced individuals with naïve ones, turnover can still accelerate cultural evolution if (1) the rate of social learning is more than twice as fast as the turnover rate and (b) newcomers are more likely to learn socially than behaviorally conservative existing group members. Although population turnover is a relatively simple factor, it is common to all animal societies, and variation in the turnover rate may potentially play an important role in explaining variation in the occurrence and rates of adaptive cultural evolution across species.

Linguacultural and Cognitive Peculiarities of Linguistic Universals

The discussion about linguistic universals, initiated over 50 years ago by J. Greenberg, remains a topic of significant interest today. While there's an ongoing debate on the universality of linguistic forms - with some supporting the notion and others dismissing it as baseless-the idea of a unifying linguistic essence stands firm. The article aims to explore the linguacultural values of language, particularly how they enable the reconstruction of ideas and stereotypes within specific segments of a language system. The research found that universal language characteristics serve as a rich source of information for those studying linguacultural aspects. These traits offer nationally determined interpretations of words, drawing from associations rooted in either tangible or cultural codes. When delving into cultural codes present within every culture, the study discerned the presence of basic and universal codes. The existence of these codes provides insights into the formation of stereotypes, which encapsulate the experiences and knowledge intrinsic to the bearers of a culture. Linguistic universals, underpinned by universal grammar and semantic foundations, occupy a central position in linguacultural examinations, especially when reconstructing cultural ideas and stereotypes. Basic and universal cultural codes inherent in each culture facilitate the creation of linguistic worldviews.

From One Bilingual to the Next: An Iterated Learning Study on Language Evolution in Bilingual Societies

Studies of language evolution in the lab have used the iterated learning paradigm to show how linguistic structure emerges through cultural transmission-repeated cycles of learning and use across generations of speakers . However, agent-based simulations suggest that prior biases crucially impact the outcome of cultural transmission. Here, we explored this notion through an iterated learning study of English-French bilingual adults (mostly sequential bilinguals dominant in English). Each participant learned two unstructured artificial languages in a counterbalanced fashion, one resembling English, another resembling French at the phono-orthographic level. The output of each participant was passed down to the next participant, forming diffusion chains of 10 generations per language. We hypothesized that artificial languages would become easier to learn and exhibit greater structure when they were aligned with participants' bilingual experience (i.e., English languages being easier to learn overall), or as a function of practice (i.e., languages learned second being easier to learn overall). Instead, we found that English-like languages became more structured over generations, but only when they were learned first. In contrast, French-like languages became more structured regardless of the order of learning, suggesting the presence of an asymmetric switch cost during artificial language learning. Moreover, individual differences in language usage modulated the amount of structure produced by the participants. Overall, these data suggest that bilingual experience impacts how novel languages are learned at an individual level, which can then scale up to cultural transmission of novel language at a group level.

The emergence of word order from a social network perspective

The distribution of word order across languages is skewed with SOV order (e.g., researchers sentences write) and SVO order (e.g., researchers write sentences) being >100 times more common than OSV order (sentences researchers write). It is commonly assumed that cross-linguistic preferences reflect cognitive biases, but it is unknown why some languages exhibit dispreferred patterns, or why languages settle on a specific pattern out of several preferred ones. This paper tests whether larger communities are more likely to rely on cross-linguistically preferred patterns as a way to overcome the greater communicative challenges they encounter. Participants played a communication game in large groups, small groups, or alone. Results support the hypothesis that community size influences word order as well as suggest that SOV and SVO orders are prevalent for different reasons with SVO specifically addressing communicative pressures. The studies thus show how community structure can give rise to cross-linguistic preferences, when these preferences can be overridden, and suggest how language might change with changes in social structure.

What made us "hunter-gatherers of words"

This paper makes three interconnected claims: (i) the "human condition" cannot be captured by evolutionary narratives that reduce it to a recent 'cognitive modernity', nor by narratives that eliminates all cognitive differences between us and out closest extinct relatives, (ii) signals from paleogenomics, especially coming from deserts of introgression but also from signatures of positive selection, point to the importance of mutations that impact neurodevelopment, plausibly leading to temperamental differences, which may impact cultural evolutionary trajectories in specific ways, and (iii) these trajectories are expected to affect the language phenotypes, modifying what is being learned and how it is put to use. In particular, I hypothesize that these different trajectories influence the development of symbolic systems, the flexible ways in which symbols combine, and the size and configurations of the communities in which these systems are put to use.

Reconstructing social networks of Late Glacial and Holocene hunter-gatherers to understand cultural evolution

Culture is increasingly being framed as a driver of human phenotypes and behaviour. Yet very little is known about variations in the patterns of past social interactions between humans in cultural evolution. The archaeological record, combined with modern evolutionary and analytical approaches, provides a unique opportunity to investigate broad-scale patterns of cultural change. Prompted by evidence that a population's social connectivity influences cultural variability, in this article, we revisit traditional approaches used to infer cultural evolutionary processes from the archaeological data. We then propose that frameworks considering multi-scalar interactions (from individuals to populations) over time and space have the potential to advance knowledge in cultural evolutionary theory. We describe how social network analysis can be applied to analyse diachronic structural changes and test cultural transmission hypotheses using the archaeological record (here specifically from the Marine Isotope Stage 3 ca 57-29 ka onwards). We argue that the reconstruction of prehistoric networks offers a timely opportunity to test the interplay between social connectivity and culture and ultimately helps to disentangle evolutionary mechanisms in the archaeological record. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.

The origins of human cumulative culture: from the foraging niche to collective intelligence

Various studies have investigated cognitive mechanisms underlying culture in humans and other great apes. However, the adaptive reasons for the evolution of uniquely sophisticated cumulative culture in our species remain unclear. We propose that the cultural capabilities of humans are the evolutionary result of a stepwise transition from the ape-like lifestyle of earlier hominins to the foraging niche still observed in extant hunter-gatherers. Recent ethnographic, archaeological and genetic studies have provided compelling evidence that the components of the foraging niche (social egalitarianism, sexual and social division of labour, extensive co-residence and cooperation with unrelated individuals, multilocality, fluid sociality and high between-camp mobility) engendered a unique multilevel social structure where the cognitive mechanisms underlying cultural evolution (high-fidelity transmission, innovation, teaching, recombination, ratcheting) evolved as adaptations. Therefore, multilevel sociality underlies a 'social ratchet' or irreversible task specialization splitting the burden of cultural knowledge across individuals, which may explain why human collective intelligence is uniquely able to produce sophisticated cumulative culture. The foraging niche perspective may explain why a complex gene-culture dual inheritance system evolved uniquely in humans and interprets the cultural, morphological and genetic origins of Homo sapiens as a process of recombination of innovations appearing in differentiated but interconnected populations. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.

When does cultural evolution become cumulative culture? A case study of humpback whale song

Culture presents a second inheritance system by which innovations can be transmitted between generations and among individuals. Some vocal behaviours present compelling examples of cultural evolution. Where modifications accumulate over time, such a process can become cumulative cultural evolution. The existence of cumulative cultural evolution in non-human animals is controversial. When physical products of such a process do not exist, modifications may not be clearly visible over time. Here, we investigate whether the constantly evolving songs of humpback whales (Megaptera novaeangliae) are indicative of cumulative cultural evolution. Using nine years of song data recorded from the New Caledonian humpback whale population, we quantified song evolution and complexity, and formally evaluated this process in light of criteria for cumulative cultural evolution. Song accumulates changes shown by an increase in complexity, but this process is punctuated by rapid loss of song material. While such changes tentatively satisfy the core criteria for cumulative cultural evolution, this claim hinges on the assumption that novel songs are preferred by females. While parsimonious, until such time as studies can link fitness benefits (reproductive success) to individual singers, any claims that humpback whale song evolution represents a form of cumulative cultural evolution may remain open to interpretation. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.

Paradox of diversity in the collective brain

Human societies are collective brains. People within every society have cultural brains-brains that have evolved to selectively seek out adaptive knowledge and socially transmit solutions. Innovations emerge at a population level through the transmission of serendipitous mistakes, incremental improvements and novel recombinations. The rate of innovation through these mechanisms is a function of (1) a society's size and interconnectedness (sociality), which affects the number of models available for learning; (2) fidelity of information transmission, which affects how much information is lost during social learning; and (3) cultural trait diversity, which affects the range of possible solutions available for recombination. In general, and perhaps surprisingly, all three levers can increase and harm innovation by creating challenges around coordination, conformity and communication. Here, we focus on the 'paradox of diversity'-that cultural trait diversity offers the largest potential for empowering innovation, but also poses difficult challenges at both an organizational and societal level. We introduce 'cultural evolvability' as a framework for tackling these challenges, with implications for entrepreneurship, polarization and a nuanced understanding of the effects of diversity. This framework can guide researchers and practitioners in how to reap the benefits of diversity by reducing costs. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.

Collective minds: social network topology shapes collective cognition

Human cognition is not solitary, it is shaped by collective learning and memory. Unlike swarms or herds, human social networks have diverse topologies, serving diverse modes of collective cognition and behaviour. Here, we review research that combines network structure with psychological and neural experiments and modelling to understand how the topology of social networks shapes collective cognition. First, we review graph-theoretical approaches to behavioural experiments on collective memory, belief propagation and problem solving. These results show that different topologies of communication networks synchronize or integrate knowledge differently, serving diverse collective goals. Second, we discuss neuroimaging studies showing that human brains encode the topology of one's larger social network and show similar neural patterns to neural patterns of our friends and community ties (e.g. when watching movies). Third, we discuss cognitive similarities between learning social and non-social topologies, e.g. in spatial and associative learning, as well as common brain regions involved in processing social and non-social topologies. Finally, we discuss recent machine learning approaches to collective communication and cooperation in multi-agent artificial networks. Combining network science with cognitive, neural and computational approaches empowers investigating how social structures shape collective cognition, which can in turn help design goal-directed social network topologies. This article is part of a discussion meeting issue 'The emergence of collective knowledge and cumulative culture in animals, humans and machines'.