Limor Raviv

Publications

Displaying 1 - 4 of 4
  • Raghavan, R., Raviv, L., & Peeters, D. (2023). What's your point? Insights from virtual reality on the relation between intention and action in the production of pointing gestures. Cognition, 240: 105581. doi:10.1016/j.cognition.2023.105581.

    Abstract

    Human communication involves the process of translating intentions into communicative actions. But how exactly do our intentions surface in the visible communicative behavior we display? Here we focus on pointing gestures, a fundamental building block of everyday communication, and investigate whether and how different types of underlying intent modulate the kinematics of the pointing hand and the brain activity preceding the gestural movement. In a dynamic virtual reality environment, participants pointed at a referent to either share attention with their addressee, inform their addressee, or get their addressee to perform an action. Behaviorally, it was observed that these different underlying intentions modulated how long participants kept their arm and finger still, both prior to starting the movement and when keeping their pointing hand in apex position. In early planning stages, a neurophysiological distinction was observed between a gesture that is used to share attitudes and knowledge with another person versus a gesture that mainly uses that person as a means to perform an action. Together, these findings suggest that our intentions influence our actions from the earliest neurophysiological planning stages to the kinematic endpoint of the movement itself.
  • Raviv, L., & Kirby, S. (2023). Self domestication and the cultural evolution of language. In J. J. Tehrani, J. Kendal, & R. Kendal (Eds.), The Oxford Handbook of Cultural Evolution. Oxford: Oxford University Press. doi:10.1093/oxfordhb/9780198869252.013.60.

    Abstract

    The structural design features of human language emerge in the process of cultural evolution, shaping languages over the course of communication, learning, and transmission. What role does this leave biological evolution? This chapter highlights the biological bases and preconditions that underlie the particular type of prosocial behaviours and cognitive inference abilities that are required for languages to emerge via cultural evolution to begin with.
  • Raviv, L., Jacobson, S. L., Plotnik, J. M., Bowman, J., Lynch, V., & Benítez-Burraco, A. (2023). Elephants as an animal model for self-domestication. Proceedings of the National Academy of Sciences of the United States of America, 120(15): e2208607120. doi:10.1073/pnas.2208607120.

    Abstract

    Humans are unique in their sophisticated culture and societal structures, their complex languages, and their extensive tool use. According to the human self-domestication hypothesis, this unique set of traits may be the result of an evolutionary process of self-induced domestication, in which humans evolved to be less aggressive and more cooperative. However, the only other species that has been argued to be self-domesticated besides humans so far is bonobos, resulting in a narrow scope for investigating this theory limited to the primate order. Here, we propose an animal model for studying self-domestication: the elephant. First, we support our hypothesis with an extensive cross-species comparison, which suggests that elephants indeed exhibit many of the features associated with self-domestication (e.g., reduced aggression, increased prosociality, extended juvenile period, increased playfulness, socially regulated cortisol levels, and complex vocal behavior). Next, we present genetic evidence to reinforce our proposal, showing that genes positively selected in elephants are enriched in pathways associated with domestication traits and include several candidate genes previously associated with domestication. We also discuss several explanations for what may have triggered a self-domestication process in the elephant lineage. Our findings support the idea that elephants, like humans and bonobos, may be self-domesticated. Since the most recent common ancestor of humans and elephants is likely the most recent common ancestor of all placental mammals, our findings have important implications for convergent evolution beyond the primate taxa, and constitute an important advance toward understanding how and why self-domestication shaped humans’ unique cultural niche.

    Additional information

    supporting information
  • Raviv, L., De Heer Kloots, M., & Meyer, A. S. (2021). What makes a language easy to learn? A preregistered study on how systematic structure and community size affect language learnability. Cognition, 210: 104620. doi:10.1016/j.cognition.2021.104620.

    Abstract

    Cross-linguistic differences in morphological complexity could have important consequences for language learning. Specifically, it is often assumed that languages with more regular, compositional, and transparent grammars are easier to learn by both children and adults. Moreover, it has been shown that such grammars are more likely to evolve in bigger communities. Together, this suggests that some languages are acquired faster than others, and that this advantage can be traced back to community size and to the degree of systematicity in the language. However, the causal relationship between systematic linguistic structure and language learnability has not been formally tested, despite its potential importance for theories on language evolution, second language learning, and the origin of linguistic diversity. In this pre-registered study, we experimentally tested the effects of community size and systematic structure on adult language learning. We compared the acquisition of different yet comparable artificial languages that were created by big or small groups in a previous communication experiment, which varied in their degree of systematic linguistic structure. We asked (a) whether more structured languages were easier to learn; and (b) whether languages created by the bigger groups were easier to learn. We found that highly systematic languages were learned faster and more accurately by adults, but that the relationship between language learnability and linguistic structure was typically non-linear: high systematicity was advantageous for learning, but learners did not benefit from partly or semi-structured languages. Community size did not affect learnability: languages that evolved in big and small groups were equally learnable, and there was no additional advantage for languages created by bigger groups beyond their degree of systematic structure. Furthermore, our results suggested that predictability is an important advantage of systematic structure: participants who learned more structured languages were better at generalizing these languages to new, unfamiliar meanings, and different participants who learned the same more structured languages were more likely to produce similar labels. That is, systematic structure may allow speakers to converge effortlessly, such that strangers can immediately understand each other.

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