Empirical advances have been made in understanding how human language, in its combinatorial complexity and unbounded expressivity, may have evolved from the communication systems present in our evolutionary ancestors. However, a number of cognitive processes and neurobiological mechanisms that support language may not have evolved specifically for communication, but rather from abilities that support perception and cognition more generally. We review recent evidence from comparative behavioural and neurobiological studies on structured sequence learning in human and nonhuman primates. These studies support (...) the notion that certain sequence learning abilities are evolutionarily conserved and engage corresponding inferior frontal brain regions across the species, regions also involved in processing language in humans. Alongside the cross-species similarities is evidence for human specialisations, illuminating the likely evolutionary pathways towards language in modern humans. We argue that cognitive abilities that were in place for animals to learn combinatorial relationships in the sensory world were available and co-opted for language in humans. (shrink)

The puzzle of resultant moral luck arises when we are disposed to think that an agent who caused a harm deserves to be blamed more than an otherwise identical agent who did not. One popular perspective on resultant moral luck explains our dispositions to produce different judgments with regard to the agents who feature in these cases as a product not of what they genuinely deserve but of our epistemic situation. On this account, there is no genuine resultant moral luck; (...) there is only luck in what evidence becomes available to observers. In this paper, I develop an evolutionary account of our inclination to take the results of actions as evidence for the mental states of agents, thereby explaining why the resulting intuitions are recalcitrant to correction. The account explains why the puzzle of resultant moral luck arises: because our disposition to take the harms agents cause as evidence of their mental states can produce intuitions which conflict with those that arise when we examine agents’ mental states without reference to the results of their actions. The account also helps to solve the puzzle of resultant moral luck, by providing a strong reason to ignore the intuitions caused by our disposition to regard actual harms as evidence of mental states. Since these intuitions arise using an unreliable proxy for agents’ mental states, they ought to be trumped by more reliable evidence. (shrink)

Studies of AGL have frequently used training and test stimuli that might provide multiple cues for learning, raising the question what subjects have actually learned. Using a selected subset of studies on humans and non‐human animals, Trotter et al. demonstrate how a meta‐analysis can be used to identify relevant experimental variables, providing a first step in asssessing the relative contribution of design features of grammars as well as of species‐specific effects on AGL.

Human language is a salient example of a neurocognitive system that is specialized to process complex dependencies between sensory events distributed in time, yet how this system evolved and specialized remains unclear. Artificial Grammar Learning (AGL) studies have generated a wealth of insights into how human adults and infants process different types of sequencing dependencies of varying complexity. The AGL paradigm has also been adopted to examine the sequence processing abilities of nonhuman animals. We critically evaluate this growing literature in (...) species ranging from mammals (primates and rats) to birds (pigeons, songbirds, and parrots) considering also cross‐species comparisons. The findings are contrasted with seminal studies in human infants that motivated the work in nonhuman animals. This synopsis identifies advances in knowledge and where uncertainty remains regarding the various strategies that nonhuman animals can adopt for processing sequencing dependencies. The paucity of evidence in the few species studied to date and the need for follow‐up experiments indicate that we do not yet understand the limits of animal sequence processing capacities and thereby the evolutionary pattern. This vibrant, yet still budding, field of research carries substantial promise for advancing knowledge on animal abilities, cognitive substrates, and language evolution. (shrink)

Extracting the regularities of our environment is one of our core cognitive abilities. To study the fine-grained dynamics of the extraction of embedded regularities, a method combining the advantages of the artificial language paradigm and the serial response time task was used with a group of Guinea baboons in a new automatic experimental device. After a series of random trials, monkeys were exposed to language-like patterns. We found that the extraction of embedded patterns positioned at the end of larger patterns (...) was faster than the extraction of initial embedded patterns. This result suggests that there is a learning advantage for the final element of a sequence that benefits from the contextual information provided by previous elements. (shrink)

How do listeners learn about the statistical regularities underlying musical harmony? In traditional Western music, certain chords predict the occurrence of other chords: Given a particular chord, not all chords are equally likely to follow. In Experiments 1 and 2, we investigated whether adults make use of statistical information when learning new musical structures. Listeners were exposed to a novel musical system containing phrases generated using an artificial grammar. This new system contained statistical structure quite different from Western tonal music. (...) Our results suggest that learners take advantage of the statistical patterning of chords to acquire new musical structures, similar to learning processes previously observed for language learning. (shrink)

In this article, we consider infants’ acquisition of foundational aspects of language and emotion through the lens of statistical learning. By taking a comparative developmental approach, we highlight ways in which the learning problems presented by input from these two rich communicative domains are both similar and different. Our goal is to encourage other scholars to consider multiple domains of human experience when developing theories in developmental cognitive science.