Capacities and neural mechanisms for auditory statistical learning across species

Abstract

Statistical learning has been proposed as a possible mechanism by which individuals can become sensitive to the structures of language fundamental for speech perception. Since its description in human infants, statistical learning has been described in human adults and several non-human species as a general process by which animals learn about stimulus-relevant statistics. The neurobiology of statistical learning is beginning to be understood, but many questions remain about the underlying mechanisms. Why is the developing brain particularly sensitive to stimulus and environmental statistics, and what neural processes are engaged in the adult brain to enable learning from statistical regularities in the absence of external reward or instruction? This review will survey the statistical learning abilities of humans and non-human animals with a particular focus on communicative vocalizations. We discuss the neurobiological basis of statistical learning, and specifically what can be learned by exploring this process in both humans and laboratory animals. Finally, we describe advantages of studying vocal communication in rodents as a means to further our understanding of the cortical plasticity mechanisms engaged during statistical learning. We examine the use of rodents in the context of pup retrieval, which is an auditory-based and experience-dependent form of maternal behavior.

Learning to predict: Neuronal signatures of auditory expectancy in human event-related potentials

“…For instance, infants learn word boundaries from the continuous stream of speech they encounter putatively by passive computation of the transitional probabilities between phonemes ( Saffran et al, 1999 , 1996 ). Similar implicit learning capabilities are observed in human adults and non-human animals in non-linguistic contexts ( Moldwin et al, 2017 ; Lu and Vicario, 2014 ; Heimbauer et al, 2018 ; Schiavo and Froemke, 2019 ; Saffran et al, 1999 ). This type of statistical learning, herein called ‘learned expectancy’, is crucial for the survival of many organisms, enabling them to extract regularities in the environment and thereby anticipate future events.…”

Social isolation improves the performance of rodents in a novel cognitive flexibility task

“…Thus, it is conceivable that inhibitory control deficits might be the neural basis for increases in novel exploration and subsequently for the improvement in unconstrained flexibility. Moreover, as gregarious animals, mice normally live in groups and are adapted to supporting and interacting with conspecific individuals [1–3, 46, 47]. However, isolation rearing would interrupt these relationships and individual mice would be forced to navigate their the complex surroundings and survival problems alone, which may increase investigation motivation to compensate for the absence of social support [12, 41].…”

Belief it or not: How children construct a theory of mind

“…Evolution has likely primed animals of all types to constantly predict events to survive and flourish (e.g., to determine where food is, how to avoid predators, how to scale the dominance hierarchy, how to win a mate's affections). Detecting regularities is a feature of how songbirds learn the patterns in the songs they hear and copy (James et al, 2020) and is within the capabilities of a range of species such as nonhuman primates and rodents (Schiavo & Froemke, 2019). In addition, as I argued earlier, it is the skill that explains cows' ability to predict the motion of a ball kicked by a human.…”