Statistical learning in domestic chicks is modulated by strain and sex

Chiara Santolin,Orsola Rosa-Salva,Lucia Regolin,Giorgio Vallortigara,Bastien S Lemaire

doi:10.1038/s41598-020-72090-8

Chiara Santolin, Orsola Rosa-Salva + Show 3 more

Open Access

https://doi.org/10.1038/s41598-020-72090-8

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Abstract

Statistical learning is a key mechanism for detecting regularities from a variety of sensory inputs. Precocial newborn domestic chicks provide an excellent model for (1) exploring unsupervised forms of statistical learning in a comparative perspective, and (2) elucidating the ecological function of statistical learning using imprinting procedures. Here we investigated the role of the sex of the chicks in modulating the direction of preference (for familiarity or novelty) in a visual statistical learning task already employed with chicks and human infants. Using both automated tracking and direct human coding, we confirmed chicks’ capacity to recognize the presence of a statistically defined structure underlying a continuous stream of shapes. Using a different chicken strain than previous studies, we were also able to highlight sex differences in chicks’ propensity to approach the familiar or novel sequence. This could also explain a previous failure to reveal statistical learning in chicks which sex was however not determined. Our study confirms chicks’ ability to track visual statistics. The pivotal role of sex in determining familiarity or novelty preferences in this species and the interaction with the animals’ strain highlight the importance to contextualize comparative research within the ecology of each species.

Highlights

Statistical learning is a key mechanism for detecting regularities from a variety of sensory inputs
Over the past 20 years, a substantial body of research has pointed to statistical learning as a key mechanism
The general nature of statistical learning has been shown across modalities, tasks and species, pointing to a powerful, yet constrained, learning process[1,2,3,4]

Summary

Introduction

Statistical learning is a key mechanism for detecting regularities from a variety of sensory inputs. Statistical learning in infants has been shown for both temporal and spatial inputs, such as streams of shapes or multi-element displays[5,6,7,8,9,10,11] Such mechanism seems to be spontaneous, rapid and available from birth, allowing infants to extract relevant patterns for further processing of visual s cenes[4]. Chicks revealed even superior abilities than human infants, succeeding in the task when sequences were composed of up to six e lements[9,28] This may be due to biological constraints on visual processing in human newborns, while the maturation of chicks’ visual system is already advanced at birth[29,30,31]

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