(2012, 2013) first exposed participants to a stream of stimuli made up of the repeated presentation of 12 shapes, each of them being part of a triplet, namely a sequence of three visual shapes presented successively in a fixed order. On the contrary, visual statistical learning (VSL) was mostly based on explicit knowledge acquisition (see also Bertels et al., 2013). (2012) demonstrated that participants’ performance was not exclusively based on implicit knowledge. However, in a replication of their study using more sensitive and subjective measures of the acquired knowledge, Bertels et al. Based on a dissociation between direct and indirect measures of learning (i.e., in which task instructions respectively do or do not explicitly refer to the to-be-learned dimension), they concluded that participants learned the sequences implicitly. These authors investigated whether the statistical regularities between geometrical shapes can be learned outside awareness. (2009) were the first to tackle this issue. However, this assumption has seldom been tested directly. Therefore, the knowledge acquired through SL has generally been taken to be implicit, a perspective that is tacitly assumed by most authors in this domain, who generally tend to consider that any SL process always takes place outside awareness. Remarkably, SL is observed even though most participants do not report any conscious knowledge of the regularities (e.g., Kim et al., 2009 Arciuli and Simpson, 2011, 2012). It also occurs outside the focus of attention, that is, even when participants are engaged in an unrelated concurrent task (e.g., Saffran et al., 1997 but see Turk-Browne et al., 2005). Moreover, SL occurs incidentally, that is even when participants are not informed about the existence of regularities in the material. As a matter of fact, the occurrence of SL has been observed in infants ( Saffran et al., 1996 Kirkham et al., 2002 Bulf et al., 2011) as well as in non-human primates ( Goujon and Fagot, 2013 Rakoczy et al., 2014). Statistical learning is usually thought of as a form of implicit learning, which is a fundamental and ubiquitous process in cognition ( Perruchet and Pacton, 2006). Congruently, many authors have documented such an ability to extract statistical regularities from auditory and visual inputs in adults, children and infants (for a review of SL across development, see Krogh et al., 2013). In particular, learning of transitional probabilities is crucial to predict upcoming events on the basis of previous ones. This process is essential when facing a complex environment. Statistical learning (SL) refers to the learning mechanisms that subtend sensitivity to the statistical regularities present in the environment. These results suggest that the role of implicit and explicit influences in VSL may follow a developmental trajectory. Nevertheless, although adults performed above chance even when they claimed to guess, there was no evidence of implicit knowledge in children. In both age groups, participants who performed above chance in the completion task had conscious access to their knowledge. Results revealed that both children and young adults learned the statistical regularities between shapes. In order to assess the extent to which learning occurred explicitly, we also measured confidence through subjective measures in the direct task (i.e., binary confidence judgments). Learning of these sequences was then assessed using both direct and indirect measures. Fifth graders and undergraduates were exposed to a stream of visual shapes arranged in triplets.
Using the same version of the paradigm, we also tested young adults so as to directly compare results from both age groups. Here, we adapted their paradigm to investigate VSL and conscious awareness in children. (2012) addressed this question in young adults. However, there is continuing debate as to whether VSL is accompanied by conscious awareness of the statistical regularities between sequence elements. Evidence indicates that even infants are sensitive to these regularities (e.g., Kirkham et al., 2002). Visual statistical learning (VSL) is the ability to extract the joint and conditional probabilities of shapes co-occurring during passive viewing of complex visual configurations. 2Fonds de la Recherche Scientifique – Fonds National de la Recherche Scientifique, Brussels, Belgium.1Faculty of Psychology and Educational Sciences, Center for Research in Cognition and Neurosciences, Université Libre de Bruxelles, Brussels, Belgium.Julie Bertels 1, 2 *, Emeline Boursain 1, Arnaud Destrebecqz 1 and Vinciane Gaillard 1
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