Autonomy in Action: Linking the Act of Looking to Memory Formation in Infancy via Dynamic Neural Fields

Abstract

Looking is a fundamental exploratory behavior by which infants acquire knowledge about the world. In theories of infant habituation, however, looking as an exploratory behavior has been deemphasized relative to the reliable nature with which looking indexes active cognitive processing. We present a new theory that connects looking to the dynamics of memory formation and formally implement this theory in a Dynamic Neural Field model that learns autonomously as it actively looks and looks away from a stimulus. We situate this model in a habituation task and illustrate the mechanisms by which looking, encoding, working memory formation, and long-term memory formation give rise to habituation across multiple stimulus and task contexts. We also illustrate how the act of looking and the temporal dynamics of learning affect each other. Finally, we test a new hypothesis about the sources of developmental differences in looking.

Beyond slots and resources: Grounding cognitive concepts in neural dynamics

“…The developmental mechanism implemented in the DFT—the Spatial Precision Hypothesis—extends from previous work in spatial cognition, which has captured developmental changes in spatial recall and position discrimination, including the influences of reference frames and long-term memory. According to this hypothesis, neural interactions strengthen over development (Perone, Simmering, & Spencer, 2011; Perone & Spencer, in press, 2013; Schutte, Spencer, & Schöner, 2003; Schutte & Spencer, 2009; Simmering et al, 2013, 2008; Simmering & Patterson, 2012; Simmering, 2013; Spencer et al, 2007; cf. Edin, Macoveanu, Olesen, Tegner, & Klingberg, 2007).…”

“…Samuelson, Schutte, and Horst (2009) applied a dynamic neural field architecture to word learning tasks, and showed that changing input strength for different object characteristics (e.g., shape versus material) captured children’s performance on multiple novel noun generalization tasks. Finally, Perone and Spencer (in press, 2013) have shown how a dynamic neural field architecture can explain developmental changes in infants’ looking behavior in both habituation and paired comparison tasks through changes in neural interactions in memory and looking dynamics. As these examples demonstrate, a model like the DFT has broad application across behavioral tasks, cognitive domains, and developmental periods.…”

Models provide specificity: Testing a proposed mechanism of visual working memory capacity development

“…This also highlights the importance of stability at different timescales: not only is an individual peak more susceptible to perturbation on an individual trial, but the variation in peak position and strength also varies considerably across trials early in development. Given the successful application to developmental changes in spatial cognition during early childhood (Ortmann & Schutte, 2010; Schutte & Spencer, 2009, 2010; Schutte et al, 2003; Simmering et al, 2008; Simmering & Spencer, 2008) and recent extensions to developmental changes in infant looking behavior (Perone et al, 2011; Perone & Spencer, 2011; Perone, Spencer, & Schöner, 2007), Simmering (2008) tested whether the SPH could also account for developmental increases in capacity.…”

Contributions of dynamic systems theory to cognitive development

“…The first avenue involves developing the feed-forward mapping from the input layer into the neural field. This type of slow learning—akin to perceptual learning—has been important in several projects where we have modeled infants' and young children's performance in quantitative detail (Schutte & Spencer, 2009; Perone & Spencer, in press). In these cases, we have implemented this form of developmental change by changing the precision (i.e., the width) and strength of the input pattern.…”

“…This posits that locally excitatory and laterally inhibitory interactions become stronger over development. For instance, in several projects, we have captured developmental change by increasing the strength of neural interactions in excitatory and inhibitory layers (Schutte & Spencer, 2009; Perone & Spencer, in press). This has effectively captured both quantitative and qualitative changes over development as we discuss in greater detail below.…”