Prediction-learning in infants as a mechanism for gaze control during object exploration.

Matthew Schlesinger,Scott P Johnson,Dima Amso

doi:10.3389/fpsyg.2014.00441

Abstract

We are pursuing the hypothesis that visual exploration and learning in young infants is achieved by producing gaze-sample sequences that are sequentially predictable. Our recent analysis of infants’ gaze patterns during image free-viewing (Schlesinger and Amso, 2013) provides support for this idea. In particular, this work demonstrates that infants’ gaze samples are more easily learnable than those produced by adults, as well as those produced by three artificial-observer models. In the current study, we extend these findings to a well-studied object-perception task, by investigating 3-month-olds’ gaze patterns as they view a moving, partially occluded object. We first use infants’ gaze data from this task to produce a set of corresponding center-of-gaze (COG) sequences. Next, we generate two simulated sets of COG samples, from image-saliency and random-gaze models, respectively. Finally, we generate learnability estimates for the three sets of COG samples by presenting each as a training set to an SRN. There are two key findings. First, as predicted, infants’ COG samples from the occluded-object task are learned by a pool of simple recurrent networks faster than the samples produced by the yoked, artificial-observer models. Second, we also find that resetting activity in the recurrent layer increases the network’s prediction errors, which further implicates the presence of temporal structure in infants’ COG sequences. We conclude by relating our findings to the role of image-saliency and prediction-learning during the development of object perception.

Highlights

The capacity to perceive and recognize objects begins to develop shortly after birth (e.g., Fantz, 1956; Slater, 2002)
Standard deviation presented in parentheses; values in italics correspond to the two measures that were yoked across the three observer models
Dimensions that were systematically equated between observer groups

Summary

Introduction

The capacity to perceive and recognize objects begins to develop shortly after birth (e.g., Fantz, 1956; Slater, 2002). There are a number of relatively well-studied mechanisms that help drive the development of gaze control – in particular, during infants’ visual object exploration – including improvements in acuity and contrast perception, inhibition-of-return, and selective attention (e.g., Banks and Salapatek, 1978; Clohessy et al, 1991; Dannemiller, 2000). While these mechanisms help to explain when, why, and in which direction infants shift their gaze, they may offer limited explanatory power in accounting for gaze-shift patterns at a more fine-grained level (e.g., the particular visual features sampled by the fovea at the fixation point). We use a simple recurrent network (SRN) as a computational tool for estimating the presence of temporal or sequential structure within infants’ COG gaze patterns

Methods

Results

Discussion

Conclusion