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A neurocomputational model of the effect of learned labels on infants’ objectrepresentations
Abstract
The effect of labels on nonlinguistic representations is the focusof substantial debate in the developmental literature. A recentempirical study (Twomey & Westermann, 2016) suggested thatlabels are incorporated into object representations, such thatinfants respond differently to objects for which they know alabel relative to unlabeled objects. However, these empiricaldata cannot differentiate between two recent theories ofintegrated label-object representations, one of which assumeslabels are features of object representations, and one whichassumes labels are represented separately, but become closelyassociated with learning. We address this issue using aneurocomputational (auto-encoder) model to instantiate boththeoretical approaches. Simulation data support an account inwhich labels are features of objects, with the samerepresentational status as the objects’ visual and hapticcharacteristics.
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