Domain generality versus modality specificity: the paradox of statistical learning

Abstract

Statistical learning (SL) is typically considered to be a domain-general mechanism by which cognitive systems discover the underlying distributional properties of the input. However, recent studies examining whether there are commonalities in the learning of distributional information across different domains or modalities consistently reveal modality and stimulus specificity. Therefore, important questions are how and why a hypothesized domain-general learning mechanism systematically produces such effects. Here, we offer a theoretical framework according to which SL is not a unitary mechanism, but a set of domain-general computational principles that operate in different modalities and, therefore, are subject to the specific constraints characteristic of their respective brain regions. This framework offers testable predictions and we discuss its computational and neurobiological plausibility.

Keywords: domain-general mechanisms; modality specificity; neurobiologically plausible models; statistical learning; stimulus specificity.

Figure 1. Theoretical Model of Statistical Learning

Schematic representation of the processing of distributional information in the visual, auditory, and somatosensory cortex, for unimodal and multimodal events. Different encoded representations of continuous input presented in time or space result in task-stimulus specificity, in spite of similar computations and contributions from partially shared neurocomputational networks.

Figure 2. Key Neural Networks involved in Visual and Auditory Statistical Learning

Key brain regions associated with domain-general (blue), and lower- and higher-level auditory (green) and visual (red) modality-specific processing and representation, plotted on a smoothed ICBM152 template brain. The depicted regions are not intended to constitute an exhaustive set of brain regions subserving each domain. C = Cuneus, FG = Fusiform Gyrus, STG = Superior Temporal Gyrus, IPL = Inferior Parietal Lobule, H = Hippocampus, T = Thalamus, CA = Caudate, IFG = Inferior Frontal Gyrus. Generated with the BrainNet Viewer [89].