The Emergence of Orthographic Word Representations in the Brain: Evaluating a Neural Shape-Based Framework Using fMRI and the HMAX Model

Evidence has recently accumulated that learning to read shapes responses and selectivity throughout the ventral visual pathway in both children and adults. However, we are far from a mechanistic understanding of how visual word form representations are con-structed in the brain. Here, we adapt a neural object recognition model to include case-specific and case-invariant letter string rep-resentations, resulting in the model HMAX-WORD, and we compare its output with data from a functional magnetic resonance imaging experiment including words presented in 2 cases (e.g., “HAAN ” vs. “haan ” [rooster]). Population-level analyses on the responses within different layers of HMAX-WORD provide specific predictions about a progression from a representational space defined by case to a representational space defined by word identity. The imaging data, analyzed through multivoxel pattern analyses, show a similar pro-gression from case-dependent to case-invariant representational spaces in the word recognition system. These data provide evi-dence that word recognition, which is tolerant to CHANGES IN CASE, is consistent with the implementation of abstract ortho-graphic units in a feed-forward architecture. These findings reveal the potential of a combined computational and pattern analyses-based approach to understand how visual word forms are con-structed in the brain