Reading’s neural fingerprint: Multivariate classification of brain activity in four writing systems

Abstract

Understanding how the structure of a writing system shapes neural organization is critical to uncovering the biological and experiential bases of literacy and neurocognition. Here we used machine learning and functional magnetic resonance imaging to identify language-distinct brain activity patterns in Chinese, English, Hebrew and Spanish readers. This model captured neural activity patterns common across readers of a given language, and those which discriminated readers of different writing systems. Accordingly, we observed strong differentiation of visually distinct languages (Chinese vs. Hebrew vs. English/Spanish) in ventral occipital regions, but little ability to differentiate English from Spanish, which use a common alphabetic code. In contrast, left posterior fusiform and occipital-temporal cortex provided accurate classification of English, Spanish, and Hebrew, but chance performance of Chinese. More idiosyncratic patterns were also observed, including a unique advantage toward Hebrew in left inferior parietal gyrus, perhaps reflecting its right-to-left writing direction. Finally, weak overall classification in temporal and frontal regions that form the classical speech network suggests these regions are less likely to be shaped by reading-specific experience. Overall, the finding that writing systems induce dissociable patterns of activity in only selective subregions of the reading network expands our understanding of how a universally constrained reading network can be shaped by the varying characteristics of the world’s writing systems.