Using data-driven, lesion-symptom mapping to study the relationship between neural and theoretical components of numeracy

Numeracy, the ability to understand and manipulate numbers, is a crucial foundational ability for many daily life skills. Numeracy tasks have been categorized using different taxonomic approaches, and understanding of the relationship between tasks categories and neural models of numeracy remains poor. In this study, we use the lesion method to address this key gap. The study employs a data-driven approach with support vector regression lesion-symptom mapping (SVR-LSM) of extracted factors from two left hemisphere chronic stroke survivor datasets: one with data from a battery of math and language tests (N = 100) and the other with data from the EC301 math battery (N = 64). We find that our data best support a separation of number tasks requiring verbal vs. magnitude number knowledge, aligning with a broad theme that emerges across theories in different variations. This is supported by distinct neuroanatomical correlates that link verbal coding of number to the language-centered regions including left perisylvian area and insula, and that link magnitude coding to the parietal lobe, as described in prior models. Our findings indicate that these two different sources of representation variously contribute to a range of math tasks, including different types of arithmetic calculation tasks, in ways which cannot be cleanly defined by one singular theoretical model of math cognition.