Neural investigation of multiplication processes in expert sign language users

The project’s aim is to compare native adult ASL signers to native adult English speakers using functional Magnetic Resonance Imaging (fMRI) as a lens into the neural networks involved in small and large single-digit arithmetic problems.

One question of relevance is whether the neural networks for solving single-digit arithmetic problems is modality-dependent or modality-independent. It could be that the different experiences of learning in distinct modalities impact this processing. Calculation-based strategies, often used for addition and subtraction, call upon the classic number processing areas in the parietal cortex.

Conversely, multiplication utilizes the classic left-lateralized language areas, using a verbal retrieval strategy in recalling simple, rote multiplication problems. When considering the modality debate of arithmetic fact retrieval, it calls into question the reliance of multiplication fact retrieval on the language networks.

Might using a visual language impact the neural networks for calculating multiplication problems?

This has yet to be investigated within the deaf signing population, rendering the extent of the impact of learning experience on the different operations still unclear. Examining the neural networks in participants native in languages that differ in their modality could be a way to investigate how deeply the learning experience impacts the networks for simple arithmetic.

In learning arithmetic, a child using a visual language might rely more on visuospatial processes and internal representations of manual number signs. Evidence suggests that the brain of adult fluent signers automatically activates areas related to sensorimotor representations when processing linguistic information.

Fluent signers have also shown to have increased proficiency in mental representation and mental rotation, indicating a heightened visuospatial capability over their hearing, non-signing peers.

As a result, we expect to find more visuospatial and fine motor activations in adult native signers compared to non-signers when solving single-digit arithmetic problems. Additionally, if operations are indeed intrinsically different, we should find distinct neural networks for multiplication and subtraction problems evident in native signers.

Because native signers process linguistic information in the same left-lateralized language areas, we can expect to see that multiplication facts are also stored in the language network. The current body of research on arithmetic processing does not take into account a visual modality.

Gaining a better understanding of the neural networks involved, and to what extent they are involved, in deaf, native signers would deepen our understanding of this learning mechanism, allowing for more nuanced research beyond these foundational findings.

If we find that native signers’ learning displays a unique network for computing arithmetic, remediation of the current system for educating native signers may be beneficial to the deaf learner.

As deaf students historically lag behind their hearing peers in academic achievement, improving access and quality of education is paramount to ensure optimal learning and development. Disseminating these findings to policymakers and educators may encourage a closer look at how we can better serve our deaf students.