A dynamic network approach to language in aphasia: Individual differences in spoken and non-verbal communication

Abstract Aphasia is an acquired language disorder that can affect comprehension and production. While traditionally categorized into subtypes such as Broca’s, Wernicke’s, and anomic aphasia, many individuals exhibit features from multiple types, challenging rigid classifications. Historically, linguistic research into aphasia has often been guided by rule-based theories, influencing both assessment and treatment. However, alternative perspectives, such as the Usage-Based (UB) approach, offer a more dynamic view, emphasizing individual differences in language capabilities, and predicting variation along a continuum. Within this theoretical perspective, we apply a “Dynamic Network Model” (DNM), which combines word frequencies and transitional probabilities to elucidate individual networks of usage patterns for each person’s language. This study extends the DNM approach to clinical data, analyzing the language networks of six speakers with aphasia (two each with anomic, Wernicke’s, and Broca’s) alongside two control participants, to explore individual differences in spoken language and non-verbal communication. Results reveal that the speakers with aphasia generally have smaller networks, with disrupted connections. However, network size varies within and across aphasia types. Additionally, the speakers with aphasia use more non-verbal communication than control participants, with those with Broca’s and Wernicke’s aphasias using it the most. While some findings may be predicted based on traditional aphasia sub-classifications, the results indicate considerable individual differences within each of the participant groups, both in their spoken language and non-verbal communication, supporting a usage-based approach and adding to questions about the validity of discrete aphasia classifications.