The Cognitive Makeup of Writing: Multivariate Analysis of Writing Impairments Following Stroke

Writing is a recently acquired skill to human behavioral repertoire, essential in industrialized societies. In the clinic, writing impairment is evident in one-third of stroke patients. This study aimed to find out the cognitive features that contribute to writing impairment of stroke patients in two different writing systems (logographic and phonological). Cognitive profiles were assessed using the Birmingham Cognitive Screen in two cohorts, China (244 patients) and UK (501 patients). The datasets were analyzed separately using an identical procedure. Elastic net was used to rank the importance of different cognitive abilities (features) to writing skill; and linear support vector machine was used to identify the discriminative features needed to accurately identify the stroke patients with and without writing impairments. The prediction performance was evaluated with the area under the curve (AUC), accuracy (ACC), sensitivity (SEN), and specificity (SPE). For the China cohort, writing numbers, complex figure copy, and number calculation obtained good prediction performance on writing impairments with AUC 0.85 ± 0.06, ACC (89 ± 3) %, SEN (81 ± 10) %, and SPE (90 ± 27) %. Concerning the UK data, writing numbers, number calculation, non-word reading, and auditory sustain attention achieved AUC 0.79 ± 0.04, ACC (83 ± 3) %, SEN (74 ± 9) %, and SPE (84 ± 3) %. A small number of patients in both cohorts (China: 9/69, UK: 24/137), who were impaired in writing, were consistently misclassified. Two patients, one in each cohort, showed selective impairments in writing, while all remaining patients were impaired in attention, language, and/or praxis tasks. The results showed that the capability to write numbers and manipulate them were critical features for predicting writing abilities across writing systems. Reading abilities were not a good predictor of writing impairments across both cohorts. Constructive praxis (measured by complex figure copy) was relevant to impairment classification in characters-based writing (China), while phonological abilities (measured by non-word reading) were important features for impairment prediction in alphabetic writing (UK). A small proportion minority of cases with writing deficits were related to different impairment profiles. The findings in this study highlight the multifaceted nature of writing deficits and the potential use of computation methods for revealing hidden cognitive structures in neuropsychological research.