Abstract
Persistent cognitive symptoms following SARS-CoV-2 infection have been widely reported, yet their underlying neural mechanisms remain poorly understood. Here, we applied an integrative framework—combining EEG, diffusion MRI, and computational cognitive modeling—to investigate brain–behavior relationships in patients recovered from COVID-19 (n = 70) and other non-COVID respiratory infections (n = 26). Participants completed tasks probing cognitive control, working memory, and decision-making. Across tasks, individuals with prior COVID-19 showed altered low-frequency oscillatory activity and performance deficits, despite mild or moderate acute illness. These oscillatory alterations were linked to reduced white matter integrity in distinct long-range tracts, including the cingulum and thalamo-occipital fasciculi, depending on the cognitive computation involved. Crucially, model-based clustering revealed two distinct neurophysiological profiles among post-COVID participants, reflecting different combinations of structural and functional alterations. These profiles were not explained by clinical severity markers or other symptoms like anosmia, suggesting the emergence of neurocognitive phenotypes beyond binary classifications. Our findings identify a generalizable principle whereby specific brain network disruptions underlie cognitive dysfunction, highlighting biomarkers that may guide personalized intervention strategies. Beyond COVID-19, this multimodal framework offers a scalable approach for uncovering structure–function–computation coupling in other post-infectious or neuroinflammatory conditions, with broad relevance for the prevention and treatment of cognitive impairment.