Isaac Liao¹, Zeynep M. Saygin¹, David E. Osher¹; ¹The Ohio State University

Most studies of ventral visual networks use resting-state functional connectivity (FC) to characterize the brain’s intrinsic functional organization. However, recent work has questioned whether we should rely exclusively on resting-state data to define this organization (Finn, 2021). In this study, we test whether functional connectivity estimated from residualized task fMRI data can predict task responses in ventral visual regions at the individual subject level. While previous studies have demonstrated that responses of visual regions can be predicted from resting-state FC at the level of individual subjects (Saygin et al., 2012; Osher et al., 2016; Molloy et al., 2024; Tavor et al., 2016; Osher et al., 2019), it is unclear whether residual connectivity from task fMRI of a completely different domain (e.g. language) can a) predict responses to visual processing; and b) if it can do so in a selective manner (i.e. for functional regions of interest within each network). We find that connectivity derived from task data predicts responses just as well as connectivity derived from resting-state data. Task data, regardless of the specific task performed, are sufficient to capture fine-grained individual differences in ventral visual activations. These findings suggest that dedicated resting-state scans may not be necessary and broaden the utility of task fMRI for investigating the functional organization of brain networks.