Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships

Publication date: Available online 18 November 2019Source: NeuroImageAuthor(s): Rongtao Jiang, Nianming Zuo, Judith M. Ford, Shile Qi, Dongmei Zhi, Chuanjun Zhuo, Yong Xu, Zening Fu, Juan Bustillo, Jessica A. Turner, Vince D. Calhoun, Jing SuiAbstractAlthough both resting and task-induced functional connectivity (FC) have been used to characterize the human brain and cognitive abilities, the potential of task-induced FCs in individualized prediction for out-of-scanner cognitive traits remains largely unexplored. A recent study Greene et al. (2018) predicted the fluid intelligence scores using FCs derived from rest and multiple task conditions, suggesting that task-induced brain state manipulation improved prediction of individual traits. Here, using a large dataset incorporating fMRI data from rest and 7 distinct task conditions, we replicated the original study by employing a different machine learning approach, and applying the method to predict two reading comprehension-related cognitive measures. Consistent with their findings, we found that task-based machine learning models often outperformed rest-based models. We also observed that combining multi-task fMRI improved prediction performance, yet, integrating the more fMRI conditions can not necessarily ensure better predictions. Compared with rest, the predictive FCs derived from language and working memory tasks were highlighted with more predictive power in predominantly default mode and frontoparietal networks. Moreov...
Source: NeuroImage - Category: Neuroscience Source Type: research