LAUSR

A simple motor behaviour or a more complex behaviour is the result of the neural activity of those neural networks responsible for the behaviour. To understand how the network activity is transformed into human behaviours, it is necessary to identify task-specific networks and analyse the dynamic network activity that changes with time. Here we report a novel task-fMRI technique to identify task-specific networks and analyse their dynamic activity. Nine subjects participated in a task-fMRI study in which the subjects were cued to perform three different tasks of word-reading, pattern-viewing and finger-tapping. A functional area of unitary pooled activity (FAUPA) is defined as an area in which the temporal variation of the activity is the same across the entire area, and a task-associated FAUPA plays the role of a functional unit for the task. A novel method is presented to (1) identify FAUPAs that are associated with each task as well as their functional groupings; (2) identify the three task-specific networks; and (3) analyse the network activity from trial to trial. Task-associated FAUPAs were identified for each task and each subject. A task-specific large-scale neural network across the whole brain consisted of all FAUPAs that were activated each time the task was performed, and all three task-specific networks were identified for each individual subject. The temporal changes of activation and functional connectivity of the FAUPAs within each network from trial to trial characterized the dynamic activity of the network. The results demonstrated a one-to-one relation between the network activity and the task performance from trial to trial, offering a means of testing the causal relationship between network activity and human task performance by systematically manipulating task performance and measuring corresponding network activity change.