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The anatomical connectivity of the human brain supports diverse patterns of correlated neural activity that are thought to underlie cognitive function. In a manner sensitive to underlying structural brain architecture, we examine the extent to which such patterns of correlated activity systematically vary across cognitive states. Anatomical white matter connectivity is compared with functional correlations in neural activity measured via blood oxygen level dependent (BOLD) signals. Functional connectivity is separately measured at rest, during an attention task, and during a memory task. We assess these structural and functional measures within previously-identified resting-state functional networks, denoted task-positive and task-negative networks, that have been independently shown to be strongly anticorrelated at rest but also involve regions of the brain that routinely increase and decrease in activity during task-driven processes. We find that the density of anatomical connections within and between task-positive and task-negative networks is differentially related to strong, task-dependent correlations in neural activity. The space mapped out by the observed structure-function relationships is used to define a quantitative measure of separation between resting, attention, and memory states. We find that the degree of separation between states is related to both general measures of behavioral performance and relative differences in task-specific measures of attention versus memory performance. These findings suggest that the observed separation between cognitive states reflects underlying organizational principles of human brain structure and function.

The aim of the study is to understand how Mirror Neuron System (MNS) and Mentalizing Network (MZN) interact with each other. EEG data was collected during a photo judgment task with pictures of actions or facial expressions. Participants (N = 30, 63% women) were asked to either identify how the shown action/expression was being performed (MNS) or what the goal or intention behind the action was (MZN). Data were analyzed using microstate analysis, source localization and Event-Related Potentials. When comparing the action types, we found early divergence between the brain states of MNS and MZN when comparing the same action type. There was temporal alignment between the start and end time of the induced microstates, among the same action type. Between different action types, the timing was slightly shifted. Temporally, there was a greater overlap between the timing of the states between networks within the same action type as compared to within networks across action types. The MNS and MZN are acting in parallel rather then subsequently and possibly feed into each other. Furthermore, the MNS and MZN do not specifically react to one action type over the other, but their activity is influenced by the action type. [ABSTRACT FROM AUTHOR]