These slow changes occurred even in the absence of any endogenous or exogenous drive. These findings have been confirmed and extended in a series of computational studies revealing the critical role of noise and dynamic instability in inducing spontaneous fluctuations of resting brain activity.113-116 An emerging theoretical idea is that of a “functional repertoire” of network states that is continually revisited and rehearsed in the course of noise-driven endogenous neural activity.117,118 In line with these computational observations, recent empirical studies Inhibitors,research,lifescience,medical carried out in human, macaque, and rat brain119-125 have shown that functional couplings among remote brain regions

can indeed exhibit non-stationarities in coupling strength, manifesting as slow variations in functional connectivity and hence in the topology of functional Inhibitors,research,lifescience,medical networks across time. The

relation of these slow network dynamics to cognitive processes, their relation to much faster non-stationarities in synchronization patterns measured with EEG126,127 and MEG,128 and their potential significance for clinical studies remain Inhibitors,research,lifescience,medical to be explored. Over the past few years, network studies of the brain’s structural connections as well as resting or task-evoked functional connectivity have delivered a wealth of insights into brain organization and integrative function. Increasingly, network measures are deployed to characterize patterns of development129-133 and individual differences within cohorts of healthy participants.134 The mapping of individual network differences is a principal goal of the Human Connectome Project135,136 which aims at drawing relations between network structure and Inhibitors,research,lifescience,medical dynamics on the one side, and patterns of heritability, behavior, and genomic variations on the other. These studies will allow, for the first time, to construct an overview of the range of variability Inhibitors,research,lifescience,medical in network organization across the human population.

An important additional step, which is already pursued in a growing number of recent and ongoing studies of brain networks, involves identifying network correlates of brain and mental disorders. Clinical applications So far, this review has focused on how network approaches can become useful tools for understanding MRIP and characterizing the structure and function of the intact, healthy brain. However, a major promise of human connectomics is that it will lead to a deeper understanding of the biological substrates underlying brain and mental disorders,137-140 including their genetic bases.141 The primary aim of human connectomics is to map patterns of structural brain connectivity and uncover their relationship to emerging patterns of brain dynamics. Disturbed interactions among brain regions have been shown to be associated with virtually all brain and mental disorders, as well as with brain injury and Trichostatin A recovery.