Information processing during human cognitive and emotional operations is thought to involve the dynamic interplay of several large-scale neural networks, including the fronto-parietal central executive network (CEN), cingulo-opercular salience network (SN), and the medial prefrontal-medial parietal default mode networks (DMN). It has been theorized that there is a causal neural mechanism by which the CEN/SN negatively regulate the DMN. Support for this idea has come from correlational neuroimaging studies; however, direct evidence for this neural mechanism is lacking. Here we undertook a direct test of this mechanism by combining transcranial magnetic stimulation (TMS) with functional MRI to causally excite or inhibit TMS-accessible prefrontal nodes within the CEN or SN and determine consequent effects on the DMN. Single-pulse excitatory stimulations delivered to only the CEN node induced negative DMN connectivity with the CEN and SN, consistent with the CEN/SN's hypothesized negative regulation of the DMN. Conversely, low-frequency inhibitory repetitive TMS to the CEN node resulted in a shift of DMN signal from its normally low-frequency range to a higher frequency, suggesting disinhibition of DMN activity. Moreover, the CEN node exhibited this causal regulatory relationship primarily with the medial prefrontal portion of the DMN. These findings significantly advance our understanding of the causal mechanisms by which major brain networks normally coordinate information processing. Given that poorly regulated information processing is a hallmark of most neuropsychiatric disorders, these findings provide a foundation for ways to study network dysregulation and develop brain stimulation treatments for these disorders. task positive network | task negative network | fMRI | neuromodulation E xtensive neuroimaging work has described a set of largescale, intrinsically organized networks in the human brain, as well as those of other mammals, which are thought to underlie a broad range of functions, from basic sensory and motor capacities to cognition and higher-level functions (1-4). Three networks in particular have been the focus of work related to these higher-level functions (5): the fronto-parietal central executive network (CEN), the cingulo-opercular salience network (SN), and the medial prefrontal-medial parietal default mode network (DMN). These networks are thought to interact and together control attention, working memory, decision making, and other higher-level cognitive operations (6-8).Findings to date, however, emphasize the need for a direct test of the proposed causal relationship between these networks. On the basis of observations in resting-state functional MRI (rsfMRI) scans in humans of time-locked negative CEN/DMN and SN/DMN connectivity (9-11), as well as mathematical modeling of temporal relationships between these networks (12), it has been argued that the CEN and/or SN negatively regulate activity in the DMN. However, because a similar pattern of connectivity can be spuriously introduced du...

SUMMARY:Resting-state fMRI was first described by Biswal et al in 1995 and has since then been widely used in both healthy subjects and patients with various neurologic, neurosurgical, and psychiatric disorders. As opposed to paradigm-or task-based functional MR imaging, resting-state fMRI does not require subjects to perform any specific task. The low-frequency oscillations of the resting-state fMRI signal have been shown to relate to the spontaneous neural activity. There are many ways to analyze resting-state fMRI data. In this review article, we will briefly describe a few of these and highlight the advantages and limitations of each. This description is to facilitate the adoption and use of resting-state fMRI in the clinical setting, helping neuroradiologists become familiar with these techniques and applying them for the care of patients with neurologic and psychiatric diseases.ABBREVIATIONS: ALFF ϭ Amplitude of Low Frequency Fluctuations; BOLD ϭ blood oxygen level-dependent; FCD ϭ functional connectivity density; ICA ϭ

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