Psychopathology is increasingly viewed from a circuit perspective in which a

Psychopathology is increasingly viewed from a circuit perspective in which a disorder stems not from circumscribed anomalies in discrete brain regions but rather from impairments in distributed neural networks. of ADHD focusing on neural circuits implicated in the disorder especially the default mode network cognitive control network and cortico-striato-thalmo-cortical loops. We conclude by suggesting future directions that may help advance subsequent rs-fcMRI research in ADHD. (which focuses on the size and shape of various brain regions) (which correlates patterns of fMRI signal with participants’ performance on a cognitive task) and (which examines metabolic activity cerebral perfusion and receptor binding potentials within examined brain regions or receptor systems). These neuroimaging modalities focus Flumequine primarily on the properties of discrete brain regions and have left the interactions between brain regions largely unexplored in ADHD. This however has changed dramatically over the past decade with the development of the connectivity measures provided by rs-fcMRI which analyzes temporal correlations in neural activity between brain regions. Flumequine Though prior reviews (Castellanos et al. 2009; Konrad and Eickhoff 2010) have discussed the extant rs-fcMRI literature in ADHD rapid advances in this field render an updated review desirable. Methodological Considerations First described in 1995 by Biswal et al (1995) rs-fcMRI focuses on spontaneous fluctuations in neural activity as indexed by fMRI signal present during the resting condition-that is in the absence IL18BP antibody of overt task performance or stimulation (Fox and Greicius 2010). Brain regions that Flumequine demonstrate strong coherence of neural activity (i.e. fMRI signal that is highly correlated over time) are considered “functionally connected.” (Fox and Raichle 2007; Posner et al. 2013a) When the fMRI signal across multiple brain regions is correlated this is termed a “resting state network.” These networks (e.g. the cognitive control network) consist of brain regions that are known to co-activate during task-based fMRI studies. For example using task-based fMRI task-related activations within regions associated with cognitive control such as the dorsolateral prefrontal cortex supplementary motor area and the anterior insular cortex can be detected as participants engage in a task with cognitive control demands such as the Go/No Go (Casey et al. 1997) or Stroop (Whalen et al. 2006) Tasks. Flumequine Using rs-fcMRI functional connections are reliably detected across these same regions and thus the cognitive control network can be termed a “resting state network.” (Posner et al. 2013b; Sheline et al. 2010) The function of resting state activity remains an area of active investigation but may reflect an endogenous mechanism of the brain to self-organize (Fox et al. 2005). Spontaneous neural activity strengthens synaptic connections across neural networks and thereby may maintain the coherence or architecture of these neural networks (Fair et al. 2007; Fair et al. 2009). Resting-state functional connectivity MRI typically relies upon two approaches: seed-based and independent component analysis. In seed-based correlations the fMRI signal from a single or cluster of voxels is extracted from a specific neural region of interest and a map of the brain is created by Flumequine calculating the correlations between the designated seed region and all other voxels of the brain (Biswal et al. 1995; Fox and Raichle 2007). A second method independent component analysis (ICA) is a data-driven approach that considers all voxels simultaneously and separates a dataset into spatially distinct maps of four-dimensional fMRI signal (i.e. three spatial dimensions and a fourth dimension indexing time) (Calhoun et al. 2003; Wang and Peterson 2008). Conceptually and computationally more intuitive than ICA seed-based analyses have been used in most rs-fcMRI studies of ADHD. However as noted elsewhere (Power et al. 2011; Fox and Greicius 2010) seed-based approaches are susceptible to investigator biases. For example investigators must decide upon the specific seed region for a given analysis as well as the anatomical definitions to characterize the seed regions. Each of these decisions can in turn influence the rs-fcMRI findings. If an investigator chooses for example to examine connectivity based Flumequine on the dorsolateral.