Anticorrelated relationships in spontaneous signal fluctuation have been previously observed in resting-state functional magnetic resonance imaging (fMRI). In particular, it was proposed that there exists two systems in the brain that are intrinsically organized into anticorrelated networks, the default mode network, which usually exhibits task-related deactivations, and the task-positive network, which usually exhibits task-related activations during tasks that demands external attention. However, it is currently under debate whether the anticorrelations observed in resting state fMRI were valid or were instead artificially introduced by global signal regression, a common preprocessing technique to remove physiological and other noise in resting-state fMRI signal. We examined positive and negative correlations in resting-state connectivity using two different preprocessing methods: a component base noise reduction method (CompCor, Behzadi et al., 2007), in which principal components from noise regions-of-interest were removed, and the global signal regression method. Robust anticorrelations between a default mode network seed region in the medial prefrontal cortex and regions of the task-positive network were observed under both methods. Specificity of the anticorrelations was similar between the two methods. Specificity and sensitivity for positive correlations were higher under CompCor compared to the global regression method. Our results suggest that anticorrelations observed in resting-state connectivity are not an artifact introduced by global signal regression and might have biological origins, and that the CompCor method can be used to examine valid anticorrelations during rest.

Bipolar disorder and schizophrenia overlap in symptoms and may share some underlying neural substrates. The medial prefrontal cortex (MPFC) may have a crucial role in the psychophysiology of both these disorders. In this study, we examined the functional connectivity between MPFC and other brain regions in bipolar disorder and schizophrenia using resting-state functional magnetic resonance imaging (fMRI). Resting-state fMRI data were collected from 14 patients with bipolar disorder, 16 patients with schizophrenia, and 15 healthy control subjects. Functional connectivity maps from the MPFC were computed for each subject and compared across the three groups. The three groups showed distinctive patterns of functional connectivity between MPFC and anterior insula, and between MPFC and ventral lateral prefrontal cortex (VLPFC). The bipolar disorder group exhibited positive correlations between MPFC and insula, and between MPFC and VLPFC, whereas the control group exhibited anticorrelations between these regions. The schizophrenia group did not exhibit any resting-state correlation or anticorrelation between the MPFC and the VLPFC or insula. In contrast, neither patient group exhibited the significant anticorrelation between dorsal lateral prefrontal cortex (DLPFC) and MPFC that was exhibited by the control group. The decoupling of DLPFC with MPFC in bipolar disorder and schizophrenia is consistent with the impaired executive functioning seen in these disorders. Functional connectivity between MPFC and insula/VLPFC distinguished bipolar disorder from schizophrenia, and may reflect differences in the affective disturbances typical of each illness.

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