Significant results of the ALE meta-analysis delineating the ISA network (A; taken from¹³) and volumes of interest (VOIs) used for the functional connectivity analysis in healthy controls and patients (B).

<p>ACC: anterior cingulate cortex; AmyL: left Amygdala; dmPFC: dorsomedial prefrontal cortex; PrC: precuneus; SGC: subgenual cingulate cortex.</p

Group characteristics. <i>SD: standard deviation; M: male; F: female; BDI: Beck Depression Inventory II, HRSD: Hamilton Rating Scale for Depression</i>.

<p>Group characteristics. <i>SD: standard deviation; M: male; F: female; BDI: Beck Depression Inventory II, HRSD: Hamilton Rating Scale for Depression</i>.</p

Medication data for all patients.

<p>Medication data for all patients.</p

Meta-Analytically Informed Network Analysis of Resting State fMRI Reveals Hyperconnectivity in an Introspective Socio-Affective Network in Depression

<div><p>Alterations of social cognition and dysfunctional interpersonal expectations are thought to play an important role in the etiology of depression and have, thus, become a key target of psychotherapeutic interventions. The underlying neurobiology, however, remains elusive. Based upon the idea of a close link between affective and introspective processes relevant for social interactions and alterations thereof in states of depression, we used a meta-analytically informed network analysis to investigate resting-state functional connectivity in an introspective socio-affective (ISA) network in individuals with and without depression. Results of our analysis demonstrate significant differences between the groups with depressed individuals showing hyperconnectivity of the ISA network. These findings demonstrate that neurofunctional alterations exist in individuals with depression in a neural network relevant for introspection and socio-affective processing, which may contribute to the interpersonal difficulties that are linked to depressive symptomatology.</p></div

Activation peaks of control network (taken from¹⁸).

<p>Activation peaks of control network (taken from¹⁸).</p

Results of the resting state functional connectivity analysis in the control and patient group for ISA (left) and control network (right).

<p>Bar plots depict measures of functional connectivity for patients (red) and controls (green) across the two different measurement sites (light colors: Aachen; dark colors: Goettingen).</p

Significant results of the comparison of functional connectivity between patient subgroups of short and long disease duration and early and late onset of illness.

<p>Subgroups were defined each by a median split of the patient group with ≥5 years for long duration and ≥24 years of age for late disease onset. ACC: anterior cingulate cortex; AmyL: left amygdala; PrC: precuneus; SGC: subgenual cingulate cortex.</p

Activation peaks of ISA network (taken from¹³).

<p>Activation peaks of ISA network (taken from¹³).</p

Comparison of motion parameters across groups and sites. <i>SD: standard deviation, DVARS: temporal derivative of timecourses (cf. Power et al. 2012), FD: framewise displacement (cf. van Dijck et al. 2012), RMS: variance over voxels (cf. Satterthwaite et al. 2013).</i>

<p>Comparison of motion parameters across groups and sites. <i>SD: standard deviation, DVARS: temporal derivative of timecourses (cf. Power et al. 2012), FD: framewise displacement (cf. van Dijck et al. 2012), RMS: variance over voxels (cf. Satterthwaite et al. 2013).</i></p

Table_4_Differential Resting-State Connectivity Patterns of the Right Anterior and Posterior Dorsolateral Prefrontal Cortices (DLPFC) in Schizophrenia.DOCX

<p>In schizophrenia (SCZ), dysfunction of the dorsolateral prefrontal cortex (DLPFC) has been linked to the deficits in executive functions and attention. It has been suggested that, instead of considering the right DLPFC as a cohesive functional entity, it can be divided into two parts (anterior and posterior) based on its whole-brain connectivity patterns. Given these two subregions' differential association with cognitive processes, we investigated the functional connectivity (FC) profile of both subregions through resting-state data to determine whether they are differentially affected in SCZ. Resting-state magnetic resonance imaging (MRI) scans were obtained from 120 patients and 172 healthy controls (HC) at 6 different MRI sites. The results showed differential FC patterns for the anterior and posterior parts of the right executive control-related DLPFC in SCZ with the parietal, the temporal and the cerebellar regions, along with a convergent reduction of connectivity with the striatum and the occipital cortex. An increased psychopathology level was linked to a higher difference in posterior vs. anterior FC for the left IFG/anterior insula, regions involved in higher-order cognitive processes. In sum, the current analysis demonstrated that even between two neighboring clusters connectivity could be differentially disrupted in SCZ. Lacking the necessary anatomical specificity, such notions may in fact be detrimental to a proper understanding of SCZ pathophysiology.</p