Resting state functional connectivity and structural abnormalities of the brain in acute retarded catatonia: an exploratory MRI study.

ABSTRACT

In this first cross-sectional MRI study in acute catatonia, we compared the resting state whole-brain, within-network and seed (left precentral gyrus)-to-voxel connectivity, as well as cortical surface complexity between a sample of patients in acute retarded catatonic state (n = 15) diagnosed as per DSM-5 criteria and a demographically matched healthy control sample (n = 15). The patients had comorbid Axis-I psychiatric disorders including schizophrenia spectrum disorders and psychotic mood disorders, but did not have diagnosable neurological disorders. Acute retarded catatonia was characterized by reduced resting state functional connectivity, most robustly within the sensorimotor network; diffuse region of interest (ROI)-ROI hyperconnectivity; and seed-to-voxel hyperconnectivity in the frontoparietal and cerebellar regions. The seed (left precentral gyrus)-to-voxel connectivity was positively correlated to the catatonia motor ratings. The ROI-ROI as well as seed-to-voxel functional hyperconnectivity were noted to be higher in lorazepam responders (n = 9) in comparison to the non-responders (n = 6). The overall Hedges' g effect sizes for these analyses ranged between 0.82 and 3.53, indicating robustness of these results, while the average Dice coefficients from jackknife reliability analyses ranged between 0.6 and 1, indicating fair (inter-regional ROI-ROI connectivity) to perfect (within-sensorimotor network connectivity) reliability of the results. The catatonia sample showed reduced vertex-wise cortical complexity in the right insular cortex and contiguous areas. Thus, we have identified neuroimaging markers of the acute retarded catatonic state that may show an association with treatment response to benzodiazepines. We discuss how these novel findings have important translational implications for understanding the pathophysiology of catatonia as well as for the mechanistic understanding and prediction of treatment response to benzodiazepines.