Multimodal Magnetic Resonance Imaging Data Fusion Reveals Distinct Patterns of Abnormal Brain Structure and Function in Catatonia

Abstract

Catatonia is a nosologically unspecific syndrome, which subsumes a plethora of mostly complex affective, motor, and behavioral phenomena. Although catatonia frequently occurs in schizophrenia spectrum disorders (SSD), specific patterns of abnormal brain structure and function underlying catatonia are unclear at present. Here, we used a multivariate data fusion technique for multimodal magnetic resonance imaging (MRI) data to investigate patterns of aberrant intrinsic neural activity (INA) and gray matter volume (GMV) in SSD patients with and without catatonia. Resting-state functional MRI and structural MRI data were collected from 87 right-handed SSD patients. Catatonic symptoms were examined on the Northoff Catatonia Rating Scale (NCRS). A multivariate analysis approach was used to examine co-altered patterns of INA and GMV. Following a categorical approach, we found predominantly frontothalamic and corticostriatal abnormalities in SSD patients with catatonia (NCRS total score ≥ 3; n = 24) when compared to SSD patients without catatonia (NCRS total score = 0; n = 22) matched for age, gender, education, and medication. Corticostriatal network was associated with NCRS affective scores. Following a dimensional approach, 33 SSD patients with catatonia according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision were identified. NCRS behavioral scores were associated with a joint structural and functional system that predominantly included cerebellar and prefrontal/cortical motor regions. NCRS affective scores were associated with frontoparietal INA. This study provides novel neuromechanistic insights into catatonia in SSD suggesting co-altered structure/function-interactions in neural systems subserving coordinated visuospatial functions and motor behavior.

Brain imaging in catatonia: systematic review and directions for future research

“…By using a categorical approach (comparing 24 patients with schizophrenia and catatonia, and 22 schizophrenia patients without catatonia), these authors found that catatonia was associated with fronto-thalamic and cortico-striatal abnormalities. In a dimensional approach they found that behavioural symptoms were associated with cerebellar and prefrontal/cortical motor regions, and affective symptoms according to NCRS correlated with frontoparietal functional abnormalities (Hirjak et al, 2019 c ).…”

Patterns of co‐altered brain structure and function underlying neurological soft signs in schizophrenia spectrum disorders

“…Furthermore, we chose to investigate intrinsic neural activity (INA), because INA explores the intrinsically (functionally) segregation or specialization of brain regions/networks (Logothetis, ; Zhang et al, ). For this particular reason, we used fractional amplitude of low‐frequency fluctuations (fALFF), because fALFF captures the relative magnitude of blood oxygen level‐dependent (BOLD) signal changes on INA and might help to identify brain regions/networks with aberrant local functioning (Egorova, Veldsman, Cumming, & Brodtmann, ; Hirjak et al, ; Kubera et al, ). Whereas ReHo measures connectivity between a given voxel and its neighbors in the time domain (Long et al, 2008; Zang et al, 2004), ALFF measures signal variability of a single voxel in the frequency domain (Xu, Zhuo, Qin, Zhu, & Yu, 2015).…”

“…Still, one of the major benefits of using fALFF and combining both modalities is getting the information about both GMV and INA as well as increasing the power of data fusion analysis. There are also several recent fMRI studies that have successfully used fusion ICA methods with fALFF in healthy and SSD samples (Di et al, ; Hirjak, Rashidi, et al, ; Kubera et al, ; Lottman et al, ; Sui et al, ; Xu et al, 2015). Finally, GMV volume changes can cause spatiotemporal changes in INA and these joint network alterations might result in aberrant sensorimotor functioning and the development of NSS in SSD patients (Mittal, Bernard, & Northoff, ; Northoff & Duncan, ).…”

Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

“…The study found that the tau load had little effect on the gray matter atrophy, and this might imply that tau protein deposit precedes and predicts brain atrophy. The multimodal imaging studies require statistical and analytical models, advanced computing algorithms, and especially, novel data fusion methods [113] , [114] , [115] , [116] , which will be reviewed in detail in the following sections.…”