Spatial source phase: A new feature for identifying spatial differences based on complex‐valued resting‐state fMRI data

Abstract

Spatial source phase, the phase information of spatial maps extracted from functional magnetic resonance imaging (fMRI) data by data‐driven methods such as independent component analysis (ICA), has rarely been studied. While the observed phase has been shown to convey unique brain information, the role of spatial source phase in representing the intrinsic activity of the brain is yet not clear. This study explores the spatial source phase for identifying spatial differences between patients with schizophrenia (SZs) and healthy controls (HCs) using complex‐valued resting‐state fMRI data from 82 individuals. ICA is first applied to preprocess fMRI data, and post‐ICA phase de‐ambiguity and denoising are then performed. The ability of spatial source phase to characterize spatial differences is examined by the homogeneity of variance test (voxel‐wise F‐test) with false discovery rate correction. Resampling techniques are performed to ensure that the observations are significant and reliable. We focus on two components of interest widely used in analyzing SZs, including the default mode network (DMN) and auditory cortex. Results show that the spatial source phase exhibits more significant variance changes and higher sensitivity to the spatial differences between SZs and HCs in the anterior areas of DMN and the left auditory cortex, compared to the magnitude of spatial activations. Our findings show that the spatial source phase can potentially serve as a new brain imaging biomarker and provide a novel perspective on differences in SZs compared to HCs, consistent with but extending previous work showing increased variability in patient data.

Shift-Invariant Canonical Polyadic Decomposition of Complex-Valued Multi-Subject fMRI Data With a Phase Sparsity Constraint

“…More precisely, the proposed algorithm detects 73.9% more contiguous voxels in RPMA+SMA (932 vs. 536) and 746.5% more contiguous voxels in LPMA (838 vs. 99) than ICA-sCPD. In summary, our proposed method extracts 178.7% more contiguous task-related activations than ICA-sCPD, consistent with the previous finding that phase data provides additional brain information [15], [18], [20], [35], [39].…”

“…Our previous studies have verified that the complexvalued fMRI data analysis can detect more contiguous and reasonable activations than magnitude-only fMRI data analysis [15], [18], [20], [35]. By using complex-valued ICA and IVA algorithms, the complex-valued analyses extracted 139% more voxels for ICA and 393% more voxels for IVA than the magnitude-only analyses for the task fMRI data [15], [35].…”

“…To our best knowledge, CPD has not yet been applied to complex-valued multi-subject fMRI data. Motivated by the benefits of using both magnitude and phase information in fMRI data [15]- [20], we propose to exploit the phase in a CPD algorithm to take advantage of the full brain information contained in complex-valued fMRI data. Different from spatial independence, we propose the incorporation of a spatial sparsity constraint on CPD.…”

Adjunct ketamine treatment effects on treatment-resistant depressive symptoms in chronic treatment-resistant schizophrenia patients are short-term and disassociated from regional homogeneity changes in key brain regions – a pilot study

“…Previous studies reporting that a single ketamine treatment may alleviate treatment resistant depression by normalizing aberrant activity in DMN components and the frontal cortex [66][67][68]. Although it is well established that ketamine can decrease functional activity in the DMN and other brain regions [47][48][49][50][51][52][53][54][55][56][57][58][59][60], we found increased ReHo in the DMN in CTRS patients with TRD symptoms in this pilot study. We postulated that this seemingly contradictory finding may be related to neuropathological features of schizophrenia.…”

“…Notably, neural activities in the DMN and OFC have been reported to be markedly decreased in depressive patients [51][52][53][54][55][56]. Furthermore, structural and functional deficits in the DMN and OFC have been related to affective and memory processing disturbances in patients with schizophrenia [57][58][59][60][61][62][63][64].…”