T80. Changes in the Overall Pattern of Fmri and Meg Functional Connectivity in Patients With Schizophrenia
Year: 2019
Type: conference-abstract
Abstract: Considerable research suggests that one of the pathophysiological mechanisms underlying schizophrenia (SZ) is aberrant functional connectivity (fnc) between brain regions. Typically, one explores this issue by determining if the fnc between two specified brain regions is either consistently higher or consistently lower in SZ than in matched healthy controls (HC). However, suppose that in SZ there is a problem in how the brain regulates the connectivity between brain regions: in this case, SZ might show increased deviation from an optimal global pattern of functional connectivity, but not have consistently higher or lower values of fnc between any two specific regions. Here we investigated whether there was evidence for global shifts in the pattern of fnc in HC and SZ in resting state fMRI and also resting state magnetoencephalography (MEG). Minimally treated first episode SZ (n=19) and HC (n=24) matched for age, gender, and family socio-economic status were recruited. MEG was performed in a 4D systems 148 channel magnetometer and the resting state was recorded. MEG activity was filtered into EEG bands and the low-frequency envelope extracted. The fMRI BOLD resting state activity was recorded in a 7T scanner. fMRI and MEG data were decomposed into components reflecting resting state networks using a group spatial independent component analysis. Functional connectivity between resting-state components was computed separately for fMRI and the different MEG frequency bands. We created a mean template of the fnc matrix of correlation coefficients for both SZ and HC combined, and determined the similarity between this mean template and each individual subject’s fnc by using the dot product. We calculated the fnc between 30 regions for fMRI and 33 regions for MEG for each subject. SZ had on average lower similarity to the mean fnc matrix than HC for the fMRI data (HC: 33.2 +/- 1.6 stderr, SZ: 28.3 +/- 1.0, P=0.018 by t-test). This was also true for the MEG alpha band (HC: 90.6 +/- 5.2 stderr, SZ: 76.1 +/- 3.6, P=0.036 by t-test) and the MEG beta band (HC: 107.8 +/- 5.7, SZ: 87.7 +/- 4.9, P=0.014 by t-test). However, there were no significant differences between SZ and HC in the MEG gamma, delta, or theta bands. When exploring the pattern of connectivity between every brain region and every other brain region, the number of potential connections goes up as the square of the number of regions. You can maintain statistical power by limiting yourself a priori to a subset of all possible brain regions - for example, just the default network, or just sensorimotor. Or you can look at the entire brain, but the loss of statistical power means that you will only be able to detect the dysconnectivities with the largest differences between HC and SZ. Our results here suggest that to some extent it is the overall pattern of connectivity in SZ that is aberrant compared to HC, and that some SZ may have a functional connection strength between two regions that is aberrantly low, and others, that is aberrantly high. It is proposed that future studies using large number of subjects, and standardized maps of functional connectivity, might further address this possibility.
Source: Schizophrenia Bulletin
Institutions: University of Alabama at Birmingham, Auburn University
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W2939629874