Altered Small-World Brain Networks in Temporal Lobe in Patients with Schizophrenia Performing an Auditory Oddball Task

The functional architecture of the human brain has been extensively described in terms of complex networks characterized by efficient small-world features. Recent functional magnetic resonance imaging (fMRI) studies have found altered small-world topological properties of brain functional networks in patients with schizophrenia (SZ) during the resting state. However, little is known about the small-world properties of brain networks in the context of a task. In this study, we investigated the topological properties of human brain functional networks derived from fMRI during an auditory oddball (AOD) task. Data were obtained from 20 healthy controls and 20 SZ; A left and a right task-related network which consisted of the top activated voxels in temporal lobe of each hemisphere were analyzed separately. All voxels were detected by group independent component analysis. Connectivity of the left and right task-related networks were estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. The small-worldness values were decreased in both hemispheres in SZ. In addition, SZ showed longer shortest path length and lower global efficiency only in the left task-related networks. These results suggested small-world attributes are altered during the AOD task-related networks in SZ which provided further evidences for brain dysfunction of connectivity in SZ

BOLD fMRI Simulation

Background: Brain functional magnetic resonance imaging (fMRI) is sensitive to changes in blood oxygenation level dependent (BOLD) brain magnetic states. The fMRI scanner produces a complex-valued image, but the calculation of the original BOLD magnetic source is not a mathematically tractable problem. We conduct numeric simulations to understand the BOLD fMRI model

Components of Cross-Frequency Modulation in Health and Disease

The cognitive deficits associated with schizophrenia are commonly believed to arise from the abnormal temporal integration of information, however a quantitative approach to assess network coordination is lacking. Here, we propose to use cross-frequency modulation (cfM), the dependence of local high-frequency activity on the phase of widespread low-frequency oscillations, as an indicator of network coordination and functional integration. In an exploratory analysis based on pre-existing data, we measured cfM from multi-channel EEG recordings acquired while schizophrenia patients (n = 47) and healthy controls (n = 130) performed an auditory oddball task. Novel application of independent component analysis (ICA) to modulation data delineated components with specific spatial and spectral profiles, the weights of which showed covariation with diagnosis. Global cfM was significantly greater in healthy controls (F1,175 = 9.25, P < 0.005), while modulation at fronto-temporal electrodes was greater in patients (F1,175 = 17.5, P < 0.0001). We further found that the weights of schizophrenia-relevant components were associated with genetic polymorphisms at previously identified risk loci. Global cfM decreased with copies of 957C allele in the gene for the dopamine D2 receptor (r = −0.20, P < 0.01) across all subjects. Additionally, greater “aberrant” fronto-temporal modulation in schizophrenia patients was correlated with several polymorphisms in the gene for the α2-subunit of the GABAA receptor (GABRA2) as well as the total number of risk alleles in GABRA2 (r = 0.45, P < 0.01). Overall, our results indicate great promise for this approach in establishing patterns of cfM in health and disease and elucidating the roles of oscillatory interactions in functional connectivity