Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Disarrangement of Collagen Fibers in Reinke`s Edema

Objective/Hypothesis: To describe the arrangement of collagen fibers in the superficial layer of the lamina propria of the vocal folds with Reinke` edema. Study Design: Cross sectional analysis of the lamina propria of the vocal folds with Reinke`s edema (RE). Method: The picrosirius polarization method was used to study the arrangement of collagen fiber. Findings of collagen disarrangement were categorized semiquantitatively and correlated with RE severity, age, cigarette smoking and duration of dysphonia. Results: Analysis of 20 specimens of vocal folds with RE showed that the intertwined network of collagen fibers resembling a wicker-basket normally observed in vocal folds was disarranged in RE. The collagen fibers were loosely arranged, fragmented and intermixed with varying amounts of myxoid stroma. Moderate and large areas of disarrangement (90% of cases) predominated. Collagen fiber arrangement in the region underneath the epithelium was better preserved when compared with fibers in the deeper region of the superficial layer of the lamina propria. There was a statistical difference in collagen disarrangement between grade II and grade III severity (P = .007) that appeared to be due to the large areas of disarrangement observed in 73% of patients with grade III severity and in 44% of grade II severity. Age was the only variable correlated with collagen fiber disarrangement (r = 0.47, P = .037). Conclusion: Our findings suggest that the flexible framework which maintains the uniformity of the lamina propria was lost in RE caused by the disarrangement of the collagen fibers.