A combinational feature selection and ensemble neural network method for classification of gene expression data-1

<p><b>Copyright information:</b></p><p>Taken from "A combinational feature selection and ensemble neural network method for classification of gene expression data"</p><p>BMC Bioinformatics 2004;5():136-136.</p><p>Published online 27 Sep 2004</p><p>PMCID:PMC522806.</p><p>Copyright © 2004 Liu et al; licensee BioMed Central Ltd.</p

ROI analyses of the rsFC between the S1 and visual areas.

<p><b><i>A</i></b> and <b><i>B</i></b>, the mean rsFC of CB (blue bar) and SC (green bar) subjects between intra-hemisphere and intra-hemisphere, respectively. An asterisk represents significantly differences (<i>P</i><0.05, Bonferroni corrected). <b><i>C</i></b>, the defined S1 and visual ROIs. <b><i>D</i></b>, rsFC patterns between S1 and visual areas in the SC. <b><i>E</i></b>, rsFC patterns between S1 and visual areas in the CB. <b><i>F</i></b>, group differences of rsFC between CB and SC subjects. Orange and light blue edges represent positive and negative effects. Blue, red and green nodes represent S1, affected and non-affected visual areas. Compared with SC subjects, CB subjects showed significantly decreased rsFC of the S1 with the early visual areas and the ventral stream ones, with no difference being observed in several higher-tier visual areas.</p

A combinational feature selection and ensemble neural network method for classification of gene expression data-2

<p><b>Copyright information:</b></p><p>Taken from "A combinational feature selection and ensemble neural network method for classification of gene expression data"</p><p>BMC Bioinformatics 2004;5():136-136.</p><p>Published online 27 Sep 2004</p><p>PMCID:PMC522806.</p><p>Copyright © 2004 Liu et al; licensee BioMed Central Ltd.</p

The rsFC patterns within the visual areas in CB and SC subjects.

<p><b><i>A</i></b>, the mean rsFC in CB and SC subjects, and group comparisons (<i>P</i><0.05, Bonferroni corrected), in which hot and cool colors represent positive and negative effects, respectively. Color bar represents the log-transformed <i>P</i> value. <b><i>B</i></b>, the rsFC patterns between each pair of the ipsilateral visual areas. <b><i>C</i></b>, The rsFC patterns between each pair of inter-hemispheric visual areas. Orange and light blue lines represent increased and decreased rsFC. Both CB and SC subjects show positive rsFC between visual areas. Significantly increased rsFC between the early (V1 and V2) and several ipsilateral higher-tier visual areas (V8 and LO), while decreased rsFC between inter-hemispheric visual areas are shown in CB subjects.</p

The rsFC maps between the S1 and the visual areas.

<p><b><i>A</i></b>, the rsFC map of SC subjects. <b><i>B</i></b>, the rsFC map of CB subjects. <b><i>C</i></b>, the differential maps of rsFC between CB and SC subjects with thresholded at P<0.05 (FDR corrected). The upper and lower panel represents the FC results of the S1 area in the left and right hemisphere, respectively. Compared with SC subjects, CB subjects showed significantly decreased (cool color) rsFC between the S1 and the visual areas, especially the early visual areas (V1 and V2) and the ventral stream (VP and V4v).</p

A combinational feature selection and ensemble neural network method for classification of gene expression data-0

<p><b>Copyright information:</b></p><p>Taken from "A combinational feature selection and ensemble neural network method for classification of gene expression data"</p><p>BMC Bioinformatics 2004;5():136-136.</p><p>Published online 27 Sep 2004</p><p>PMCID:PMC522806.</p><p>Copyright © 2004 Liu et al; licensee BioMed Central Ltd.</p

The mean r-value matrices (A) and hierarchical clustering analyses (B) for the four task conditions: the preferential choice in the gain domain, the preferential choice in the loss domain, the trade-off instruction choice in the gain domain and the trade-off instruction choice in the loss domain.

<p>(A): Each figure shows a 19×19 square matrix in which the x and y axes correspond to the regions listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041048#pone-0041048-t001" target="_blank">Table 1</a> and in which each entry indicates the mean strength of the functional connectivity between each pair of brain regions. The z score of the functional connectivity is indicated with a colored bar. (B): The vertical axis represents distance. The numbers in the horizontal axis represent the seed regions. Please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041048#pone-0041048-t001" target="_blank">Table 1</a> for a detailed interpretation of the numbers.</p

A combinational feature selection and ensemble neural network method for classification of gene expression data-3

<p><b>Copyright information:</b></p><p>Taken from "A combinational feature selection and ensemble neural network method for classification of gene expression data"</p><p>BMC Bioinformatics 2004;5():136-136.</p><p>Published online 27 Sep 2004</p><p>PMCID:PMC522806.</p><p>Copyright © 2004 Liu et al; licensee BioMed Central Ltd.</p

Comparison maps of cortical thickness between CB and SC subjects in a vertex-wise manner.

<p><b><i>A</i></b>, significantly increased cortical thickness in CB subjects is observed in the visual areas while absent in primary somatosensory cortex (S1) within a searching mask including the whole visual cortex and S1 (<i>P</i><0.01, FDR corrected). <b><i>B</i></b>, significantly increased cortical thickness in CB subjects is observed in the early visual areas (V1, V2 and VP), but not in higher-tier ones (V3A, V7, MT+ and V8) and in S1. Scale bar represents the log-transformed <i>P</i> value.</p

Demographic information of congenitally blind subjects.

*<p>These two CB subjects were excluded from rest-state functional connectivity analysis for excessive head motion. CB  =  congenitally blind.</p