A B C D E F G H I L M N P R S V W X misc
| AAL | Coordinates for data from the AAL-based atlases |
| aal116 | Coordinates for data from the AAL-based atlases |
| aal2.120 | Coordinates for data from the AAL-based atlases |
| aal2.94 | Coordinates for data from the AAL-based atlases |
| aal90 | Coordinates for data from the AAL-based atlases |
| analysis_random_graphs | Perform an analysis with random graphs for brain MRI data |
| aop | Approaches to estimate individual network contribution |
| apply_thresholds | Threshold additional set of matrices |
| bg_to_mediate | Mediation analysis with brain graph measures as mediator variables |
| Bootstrapping | Bootstrapping for global graph measures |
| brainGraph_boot | Bootstrapping for global graph measures |
| brainGraph_GLM | Fit linear models at each vertex of a graph |
| brainGraph_GLM_design | Create a design matrix for linear model analysis |
| brainGraph_GLM_fit_f | Fit linear models for t contrasts |
| brainGraph_GLM_fit_t | Fit linear models for t contrasts |
| brainGraph_mediate | Mediation analysis with brain graph measures as mediator variables |
| brainGraph_permute | Permutation test for group difference of graph measures |
| brainsuite | Coordinates for data from BrainSuite atlas |
| centr_betw_comm | Calculate communicability betweenness centrality |
| centr_lev | Calculate a vertex's leverage centrality |
| coeff_var | Calculate coefficient of variation |
| communicability | Calculate communicability |
| contract_brainGraph | Contract graph vertices based on brain lobe and hemisphere |
| cor.diff.test | Calculate the p-value for differences in correlation coefficients |
| corr.matrix | Calculate correlation matrix and threshold |
| CountEdges | Count number of edges of a brain graph |
| count_homologous | Count number of edges of a brain graph |
| count_inter | Count number of edges of a brain graph |
| count_interlobar | Count number of edges of a brain graph |
| craddock200 | Coordinates for data from the Craddock200 atlas |
| create_mats | Create connection matrices for tractography or fMRI data |
| DataTables | Create a data table with graph global and vertex measures |
| destrieux | Coordinates for data from Freesurfer atlases |
| destrieux.scgm | Coordinates for data from Freesurfer atlases |
| dk | Coordinates for data from Freesurfer atlases |
| dk.scgm | Coordinates for data from Freesurfer atlases |
| dkt | Coordinates for data from Freesurfer atlases |
| dkt.scgm | Coordinates for data from Freesurfer atlases |
| dosenbach160 | Coordinates for data from the Dosenbach160 atlas |
| edge_asymmetry | Calculate an asymmetry index based on edge counts |
| edge_spatial_dist | Calculate Euclidean distance of edges and vertices |
| efficiency | Calculate graph global, local, or nodal efficiency |
| Extract.brainGraph_resids | Linear model residuals in structural covariance networks |
| FreesurferAtlases | Coordinates for data from Freesurfer atlases |
| gateway_coeff | Gateway coefficient, participation coefficient, and within-mod degree z-score |
| get.resid | Linear model residuals in structural covariance networks |
| GLM | Fit linear models at each vertex of a graph |
| GLMdesign | Create a design matrix for linear model analysis |
| GLMfit | Fit linear models for t contrasts |
| GraphDistances | Calculate Euclidean distance of edges and vertices |
| graph_attr_dt | Create a data table with graph global and vertex measures |
| hoa112 | Coordinates for data from Harvard-Oxford atlas |
| hubness | Calculate vertex hubness |
| import_scn | Import data for structural connectivity analysis |
| IndividualContributions | Approaches to estimate individual network contribution |
| loo | Approaches to estimate individual network contribution |
| lpba40 | Coordinates for data from the LONI probabilistic brain atlas |
| make_brainGraph | Create a brainGraph object |
| make_ego_brainGraph | Create a graph of the union of multiple vertex neighborhoods |
| make_empty_brainGraph | Create an empty graph with attributes for brainGraph |
| make_glm_brainGraph | Create a graph with GLM-specific attributes |
| make_intersection_brainGraph | Create the intersection of graphs based on a logical condition |
| make_mediate_brainGraph | Create a graph with mediation-specific attributes |
| make_nbs_brainGraph | Create a graph with NBS-specific attributes |
| MediationAnalysis | Mediation analysis with brain graph measures as mediator variables |
| mtpc | Multi-threshold permutation correction |
| NBS | Network-based statistic for brain MRI data |
| part_coeff | Gateway coefficient, participation coefficient, and within-mod degree z-score |
| plot.bg_GLM | Fit linear models at each vertex of a graph |
| plot.brainGraph | Plot a brain graph with a specific spatial layout |
| plot.brainGraph_boot | Bootstrapping for global graph measures |
| plot.brainGraph_GLM | Plot a graph with results from brainGraph_GLM |
| plot.brainGraph_mediate | Plot a graph with results from a mediation analysis |
| plot.brainGraph_mtpc | Plot a graph with results from MTPC |
| plot.brainGraph_NBS | Plot a graph with results from the network-based statistic |
| plot.brainGraph_permute | Permutation test for group difference of graph measures |
| plot.brainGraph_resids | Linear model residuals in structural covariance networks |
| plot.IC | Approaches to estimate individual network contribution |
| plot.mtpc | Multi-threshold permutation correction |
| plot_brainGraph | Plot a brain graph with a specific spatial layout |
| plot_brainGraph_gui | GUI for plotting graphs overlaid on an MNI152 image or in a circle. |
| plot_brainGraph_list | Write PNG files for a list of graphs |
| plot_brainGraph_multi | Save PNG of three views of a brain graph |
| plot_corr_mat | Plot a correlation matrix |
| plot_global | Plot global graph measures across densities |
| plot_rich_norm | Plot normalized rich club coefficients against degree threshold |
| plot_vertex_measures | Plot vertex-level graph measures at a single density or threshold |
| plot_volumetric | Plot group distributions of volumetric measures for a given brain region |
| RandomGraphs | Perform an analysis with random graphs for brain MRI data |
| Residuals | Linear model residuals in structural covariance networks |
| RichClub | Rich club calculations |
| rich_club_all | Rich club calculations |
| rich_club_attrs | Assign graph attributes based on rich-club analysis |
| rich_club_coeff | Rich club calculations |
| rich_club_norm | Rich club calculations |
| rich_core | Rich club calculations |
| robustness | Analysis of network robustness |
| set_brainGraph_attr | Set graph, vertex, and edge attributes common in MRI analyses |
| sim.rand.graph.clust | Perform an analysis with random graphs for brain MRI data |
| sim.rand.graph.par | Perform an analysis with random graphs for brain MRI data |
| small.world | Calculate graph small-worldness |
| summary.bg_GLM | Fit linear models at each vertex of a graph |
| summary.bg_mediate | Mediation analysis with brain graph measures as mediator variables |
| summary.brainGraph | Create a brainGraph object |
| summary.brainGraph_boot | Bootstrapping for global graph measures |
| summary.brainGraph_permute | Permutation test for group difference of graph measures |
| summary.brainGraph_resids | Linear model residuals in structural covariance networks |
| summary.IC | Approaches to estimate individual network contribution |
| summary.mtpc | Multi-threshold permutation correction |
| summary.NBS | Network-based statistic for brain MRI data |
| symmetrize_array | Create a symmetric matrix |
| symmetrize_mats | Create a symmetric matrix |
| s_core | Calculate the s-core of a network |
| VertexRoles | Gateway coefficient, participation coefficient, and within-mod degree z-score |
| vertex_attr_dt | Create a data table with graph global and vertex measures |
| vertex_spatial_dist | Calculate Euclidean distance of edges and vertices |
| vulnerability | Calculate graph vulnerability |
| within_module_deg_z_score | Gateway coefficient, participation coefficient, and within-mod degree z-score |
| write_brainnet | Write files to be used for visualization with BrainNet Viewer |
| xfm.weights | Transform edge weights |
| [.brainGraph_resids | Linear model residuals in structural covariance networks |