Functional connectivity¶
See Clustering to parcellate the brain in regions, Extracting functional brain networks: ICA and related or Extracting times series to build a functional connectome for more details.
![](../../_images/sphx_glr_plot_inverse_covariance_connectome_thumb.png)
Computing a connectome with sparse inverse covariance
![](../../_images/sphx_glr_plot_probabilistic_atlas_extraction_thumb.png)
Extracting signals of a probabilistic atlas of functional regions
![](../../_images/sphx_glr_plot_simulated_connectome_thumb.png)
Connectivity structure estimation on simulated data
![](../../_images/sphx_glr_plot_multi_subject_connectome_thumb.png)
Group Sparse inverse covariance for multi-subject connectome
![](../../_images/sphx_glr_plot_seed_to_voxel_correlation_thumb.png)
Producing single subject maps of seed-to-voxel correlation
![](../../_images/sphx_glr_plot_compare_decomposition_thumb.png)
Deriving spatial maps from group fMRI data using ICA and Dictionary Learning
![](../../_images/sphx_glr_plot_extract_regions_dictlearning_maps_thumb.png)
Regions extraction using dictionary learning and functional connectomes
![](../../_images/sphx_glr_plot_atlas_comparison_thumb.png)
Comparing connectomes on different reference atlases
![](../../_images/sphx_glr_plot_group_level_connectivity_thumb.png)
Classification of age groups using functional connectivity
![](../../_images/sphx_glr_plot_data_driven_parcellations_thumb.png)
Clustering methods to learn a brain parcellation from fMRI