References: If you are using this repo please cite: xxx
Usage: The code utilized in this study include eight main steps:
-
prepare data and check information step1_check_subjects.m: Check subjects' information include subject id, session, file path step1_prepare_sleep_subject_info_analysis.m: Organize relevant data of individuals for analysis: demographic information, FD, swa, behavior measures step1_select_control_sublist.m: Select subjects as control group for validation step1_compute_cortex_snr_weight.m: Compute snr map of cortex for mapping subcortex atlas
-
construct individual and group average atlas step2_HFR_mod_multi.m/step2_HFR_mod_single_session.m: Construct individual atlas in cortex using Wang et al., 2015. step2_subcortex_mapping.m/step2_subcortex_mapping_multi_all.m/step2_subcortex_mapping_multi_control.m: Mapping individual atlas in subcortex using Lisa et al., 2019. step2_cleanup_subcortex.m/step2_cleanup_subcortex_multi.m: Clean up individual atlas in sucortex step2_Dice_coefficient_sleep_stage_splithalv_control.m/step2_Dice_coefficient_sleep_stage_splithalv.m: Compute Dice's coefficient for group average atlas
-
visualization of group average atlas step3_visualization_subcortex_atlas.m/step3_visualization_subcortex_atlas_control.m: Visualization of group_average atlas
-
compute network size step4_compute_network_size_lme_whole.m/step4_compute_network_size_lme_whole_control.m: Calculate the network size of individual atlas and save the data in LME model input file format compute_linear_mixed_model_significance.R: LME model
-
predict sleep stage using network topography step5_classify_sleep_stage_binary_whole.m: SVM binary classification step5_classify_sleep_stage_multiclass_7_whole.m/step5_classify_sleep_stage_multiclass_7_control_whole.m: SVM multi classification step5_classify_sleep_stage_multiclass_7_whole_hemi.m: SVM multi classification, using network topology features with the left and right hemispheres step5_classify_sleep_stage_RF_multiclass_7_whole.m: RF multi classification step5_classify_sleep_stage_KNN_multiclass_7_whole.m: KNN multi classification step5_classify_sleep_stage_ANN_multiclass_7_whole.m: ANN multi classification
-
compute encroaching step6_compute_network_encroaching.m: Calculate the encroaching regions and types of AMN network step6_compute_network_encroaching_rsfc.m: Calculate the RSFC between the encroaching regions of the AMN network in each sleep stage compared to the awake stage step6_compute_network_spring_embeded.m: Calculate the data for spring embeded plotting step6_compute_network_modularity.m: Calculate the modularity
-
calculate the correlation between network area and SWA step7_swa_related_with_surface_area_wholebrain.m: Calculate the correlation between the network area and SWA for all sleep stages compared to the awake stage step7_swa_related_with_surface_area_single.m: Calculate the correlation between the network area and SWA during a single sleep stages compared to the awake stages
-
calculate the correlation between network area and PSQI step8_behavior_related_with_surface_area_whole_brain.m Calculate the correlation between the network area and PSQI during a single sleep stages compared to the awake stages