Investigating the functional neural network dynamics of cognitive-affective action planning during threat processing.

1. function [p, ADJ, NULL] = CBIG_ASDf_FCDiffInSubgrp_NBS(tThresh, id_asd_subgrp_file, ...
2. id_con_subgrp_file, id_asd_file, id_con_file, Nperm, output_name)
3. % [p, ADJ, NULL] = CBIG_ASDf_FCDiffInSubgrp_NBS(tThresh, id_asd_subgrp_file,
4. % id_con_subgrp_file, id_asd_file, id_con_file, Nperm, output_name)
5. %
6. % This function compares FC difference between ASD and control participants
7. % in factor subgroups. Statistical significance is tested using network-based statistic
8. % (NBS; Zalesky et al., 2010).
9. % The results will be saved in the directory specified by output_name.
10. %
11. % Input:
12. % - tThresh:
13. % t-statistic threshold for NBS. E.g., 1.5 or 2
14. % - id_asd_subgrp_file:
15. % Absolute path to the .mat file including all ASD subjects' IDs
16. % in the subgroup. Assuming the .mat file is named as
17. % "id_asd_subgrp", and it is a N_s1x1 cell array, where N_s1 is the
18. % number of ASD subjects in the subgroup, and the i-th cell is
19. % the i-th ASD subject's ID (a string)
20. % - id_con_subgrp_file:
21. % Absolute path to the .mat file including all control subjects' IDs
22. % in the subgroup.. Assuming the .mat file is named as
23. % "id_con_subgrp", and it is a N_s2x1 cell array, where N_s2 is the
24. % number of control subjects in the subgroup, and the i-th cell is
25. % the i-th control subject's ID (a string)
26. % - id_asd_file:
27. % Absolute path to the .mat file containing all ASD subjects'
28. % IDs. Assuming the .mat file is named as "id_asd", and it is a
29. % N1x1 cell array, where N1 is the number of ASD subjects, and the
30. % i-th cell is the i-th ASD subject's ID (a string).
31. % - id_con_file:
32. % Absolute path to the .mat file containing all control subjects'
33. % IDs. Assuming the .mat file is named as "id_con", and it is a
34. % N2x1 cell array, where N2 is the number of control subjects, and
35. % the i-th cell is the i-th control subject's ID (a string).
36. % - Nperm:
37. % Number of permutations. E.g., 10000.
38. % - output_name:
39. % Output file name including the full path where the results of
40. % NBS will be saved
41. % Output:
42. % - p:
43. % 1xC vector, where C is the number of identified components from
44. % NBS. Corrected p-values for each component from NBS
45. % - ADJ:
46. % MxM matrix, where M is the number of edges in NBS input connectivity matrix
47. % to NBS. Adjacency matrix identifying the edges comprising each
48. % component. Edges corresponding to the first p-value stored in the
49. % vector p are assigned the value 1 in the adjacency matrix ADJ,
50. % edges corresponding to the second p-value are assigned the value 2, etc.
51. % - NULL:
52. % 1xNperm matrix. A vector of Nperm samples from the null distribution of
53. % maximal component size
54. %
55. % Example:
56. % [p, ADJ, NULL] = CBIG_ASDf_FCDiffInSubgrp_NBS(1.5, id_asd_subgrp_file,
57. % id_con_subgrp_file, id_asd_file, id_con_file, 10000, 'nbs_subgroup')
58. %
59. % Written by Siyi Tang and CBIG under MIT license: https://github.com/ThomasYeoLab/CBIG/blob/master/LICENSE.md
61. %% Read subjects' IDs
62. load(id_asd_subgrp_file); % id_asd_subgrp .mat file
63. load(id_con_subgrp_file); % id_con_subgrp .mat file
64. load(id_asd_file); % id_asd .mat file
65. load(id_con_file); % id_con .mat file
67. %% Generate permutation set using PALM package
68. permSet = CBIG_ASDf_genPermSetForNBS(id_asd_subgrp, id_con_subgrp, Nperm);
70. fprintf('------Performing NBS in subgroups\n:');
71. fprintf('t-stats threshold:%f\n', tThresh);
72. fprintf('Number of permutations:%d\n', Nperm);
74. %% load FC matrices
75. CBIG_REPDATA_DIR = getenv('CBIG_REPDATA_DIR');
76. UNIT_TEST_DIR = fullfile(CBIG_REPDATA_DIR,'stable_projects','disorder_subtypes','Tang2020_ASDFactors');
77. inputDir = fullfile(inputDir, 'data');
78. load(fullfile(inputDir, 'corrMat_ASD_inf.mat')); % load ASD FC matrices
79. load(fullfile(inputDir, 'corrMat_Con_inf.mat')); % load control FC matrices
81. idx_asd_subgrp = ismember(id_asd, id_asd_subgrp);
82. idx_con_subgrp = ismember(id_con, id_con_subgrp);
83. corrMat_asd_subgrp = corrMat_ASD(:,:,idx_asd_subgrp);
84. corrMat_con_subgrp = corrMat_Con(:,:,idx_con_subgrp);
86. %% run NBS
87. [p,ADJ,NULL] = CBIG_ASDf_NBS_permSetInput(corrMat_asd_subgrp, corrMat_con_subgrp,tThresh, permSet, 'both');
89. file_name = [output_name '.mat'];
91. save(file_name,'p','ADJ','NULL');

CBIG_ASDf_FCDiffInSubgrp_NBS.m at commit 634f676, under MIT · at the source