Hi all,
I'm currently preprocessing my resting-state data with conn.v20b with the "default preprocessing pipeline for volume-based analyses". However, I get the following error when it reaches the "Functional outlier detection (ART-based identification)" step.
[i]Index in position 2 exceeds array bounds (must not exceed 1).[/i]
[i]Error in art>art_OpeningFcn (line 546)[/i]
[i]art_disp('fprintf','%7s%10.4f%10.4f%10.4f%10.4f%10.4f%10.4f%10.4f\n','mean ',mv_stats(1,1:3),mv_stats(1,4:6),mv_stats(1,32));[/i]
[i]Error in gui_mainfcn (line 220)[/i]
[i]feval(gui_State.gui_OpeningFcn, gui_hFigure, [], guidata(gui_hFigure), varargin{:});[/i]
[i]Error in art (line 145)[/i]
[i][varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});[/i]
[i]Error in conn_art (line 8)[/i]
[i][varargout{1:nargout}]=art(varargin{:});[/i]
[i]Error in conn_setup_preproc (line 2956)[/i]
[i]else h=conn_art('sess_file',matlabbatch{n}.art,'visible','off');[/i]
[i]Error in conn (line 1143)[/i]
[i]ok=conn_setup_preproc('',varargin{2:end});[/i]
[i]Error in conn_menumanager (line 121)[/i]
[i]feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});[/i]
Once I remove the "Functional outlier detection (ART-based identification)" step the pipeline works without any errors. However, the output swau_RS.nii which has been smoothed, normalized, slice timing corrected, unwarped becomes a one time-point image. Before preprocessing dimensions are 76x76x36x250 and after preprocessing dimensions are 91x109x91x1. I thought that it would keep the 250 timepoints in the output image?
Any form of guidance or advice would be greatly appreciated.
Thank-you,
Marsha
I'm currently preprocessing my resting-state data with conn.v20b with the "default preprocessing pipeline for volume-based analyses". However, I get the following error when it reaches the "Functional outlier detection (ART-based identification)" step.
[i]Index in position 2 exceeds array bounds (must not exceed 1).[/i]
[i]Error in art>art_OpeningFcn (line 546)[/i]
[i]art_disp('fprintf','%7s%10.4f%10.4f%10.4f%10.4f%10.4f%10.4f%10.4f\n','mean ',mv_stats(1,1:3),mv_stats(1,4:6),mv_stats(1,32));[/i]
[i]Error in gui_mainfcn (line 220)[/i]
[i]feval(gui_State.gui_OpeningFcn, gui_hFigure, [], guidata(gui_hFigure), varargin{:});[/i]
[i]Error in art (line 145)[/i]
[i][varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});[/i]
[i]Error in conn_art (line 8)[/i]
[i][varargout{1:nargout}]=art(varargin{:});[/i]
[i]Error in conn_setup_preproc (line 2956)[/i]
[i]else h=conn_art('sess_file',matlabbatch{n}.art,'visible','off');[/i]
[i]Error in conn (line 1143)[/i]
[i]ok=conn_setup_preproc('',varargin{2:end});[/i]
[i]Error in conn_menumanager (line 121)[/i]
[i]feval(CONN_MM.MENU{n0}.callback{n1}{1},CONN_MM.MENU{n0}.callback{n1}{2:end});[/i]
Once I remove the "Functional outlier detection (ART-based identification)" step the pipeline works without any errors. However, the output swau_RS.nii which has been smoothed, normalized, slice timing corrected, unwarped becomes a one time-point image. Before preprocessing dimensions are 76x76x36x250 and after preprocessing dimensions are 91x109x91x1. I thought that it would keep the 250 timepoints in the output image?
Any form of guidance or advice would be greatly appreciated.
Thank-you,
Marsha