postprocessingscript.md

@@ -5,7 +5,7 @@ Throughout the pipeline the scripts make many decisions that result in marks on
 
 To visualise some of the choices that were made in the pipeline either create your own plotting functions, or try running the diagnotics script.
 
-**Using the Diagnostics Script**
+**Using the Diagnostics Script**  
 Open up a EEG dataset that has complete the dipfit stage of the pipeline to get all of the available figures. Most typically these will have the ending *_dip.set.* Make sure that the diagnostics.m file is on the MATLAB path. In the matlab editor call the diagnostics function in the MATLAB editor:
 ```
 diagnostics
@@ -27,7 +27,7 @@ The designation of *Bad* is based off a few simple calculations which parameters
 
 *As a side Note is is possible but not likely for a channel to be flagged for more than one of these classifications. This would mean diagnostics will find high numbers of bad channels but a lower number of removals. Make sure you look at the printout in the editor.*
 
- #  Channel Flags  
+ # Channel Flags  
 Channel flags are the way that channels are identified and staged for removal. A few examples of channel flag calculations are:
  * Standard Deviation (Comicaly Bad)  
  * High correlation (Bridging)  
@@ -89,7 +89,7 @@ time segment that was flagged between all of the channels combined. The percenta
   * ```[epoch_p] ``` in ```c01_scalpart.cfg``` for correlations. Default is 0.1(10%) of the channels in this time frame need to be flagged with the ```[epoch_z] ``` mark, a higher number will make the % required larger and thus less time segments will be flagged.  
   * ```[epoch_p]``` in ```c03_compart.cfg``` (or c6,c13,c14) for  ICSD. Default is 0.1(10%) of the channels in this time frame need to be flagged with the  ```[epoch_z] ``` mark, a higher number will make the % required larger and thus less time segments will be flagged.  
 
-#  Component Classification 
+# Component Classification 
 
 ![diag3](/uploads/dfa4b9cb0401bc516f5b8ebe9524f874/diag3.png)