Standard analysis design steps

UNDER CONSTRUCTION

Below are some general guidelines that help you analyze your data
Thinking about this early on, is extremely helpful as it can prevent you from acquired a lot of data without the required inputs. Some things can not be corrected after the fact

Create a github page of the project

github.com

Describe the data acquisition task by task

Auditory M100 task:

 Tone burst auditory stimuli were delivered bilaterally to the subject using the ....

Somatosensory task:

 Pneumatic stimulation was performed on the index finger at a rate of approximately 2 times per second with a jitter of 20 ms ...

For each task describe the auxilliary channels:

UADC001 was used for left hand patient responses
UADC002 was used for right hand patient responses
UADC016 was used for the projector channel to correct for timing delays
UPPT001 codes the stimuli values

Describe what each PPT value codes

2: congruent word stimuli
4: incongruent word stimuli
6: distractor words
8: high noise condition
....

If your logfile incorporates special data that is not in your meg dataset - list these entries

The logfile codes out ...

If there is external data that is collected - describe how this will be incorporated with the data

External camera data was used to judge facial expressions. Timing triggers were sent to the

Describe Your Hypothesis About The Results

We expect to see activation in the left dorsolateral prefrontal area
Timing - Prior literature has shown that

Develop code to write the triggers to your MEG dataset

Python Dataframe Based:

examples: https://github.com/nih-megcore/hv_proc/tree/main/hv_proc/Process_scripts 
requires nih2mne: https://github.com/nih-megcore/nih_to_mne.git 

Commandline Based:

requires pyctf: https://github.com/nih-megcore/pyctf OR https://github.com/nih-megcore/pyctf-lite)

==Run the