This repository was created on 31.10.2019 and contains documentation of the TMS experiment reported in:

Meers, Nuttall & Vogt: Motor imagery alone drives corticospinal excitability during simultaneous action observation and motor imagery

1. Stimuli: The zip archive contains all stimuli used:
- I0, I2, I3.mov contain movies with index finger movement and 0, 2, or 3 deviant moves
- P0, P2, P3.mov contain movies with pinky finger movement and 0, 2, or 3 deviant moves
- S0, S2, S3.mov contain movies without movement (‘static’) but 0, 2, or 3 deviant colour changes

2. programmes: A zip archive with 3 files:

2a. stimulus display program ‘Trialsessions6’ (Matlab code using the Psychophysics Toolbox version 3, Brainard et al., 1997) for stimulus display and TMS trigger pulses on Mac mini computer

2b. Two Matlab scripts for data preprocessing. We used 2 Matlab routines for extracting the MEP peak-to peak amplitudes from the above ASCII files:

2b1. LoadDeymedTruTraceMEP3 was used to parse each ASCII file from TruTrace. This script chunks up the ascii file into the following variables and was compiled by Deymed Diagnostic, the manufacturers of the TruTrace software. When an input file is read by the script, it creates the following outputs:

Data = Matrix of MEP signal data. Each value = one sample of the data. Value in [uV]
 
X = X value for each sample in [ms]
 
Markers = A matrix of Markers data (4 X number of exported Traces)
            For each trace up to four markers can be stored. If 0 present instead of the marker value, no Marker was set. The Marker value is in [ms] from the stimulus. 
            1 = I marker
            2 = A- marker
            3 = A+ marker
            4 = E marker

The markers are placidly the TruTrace software to detect the onset, max peak, min peak, and end of the MEP. We did not use this automatic marking information for our analyses.
 
Notch filter = Power source frequency [Hz]
 
RecordsCount = Number of traces in the exported file
 
SampleRate = Sampling frequency [Hz]  

SampleCount = Number of samples per each trace.
  
StimSample = Number of a sample where the stimulation was started. (1 X RecordsCount) - A StimSample value for each trace.
 
Position = Index of position where the trace was recorded in the TruTrace EMG software. (3 X RecordsCount) For each record a three values are stored.
            1 = Side = 1 for right side and 2 for left side
            2 = Set (there could be several Sets for each Side - typically 3) = 1,2,3,.. for particular Set
            3 = Run (up to 6 runs) Each run has a different colour in 

TruTrace = 1,2,3,4,5,6 depending on the colour

2b2. MEPmenu_Rosie script was used for high-resolution visual display of each MEP and interactive determination of minimum and maximum of each MEP. Script reads in the data from 4a and plots each MEP in interactive window. The user can then manually select the maximum peak and minimum peak of the MEP. The script then stores the amplitude values, and finds the difference between the values to determine the peak-to-peak value for the MEP. All information computed by the script is saved in a structure called ‘PKS’. The peak-to-peak information is ‘PKS.P2PAmps’. This is the information that is then used in subsequent analysis steps.

3. Rawdata. A zip archive containing the raw data from all 13 participants in ASCII format. These were exported from TruTrace software and compressed here for archiving. The archive for each participant contains 16 files. For example, the first participant is coded as ‘S03’ and the 16 files correspond to the following conditions in the study (Abbreviations: cAOMI = congruent AO+MI; i = index; p = little finger or pinky; for example AO_i and MI_p stands for incongruent AOMI condition with observed movement of the index and imagined movement of the little finger):

S03_1_1: cAOMI index-engaged (Session 1)
S03_2_1: cAOMI pinky-engaged
S03_3_1: AO_i and MI_p
S03_4_1: AO_p and MI_i
S03_5_1: pure AO_i
S03_6_1: pure AO_p
S03_7_1: Baseline 1
S03_8_1: Baseline 2
S03_1_2: cAOMI index-engaged (Session 2)
…
S03_8_2: Baseline 2 (Session 2).

4. Results: zip archive containing the (z-transformed) MEP averages per participant and condition for the statistical data analysis, provided in Excel and SPSS formats, plus a detailed results figure. Note that the two baseline blocks per session were averaged into a single block per session. The 28 conditions of the 2x7x2 design are entered with recorded Muscle (i=FDI/index; p = ADM/pinky) as slowest varying factor, followed by Condition (7), and by Session (a =1st; b=2nd session) as fastest varying factor. The 7 levels of the condition factor are apparent from the list below. Whilst Figure 2 of the main paper shows the results collapsed across Muscle and Session, the figure in Supplementary material shows results separately for the two recoded muscles and thus corresponds in greater detail to the data provided here (this figure is included, too).

4a. Results_MeersNuttallVogt_X:
- Rows 2 to 14 show the data separately for the n=13 participants used
- Columns A to AB show the n=28 conditions, where the first 14 columns show the data recorded from the FDI muscle (‘index’), and columns 15-28 show the data recorded from the ADM muscle (‘pinky’)

Zib1a  cAOMI: AO_i+MI_i
Zib1b  (ditto 2nd session)
Zib2a  cAOMI: AO_p+MI_p
Zib2b
Zib3a  iAOMI: AO_i+MI_p
Zib3b
Zib4a  iAOMI: AO_p+MI_i
Zib4a
Zib5a  pureAO_i (observation of moving index finger, recorded index finger)
Zib5b
Zib6a  pure AO_p observation of moving pinky, recorded index finger)
Zib6b
Zi_st_a  ‘static’ Baseline 1st Session
Zi_st_b  ‘static’ Baseline 2nd Session
Zpb1a:  same 14 conditions as above but for ADM (‘pinky’)
…
Zp_st_b

4b. AveragesMeersNuttallVogt.SPSS: same matrix structure as above Excel file (13 participants x 28 variables)

4c. Results figure (Supplementary material).