4.3 Case Two: Source localization in a segment of 0.5
was moved, BA 1 which is involved, as BAs 2 and 3, in locating the body in space. Further-more, BA 5, which is also involved in locating objects in space, was estimated just before the movement started, in the interval from −0.5 s to 0 s, when the right arm was moved.
Left Arm Movement
Time [-2,-1.5) [-1.5,-1) [-1,-0.5) [-0.5,0) [0,0.5) [0.5,1) [1,1.5) [1.5,2)
sLORETA BA 47 10 11 7 7 21 47 47
MLE BA 8 8 8 8 47 47 47 47
MNE BA 8 8 8 8 47 47 47 47
wMNE BA 8 8 8 8 45 45 47 47
Right Arm Movement
Time [-2,-1.5) [-1.5,-1) [-1,-0.5) [-0.5,0) [0,0.5) [0.5,1) [1,1.5) [1.5,2)
sLORETA BA 47 1 10 5 7 7 7 47
MLE BA 8 8 47 8 47 47 47 47
MNE BA 8 8 47 8 47 47 47 47
wMNE BA 8 8 47 8 47 45 8 45
Table 4.7: Study two: Case two: Brodmann areas located with source localization for partici-pant 6.
Left Arm Movement
Time [-2,-1.5) [-1.5,-1) [-1,-0.5) [-0.5,0) [0,0.5) [0.5,1) [1,1.5) [1.5,2)
sLORETA BA 9 10 10 10 10 10 9 10
MLE BA 9 9 9 9 9 9 9 9
MNE BA 9 9 9 9 9 9 9 9
wMNE BA 9 9 9 9 9 9 9 9
Right Arm Movement
Time [-2,-1.5) [-1.5,-1) [-1,-0.5) [-0.5,0) [0,0.5) [0.5,1) [1,1.5) [1.5,2)
sLORETA BA 10 9 10 10 7 10 10 10
MLE BA 9 9 9 10 7 10 9 9
MNE BA 9 9 9 10 7 10 9 9
wMNE BA 9 9 9 10 7 10 9 9
Table 4.8: Study two: Case two: Brodmann areas located with source localization for partici-pant 11.
The results for the participant 11 are displayed in table 4.8. The maximum brain activity estimated was predominant in the left hemisphere of the brain for this participant. Despite not finding the main brain activity in a motor area, the estimated BAs have an important role in the development of the experiment, mainly BA 7.
The results for the participant 15 are shown in table 4.9. For this participant, the left hemisphere was also the predominant with the main brain activity. Furthermore, The sec-ondary motor cortex, BA 6, is shown highly active for when the right arm was moved and also appears for the movement with the left arm. In addition, the primary motor cortex, BA 4, is also present in the last interval from 1.5 s to 2 s for the right arm movement, estimated
with sLORETA. Every area estimated for participant 15 is highly involved in the movements carried out in the experiment.
The reader can review the results for the rest of the participants in the Appendix B. All of the found BAs and their function are shown in table 4.10, where it can be observed how every area has a role in some activity from the experiment, except for BA 38 once again.
Left Arm Movement
Time [-2,-1.5) [-1.5,-1) [-1,-0.5) [-0.5,0) [0,0.5) [0.5,1) [1,1.5) [1.5,2)
sLORETA BA 6 6 10 10 3 10 6 10
MLE BA 40 40 6 40 40 10 6 10
MNE BA 40 40 6 40 40 10 6 10
wMNE BA 40 40 6 40 40 10 6 10
Right Arm Movement
Time [-2,-1.5) [-1.5,-1) [-1,-0.5) [-0.5,0) [0,0.5) [0.5,1) [1,1.5) [1.5,2)
sLORETA BA 10 6 10 45 45 6 45 4
MLE BA 6 6 6 6 6 6 6 40
MNE BA 6 6 6 6 6 6 6 40
wMNE BA 6 6 6 6 6 6 6 40
Table 4.9: Study two: Case two: Brodmann areas located with source localization for partici-pant 15.
Brodmann Areas (BA)
BA Associated function
1, 2 & 3 Location of own body
4 Primary motor cortex
5 Location of objects
6 Secondary motor cortex
7 Locating objects in space
8 Planning of complex movements
9 & 10 Related to memory and cognitive processes
11 Decision making
18, 19 & 20 Processing of visual information
21, 22, 40, 44, 45 & 47 Contemplating distances // Accessing words meanings
38 Emotional responses
39 Involve in reading
46 Attention, memory
Table 4.10: Study two: Case two: Brodmann areas located with source localization of the 15 participants.
The results that were found in conducting this study show that SLMs are reliable tools able to estimate the brain activity of a person during the development of an arbitrary activity.
Even if not all the areas estimated were motor related areas they are all related in a way or another to the activities of the experiment. This study also confirms the complexity of the
thoughts, even if it is just a simple task a lot of brain areas are involved in the execution of that action. It can be concluded that the most important areas involved in a movement are, without a doubt, BAs 4 and 6, since these are the areas in charge of the execution of the movements.
However, it can also be concluded that areas whose function is related to locate objects or the body in space are also important, like BAs 1, 2, 3, 5 and 7. Furthermore, BAs 8, 11, 21, 22, 40, 44, 45 and 46 are also heavily related, as they are involved in contemplating the distances for the movement, the planning of the movement and in taking decision for the movement.
Areas like BAs 18, 19, 20, 39 and 46 are not entirely related to the execution of movements, but are involved in secondary actions consequence of the experiment, like reading, viewing images or focusing their attention on the screen. Areas 9 and 10 are related to memory and also in cognitive processes, the latter are important in the form that the movement is executed.
Finally, BA 38, which is related to emotional responses, is the only estimated area that was not directly related to the experiment in any way. However, given that the participants are only human it is safe to assume the possibility of evoking emotions within the experiment, be it in response of the images or the tasks presented or because of the effort of remaining calm and attentive to the experiment timings, which can be tiresome as time progresses [1] [4] [6].
Study Three: Classification Performance
This chapter seeks to evaluate the performance of a machine learning algorithm when the features are either extracted from the EEG, the traditional approach, or when are extracted from the estimated brain sources that generated the EEG in the classification of movement intention (1) and no movement (0) from real data gathered from a motor tasks experiment. The algorithm used for classification was one of the most popular algorithms for motor BCIs: a support vector machine (SVM), which was implemented in MATLAB 2018b using the library libsvm version 3.24. For pre-processing the EEG signal and the estimated brain sources the implementation in MATLAB R2018b was used along with Google Colaboratory for parallel pre-processing of the data.