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Motor Imaginary Using fMRI 47

The LFP is an electric signal, which is measured from the

inside of the cortex and outside of the neuron cells. The

physical property of the LFP signal is the same as that of the

scalp-EEG signal. As a result, the fMRI experimental data

may have a close relationship with the EEG sensor signals[6].

In general, the source of brain activity has been widely

explained by three-dimensional dipole model [7]. Thus, it

seems to be reasonable to consider the dipole direction as

well as the dipole source location. It is impossible, however,

to estimate the dipole direction using fewer number of EEG

sensors. In our case, the mental tasks to be considered are

mainly related with surface brain activity, such as the

secondary motor cortex area and the posterior parietal cortex

area. Thus, we simply ignored the dipole directions of the

source of brain activity. Based upon these observations, we

have tried to find appropriate mental tasks, as well as to

estimate the optimal location for the EEG sensors indirectly,

by using fMRI equipment.

In Section 2, the fMRI experiment and data analyze will be

described. In Section 3, the relation between fMRI data and

EEG data and the EEG experiments, with analyze based upon

these fMRI analysis results will be outlined. Section 4

provides a conclusion and further research.

II. fMRI Experiment and Data Analysis

A. fMRI experiment

The fMRI experiments were conducted with the cooperation

of Brain Science Research Center (BSRC) at the KoreaAdvanced Institute of Science & Technology (KAIST). The

experiments were conducted monthly in, 2005, and each

experiment included two or three subjects. Among the eight

subjects, one subject (subject A) participated in every

experiment. The fMRI equipment included a 3T magnetic

system. We set the time-to-repetition (TR) to 3000ms and the

time-to-echo (TE) to 35ms. The motor imagery tasks were

cued through the LCD project on the RF coil inside the

gantry.

The fMRI experimental paradigm consisted of a condition

state time for 12sec and a resting state time for 24sec. The

repetitive mental tasks were repeated six times for each

session. We analyzed the data by using Statistical ParametricMapping (SPM) toolbox (FIL, London, England ).

In order to find a suitable mental task, we executed various

kinds of mental task experiment like imaging taste, and

calculation of mathematical tasks, and imagination of good

or bad experiences. We regarded suitable mental tasks as

ones shows obvious brain activation with good recurrence

and localization features in fMRI experiment data. After

execution of the some kinds of mental task experiment and

data analysis, we selected the imagination of body movement

to focus metal task. Except for this mental task, we could not

find similarities among the different subjects in the SPM

analysis results.

We have applied mental task to map the two directions of a

computer mouse point that can be controlled by the

imagining of body movement, such as movement of the left

finger and right fingers. Even though the mental task is

simple, the exact meaning of the mental tasks was explained

to the 8 subjects to avoid that subject misunderstand themental task.

B. Analysis of fMRI experiment data

First, we check whether the observed data of the same mental

tasks have similarities regarding different subjects and

experimental periods. After observing the data, we could

determine the brain activity in the supplementary motor area

(SMA) for both left and right motor imagery. Figs. 1 and 2

show five months of data for subject A. Fig. 1 shows the SPM

analysis results of the left-finger movement imagination

experiment for the experimental periods between May and

November. Fig. 2 shows the SPM analysis results the

imagined of right-finger movement for each period. The firstline of each figure indicates right-cerebral hemisphere

activation and the second line shows left-cerebral hemisphere

activation. The last line shows the dorsal view of the cortex

activation. The SMA area is in the secondary motor cortex

area, which plays an important role in planning body

movements [8]-[10]. Furthermore, as shown in Figs. 1 and 2,

the activation area near the SMA has clear localization and

activation features. The data analysis results obtained from

other subjects also show these SMA activation features

clearly when mental task is imagination of body movement.

By using these observations, we can conclude that the SMA

area is always activated whenever subject performs imagery

tasks.

Moreover, it is interesting to note that there are no

prominent hotspots in the M1 area for both imaginations of

right and left-finger movements. Moreover, it is difficult to

find significant contralateral characteristics concerning the

mental tasks in our experiment.

Figure 1. The result of fMRI imaging of imagined left-finger

movements.

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48 Sang Han Choi and Minho Lee

Figure 2. The result of fMRI imaging of imagined

right-finger movement.

III. EEG Experiment and Data Analysis

A. EEG experiment

The EEG experiments were conducted using 16-channel

BIO-PAC EEG acquisition equipment. The sampling rate of

our experiment is 250Hz and the gain is 10,000. In the case

of skin resistance, the amount was set below 5k ohm. There

was little amount of 60Hz frequency power element in the

Fourier transform data of the EEG data, and the amplitude

of EEG is 30~60V, so the EEG data set was regarded as fair.

In this experiment, we set the paradigms to similar format

with the fMRI experiments to make similar conditions for

both cases. The paradigm of the resting state time was set to

5 sec and the conditioning state time to 5 sec.In this experiment, we set the experimental paradigm to a

similar format for the fMRI experiments in order to

standardize conditions. Our purpose for this EEG

experiment was to verify the results of the fMRI experiment

comparing those with the EEG sensor data. We choose the

electrode positions: C3, C4, with Pz, Fz, AFz and Cz, of the

10-20 EEG electrode placement systems. The C3 and C4

areas are located in the primary motor cortex area (M1)

especially, near the hand area in the penfield somatotopic

map [9], and this area is usually referenced electrode

location of BCI system whose mental task is imagination of

finger movements. The SMA is the secondary motor cortex

area (M2) and this area is located in middle of Cz and Fz,We executed EEG experiments with the imagination of left

and right finger movements, resting. The experiment was

repeated to ten times per each sequence.

B. Analysis of EEG experiment data

The two EEG features we regarded for offline analysis were

the absolute values of 10~15Hz band filtering data and a

variance of raw data. The 10~15Hz band EEG signal is

related with rhythm which is usually recorded from the

motor cortex of the dominant hemisphere. It was possible to

observe that variance of EEG signal decreased when the

mental task was in a condition state. Fig. 3 shows the

variance features. The interval of black line indicates the

condition time interval. As shown in Fig. 3, it can be seen that

the level of variance decreased when it is in condition

interval, especially in channel 1 and channel 2, which is near

the SMA area. We set the sampling interval time to 0.1sec

and a 0% overlap time for extraction of the variance featureof the EEG data.

Figure 3. Raw EEG signals with the lines, which

acknowledge the conditions state time.

By using the absolute values of the filtered data and the

variance of the raw EEG sensor signals, we implemented two

LDA classifiers to discriminate the mental tasks. We

regarded two kinds of discrimination method. One is

distinguishing between resting state and condition state

(imagination of left and right finger movement) and the other

is distinguishing between imagination of left-finger

movements and imagination of right-finger movements in the

case of the condition state. Table 1 and 2 shows the result of

analysis. Table 1 shows the results of discrimination between

left finger motor imagery and right finger motor imagery.

Table 2 shows the results of distinguishing between

conditioned and resting state. Fig. 4 shows one example of

LDA results. These are the result of distinguishing between

imagined right and left-finger movement

Reference C3 C4

Pz

Cz

Fz

AFz

Ear lobe

70%

80%

90%

90%

60%

90%

80%

90%

90%

60%

Table 1. The hit rate of single channel EEG data whichdistinguishes between an imagined left-finger motor imagery

condition state and right-finger motor imagery condition

state using LDA.

Electrode location Left ear AFz

Pz

Cz

Fz

AFz

79%

85%

81%

80%

75%

75%

85%

Table 2. The hit rate of single-channel EEG data which

distinguishes between a conditional state and a state of rest

using LDA

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Motor Imaginary Using fMRI 49

-0.02 0 0.02 0.04 0.06 0.08 0.1-0.06

-0.04

-0.02

0

0.02

0.04

0.06

0.08

filtering feature

varinace

Figure 4. The LDA results of 16 examples of data from the

EEG sensors of C4-Cz. The line shows the LDA results. o

shows the features of the imagination of right-finger

movements. * shows the features of the imagination of

right-finger movements. The hit rate of this data is(12/16)*100=75%.

From the results of the EEG signal, the motor-imagery

mental task induces reliable distinct changes in the EEG

signal features in the SMA area. The SMA area is located

between the Fz and Cz. From the Tables 1 and 2, it is seen

better discrimination performance in those areas. These

results corresponded with those of the fMRI experiment

analysis. Moreover, we can confirm that the location of the

reference electrode is important. In the case of discrimination

between left-finger motor imagery and right-finger motor

imagery, the performance of the unipolar type EEG signal(earlobe-C3, earlobe-C4) is not as good as that of another

case whose reference is in brain activity areas.

IV. Conclusion

In this paper, we examined the reliable mental tasks and the

location of EEG sensor to improve the performance of the

BCI system using fMRI experiments and data analysis. We

suggested the SMA as the suitable location for the BCI

system, which was based on imagining finger movements.

We mentioned that the proposed neurophysiological

approach is highly necessary in order to improve the

performance of the conventional BCI system, and also the

fMRI experiments were able to provide opportunities to

acquit reasonable answers to unsolved questions of the BCI

system. We were able to estimate the location of reliable

EEG sensors according to other proper mental tasks by using

fMRI equipment, especially the non body movement

imagination mental task, which is useful for the BCI system

but proper EEG sensor locations of this are unknown.

AcknowledgmentThis work was supported by the Korea Research Foundation

Grant funded by the Korea Government (MOEHRD).

(KRF-2005-202-D00459).

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Author Biographies

Sang Han Choi birth in Korea in 1979. He is in mastercourse in Kyungpook national university, electrical

engineering and computer science. His major field is

brain computer interface.

Minho Lee received the Ph.D. from Korea Advanced

Institute of Science and Technology in 1995, and iscurrently an associate professor of School of Electrical

Engineering and Computer Science, Kyungpook

National University, Taegu, Korea, and visiting scholar

in Dept. of Brain and Cognitive Science, Cambridge,MIT. His research interests include biologically inspired

vision systems, brain computer interface and intelligent

sensor systems. (Home page: http://abr.knu.ac.kr)