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Estimation of motor imaginary using fMRI experiment based EEG sensor location.



Abstract: Brain computer interface (BCI BCI Bat Conservation International
BCI Brain-Computer Interface
BCI Business Continuity Institute
BCI Business Cycle Indicators
BCI Banco de Credito e Inversiones (Chilean bank)
BCI Bell Canada International
) is based on brain activity. It controls a computer system by imagination or other mental activities. In order to improve the performance of the BCI system based on the scalp EEG EEG: see electroencephalography. , it is critical to get reliable EEG signals. In addition, it is important to minimize the noise and artifacts artifacts

see specimen artifacts.
 from EEG signals. In this paper, we focus on minimizing the artifacts besides maximizing brain activity information that is related with mental tasks obtained from EEG signals. To make EEG signals more informative, it is necessary to consider suitable mental tasks and the location of the EEG sensor. Using fMRI experiments, we found that the supplementary motor area The supplementary motor area (SMA) is a part of the sensorimotor cerebral cortex (perirolandic, i.e. on each side of the Rolando or central sulcus). It was included, on purely cytoarchitectonic arguments, in area 6 of Brodmann and the Vogts.  (SMA (1) See SMA connector.

(2) (Shared Memory Architecture) See shared video memory.

(3) (Software Maintenance Association) A membership organization that began in 1985 and ended in 1996.
) is activated whenever mental tasks include the imaginary of body movements. Based on this observation, we implement a primitive type In computer science, primitive types — as distinct from composite types — are data types provided by a programming language as basic building blocks. Primitive types are also known as built-in types or basic types.  of EEG based brain computer interface using linear discriminant analysis Linear discriminant analysis (LDA) and the related Fisher's linear discriminant are methods used in statistics and machine learning to find the linear combination of features which best separate two or more classes of objects or events.  (LDA (Local Delivery Agent) Software in a mail server that delivers mail to a local recipient. See messaging system. ).

Keywords: BCI, EEG, fMRI, SMA, LDA

I. Introduction

Brain computer interface (BCI) is a computer interface system, which is based on brain activity as determined by voluntary will. Using the BCI, we can control a computer system via imagination or other mental tasks. In our BCI research, we consider a BCI system, which is based on non-invasive EEG signals, and endogenous mental activity was used [1], [2]. In order to improve the performance of the BCI system, it is important to get reliable EEG signals. In order to get reliable EEG signals, noise and artifacts from EEG signals need to be removed. Noise can be removed by anti-electromagnetic or by enhancing amplifier performance or by other hardware-type methods. Also, the removal of artifacts means the illumination of brain activity element from EEG signal except for the brain activity elements, which are related with the specific mental tasks of the BCI system. In order to remove the artifacts, we need to determine mental tasks carefully. If an inappropriate mental task is used (for example, mental tasks which induce little distinct change in EEG signals feature), it is difficult to get meaningful EEG signals. After the mental tasks are determined, we need to find the proper location of the EEG sensor according to according to
prep.
1. As stated or indicated by; on the authority of: according to historians.

2. In keeping with: according to instructions.

3.
 the specific mental task. Brain activity, according to specific mental tasks, is considerably localized, and the location where we can expect the features of the EEG signal is probably also localized according to the specific mental tasks.

The conventional BCI researches are mainly focused on developing more plausible signal processing See DSP.  methods that can obtain more accurate EEG signals. These kinds of conventional BCI systems apply almost same approach for deciding mental tasks and locations of EEG sensors. Mental tasks for conventional BCI systems are generally imagination of body movements. The locations of EEG electrodes for conventional BCI systems are the motor sensory cortex sensory cortex
n.
The somatic sensory, auditory, visual, and olfactory regions of the cerebral cortex considered as a group.
 areas or whole the brain area based on 10-20 standard EEG electrode system [1], [2].

In order to make efficient and economic BCI system, we need to minimize the number of EEG sensors. When we set the location of EEG sensors, location is closely related with the mental task. The illumination of the artifacts, however, is very difficult, because we don't know Don't know (DK, DKed)

"Don't know the trade." A Street expression used whenever one party lacks knowledge of a trade or receives conflicting instructions from the other party.
 which the EEG signal is activated in accordance related with which specific mental task.

Our approach in solving this problem is using fMRI equipment. From fMRI, a higher level of spatial resolution (Data West Research Agency definition: see GIS glossary.) A measure of the accuracy or detail of a graphic display, expressed as dots per inch, pixels per line, lines per millimeter, etc. It is a measure of how fine an image is, usually expressed in dots per inch (dpi).  data of brain activity area can be achieved than that of an EEG signal. The fMRI equipment measures the blood oxygenation oxygenation /ox·y·gen·a·tion/ (ok?si-je-na´shun)
1. the act or process of adding oxygen.

2. the result of having oxygen added.
 level dependant (BOLD) signal [3], [4]. The BOLD signal represents the level of oxygen consumed by brain activity, according to a mental task. Otherwise, the EEG sensor signal is data, which measure the electrical activity of neurons in the brain. Thus, the physical property of the data is different. There are, however, many reports, which state that the relation of BOLD and the local field potential (LFP LFP left frontoposterior (position of the fetus). ) have an almost linear relationship [3]-[5]. 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 motor cortex
n.
The region of the cerebral cortex influencing movements of the face, neck and trunk, and arm and leg. Also called excitable area, motor area, Rolando's area.
 area and the posterior parietal cortex Noun 1. parietal cortex - that part of the cerebral cortex in either hemisphere of the brain lying below the crown of the head
parietal lobe

cerebral cortex, cerebral mantle, cortex, pallium - the layer of unmyelinated neurons (the grey matter) forming the
 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 BSRC Build Spacecraft Real-Time Command ) at the Korea Advanced Institute of Science & Technology (KAIST KAIST Korea Advanced Institute of Science and Technology ). 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 Gantry
A name for the couch or table used in a CT scan. The patient lies on the gantry while it slides into the x-ray scanner portion.

Mentioned in: Computed Tomography Scans
.

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 Parametric Mapping Statistical parametric mapping or SPM is a statistical technique for examining differences in brain activity recorded during functional neuroimaging experiments using neuroimaging technologies such as fMRI or PET.  (SPM SPM - Sequential Parlog Machine ) 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 Customizing software and documentation for a particular country. It includes the translation of menus and messages into the native spoken language as well as changes in the user interface to accommodate different alphabets and culture. See internationalization and l10n.  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 the mental 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 first line 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.

[FIGURES 1-2 OMITTED]

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 contralateral /con·tra·lat·er·al/ (-lat´er-al) pertaining to, situated on, or affecting the opposite side.

con·tra·lat·er·al
adj.
 characteristics concerning the mental tasks in our experiment.

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 ohm (ōm) [for G. S. Ohm], unit of electrical resistance, defined as the resistance in a circuit in which a potential difference of one volt creates a current of one ampere; hence, 1 ohm equals 1 volt/ampere. . 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 The primary motor cortex (or M1) works in association with pre-motor areas to plan and execute movements. M1 contains large neurons known as Betz cells which send long axons down the spinal cord to synapse onto alpha motor neurons which connect to the muscles.  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 dominant hemisphere
n.
The cerebral hemisphere that is more involved than the other in governing certain body functions, such as controlling the arm and leg used preferentially in skilled movements.
. 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 feature of the EEG data.

[FIGURE 3 OMITTED]

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

[FIGURE 4 OMITTED]

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 unipolar /uni·po·lar/ (u?ni-po´ler)
1. having a single pole or process, as a nerve cell.

2. pertaining to mood disorders in which only depressive episodes occur.
 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 neu·ro·phys·i·ol·o·gy  
n.
The branch of physiology that deals with the functions of the nervous system.



neu
 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 To set free, release or discharge as from an obligation, burden or accusation. To absolve one from an

obligation or a liability; or to legally certify the innocence of one charged with a crime.


acquit v.
 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.

Acknowledgment

This work was supported by the Korea Research Foundation The Korea Research Foundation is a grant organization supported by the South Korean Ministry of Culture and Tourism. It provides support for research into new theories for the advancement of science, the arts, and the Korean culture in general.  Grant funded by the Korea Government (MOEHRD). (KRF-2005-202-D00459).

References

[1] Wolpaw, R., Niels Birbaumer, Dennis, J., McFarland, Gert Pfurtscheller, Theresa, M., Vanughan. "Brain-Computer Interfaces for Communication and Control", Clinical Neurophysiology, Vol. 112, pp. 767-791, 2002

[2] Garcia, G. Direct brain-computer communication through scalp recorded EEG signal. Lausanne EPFL EPFL Ecole Polytechnique Fédérale de Lausanne (French: Swiss Federal Institute of Technology, Lausanne, Switzerland)
EPFL Enoch Pratt Free Library (Baltimore, Maryland)
EPFL European Professional Football Leagues
 Ph.D Thesis. 2004

[3] Niessing, J., Ralf A.W., Galuske, Boris Ebisch, Kerstin, E., Schmidt, Michael Niessing, Wolf Singer. "Hemodynamic he·mo·dy·nam·ics  
n. (used with a sing. verb)
The study of the forces involved in the circulation of blood.



he
 Signal Correlate Tightly with Synchronized Gamma Oscillation", Science, 309 (5736). pp. 941-948, 2005

[4] Sameer, A., Sheth, Masahito Nemoto, Michael Guiou, Melissa Walker, Nader Pouratian, Arthur W., Toga. "Linear and Nonlinear Relationships between Neuronal Activity Oxygen Metabolism and Hemodynamic Response hemodynamic response Cardiology Response of the circulatory system to stimuli such as exercise, emotional stress, etc ", Neuron, Vol. 42, pp. 347-355, 2004

[5] Nikos, K., Logothetis, Jon Pauls, Mark Augath, Torsten Trinath & Axel Oeltermann. "Neurophysiological Investigation of the Basis of the fMRI Signal", Nature, Vol. 412, 2001

[6] Christoph Mulert, Lorenz Jager, Robert Schmitt, Patrick Bussfeld, Olive Pogarell, Ulrech Hegerl. "Integration of fMRI and Simultaneous EEG: towards a Comprehensive Understanding of Localization and Time-course of Brain Activity in Target Detection", Neuroimage, Vol. 22, pp. 83-94, 2004

[7] Christoph M.Michel, Micah M,Murray, Goran Lantz, Sara Gonzalez, Laurent Spinelli, Rolando Grabe de Peralta. "EEG Source Imaging", Clinical Neurophysiology, Vol. 115, pp. 2195-2222, 2004

[8] Michael, S., Gazzaniga, Richard, B. ivry. George R. Mangun. Cognitive neuroscience, W.W. Norton .New York New York, state, United States
New York, Middle Atlantic state of the United States. It is bordered by Vermont, Massachusetts, Connecticut, and the Atlantic Ocean (E), New Jersey and Pennsylvania (S), Lakes Erie and Ontario and the Canadian province of
. London, New York, pp. 445-498, 2001

[9] Mark, F. Bear, Barry W. Connors, Micheal, A. Paradiso. Neuroscience exploring the brain, Lippincott Williams & Wilkins, Baltimore Maryland, pp. 43-44, 2000

[10] P. Dechent, K.-D., Merboldt, J. Frahm. "Is the Human Primary Motor Cortex Involved in Motor Imagery", Cognitive Brain Res, Vol. 19, pp. 138-144, 2004

Author Biographies

Sang Han Choi birth in Korea in 1979. He is in master course in Kyungpook national university History of Kyungpook National University
Kyungpook National University (KNU) was founded in the spirit of truth, pride, and service: pursuing truth through academic study; developing pride as a member of the University and future leader; and inspiring service towards the
, 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 This article reads like a news release, or is otherwise written in an overly promotional tone.
Please help [ rewrite this article] from a to be less promotional, per Wikipedia .
 in 1995, and is currently 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 MIT - Massachusetts Institute of Technology . His research interests include biologically inspired vision systems, brain computer interface and intelligent sensor systems. (Home page: http://abr.knu.ac.kr)

Sang Han Choi (1) and Minho Lee1, (2)

(1) School of Electrical Engineering and Computer Science, Kyungpook National University 1370 Sankyuk-Dong, Puk-Gu, Taegu 702-701, Korea shchoi@ee.knu.ac.kr, mholee@knu.ac.kr

(2) Department of Brain and Cognitive Science, Massachusetts Institute of Technology Massachusetts Institute of Technology, at Cambridge; coeducational; chartered 1861, opened 1865 in Boston, moved 1916. It has long been recognized as an outstanding technological institute and its Sloan School of Management has notable programs in business,  77 Massachusetts Avenue, Cambridge, MA 02139, USA mholee@mit.edu
Table 1. The hit rate of single channel EEG data which
distinguishes between an imagined left-finger motor imagery
condition state and right-finger motor imagery condition
state using LDA.

Reference   C3    C4

Pz          70%   90%
Cz          80%   80%
Fz          90%   90%
AFz         90%   90%
Ear lobe    60%   60%

Table 2. The hit rate of single-channel EEG data which
distinguishes between a conditional state and a state of rest
using LDA

Electrode location   Left ear   AFz

Pz                     79%      75%
Cz                     85%      75%
Fz                     81%      85%
AFz                    80%
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Title Annotation:Brain computer interface
Author:Choi, Sang Han; Lee, Minho
Publication:International Journal of Computational Intelligence Research
Geographic Code:1USA
Date:Jan 1, 2007
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