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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 56, NO. 10, OCTOBER 2009

Functional Imaging of Spinal Cord Electrical
Activity From Its Evoked Magnetic Field
Tomoya Sato∗ , Yoshiaki Adachi, Member, IEEE, Masaki Tomori, Senichi Ishii, Shigenori Kawabata,and Kensuke Sekihara, Fellow, IEEE

Abstract—This paper investigates dynamic source imaging of the
spinal cord electrophysiological activity from its evoked magnetic
field by applying the spatial filter version of standardized lowresolution brain electromagnetic tomography (sLORETA). Our
computer simulation shows that the sLORETA-based spatial filter
can reconstruct the four current sources typically associated withthe elicitation of the spinal cord evoked magnetic field (SCEF). The
results from animal experiments show that significant changes in
the latency and intensity of the reconstructed volume current arise
near the location of the artificial incomplete conduction block. The
results from the human SCEF show that the SCEF source imaging
can visualize the dynamics of the volume currents and other nerve
electrical activity propagating along the human spinal cord. Theseexperimental results demonstrate the potential of SCEF source
imaging as a future clinical tool for diagnosing cervical spinal corddisorders.
Index Terms—Biomagnetism, spatial filter, spinal cord conduction block, spinal cord evoked magnetic field (SCEF), standardized
low-resolution brain electromagnetic tomography (sLORETA).

I. INTRODUCTIONNERVE conduction block of the cervical spinal cord compressed by intervertebral disks and ligaments may cause
myelopathy (such as numbness and paralysis in the limbs). Suchspinal cord disorders are common, and the number of patients
suffering from these spinal cord disorders exceeds 400 000 in
Japan. Unfortunately, because compression and other spinal
cord abnormalities found on patient’s anatomical images (suchas MRI or X-ray images) do not always cause spinal cord disorders, there are no effective methods for accurate diagnosis ofspinal cord lesions except for the spinal cord evoked potential(SCEP) measurement [1]. The SCEP measurement can provide
functional information on the spinal cord electrical activity, andit has been used for detecting such spinal cord lesions.

A

Manuscript received December 15, 2008; revised April 20, 2009. Current
version published September 16, 2009. This work was supported by Ishikawa
High-Tech Sensing Technology Cluster, Ministry of Education, Culture, Sports,
Science and Technology, Japan. Asterisk indicates corresponding author.
∗ T. Sato is with the Department of Systems Design and Engineering,Tokyo Metropolitan University, Tokyo 191-0065, Japan (e-mail: sato.tomoya.
ieee@gmail.com).
Y. Adachi is with the Applied Electronics Laboratory, Kanazawa Institute ofTechnology, Kanazawa 921-1331, Japan.
M. Tomori, S. Ishii, and S. Kawabata are with the Department of Orthopedic
Surgery, Tokyo Medical and Dental University, Tokyo 113-8519, Japan.
K. Sekihara is with the Department of Systems Design and Engineering,Tokyo Metropolitan University, Tokyo 191-0065, Japan (e-mail: ksekiha@
cc.tmit.ac.jp).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TBME.2009.2025506

However, since the SCEP measurement requires inserting anelectrode array in the epidural space of a patient, it is a highly invasive diagnostic method [2]. Because highly skilled techniques
are needed for this electrode insertion, the SCEP measurement
actually has been implemented only at a limited number ofhospitals. Accordingly, there has been growing interest in developing biomagnetometers optimized for measuring the spinal
cord evoked magnetic field (SCEF), because the SCEF measurement can be carried out mostly noninvasively. A 105-channel
biomagnetometer system for human SCEF measurements has
been developed recently, and the detection of the SCEF fromhuman subjects has already been reported [3], [4].
In this paper, we investigate dynamic (spatio-temporal) source
imaging of the spinal cord electrophysiological activity from its
evoked magnetic field, aiming at developing a novel, noninvasive diagnostic tool for cervical spinal cord disorders. Here, weapply a spatial filter imaging algorithm based on standardized
low-resolution brain electromagnetic tomography (sLORETA),
which was originally developed for brain neuromagnetic source
imaging [5]. The sLORETA-based spatial filter is known to have
no localization bias and provide 3-D reconstruction of source
activities [6], [7].
In this paper, following the brief introduction of thesLORETA-based spatial filter algorithm, in Section III, we
present the results of a computer simulation that was conductedto check whether the sLORETA-based spatial filter can reconstruct four sources typically associated with the generation of
the SCEF. In Section IV, the spatial filter imaging is applied
to SCEF obtained in animal experiments where the animal has
an artificial incomplete conduction block of the spinal cord.
The results from these animal experiments show that significant
changes in the latency and intensity of the reconstructed volume current exist near the location of the artificial incomplete
conduction block.
In Section V, we apply the source imaging method to the
SCEF measured from a human subject. The results show that
the SCEF source imaging can visualize the dynamics of thevolume currents and other nerve electrical activities travelingalong the human spinal cord. The results of our animal andhuman experiments clearly indicate that SCEF source imaging
can be a promising tool for diagnosing cervical spinal corddisorders.
All experiments in this paper were performed at the Section of
Orthopedic Spinal Surgery of Tokyo Medical and Dental University. The animal experiments were performed with the approvalof the Tokyo Medical and Dental University Animal Care Committee. The human SCEF experiments were performed with the0018-9294/$26.00 © 2009 IEEE
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approval of the Ethics Committee of Tokyo Medical and Dental
University.
II. SLORETA IMAGING ALGORITHM
The sLORETA source reconstruction algorithm was originally proposed in [5]. Since we use its spatial filter modification,
the spatial filter version of the sLORETA algorithm is briefly
described here, although it was described in [6] and [7]. We
define the magnetic field measured by the mth sensor at time t
as bm (t). The entire magnetic measurement at t is expressed asa column vector b(t)b(t) = [b1 (t), b2 (t), . . . , bM (t)]T(1)

where M is the total number of sensors and the superscript T
represents the matrix transpose. The spatial location is represented by the 3-D vector r: r = (x, y, z). The source vector at
a location r is denoted bys(r, t) = [sx (r, t), sy (r, t), sz (r, t)]T .

(2)

We define the outputs of the mth sensor due to a unitmagnitude source at r, directed in the x-, y-, and z-direction, as
x
y
z
x
y
(r), lm(r), and lm(r), respectively. These lm(r), lm(r), andlmzlm (r) represent the sensitivity of the mth sensor to a source at r
directed in the x-, y-, and z-direction. The three column vectors
are denoted asx(r)]Tlx (r) = [l1x (r), l2x (r), . . . , lM

(3)yly (r) = [l1y (r), l2y (r), . . . , lM
(r)]T

(4)

z
lz (r) = [l1z (r), l2z (r), . . . , lM(r)]T .

(5)

The lead-field matrix, which represents the sensitivity of thewhole sensor array at r, is defined as
L(r) = [lx (r), ly (r), lz (r)].

(6)

The spatial filter reconstructs the source vector at r usingŝ(r, t) = W T (r)b(t)(7)

where ŝ(r, t) is the reconstructed source vector and the matrix
W (r) is a set of spatial filter weights. The sLORETA filter uses
the weights defined in [6] and [7]W (r) = G−1 L(r)[LT (r)G−1 L(r)]−1/2
where G is the gram matrix defined as

G = L(r)LT (r)dr.

Fig. 1. Schematic illustration of the electrical currents and magnetic field
associated with the generation of the SCEF. The halved tube is a model of thenerve axon. The two filled arrows in the axon represent the leading and trailing
dipoles traveling in the axon. The other two arrows perpendicular to the axon
represent volume currents flowing into the axon.

(8)

(9)

In our investigations, when computing the lead-field matrix
L(r), we do not assume any kind of conductor models, anduse the Biot–Savart law, which is derived using the quasi-static
approximation of the Maxwell equations [8], [9]. Therefore, theoutput of the spatial filter in (7) is the density of the total current including both the impressed and volume currents.1 Also
note that the spatial filter version of sLORETA is mathematically equivalent to its original tomographic imaging version,
1 Strictly speaking, the output of the sLORETA-based spatial filter is a standardized form of the total current density.

and both versions give exactly the same results. The use of thespatial filter version in our investigation was primarily due toour convenience in the software development.
III. COMPUTER SIMULATIONThe electrophysiological sources propagating in the nerveaxon are known to consist of two antidirectional current dipoles[10], which are referred to as the leading and the trailing dipoles[11], [12]. In addition to these two dipole sources, volume currents associated with these dipole sources also produce magnetic
fields. The volume current flows from the extracellular milieu
to the site between the two dipole sources in the nerve axon,
and its direction is perpendicular to the nerve axon. Therefore,
we use a source model consisting of four equi-intensity current
vectors to express the SCEF sources. These four sources travelwith fixed intensity along the nerve axon in the direction of the
propagation. They are schematically illustrated in Fig. 1. In the
figure, the leading dipole has a direction parallel to the propagation direction, and the trailing dipole has a direction opposite to
the propagating direction. Computer simulation was performed
to check whether the sLORETA imaging method could resolvethese four sources in a realistic measurement condition.
Simulated data at a single time point are generated. The four
sources are assumed to exist on a plane located 20 mm below the sensor array, and this plane is defined as z = 0 cm.
The coordinates and the orientations of these four sources are
given in Table I. The first and the second sources are locatedon the line x = −10 mm. Since the propagation direction isassumed to be the positive y-direction, the first source represents the leading dipole and the second source represents thetrailing dipole. The third and fourth sources, located on the liney = 25 mm, represent the volume currents. We assume the same
sensor array as the one used in the animal experiments describedin the next section. Here, the sensors are vector sensors, which
detect the magnetic field in the three orthogonal field directions.
The magnetic field from these four sources was computed using
the Biot–Savart law [8], [9]. The contour plots of the generated

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TABLE 1
COORDINATES AND ORIENTATIONS OF FOUR SOURCES USED IN COMPUTERSIMULATION

Fig. 2. Contour plots of the magnetic field generated by the source model
shown in Fig. 1, which consists of four current sources. (a) x component of themagnetic field. (b) y component of the magnetic field. (c) z components of themagnetic field. The cross marks indicate the locations of the four sources. The
field intensity is color-coded according to the color bar.

magnetic field are shown in Fig. 2(a)–(c), where (a), (b), and(c), respectively, represent the x, y, and z components of themagnetic field.
The source reconstruction was performed using thesLORETA-based spatial filter described in the preceding section. The reconstruction region is defined as −55 ≤ x ≤38, −10 ≤ y ≤ 60, and −15 ≤ z ≤ 5 mm. The gram matrix
was first computed by integrating the sensor lead field in thisregion using (9). The source vector was then estimated using (7)and (8). The results of the 3-D source reconstruction are shownin Fig. 3(a)–(c). Fig. 3(a) shows the magnitude distribution of
the source vector on the plane z = 0 mm. The distribution on
the plane x = −10 mm is shown in Fig. 3(b). The distribution
on the plane y = 25 mm is shown in Fig. 3(c). In these results,
the positions of maximum intensity of the reconstructed sources
are in good agreement with their assumed locations, indicatingthat the four sources are reconstructed at the correct locations.
These results show that the sLORETA method is capable ofreconstructing four sources typically associated with the spinal
cord electrophysiological activity.
IV. ANIMAL EXPERIMENTS
A. SCEF Measurement
sLORETA imaging was then applied to the SCEF measured
from an anesthetized rabbit. A catheter with a balloon tip wasinserted into the cervical epidural space, and the cervical spinal
cord was artificially compressed by inflating the balloon to makean artificial incomplete conduction block between the fifth cervical vertebra (C5) and the sixth cervical vertebra (C6). The
experimental setup is shown in Fig. 4 in which an X-ray image

capturing the subject and the sensors is shown together withthe location of the artificial conduction block and the reconstruction region. A 24-channel biomagnetometer equipped with
vector sensors was used for measuring the cervical SCEF [13].
As shown in Fig. 4, the sensor array was positioned over theneck of the subject.
The sensor array, arranged in a 2 × 4 matrix structure, cansimultaneously measure eight spatial locations, and its coverage
is a 6 × 2 cm region. In these experiments, the position of thesensor array was changed over the cervix ten times to increase
the observation area and the density of the observation site.
Finally, the magnetic signals were acquired from 64 sites at
sensor intervals of 7 and 11 mm in the x- and y-direction,
respectively. The data were acquired with a sampling frequencyof 40 kHz, and an analog bandpass filter with a bandwidth of
100–5000 Hz was applied. The electrical stimulus was delivered
to the spinal cord at the level of the lower thoracic spine using
an epidural catheter electrode. A stimulus of 0.03 ms durationand intensity of 5 mA was repeated 3000 times with a repetitioninterval of 100 ms. The signal was averaged across these 3000
measured trials. We conducted the SCEF measurements twice:once before and once after the artificial incomplete conduction
block was induced.
The averaged SCEF recordings are shown in Fig. 5 in which
all sensor recordings are displayed, in overlapped fashion.
Fig. 5(a) and (b) shows the SCEF waveforms measured before
and after the conduction block was made. The electrical stimulus was given at a latency of 0 ms. In Fig. 5, the artifacts causedby the electrical stimulus are observed between 0 and 1 ms ofthe measured waveforms. In these waveforms, peaks existing
after a latency of 1.7 ms are considered to the SCEF signals
caused by the stimulus. Comparing the waveforms in Fig. 5(a)with those in Fig. 5(b), one can observe that the amplitudes ofthe peaks around 3 ms of the latency are significantly reduced inFig. 5(b). This reduction of the waveform amplitudes is causedby the conduction block and corresponds to the reduction of thevolume current intensity, which is argued later.
The measured contour maps of the SCEF at 2.5 ms, as indicated by the broken line in Fig. 5(b), are shown in Fig. 6. The
x and y components of the magnetic field, which are tangential
to the body surface, are shown in Fig. 6(a) and (b), and the z
component of the magnetic field, which is radial to the bodysurface, is shown in Fig. 6(c). Note that these contour maps
are similar to those of the magnetic fields in Fig. 3(a)–(c), andthis similarity validates our source model used in the computer
simulation.
B. Source Reconstruction Experiments
The source reconstruction was performed in the 3-D region including the subject’s spinal cord. In Fig. 4, the dottedsquare indicates the reconstruction region, which consists of
16 × 16 × 16 voxels. We applied the sLORETA-based spatial
filter to the measured SCEF datasets. The source reconstruction
results obtained from the SCEF measured after the conduction
block was induced are shown in Fig. 7. Here, results at a latency of 2.5 ms were overlaid onto the subject’s X-ray image. In
this figure, the relative magnitude of the reconstructed sources

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Fig. 3. Results of reconstructing the simulated spinal cord sources using the sLORETA-based spatial filter. (a) Source magnitude distribution on the x–y plane(z = 0 mm), on which all the four sources exist. (b) Source magnitude distribution on the y–z plane (x = −10 mm), on which the first and second sources exist.
(c) Source magnitude distribution on the x–z plane (y = 25 mm), on which the third and fourth sources exist. The cross marks represent the source locations. The
relative source intensity is color-coded according to the color bar.

Fig. 4. Animal experiment setup. An X-ray image of the subject and thesensors is shown. The reconstruction region is indicated by the dotted square.
The artificial incomplete conduction block was made between the fifth cervicalvertebra (C5) and the sixth cervical vertebra (C6). The electrical stimulus wasgiven to the subject’s spinal cord at the level of the lower thoracic spine asindicated by the arrow.

Fig. 6. Measured contour maps of the SCEF at the latency of 2.5 ms indicatedby the vertical broken line in Fig. 5. (a) x component of the magnetic field.
(b) y component of the magnetic field. (c) z component of the magnetic field.
The field intensity is color-coded according to the color bar. The x and ycomponents are tangential to the body surface and the z component is normal
to the body surface.

Fig. 7. Results of 3-D reconstruction of the SCEF sources at the latency of
2.5 ms. The results are overlaid onto the subject’s X-ray image on which theoutline of the subject’s spine is superimposed. (a) Source distribution on an x–yplane containing the maximum source activity. (b) Source distribution on a y–z
plane containing the maximum source activity. The relative source intensity iscolor-coded according to the color bar. The arrow indicates the source direction
at each voxel. The positive y-direction and the negative y-direction are thecranial and caudal directions, respectively.

Fig. 5. Sensor recordings of the SCEF obtained in the animal experiments.
(a) Recordings taken before the conduction block was induced. (b) Recordings
taken after the conduction block was induced. The electrical stimulus was given
at a latency of 0 ms. The large magnetic fields between the latencies of 0 and
1 ms are considered artifacts caused by the electrical stimulus, and the peaks
after the latency of 1.7 ms are considered to represent the SCEF signals causedby the stimulus.

is color-coded. The arrow represents the direction of a reconstructed source at each voxel, and its length is proportional to therelative magnitude of the source vector. In these experiments,
we reconstructed the x, y, and z components of the source current vector, and the color-coded intensity was obtained using
these three components.

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Fig. 8. Reconstructed source distributions on an x–y plane at latencies from 2.1 to 2.9 ms. The outline of the subject’s spine is superimposed. The displayedplane is selected as the one that contains the maximum source activity. The artificial incomplete conduction block is located at approximately y = 30 mm. The
positive y-direction and the negative y-direction are the cranial and the caudal directions, respectively. The relative source intensity is color-coded according to
the color bar. The arrow indicates the source direction at each voxel.

The outline of the subject’s spine is superimposed onto the
X-ray image. In Fig. 7(a), the results on an x–y plane are displayed with the displayed plane chosen as the one that contained
the maximum source activity. The results on a y–z plane areshown in Fig. 7(b), and the displayed y–z plane was selected in
the same manner. The localized source near (−10, 40, 170) mm
can be interpreted as the leading dipole. The trailing dipole isobserved near (−10, 5, 165) mm.
Note that, when computing the lead field, we do not use any
kind of conductor models, but rather use the formula from the
Biot–Savart law, as mentioned previously. Thus, the total current
including the volume current is reconstructed as the output of thespatial filter. The two localized sources whose y coordinates are
between 10 and 20 mm can be interpreted as the volume currents.
The reconstructed source distributions after the blocking in thex–y plane at latencies from 2.1 to 2.9 ms are shown in Fig. 8.
In these results, the movement of the sources along the spinal
cord toward the subject’s head can be observed.
To estimate the temporal change in the intensity of the volume
current before and after the block was induced, the time courses
at ten selected voxels along the line x = 14 mm are plotted. The
choice of the line x = 14 mm is due to the fact that the maxima
of the volume currents travel along this line. These voxels arelabeled “A” to “J.” The locations and the time courses of thesevoxels are shown in Fig. 9. Fig. 9(a) and (b) represents the timecourses before and after the conduction block was given, respectively. In Fig. 9(a), each time course has a clear peak indicatedby an arrow. The latencies of these peaks indicate the instants
when the volume current arrived at these voxel locations. On
the contrary, in Fig. 9(b), the peaks of the time courses from

Fig. 9. Time courses of reconstructed source intensity at voxels labeled “A” to“J.” (a) Time courses before the conduction block was induced. (b) Time courses
after the conduction block was induced. The artificial incomplete conduction
block is located between the voxels labeled “D” and “E.” The arrow indicates thelocation of the peak in each time course. The latency of the peak is considered
to represent the time when the volume current arrives at that voxel location.
The intensity of the peak is considered to represent the intensity of the volume
current at that voxel location.

the voxel “G” to “A” become blurred and their amplitudes arelower compared to the corresponding time courses in Fig. 9(a).
The latency of the peaks as well as the intensity of the peaks
in Fig. 9(b) is plotted with respect to the y coordinate of thesevoxels. The results are shown in Fig. 10. The solid circles withbroken lines represent the intensity of the peaks, and the open
circles with solid lines indicate the latency of the peaks. Note

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Fig. 10. Latencies and intensities of the peaks in Fig. 9(b) plotted with respect
to the y coordinate of the voxels. The plots with the open and solid circles,
respectively, show the latency and intensity changes with regard to the voxel ycoordinates. The artificial incomplete conduction block is located between thevoxels labeled “D” and “E.”that the artificial incomplete block is located at a position withy approximately equal to 30 mm; the position is between voxel“D” and voxel “E.” In the latency plot, there is a clear discontinuity between voxel “D” and voxel “E.” Also, the intensity
significantly decreases between voxel “G” and voxel “D.” These
results show that significant changes in the latency and intensityof the volume current arise near the location of the incomplete
block, and this fact indicates that imaging of the volume current can be a useful tool for diagnosing such spinal cord disorders. Note that similar results can be obtained from the volume
currents existing on the opposite side. Also note that we haveconducted nine cases of the same animal experiment, and in allcases we have obtained results similar to the representative ones
shown in this section.

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Fig. 11. Schematic view of the human SCEF measurement. An electrical stimulus was applied to the subject’s spinal cord at the level of the lower thoracic
spine using an epidural catheter-type electrode. The 105-channel biomagnetometer was positioned above the subject’s neck.

Fig. 12. Sensor recordings of the SCEF from a human subject. The electricalstimulus was given at the latency of 0 ms, and the large magnetic fields between
the latencies of 0 and 3 ms are considered stimulus artifacts. The peaks after thelatency of 3 ms are considered to represent the SCEF signals corresponding to
the electrical stimulus.

V. HUMAN SCEF SOURCE IMAGING
Spatial filter imaging was applied to the SCEF of a 60-yearold female patient. Although the patient has an atlant-axial subluxation with myelopathy, other parts of her cervical spinal
cord were shown to be normal by neurological and image diagnoses. The newly developed 105-channel biomagnetometer wasused for measuring the human SCEF [3]. This biomagnetometer is equipped with 35 vector sensors, which are arranged at
7 × 5 measurement locations covering an 8 × 9 cm area. The
experimental setup is schematically shown in Fig. 11.
A stimulus current with intensity of 4 mA and 0.3 ms duration
was applied to the subject’s spinal cord at the level of the lower
thoracic spine using an epidural catheter-type electrode, and thestimulus was repeated 4000 times at a repetition rate of 20 Hz,
with the sampling frequency set to 40 kHz. An analog bandpass
filter with a bandwidth of 500–5000 Hz was applied during thedata acquisition, and the averaged signal was digitally low-passfiltered with a cutoff frequency of 1.9 kHz. The signal was averaged across the 4000 measured trials. The averaged recordingsof the human SCEF are shown in Fig. 12. The latency of 0 ms

indicates the time of stimulus application. The peaks after about
3 ms are considered to represent the human SCEF signals causedby the stimulus, while the peaks before about 3 ms are considered stimulus artifacts.
The reconstruction area, indicated by the square in Fig. 11,
consists of 16 × 16 × 4 voxels. The voxel intervals are 7.5, 9.5,
and 5 mm in the x-, y-, and z-direction, respectively. The reconstructed source distributions on an x–y plane at three latencies
from 4.4 to 4.8 ms are shown in Fig. 13. In these results, we
can observe the leading and trailing dipoles, as well as the twovolume currents propagating toward the subject’s head. The
source reconstruction results are similar to those of the animal
experiments in Fig. 7, and these results show that sLORETAbased imaging can reconstruct the primary and volume currents
propagating along the human spinal cord.
VI. DISCUSSION AND SUMMARY
Several investigations have been reported regarding the detection of the magnetic signals from brachial nerves and nerve

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Fig. 13. Reconstructed source distributions on an x–y plane at three latencies from 4.4 to 4.8 ms. The displayed plane was selected as the one that contained
the maximum source activity. The relative source intensity is color-coded according to the color bar. The arrow indicates the source direction at each voxel. The
positive y-direction and the negative y-direction are the cranial and caudal directions, respectively.

Fig. 14. Estimated y coordinates of the leading and trailing dipoles at each latency. The open circles represent the y coordinate of the leading dipole and thesolid circles represent the y coordinate of the trailing dipole. The artificial incomplete conduction block is located at the position with y approximately equal to
30 mm. The small discrepancies existing around 2.2 and 3.2 ms are due to either the switch from the single- to dual-dipole searches or vice versa.

root at the cervix [14]–[16]. In these investigations, the single dipole localization method was applied with the half-spacevolume conductor model [9], and the successful localizationof the current dipole along the stimulated nerve fibers was reported [15], [16]. The previous investigations [11], [12] used thedipole localization method applied to the magnetic field generated from rabbits’ isolated nerves. In [12], the rabbits’ nerves
were electrically stimulated in a chamber containing Ringer’s
solution, and evoked compound action magnetic fields wererecorded before and after the incomplete conduction block was
introduced by using a vascular clip. The position of the clip was
estimated from the conduction velocity changes of the leading dipole. Here, the dipole velocity was estimated by applying
the dual-dipole localization to the magnetic field created by theleading and trailing dipoles.
Therefore, in our animal experiments, we first applied thedipole localization method to check whether the incomplete
conduction block can be localized. The locations of the leading
and the trailing dipoles were estimated through the dual-dipole
search. Here, the infinite half-space conductor model [9] wasused for the forward calculation. The estimated y coordinatesof the leading and the trailing dipoles with respect to time areshown in Fig. 14. In this figure, the white circles represent the ycoordinate of the leading dipole and the black circles represent
those of the trailing dipole. Here, the positive y-direction andthe negative y-direction indicate the cranial and caudal directions, respectively. The artificial incomplete conduction block
is located at the position with y approximately equal to 30 mm.
As seen in this figure, no significant changes of the conduction
velocities of the leading and the trailing dipoles exist at thelocation of the artificial incomplete conduction block.
In our investigation, we have applied the sLORETA-based
spatial filter for imaging the dynamics of human spinal cord
electrophysiological activity associated with the SCEF. It shouldbe emphasized that neither specific source model nor the volume conductor model is assumed. Therefore, the spatial filter
imaging can visualize the volume current associated with theleading and the trailing dipoles. The primary finding in our animal experiments is that the changes in the conduction velocity
and in the intensity of the volume current can detect the location

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of the incomplete conduction block. Thus, the visualization of
the volume current by using the spatial filter is potentially usefulfor diagnosing spinal cord disorders.
These volume current sources may also be detected by a multidipole search method. The problem of the dipole search method,
however, is the need to specify the number of dipoles. In the caseof our SCEF measurements, only at relatively few time points,
the sensor field maps show typical dipole or quadrupole field
patterns such as the one shown in Fig. 2. Most often, the sensor maps show some intermediate patterns different from thesetypical field patterns. Therefore, if we apply the dipole searchmethod, we have to select the number of dipoles at each time
point, either by visual inspection or by developing other methods to select the number of sources. Our spatial filter imaging
does not require determining the number of sources. Moreover,it does not use a high-dimensional search such as that used in
multidipole search methods, and it is easier to implement.
We are now investigating the clinical relevance of the proposed SCEF imaging, and more than 100 patients have participated in the study. The results from these patients are now
under careful evaluation, and the results of this evaluation will
be published in an appropriate clinical journal in near future.
The method of applying an electrical stimulus to a patient in
Section V requires surgical procedures to insert an epiduralelectrode proximal to the lower thoracic spine of a patient. Thisis a fairly invasive method. We have explored the possibility ofimaging spinal cord activity from the SCEF evoked by median
nerve stimulation, which is virtually noninvasive. Results of thisinvestigation will also be published in the future.

2459[11] Y. Fukuoka, H. Komori, S. Kawabata, H. Ohkubo, K. Shinomiya, andO. Terasaki, “Imaging of neural conduction block by neuromagnetic
recording,” Clin. Neurophysiol., vol. 113, pp. 1985–1992, 2002.
[12] Y. Fukuoka, H. Komori, S. Kawabata, H. Ohkubo, and K. Shinomiya, “Visualization of incomplete conduction block by neuromagnetic recording,”
Clin. Neurophysiol., vol. 115, pp. 2113–2122, 2004.
[13] Y. Adachi, G. Uehara, J. Kawai, S. Kawabata, H. Okubo, H. Komori,and H. Kado, “A SQUID biomagnetometer system for measurement of
spinal cord evoked magnetic fields,” Supercond. Sci. Technol., vol. 14,
pp. 1075–1080, 2001.
[14] I. Hashimoto, T. Mashiko, T. Mizuta, T. Imada, Y. Iwase, and H. Okazaki,“Visualization of a moving quadrupole with magnetic measurements ofperipheral nerve action fields,” Electroencephalogr. Clin. Neurophysiol.,vol. 72, pp. 277–280, 1989.
[15] B.-M. Mackert, M. Burghoff, L.-H. Hiss, M. Nordahn, P. Marx, L. Trahms,
and G. Curio, “Magnetoneurography of evoked compound action currents
in human cervical nerve roots,” Clin. Neurophysiol., vol. 112, pp. 330–
335, 2001.
[16] B.-M. Mackert, M. Burghoff, L.-H. Hiss, M. Nordahn, L. Trahms, andG. Curio, “Non-invasive magnetoneurography for 3D-monitoring of human compound action current propagation in deep brachial plexus,” Neurosci. Lett., vol. 289, pp. 33–36, 2000.

Tomoya Sato received the B.E. degree from Tokyo
Metropolitan Institute of Technology, Tokyo, Japan,
in 2007, and the M.E. degree from Tokyo Metropolitan University, Tokyo, in 2009.
He is currently with the Department of Systems
Design and Engineering, Tokyo Metropolitan University. His current research interests include the neuromagnetic source imaging and the reconstruction
methods, especially their application to functional
imaging of the spinal cord electrical activity.
Mr. Sato received the Young Investigator Award
from the International Conference on Biomagnetism in 2008, Sapporo, Japan.
He is a member of the Japan Biomagnetism and Biomagnetics Society.

REFERENCES[1] K. Shinomiya, K. Furuya, R. Sato, A. Okamoto, Y. Kurosa, and M.
Fuchioka, “Electrophysiologic diagnosis of cervical OPLL myelopathy
using evoked spinal cord potentials,” Spine, vol. 13, pp. 1225–1233,
1998.
[2] S. Kawabata, H. Komori, K. Mochida, H. Ohkubo, and K. Shinomiya, “Visualization of conductive spinal cord activity using a bio-magnetometer,”Spine, vol. 27, pp. 475–479, 2003.
[3] Y. Adachi, J. Kawai, M. Miyamoto, G. Uehara, S. Kawabata, M. Tomori,
S. Ishii, and T. Sato, “A 105-ch squid magnetometer system for humancervical spinal cord evoked magnetic field measurement,” in Proc. 16th Int.
Conf. Biomagn., R. Kakigi, Y. Yokosawa, and S. Kuriki, Eds. Sapporo,
Japan: Hokkaido Univ. Press, 2008, pp. 24–26.
[4] Y. Adachi, J. Kawai, G. Uehara, H. Ogata, M. Miyamoto, S. Kawabata,and S. Tomizawa, “A SQUID biomagnetometer system for measurementof a human cervical spinal cord evoked field,” Supercond. Sci. Technol.,vol. 18, pp. 303–307, 2005.
[5] R. D. Pascual-Marqui, “Standardized low resolution brain electromagnetic
tomography (sLORETA): Technical details,” Methods Find. Exp. Clin.
Pharmacol., vol. 24, pp. 5–12, 2002.
[6] K. Sekihara, M. Sahani, and S. S. Nagarajan, “Location bias and spatial
resolution of adaptive and non-adaptive spatial filters for MEG sourcereconstruction,” NeuroImage, vol. 25, pp. 1056–1067, 2005.
[7] K. Sekihara and S. S. Nagarajan, Adaptive Spatial Filters for Electromagnetic Brain Imaging. Berlin, Germany: Springer-Verlag, 2008.
[8] J. C. Mosher, R. M. Leahy, and P. S. Lewis, “EEG and MEG: Forward
solutions for inverse methods,” IEEE Trans. Biomed. Eng., vol. 46, no. 3,
pp. 245–259, Mar. 1999.
[9] J. Sarvas, “Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem,” Phys. Med. Biol., vol. 32, pp. 11–22, 1987.
[10] J. P. Wikso, “Biomagnetic sources and their models,” in Advances in Biomagnetism. S. J. Williamson and L. Kaufman, Eds. New York: Plenum,
1989, pp. 1–18.

Yoshiaki Adachi (M’99) received the M.E. and Ph.D.
degrees from Osaka University, Osaka, Japan, in 1994
and 2007, respectively.
From 1994 to 1997, he was involved in the fieldof magnetoencephalogram (MEG) measurement with
the Electrotechnical Laboratory, Ministry of International Trade and Industry (MITI), Japan. Since 1998,
he has been engaged in research and developmentof the superconducting quantum interference devices(SQUID) and other magnetic flux sensors, their applications, and signal processing at the Applied Electronics Laboratory, Kanazawa Institute of Technology, Kanazawa, Japan.
Dr. Adachi is a member of the Institute of Electrical Engineering of Japanand the Japan Biomagnetism and Biomagnetics Society.

Masaki Tomori received the Bachelor’s degree from
Tokyo Medical and Dental University, Tokyo, Japan,
in 2001.
Since 2005, he has been a Graduate Student at
Tokyo Medical and Dental University, where he iscurrently a Medical Doctor and specializes in orthopedics. His current research interests include the neuromagnetic imaging of spinal cord function.

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 56, NO. 10, OCTOBER 2009

Senichi Ishii received the Bachelor’s degree from
Tokyo Medical and Dental University, Tokyo, Japan,
in 2001.
Since 2005, he has been a Graduate Student at
Tokyo Medical and Dental University, where he iscurrently a Medical Doctor and specializes in orthopedics. His current research interests include theneuromagnetic imaging of spinal cord and peripheral
nerve function.

Shigenori Kawabata received the Bachelor’s degreefrom Tokyo Medical and Dental University, Tokyo,
Japan, in 1993, and the Ph.D. degree from the Graduate School, Tokyo Medical and Dental University,
in 2002.
Since 2003, he has been with the University Hospital of Medicine, Tokyo Medical and Dental University, where he is currently an Assistant Professor at the Section of Orthopaedic Surgery, Graduate School. His current research interests include
the spine surgery and the evaluation of spinal cord

Kensuke Sekihara (M’88–SM’06–F’09) received
the M.S. degree and the Ph.D. degree from Tokyo
Institute of Technology, Tokyo, Japan, in 1976 and1987, respectively.
From 1976 to 2000, he was with the Central Research Laboratory, Hitachi, Ltd., Tokyo, Japan. From1985 to 1986, he was a Visiting Research Scientist
at Stanford University, Stanford, CA. From 1991 to
1992, he was a Visiting Research Scientist at Basic
Development, Siemens Medical Engineering, Erlangen, Germany. From 1996 to 2000, he was involved
with the “Mind Articulation” Research Project sponsored by Japan Science andTechnology Corporation. He is currently a Professor with the Department of
Systems Design and Engineering, Tokyo Metropolitan University, Tokyo. His
current research interests include the electromagnetic source imaging, reconstruction and inverse methods, multidimensional signal processing, and statistical signal processing, especially their application to functional source imaging.
He is the author of a book Adaptive Spatial Filters for Electromagnetic Brain
Imaging (Springer-Verlag, 2008).
Dr. Sekihara is a member of the IEEE Medicine and Biology Society and theIEEE Signal Processing Society. Dr. Sekihara is a Fellow of the International
Society of Functional Source Imaging (ISFSI).

function.

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