Download quality of in vivo electrical measurements inside an mri magnet

QUALITY OF IN VIVO ELECTRICAL MEASUREMENTS
INSIDE AN MRI MAGNET
Joanna Tuppurainen1,*, Jarno M. A. Tanskanen1,2, and Markku Penttonen1,†
1 Cognitive
Neurobiology Laboratory, Department of Neurobiology
2 Department of Biomedical NMR
A. I. Virtanen Institute for Molecular Sciences, University of Kuopio,
P.O. Box 1627, FIN-70211 Kuopio, FINLAND
*
[email protected], [email protected], †[email protected]
ABSTRACT
In this study, we investigate the quality of in vivo electrical measurements, i.e., field potentials within a living
brain and electrocardiogram, from a subject (rat) in the
static magnetic field of a magnetic resonance imagining
(MRI) equipment. Generally, such a magnetic field is
known to introduce measurement errors. The presented
evaluation is a prerequisite for all our later research involving simultaneous electrical measurements and functional MRI. The in-magnet measurements are adequate
for event identification (e.g., heart beat registration),
animal status monitoring, triggering of external stimulation and fMRI, and brain oscillation frequency analysis.
1. INTRODUCTION
Neuronal network oscillations are characteristics of the
nervous system. Both the neuronal cell membrane properties and synaptic connections contribute to the generation of oscillations at the single cell and network levels.
In the awake state, oscillations contribute at least to sensory perception, movement, and learning. During sleep,
oscillations may be important for keeping the brain in a
state of readiness for an unexpected awakening and for
converting during awake state acquired short-term
memories to permanent ones [1].
Several forms of oscillations are present in the hippocampus [2]. Theta (4-8 Hz) and gamma oscillation (3070 Hz) (Figure 1) are present during active interaction
with the environment and thus may be related to the acquisition of new information. During sleep, fast oscillations (100-200 Hz) occur irregularly as short bursts.
They may be involved in the transfer of memories to the
cerebral cortex. Also slow oscillation (0.4-1 Hz) and
very slow (0.01-0.06 Hz) oscillation are prominent [3],
but their behavioral significance is not known.
Oscillations also contribute to abnormal states of
brain activity. For example, slow sleep oscillations may
gradually transform into epileptic seizures in the cortex
[1]. Moreover, hippocampus shows severe pathology after epileptic seizures.
In search for knowledge of the basic functioning of
the brain, new brain diagnostic tools, and cures for certain brain disorders, such as epilepsy, several measurement and imagining methods are in everyday use [4,5,6].
Electrophysiological measurements have been used
as a straightforward indicator of neuronal activation and
inactivation in the brain. Electroencephalogram (EEG) is
measured on intact skin of the rat’s head, and field potentials (FP) from extracellular space within the brain tissue.
The anatomy of the hippocampus is simple [7], which
makes it easier to perform FP measurements in the hippocampus than in the cerebral cortex.
Neuronal activation maps acquired with functional
magnetic resonance imaging (fMRI) represent regional
changes in blood volume, blood flow, and oxygenation.
Neuronal activity increases both blood flow and blood
volume in close vicinity of the activated area, which
causes measurable changes in the MRI signal.
Blood-oxygenation-dependent (BOLD) fMRI [6,8]
has been widely applied [5,6] for mapping of brain activity, research on basic brain functionality, and for the diagnostics of deficient brain functioning. Even tough it is
likely that there is a tight coupling between neuronal activity and vascular responses [9], the relation of neural
activation and BOLD response is not exactly known
[10]. BOLD response is expected to be only a few percents. Changes of this magnitude, however, are known to
be consistently detectable [11].
Functional imaging is commonly applied in diagnosis
and treatment of epilepsy [12]. During fMRI, subject’s
status can be observed via EEG measurements, which
can be used to initiate MRI at the onset of an epileptic
seizure. These measurements can further be combined
with FP measurements directly from the living epileptic
brain with a single or multichannel recording electrode
inserted into the brain structure of interest.
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Figure 1. Typical theta (3.5 Hz, left) and low frequency (0.7 Hz, middle) oscillations measured from the hippocampus of an anesthetized rat inside an MRI magnet. Gamma oscillations (37 Hz) modulated by a carrier oscillation of 2 Hz are shown on the right.
Our goal is to study oscillations and epilepsy with
simultaneous fMRI and FP measurements directly from a
living brain of a rat. We aim to combine BOLD and FP
measurements in order to better understand the relation
between BOLD response and the underlying electrical
activity. A combined FP measurement and MRI experiment in rat is presented in [13]. In addition, EEGs and
electrocardiograms (ECG) may be utilized for triggering
of external stimulation and fMRI, and in-magnet subject
monitoring.
MRI provides non-invasive high spatial resolution
anatomical images of a rat brain (e.g., a 3 cm x 3 cm
slice, 1.5 mm thick, imaged with 512 x 512 pixels) at the
rate of one image in a few minutes. Low resolution functional brain images (e.g., same slice with 64 x 32 pixels)
are acquired at the rate of one image per 100 ms.
Both FP and EEG techniques have the same high
time resolution (e.g., sampling rate 200 Hz – 12.5 kHz),
but FP yields better spatial localization, since only a limited number of neural cells in the vicinity of the tip of the
measurement electrode contributes to the signal, while
EEG reflects electrical activity of a relatively large cortical area. FP measurements can thus be correlated both
spatially and temporally with the MRI images.
The analysis presented in this study is a critical part
of the preparation for the work outlined above. Inmagnet electrical measurements cannot be analyzed
without clear knowledge of the effects of the static magnetic field on the electrical measurements. This work
also dictates what kind of signal analysis can be done
online with MRI imaging, and to which extent the measured signals must be post-processed in order to account
for disturbances, and further, if some of the planned
analyses are prohibited by the disturbances.
2. MEASUREMENT SYSTEM
2.1. Animal Preparation
We conducted these experiments on six male Kuopio
Wistar rats (460 g – 580 g) anesthetized with 1.3 g/kg –
1.8 g/kg urethane depending of the reflex test done to assure the anesthesia. The Provincial Government of Eastern Finland (Approval No. 99-61/2002) has approved the
methods with experimental animals used here.
The ECG electrode was 0.25 mm of diameter oxidized silver wire, approximately 2 cm of which was im-
planted subcutaneously (s.c.) close to the heart. A similar
reference electrode was implanted s.c. on the back of the
rat.
For implanting the FP measurement electrode (0.05
mm of diameter insulated tungsten wire), scalp was first
removed. Then a small bone window was drilled at 3.5
mm behind bregma, 2.5 mm left of the midline of the
scull, and the electrode was lowered 2.2 mm into the
brain from the cortical brain surface [14]. The electrode
tip was aimed at CA1 region of the hippocampus, which
also will be mostly used in our future experiments.
Placement of the electrode was verified by observing a
typical FP for the target structure. Effects of the static
magnetic field are expected to be similar for measurements from anywhere in the brain, since the size of the
rat brain is small compared to the dimensions of the
static magnetic field.
An FP measurement reference electrode and a ground
electrode were similar to the ECG electrodes, and were
bilaterally implanted s.c. to the neck of the rat. With
three rats, we placed tungsten wire electrodes (3 mm of
insulation was removed from the tip) to the cerebellum as
reference and ground electrodes. For those rats, the electrodes served as reference electrodes for the ECG measurement as well. For one rat, the oxidized silver electrode was put near the nasal bone to serve as a reference
electrode.
For insertion into the magnet, the rat was attached to
a custom made stereotaxic device, which fixes the head
into a standard position.
2.2. ECG and FP Measurement Systems
For the first two measurement sets, signals from the FP
and ECG electrodes were taken to two separate battery
powered amplifiers (DAM70-E, World Precision Instruments, Sarasota, FL, USA). The amplifiers were set to
perform AC voltage measurements. The amplifiers have
build-in filtering, and for ECG, amplification, high pass
filter cutoff, and low pass filter cutoff were set to 1000,
10 Hz, and 100 Hz, respectively. For FP measurements,
these amplifier settings were 1000, 0.1 Hz, and 100 Hz,
respectively. The amplifiers were placed in the metal
shielding room where the magnet was located.
For the four other measurement sets, we used an inhouse made multi-channel differential amplifier for both
FP and ECG measurements. The amplification factor was
1000. The high pass filter cutoff and low pass filter cutoff were fixed at 0.1 Hz and 5000 Hz, respectively. The
amplifier was placed inside the metal shielding room of
the magnet. The amplifier was powered by a Mascot
power supply type 6328 (Mascot, UK) with ±12 V which
was placed outside the metal shielding room.
Signals were digitized at 1 kHz with 12-bit analog-todigital converters (DigiData, 1200 Series Interface, Axon
Instruments, Inc., Union City, CA, USA), and read in a
PC with Axoscope 9.0 program (Axon Instruments, Inc.)
for initial display and storage.
2.3. MRI System
The MRI system consists of a horizontal 4.7 T magnet
(Magnex Scientific, Abingdon, UK) interfaced to a Varian UnityInova (Varian, Inc., Palo Alto, CA, USA) console. The imagining system contains a superconductive
main magnet, producing a static main magnetic field B0,
which cannot be turned off. A set of gradient magnetic
field coils produce magnetic fields to correct possible B0
inhomogeneities and introduce time-varying magnetic
gradient fields necessary for imaging. For example, gradient switching can be done in 250 µs with maximum
magnetic flux density of 1.7 mT/cm. A transceiver coil
transmits a radio frequency (RF) signal into the subject’s
head to deviate net magnetization created by proton spins
from the direction of B0 and subsequently receives the
signals transmitted by the same protons while the magnetization realigns with the above-mentioned direction of
B0. The whole system is located within a Faraday room
for disturbance shielding.
In the 4.7 T magnet, RF used in proton imaging is
200.15 MHz. Our maximum RF transmitter power is 1
kW, which can be fed into the transmitter coil, and which
then produces a time-varying magnetic field B1 of approximate maximum flux density of 0.1 mT. During the
measurements, the transmitter coil was placed directly
above the subject’s head, and thus also above the FP
measurement site, and was within 4 mm from the FP
electrode connector.
2.4. Sources of Measurement Artifacts
All of the MRI system components are expected to cause
artifacts [15] to any electrical signals measured inside the
magnet. Any magnetic field introduces a force on a moving charge. In addition, gradient switching and RF
transmission are received by any measurement electrodes
and wiring.
Also, subject movement in B0, including movement
of brain caused by heart beat and blood flow, causes artifacts [15,16]. In this work, skull movements were assumed negligible, since the rat was fixed in the stereotaxic device. Possible heart beat effects were analyzed
from the electrical measurements. Artifact removal in
combined ECG or EEG, and MRI measurements were
studied in [16,17], respectively.
For our planned research, it is sufficient to observe
and analyze electrical measurements taken during the inherent delays between subsequent MRI images. For MRI
at one image per second, the gradient coil and RF transmitter inactivity period is approximately 985 ms between
images. Therefore, in this study we considered only the
effects of the static magnetic field B0.
3. QUALITY OF IN-MAGNET ELECTRICAL
MEASUREMENTS
We can distinguish typical theta (3.5 Hz) and low frequency (0.7 Hz) oscillations from the signal measured in
our typical field potential measurement in the hippocampus (Figure 1). These oscillations indicate neuronal activity during active and inactive brain states, respectively. In addition, gamma oscillations (37 Hz) were present in one measurement set on a distinct 2 Hz carrier oscillation (Figure 1) typically in the in-magnet measurements. Gamma oscillation peak can be seen also in Figure 2 in the in-magnet measurement.
Although theta and low frequency oscillations do not
occur at the same time, power spectral peaks from both
oscillations types can be seen in Figure 3. since the
measurement time was long enough (3 min) to include
both states. Power spectral densities in Figures 3 and 4
are from different animals. Power spectral densities were
calculated with Welch's averaged periodogram method
with a Hanning window of 214 length. Overlapping of the
windows were 50 %.
In addition, in other measurements we can see clearly
peaks at several different frequencies indicating changes
in brain states (data not shown). However, additional
frequency components at the theta frequency that we
found in the in-magnet measurements (Figure 3) in one
occasion may be linked with brain state changes and not
with the static magnetic field, although the Müri et al.
[15] observed similar additional peak close to the main
frequency inside a magnet.
Previous work by Müri group suggested that there
was an artifact in human EEG signal caused by the heart
cycle. We found such evidence only once in our FP
measurements (Figure 4). This was the case when the
reference electrode was placed near the nasal bone of the
rat. In any other measurements, we did not find artifacts
caused by simultaneous ECG measurement. Overall, the
ECG in all of the measurements was clear and the heart
rate, for example, could easily be calculated.
We observed in our FP and ECG measurements with
the DAM70-E amplifiers a 50 Hz artifact, which we
could not isolate and remove. With the in-house made
amplifier, we noticed the 50 Hz artifact only in the outside magnet measurements (Figure 2). All of the inmagnet measurements with the in-house made amplifier
were free of the 50 Hz artifact. Appropriate design of the
in-house made amplifier, good shielding, and close location of the preamplifiers to the recording site may have
contributed to the excellent performance of the amplifier.
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Figure 2. Power spectra of the measured FP signals outside (left) and inside (right) magnetic resonance imaging
magnet. 50 Hz artifact can be seen in the measurements outside the magnet. In the in-magnet measurement,
gamma oscillations cause a spectral density peak near 30 Hz.
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Figure 3. Power spectra of the measured FP signals outside (left) and inside (right) magnetic resonance imaging
magnet.
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Figure 4. Artifact observed in only one field potential measurement (left) caused by electrocardiogram (right).
4. CONCLUSIONS
We measured field potentials from the hippocampus of
the rat and electrocardiograms inside and outside a magnetic resonance imaging magnet. We did not find any
major differences in the oscillations between the outside
and in-magnet measurements. We think that the changes
seen in the frequency analysis are probably due to different states of the brain. It is hard to study only the effect
of the static magnetic field because the sleep state of the
rat was not consistent over the measurement set and over
different rats, which made the comparisons very difficult
and some times impossible.
The right placement for the reference and ground
electrodes seemed to be essential. The cerebellum turned
out to be a good place for the electrodes even though it
usually caused some bleeding.
Post-processing of the signal is needed if we want to
clear out all of the artifacts including the 50 Hz and artifacts caused by the MRI sequences. Foremost, we can
conclude that the artifacts observed do not appear to be
overwhelming compared to the signal and that we can
easily recognize the different types of oscillations, which
is necessary to our future FMRI studies.
5. ACKNOWLEDGMENTS
The work of Joanna Tuppurainen and Jarno Tanskanen
was funded by the Academy of Finland (decision numbers 201497 and 80323, respectively). Tanskanen’s literature grant from the Finnish Cultural Foundation of
Northern Savo is greatly acknowledged.
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