Evaluation of the distortion of EEG signals caused by a hole in the skull mimicking the fontanel in...

Evaluation of the distortion of EEG signals caused by a hole in the skull

mimicking the fontanel in the skull of human neonates

Lars Flemminga,b,*, Yaozhi Wanga, Arvind Caprihanc, Michael Eiseltd,Jens Haueisenb, Yoshio Okadaa

aBiomedical Research and Integrative NeuroImaging (BRaIN Imaging) Center, Department of Neurology MSC 10-5620,

School of Medicine, University of New Mexico, Albuquerque, NM 87131, USAbDepartment of Neurology, Biomagnetic Center Jena, Friedrich-Schiller-University, D-07740 Jena, Germany

cMIND Institute, School of Medicine, University of New Mexico, Albuquerque, NM 87131, USAdDepartment of Pathophysiology, Friedrich-Schiller-University, D-07740 Jena, Germany

Accepted 19 January 2005

Abstract

Objective: Interpretation of Electroencephalography (EEG) signals from newborns is in some cases difficult because the fontanels and

open sutures produce inhomogeneity in skull conductivity. We experimentally determined how EEG is influenced by a hole mimicking the

anterior fontanel since distortion of EEG signals is important in neurological examinations during the perinatal period.

Methods: Experiments were carried out on 10 anesthetized farm swine. The fontanel was mimicked by a hole (12!12 mm) in the skull.

The hole was filled with 3 types of medium differing in conductivity (air, 0 S/m; sucrose–agar, 0.017 S/m; saline–agar, 1.28 S/m). Three

positions of the snout were stimulated with a concentric bipolar electrode to activate cortical areas near the middle, the edge, and the outside

of the hole. The somatic-evoked potential (SEP) was recorded by a 4!4 electrode array with a 4 mm grid spacing. It was placed on the 4

quadrants of a 28!28 mm measurement area on a saline-soaked filter paper over the skull, which served as artificial scalp.

Results: The SEP over the hole was clearly stronger when the hole was filled with sucrose– or saline–agar as compared to air, although

paradoxically the leakage current was stronger for the sucrose– than saline–agar. The current leaking from the hole was strongly related to

position of the active tissue. It was nearly negligible for sources 6–10 mm away from the border of the hole. The distortion was different for 3

components of the SEP elicited by each stimulus, probably indicating effects of source distance relative to the hole.

Conclusions: EEG is strongly distorted by the presence of a hole/fontanel with the distortion specifically dependent on both conductivity

of the hole and source location.

Significance: The distortion of the EEG is in contrast to the lack of distortion of magnetoencephalography (MEG) signals shown by

previous studies. In studying brain development with EEG, the infant’s head and sources should be modeled accurately in order to relate the

signals to the underlying activity. MEG may be particularly advantageous over EEG for studying brain functions in infants since it is

relatively insensitive to skull defects.

q 2005 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Keywords: Electroencephalography; Magnetoencephalography; Evoked response; Somatosensory; Fontanel; Pig; Newborn; Infant

1. Introduction

Brain functions of human infants, including pre-term and

term babies, have been traditionally evaluated with EEG as

1388-2457/$30.00 q 2005 International Federation of Clinical Neurophysiology.

doi:10.1016/j.clinph.2005.01.007

* Corresponding author. Address: Department of Neurology, Biomag-

netic Center Jena, Friedrich-Schiller-University, D-07740 Jena, Germany.

E-mail address: [email protected] (L. Flemming).

part of a neurological examination. The evaluation is useful

in infants with risk factors such as complications during

labor and delivery (Sunshine, 1997). EEG is also useful for

staging the development of the nervous system, since

differences in the functional organization of certain

brain regions are already present in newborns (Eiselt

et al., 2001), and for differential diagnosis of seizures

from non-seizures in the paroxysmal motor behavior

Clinical Neurophysiology 116 (2005) 1141–1152

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L. Flemming et al. / Clinical Neurophysiology 116 (2005) 1141–11521142

(De Weerd, 1995; Tharp, 1997). However, neonatal EEG

monitoring is still in need of development, particularly in

relating EEG signals to the underlying brain functions.

Interpretation of the underlying physiology and patho-

physiology is complicated by the presence of the fontanels

and sutures in the skull. The anterior and posterior fontanels

are present at the bregma and the lambda. The skull is not

present within the fontanels. The brain below the fontanels

is protected by the dura, which is thicker within the opening.

The fontanels and sutures are squeezed together during

delivery, but become larger during the first months and then

eventually close. The anterior fontanel may be large enough

to admit an adult’s thumb. The posterior fontanel is closed

within the first 2 month. The anterior fontanel stays open as

long as 16 months or, in abnormal cases, even for several

years. The sutures can be quite wide near the fontanels. The

mean width of the coronal and lambdoidal sutures at their

midpositions is 3–4 mm for infants between 0 and 60 days

after birth (Eramie and Ringertz, 1976). The sutures may

stay unfused for several years (Hansman, 1966). EEG

signals may be profoundly affected by the fontanels and

sutures, which are effectively skull defects, since they

represent areas of high conductivity relative to the skull.

Volume currents might be affected by these openings in the

skull. Thus, it is necessary to evaluate the effect of these

skull openings on EEG in order to accurately infer

physiological functions in human infants.

This report describes distortions of the somatosensory-

evoked potentials (SEPs) by a hole in the skull of neonatal

pigs. Although the EEG signal distortion by skull defects

can be studied using mathematical models of the head as

discussed later, we chose to study the problem in an

experimental preparation since such study is rare and

empirical assessment always provides a solid foundation for

future modeling studies. Our results may be useful for

interpreting distortions of EEG signals in humans arising

from skull defects like the fontanels and sutures in human

infants, since the head of the piglet is large and the scalp and

skull are comparable to those of human infants in thickness.

The neonatal farm swine of 1–3 weeks of age has a skull

thickness of 2–3 mm near the vertex, similar to the thickness

in human newborns (Hansman, 1966). Unlike human

neonates, the piglets do not have a fontanel and the sutures

are nearly closed at birth. A square hole was, therefore,

created in the skull to mimic a fontanel. The SEP distortion

was evaluated as a function of distance of active tissue from

the hole and for 3 different conductivities of the hole.

2. Materials and methods

2.1. Preparation

The protocol used in this study was approved by the

Animal Use Committees of the Albuquerque Veterans

Affairs Medical Center and the University of New Mexico

School of Medicine. Animals were treated according to the

National Institute of Health ‘Guide for the Care and Use of

Laboratory Animals, Revised 1996’.

Experiments were carried out on 10 farm swine (Sus

scrofa). The weight ranged between 8 and 16 kg and the age

between 4 and 6 weeks. Pigs were chosen because of their

large gyrencephalic brain resembling to some extent the

human brain. By 3–5 weeks of age, the neocortex of the pig

has a well-established 6-layer structure (Craner, 1988).

Piglets were sedated and anesthetized with a combination

of ketamine plus xylazine. Initially, the anesthetic agent was

injected in the gluteal muscle and later in the right cephalic

vein. The catheter placed in the right femoral artery was

used for monitoring the blood pressure and for blood gas

analysis. The same catheter was used for the continuous

injection of 0.9% sodium chloride solution (about 5 ml/kg

per h). This fluid substitution was necessary to maintain

blood volume and blood pressure within physiological

values under the artificial ventilation.

Tracheostomy for artificial ventilation was performed

after sedation. The ventilation rate was varied between 14

and 18/min and the volume between 150 and 220 ml to

maintain physiological conditions according to the blood

gas parameters of pCO2 (30–44 mmHg) and pO2 (90–

120 mmHg). During the surgery an anesthetic level of

12 mg/kg per h ketamine plus 1.2 mg/kg per h xylazine was

maintained. Lidocaine (1%) was used for each surgical

approach and for the pressure point of the ear bars of a

head holder. The scalp was removed and a square hole of

12!12 mm cut out in the skull over the left hemisphere

(Fig. 1). The location of the hole was over the rostrum

region of the primary somatosensory cortex (SI). The dura

was kept intact.

The level of anesthesia was reduced to 6 mg/kg per h for

ketamine and 0.6 mg/kg per h for xylazine during

the measurement. D-Tubocurarine was injected (0.3 mg/kg

per h) after the surgery to avoid involuntary movements

during the data acquisition. Body-temperature was kept

constant with a thermal jacket at 37–38 8C.

2.2. Stimulation

For the stimulation we used a concentric bipolar

electrode which was a modified 6 mm Genuine Grass

Ag/AgCl disc electrode with a tungsten needle in the center.

The electrode was fixed on the snout with collodion after the

insertion of the needle. In Exp. 1 the concentric bipolar

electrode was placed on the right side of snout with the

central needle electrode in the location which projected to a

cortical area below the hole (Fig. 1). In Exp. 2, 3 bipolar

electrodes were fixed on the right part of the snout. The

central needle electrodes were placed in the snout locations

that projected to a cortical area within the skull opening,

near the border, and 6–10 mm outside the hole (Fig. 7). The

placement of the electrode on the snout was based on

the data of Craner (1988) and Okada et al. (1999a).

Fig. 1. Sixty-four-channel EEG measurement of 3 different conductivities within the hole. The position of the hole is marked by the solid square. The

measurement covered an area of 28!28 mm over the left somatosensory cortex (dotted square). Electrode spacing is 4 mm. Time range from K10 to 100 ms,

low-pass filter of 200 Hz, high-pass filter of 0.5 Hz, and 30 averages.

L. Flemming et al. / Clinical Neurophysiology 116 (2005) 1141–1152 1143

The stimulus was a brief current pulse (50 ms, 4–7 mA)

applied at 1 pulse/s.

2.3. Electrical measurement

The SEP was recorded with a 4!4 Ag–AgCl electrode

array with an electrode spacing of 4 mm that was placed on

a 0.9% NaCl saline-soaked filter paper covering the exposed

skull. The filter paper served as an artificial scalp. The

electrode array was moved systematically to cover an area

of 28!28 mm. The reference electrode was attached to the

left ear. The measurements were carried out in an

electromagnetically shielded chamber. The custom made

preamplifier had a gain of 5 and the CyberAmp 380 of Axon

Instruments had a gain of 1000. We used a high-pass filter of

0.1 Hz and a low-pass filter of 200 Hz with a sampling rate

of 2 kHz and averaged the data across 30 epochs. The 60 Hz

noise was removed online. The A/D converter had a

resolution of 16 bits and an input range of K1 to C1 V.

Thus, we had a resolution of 3 nV.

The SEP distribution on the artificial scalp was

measured sequentially under the following conditions:

(1) air in the hole, (2) isotonic 3% agar containing

330 mEq of sucrose (sucrose–agar), (3) isotonic 3% agar

containing 0.9% NaCl (saline–agar), (4) again with

sucrose–agar and (5) finally with air in the hole. The

sucrose and air conditions were repeated to check for

possible changes in the SEP due to changes in

physiological and extraneous conditions. In the agar

conditions the sucrose– or saline–agar was poured into

the hole in liquid form with a temperature of less than

38 8C, then the skull was covered with a saline-soaked

filter paper. The SEP measurements were started 10 min

later, after allowing for the agar to gel and for its

conductivity to equilibrate. Additionally, the SEP was

measured on the dura beneath the hole in each condition

to monitor possible changes in the SEP directly on the

cortex.

The resistivities of sucrose– and saline–agar were

determined with a variation of the classical 4-electrode

method, by passing a constant 20 ms square-wave current to

a pair of large Ag–AgCl electrode plates and measuring the

potential in the agar block at 200 mm steps along the

direction of the applied current through a hole in the top of

the plate. The resistivity of sucrose–agar was 280 Um and

that of saline–agar was 0.78 Um at room temperature. These

values correspond to conductivity of 0.0036 and 1.28 S/m,

respectively. The resistivity of the sucrose–agar under the

experimental conditions with the saline-soaked filter paper

placed over the agar decreased with the time after placing

the filter paper, going from 199 Um at 10 min to 48 Um at

80 min. We estimated that the resistivity during the SEP

measurement was about 60–120 Um, corresponding to

conductivities of 0.016–0.0083 S/m.

Two experiments were carried out with each animal. In

the first experiment, the amplitude distortion of the SEP was

determined for an active tissue in the middle of the skull

opening (see Fig. 1), which was subjected to a maximum

amplitude distortion. The SEP measurements were repeated

twice at each of 64 locations in order to check for reliability.


In the second experiment, the amplitude distortion was

determined as a function of distance of the active tissue

from the hole, by activating the cortical areas 4, 7, and 10

(Fig. 7). The SEP was measured only once at each electrode

position in each condition in order to compare the SEPs as

much as possible under stable physiological conditions

during the entire experiment.

The data from 6 out of 10 animals were used for the final

analysis of results of Exp. 1 and data from 5 out of 10

animals were used for Exp. 2 because of lack of stability

across the replications and incomplete set of data in the

remaining animals.

2.4. MRI

After the experiment, the brain was perfused and fixed

with 4% formaldehyde under a deep anesthesia. The entire

head was stored in a 4% formaldehyde solution to preserve

the shape of the brain for MRI scans. MRI images of the

head were taken on a 4 T Varian scanner. A fast spin echo,

multi-slice pulse sequence (Hennig, 1988) with an effective

echo time (TE) of 45 ms and 16 averages were used. The

pulse sequence had a train of 4 echoes with the center of the

k-space being traversed in the 3rd echo. The in-plane

resolution was 0.5 mm!0.5 mm and the slice thickness was

0.5 mm giving an isotropic voxel of 0.5 mm3. A 16 cm

quadrature /bird-cage rf coil was used.

2.5. Data processing and source localization

The data were filtered with a high-pass filter of 0.3 Hz

and a low-pass filter of 200 Hz. The stimulation artifact was

removed. In the case of Experiment 1 the data from the two

replications were averaged for the analysis.

Source localization was performed at the time instant of

the peak of the first cortical response after stimulation

(component c1, see Fig. 5). A single equivalent current

dipole for the source and a boundary element method

(BEM) was used to model the head. The BEM model was

based on the MRI images of one representative animal. It

consisted of 3 compartments representing the brain, the

skull, and the scalp. The brain was modeled with 2490

surface triangles (edge length of 2.5 mm), the skull with

3306 surface triangles (edge length 2.5 mm), and the scalp

with 5786 surface triangles (edge length 2.0 mm). For the

compartments we assumed a homogeneous conductivity of

0.25 (brain), 0.013 (skull), and 0.25 (scalp) S/m (Haueisen

et al., 1997b).

For each animal, the data set of the sucrose–agar

condition was used for the source localization since the

conductivity of the sucrose–agar (0.016–0.008 S/m) was

closest to the conductivity of the skull, estimated to be

0.013 S/m. The conductivity difference between the

sucrose–agar and the skull was neglected. Source localiz-

ation was performed with the software Curry version 4.5.

2.6. Analysis and statistics

The Laplacian method was used to estimate the radial

current source density Im in the artificial scalp (Babiloni

et al., 1996, 1997; Gevins et al., 1994, 1999; He, 1999;

Hjorth, 1975; Le et al., 1994; Nunez et al., 1994). Since

there is no primary source in the artificial scalp, the potential

on the scalp follows the Laplace equation: sV$VfeZ0,

where s is the conductivity of the scalp, fe is the

potential on the scalp, Vfe is the gradient of the scalp

potential and V$ is the divergence operator on the gradient

of the potential. The equation can be written as:

sv2fe=vx2Csv2fe=vy2ZKsv2fe=vz2, approximating the

local scalp surface as a plane, where v is the partial

differential operator. The right-hand side can be re-written

as: vJz/vz, where Jz is the current density along the z-axis

perpendicular to the scalp surface. vJz/vz can be viewed as

an effective current source density KIm in units of A/m3 that

produces a divergence of current in the scalp. Im is positive

when the positive charge is entering the scalp (current

source) and negative when the positive charge is leaving the

scalp (current sink). We estimated Im from a discrete version

of the left-hand side: s{4V(x0,y0)KV(h,y0)KV(Kh,y0)KV(x0,h)KV(x0,Kh)}/h2, where V(x,y) are the potentials

measured at 5 positions centered at position xZx0 and yZy0

(He, 1999). The inter-electrode distance hZdxZdy was

4 mm in this study. The value of s for the artificial scalp

(filter paper soaked with saline) was assumed to be the

same as that of the extracellular conductivity of the brain,

0.25 S/m because of the tortuosity produced by the fibers in

the paper. The Laplacian estimate should be applicable even

when the underlying geometry of the skull and brain is

inhomogeneous as it is the case in the present preparation

since the Laplace equation is locally valid and the artificial

scalp is homogeneous.

A within-subject repeated ANOVA test was used for the

statistical analyses of both experiments. In the first

experiment, we determined the effects of the conductivity

of the hole, separately on 3 components of the SEP

produced by an active cortical tissue within the hole. In

the second experiment, we investigated the effect of

distance of the active area from the hole and conductivities

of the hole on the SEP. The Wilcoxon test was also used for

the second experiment.

3. Results

3.1. Experiment 1

The circle in the inset of Fig. 1 shows the estimated

source location in the rostrum region (shaded area

delineated by the circular coronal sulcus) of the SI cortex

activated by the snout stimulation. This area was within the

square 12!12 mm hole created in the skull. The SEP

measurements were carried out within the dashed square

Fig. 2. Difference maps of the 64-channel EEG measurement shown in Fig. 1. Measurement of air1 and air2 were averaged and subtracted from the other

measurements. The position of the hole is marked by a square. Time range, filters, etc. See Fig. 1.


area. The SEP over the hole was larger in the sucrose1–agar

condition compared to the air1 condition in which the hole

was filled with a non-conducting medium (namely air).

Similarly, the SEP over the hole in the saline–agar condition

was stronger than in the air condition. The SEP patterns in

the sucrose2–agar and air2 conditions were similar to the

sucrose1–agar and air1 conditions, indicating good repro-

ducibility of the data.

Fig. 2 shows difference maps of the SEPs between the

sucrose and air conditions and between the saline and air

conditions. The SEPs in air conditions 1 and 2 were

averaged and the averaged SEP was subtracted from the

SEPs in the sucrose and saline conditions. The SEPs were

stronger over the hole in the sucrose– and saline–agar

conditions as compared to the air condition. In contrast the

difference waves were close to zero at the edges of the

measurement area indicating that the effects of the hole were

confined within the area of measurements. The largest

differences were seen above the hole where the active tissue

was located.

These results suggest that the current leaking from the

hole was stronger when the hole was filled with

Fig. 3. Laplacian derivation maps of the difference maps shown in Fig. 2. The pos

a conducting medium. The radial current leaking from the

hole can be directly estimated by the Laplacian derivation of

the potentials. Fig. 3 shows the Laplacian derivation of the

difference waves in the 3 conditions. This analysis

demonstrates several interesting features. First, the current

clearly leaks through the hole. Second, the amount of

current leak is somewhat counter intuitively larger in the

sucrose condition than in the saline condition. Third, the

polarity of the waveform is opposite just outside the hole as

compared to the waveforms inside the hole, indicating that

the current leaking through the intact skull just outside the

hole was weaker in the saline– and sucrose–agar conditions

compared to the air condition. This last result is consistent

with the fact that the current leak was stronger in the hole in

these conditions compared to the control condition of the

hole filled with air.

The Laplacian derivations of the original SEP data in

the 3 conditions provide results that are consistent with the

results from the difference data. Fig. 4 shows the Laplacian

of the SEP data in the air, and in the sucrose–agar and

saline–agar conditions averaged across the two replications.

In the air condition, the current leaking through the hole was

ition of the hole is marked by a square. Time range, filters, etc. See Fig. 1.

Fig. 4. Maps of the Laplacian derivation of the 64-channel EEG measurement shown in Fig. 1. The effect of the hole or the position of the hole is marked by a

square. Time range, filters, etc. See Fig. 1.


negligibly small. The current through the skull just outside

the hole was, however, stronger, indicating that the volume

current leaked through this region, which was closest to the

active cortical tissue below the air-filled hole. In the

sucrose–agar condition, the current in the saline-soaked

filter paper mimicking the scalp was strongest over the hole.

The same was observed in the saline–agar condition. In both

cases there was a considerable gradient of the leak current

centered around the location of the active tissue. However,

the magnitude of the leakage current was stronger in the

sucrose–agar condition as compared to the saline–agar

condition, supporting the inference made above (see Fig. 3).

Fig. 5 summarizes these results across the group of

subjects. As shown in Fig. 5A, the maximum current leaking

through the hole in both sucrose– and saline–agar conditions

was stronger than the maximum current in the air condition,

which was leaking through the skull just outside the hole.

The leakage current was weakest in the air condition. The

main effect of conductivity was statistically significant

across the group of 6 subjects (F(2,10)Z13.35, P!0.0015).

Fig. 5 also shows another effect. The amplitude distortion

of SEP was different for 3 components of the response that

are shown in the inset. The latencies of these 3 components—

c1, c2 and c3—were approximately 15, 19, and 40 ms,

respectively. The leakage current was, first of all, strongest

for c2. This was the case even for the air condition. Relative

to the air condition, the leakage current in the sucrose–agar

condition was 15 and 26 times stronger for c1 and c2, and 6

times stronger for c3 (Fig. 5B). These values were 7, 14 and 4

for c1, c2 and c3 in the saline–agar condition as compared to

the air condition (Fig. 5B). The leakage was stronger in the

sucrose condition than in the saline condition relative to the

air condition. The main effect of the SEP component was

significant (F(2,10)Z14.33, P!0.0012).

Furthermore, the interaction between conductivity

and component was significant as well (F(4,20)Z13.47,

P!0.00001). This means that the amplitude distortion of

the SEP due to the conductivity was different for the

different SEP components.

The difference between the SEPs of the sucrose– and

saline–agar was calculated in Fig. 6. In Fig. 6A, the SEP of

the saline condition was subtracted from the averaged SEP

of the first and second sucrose condition to enhance the

difference between both conditions. The current leaking

through the sucrose condition was stronger compared to the

saline condition above the center of the source within the

hole (number 1). This is the case for all 3 components of

the SEP. The result is consistent with the results already

described in Figs. 3–5.

At about two electrode positions away from the center of

the source but still within the hole, the SEP signal was

opposite in polarity. In Fig. 6B, these two traces are

superimposed. The current in the saline–agar condition at

this position was stronger compared to the sucrose–agar

condition. A similar effect was found outside the hole. This

finding was held for all the 3 SEP components.

3.2. Experiment 2

This experiment examined the effect of distance of the

active tissue and conductivity of the hole on the SEP. Fig. 7

shows the estimated locations of the 3 cortical areas

averaged across subjects that were activated by stimulating

3 fixed locations on the snout.

Fig. 8 shows the current leaking through the hole in the 3

conditions (air, sucrose, and saline) when cortical areas 4, 7,

and 10 were stimulated. The 3 panels in each row show the

Laplacian derivation of the SEPs in the 3 conditions

differing in electrical conductivity of the hole. The results

for area 4 are similar to those just described. The noise level

is higher because the maps are based on a single set of

measurements rather than the average of two replications.

The results for cortical area 7 were similar to those for area 4

in terms of effects of the conductivity, but the leakage

currents were weaker than for area 4. In the case of area 10,

the leakage current was seen outside the hole (right top

corner) above the active cortical tissue, but the current

within the hole was not clearly evident.

Fig. 5. (a) Comparison of the amplitude of the Laplacian derivation for the 3 different conductivities and their 3 components (15, 20, 40 ms) for 6 animals. (b)

Comparison of the ratio (based on the Laplacian derivation) sucrose/air and saline/air for the 3 components. The bar in both figures shows the standard error of

the mean.


The effects of location of active tissue are shown in Fig. 9

for the group of 5 subjects. The figure shows the ratio of the

leakage currents between the sucrose–agar and air and

between the saline–agar and air conditions. The analysis

was carried out for component 1 which was strongly

distorted by the hole. Separately for the sucrose– and saline–

agar conditions, the largest absolute amplitude of this

component was divided by the absolute amplitude of the

same component of the same recording electrode of the air

condition. If there was no clear peak in the air condition the

averaged value within the time range of the first component

of sucrose and saline was used. For the case where the

amplitude of the response outside the hole was stronger than

the amplitude within the hole, the absolute amplitude of the

first component of the recording electrode within the hole

closest to the recording electrode outside the hole with the

strongest response was used for computing the ratios.

The results of 5 animals were averaged. The bars show the

standard error of mean. The SEP produced by stimulation of

area 4 was clearly more influenced by the conductivity than

areas 7 and 10. The effect of the hole was very small (ratio

of near 1) for area 10. This figure also shows the stronger

leakage current in the sucrose– than saline–agar condition

for each area of activation, corroborating the results from

Exp. 1. The effect was significant with the Wilcoxon test for

area 4 (P!0.05), but only marginal for area 7 (PZ0.08).

Fig. 6. (a) Difference maps of the 64-channel EEG measurement shown in

Fig. 1. Measurement of saline was subtracted from the average of sucrose1

and sucrose2 measurement. The position of the hole is marked by a square.

The trace of the recording electrode above the center of the active area is

labeled with the number 2. (b) Superposition of the two marked channels.

Time range, filters, etc. See Fig. 1.

Fig. 7. Map shows the measured area of 28!28 mm (dashed square) over

the left somatosensory cortex. The solid square shows the position of the

hole, and the numbers 4, 7, and 10 shows the estimated averaged source

locations (active cortical areas).


The non-significant effect could be caused by the small

number of animals. There was no difference between the

sucrose– and saline–agar for area 10. The ANOVA showed

that the main effects of distance (F(2,8)Z5.02, P!0.039)

and conductivity (F(1,4)Z9.28, P!0.038) were significant.

The SEP distortion clearly depended on the distance of the

active area and the distortion was different for the saline–

and sucrose–agar normalized to the air condition (Fig. 10).

But, the interaction of distance and conductivity was not

significant (F(2,8)Z2.01, PO0.05).

4. Discussion

The above results clearly demonstrate that a hole in the

skull of the neonatal piglet may produce a strong distortion

of EEG signals. The leakage of current through the hole

and the surrounding skull was clearly affected by the

conductivity of the hole and distance of the active tissue

producing the SEP. The distortion was different for the

different components of the SEP.

In the case of a hole filled with air, the volume current

from an active tissue below the hole cannot flow through the

air in the hole since it is non-conducting. The current must

go around the hole and flow to the conducting saline-soaked

filter paper through the region of the skull closest to

the hole. This qualitatively explains the results for the air

condition in Fig. 4.

In the case of a hole filled with saline–agar, the current

should preferentially flow through the hole, following the

path of least distance and resistance to the paper above. The

leakage current should be therefore strongest above

the active tissue and should become gradually weaker

with distance on the filter paper, as we found in Fig. 4.

The sucrose–agar is soaked by saline in the filter paper

from above. Thus, its conductivity is not zero, but it

equilibrates to about 0.016 S/m. This is about 80 times less

than the conductivity (1.28 S/m) of the saline–agar, which is

close to the conductivity of saline (1.33 S/m), and 9–16

times less than the conductivity of a brain tissue (0.15–

0.25 S/m, Okada et al., 1994). The conductivity of the

equilibrated sucrose–agar was fortuitously very close to

the conductivities of the skull in vitro and in vivo estimated

in recent studies (0.016–0.041 S/m for the spongiform layer

and 0.003–0.010 S/m for the external compact layers,

Akhtari et al., 2002; 0.032–0.080 S/m, Hoekema et al.,

2003; 0.015 S/m, Oostendorp et al., 2000). The similarity of

the sucrose–agar conductivity to these values of the skull

justifies our use of a homogeneous conductivity model for

the head in our localization model. Therefore, we should

expect the current leakage to be strongest over the active

tissue and it should decrease gradually away from the peak

location as if there was no hole. The results show strong

Fig. 8. Maps of the Laplacian derivation of the 64-channel EEG measurement for the 3 different conductivities and for active areas 4, 7, and 10. The position of

the hole is marked by a square (solid line). Time range, filters, etc. See Fig. 1.


leakage currents that seem to be largely confined to the hole

when the source was just below the hole.

The leakage current is in fact even stronger than the

current in the saline–agar condition (Fig. 4). This is quite

reliable as seen in the several lines of analyses. The result is

quite paradoxical: Since the saline–agar’s conductivity is

higher than the sucrose–agar’s, the leakage current should

be stronger for the saline– than the sucrose–agar. We offer

the following hypothesis to explain this phenomenon. In the

case of the saline–agar condition, we assume that a layer of

saline is produced between the agar and the dura. This leads

to a shunting of the volume current from the active tissue

below and a fraction of the volume current flows up through

the agar to reach the filter paper. In the case of the sucrose–

agar condition, we assume that the conductive saline layer is

thinner or absent. This leads to less shunting and flow of

a larger fraction of the volume current through the sucrose–

agar than the saline–agar, thus giving rise to stronger

leakage currents in the sucrose–agar condition. This is a

testable hypothesis and should be evaluated in the future.

The leakage of current through the hole was quite strong

for the currents produced by active tissue below the hole.

The distortion became nearly negligible when the active

tissue was located 6–10 mm away from the edge of the hole

(Fig. 10). The leakage current was up to 25 times stronger in

the sucrose and saline conditions compared to the air

condition when the source was beneath the hole and 5 times

stronger when the source was near the edge of the hole.

The differences in leakage current found for the 3

components of the SEP may be explained by the differences

in the location of the corresponding active tissue with

respect to the hole. The leakage current in the sucrose

Fig. 9. Comparison of the effect of the amplitude distortion of the EEG

measurement for the different conductivities and for the different active

areas. The biggest amplitude of the Laplacian derivation for the

conductivities saline–agar and sucrose–agar of the first component

(15 ms) was divided by the amplitude of the Laplacian derivation of the

same time-point and the same channel of the conductivity air. The results of

5 animals were averaged. The bars show the standard error of mean.


condition relatively to the air condition was 15, 26, and 6

times stronger for the first, second, and third component,

respectively. Similar results we achieved in the saline

condition. Okada et al. (1996) found that the 3 components

are located in different areas of the SI cortex of the piglets.

The cortical components within a latency range of 50 ms

become deeper (depthZapproximately 5, 8, 11 mm for c1,

c2, and c3).

Our results are principally in accordance with several

different simulation studies (Benar and Gotman, 2002;

Chauveau et al., 2004; Oostenveld and Oostendorp, 2002;

Fig. 10. Comparison of the ratio (based on the Laplacian derivation)

saline/air and sucrose/air in dependence of the distance to the border of the

hole. Negative values are for a position inside the hole and positive values

are for a position outside the hole.

Vanrumste et al., 2000; Van de Broek et al., 1998). Van

de Broek et al. (1998) used a finite element method to

represent a hole in the middle layer (skull) of a 3-shell

spherical model of the human head and found the

strongest influence on the electric potentials for a radial

dipole just below the hole. Vanrumste et al. (2000)

employed a realistic finite difference model of the human

head with a hole in the temporal skull region and found

for radial dipoles the strongest localization error below the

hole, while for tangential dipoles the strongest localization

error was at the border of the hole. Investigations of

Oostenveld and Oostendrop, and Benar and Gotman were

based on boundary element methods (BEM). Oostenveld

and Oostendrop used a 3-sphere model compared to Benar

and Gotman who based their BEM on a T1-weighted MRI

scan of a patient. Both studies achieved results that are

comparable to those of Vanrumste et al. and Van den

Broek et al. The approach of Chauveau et al. with a 3-

dimensional resistor mesh model confirmed those results.

All studies show that for dipoles far away from the hole

no distortion of the electric potentials and thus no

localization errors are to be expected. Effects of a hole

in the skull may be more extensive than our results.

Heasman et al. (2002) demonstrated effects of a hole in a

human cadaver skull on the electric potential for

superficial tangential dipoles located 50–60 mm away

from the hole. The potentials on the outer surface of the

skull were different when a 4 mm diameter hole was filled

with saline or wax and the rest of the skull was filled with

saline. The distortion was more extensive than in our case

because, as we suppose, the adult skull is thicker and thus

the resistance through the skull must have been greater

than in our study. Based on these results, it appears that

the distortion of EEG signals depends quantitatively on a

number of factors such as distance of the active tissue

from the area of skull defect, the microscopic conductivity

geometry of the hole, and more generally on the

conductivity geometry of the entire skull and the head.

The EEG distortion may not be confined to active tissues

within 10 mm of the defect as was the case in our study,

but may be more extensive.

The present results are useful for inferring effects of the

fontanel and suture in infant skull on EEG signals in

neonatal studies. In our study we did not directly compare

the SEP with a hole in the skull against the SEP over the

intact skull. Nor did we produce a condition that closely

mimics the fontanel in human infants, by creating a dura

fused to the scalp. Therefore, we do not have quantitative

estimates of EEG distortion in a condition that resembles the

skull of human infants. These studies obviously need to be

carried out. Nevertheless, the effects of conductivity of the

hole on the SEP found in the present study indicate that the

inhomogeneity in conductivity of the skull should distort

EEG signals.

Although the signal distortion by holes in the skull

is a serious problem for EEG, advances in EEG


methodology enable us to take this problem into account

in estimating brain activity from EEG signals. One can

now model the skull effects with a finite element method

and interpret EEG signals in terms of underlying

generators (Haueisen et al., 1997a). In such models,

one must take various parameters (e.g. thickness and

conductivity of the skull and scalp) into account. In long-

term studies of newborns, it would be necessary to take

into account changes in the fontanels and sutures and

thickness of the skull with age. With the help of a proper

modeling, EEG-based source localization in newborns

should be possible.

Brain activity in infants can be also studied with MEG.

In comparison to EEG, MEG does not show compli-

cations due to the inhomogeneity in skull conductivity.

Okada et al. (1999a,b) found virtually no effect of a large

hole in the skull on the MEG signals produced by shallow

cortical sources in the primary somatosensory cortex of

the piglets in vivo. Barth et al. (1986) earlier found no

obvious effect of a hole in the human cadaver skull on

MEG. This remarkable property of magnetic field points

to the study of human infants as an area where one can

take advantage of MEG.

In evaluating the practical advantages of MEG and EEG

for infant studies, one needs to consider other factors such as

movement artifacts. Both techniques suffer when the baby is

awake and moves during measurements. EEG suffers from

muscle artifacts and movement of the leads associated with

the body movement. The lead movement can be eliminated

with an electrode attached to a preamplifier. MEG suffers

from the fact that the sensors are not attached to the head, so

that the sensor positions move relative to the head. Recently

a method called signal source separation was introduced by

Taulu et al. (2004). This technique, as well as other

techniques, could be used to continuously monitor the head

movement, calculate the sensor positions on the head even

when the infant moves (Cheour et al., in press). Alter-

natively, MEG and EEG could be used while the baby is

asleep. In such a condition, both types of signals can be

measured simultaneously and can be compared in newborns

(Pihko et al., 2004).

The advances in MEG and EEG methodology indicate

that human brain development may be a fruitful area of

investigation using these completely safe, electrophysio-

logical methods.

Acknowledgements

This work was supported by the German Academic

Exchange Service (DAAD), the European Community (IST

1999-10378), and by the NIH Grant (R01-NS30968).

Special thanks go to Yoshio Okada for the great opportunity

to perform this scientific work at his laboratory.

References

Akhtari M, Bryant HC, Mamelak AN, Flynn ER, Heller L, Shih JJ,

Mandelkern M, Matlachov A, Ranken DM, Best ED, DiMauro MA,

Lee RR, Sutherling WW. Conductivities of three-layer live human

skull. Brain Topogr 2002;14:151–67.

Babiloni F, Babiloni C, Carducci F, Fattorini L, Onorati P, Urbano A.

Spline Laplacian estimate of EEG potentials over a realistic magnetic

resonance-constructed scalp surface model. Electroenceph Clin Neu-

rophysiol 1996;98:363–73.

Barth DS, Sutherling W, Broffman J, Beatty J. Magnetic localization of a

dipolar current source implanted in a sphere and a human cranium.

Electroenceph Clin Neurophysiol 1986;63:260–73.

Benar CG, Gotman J. Modeling of post-surgical brain and skull defects in

the EEG inverse problem with the boundary element method. Clin

Neurophysiol 2002;113:48–56.

Chauveau N, Franceries X, Doyon B, Rigaud B, Morucci JP, Celsis P.

Effects of skull thickness, anisotropy, and inhomogeneity on forward

EEG/ERP computations using a spherical three-dimensional resistor

mesh model. Hum Brain Mapp 2004;21:86–97.

Cheour M, Imada T, Taulu S, Ahonen A, Salonen J, Kuhl P.

Magnetoencephalography is feasible for infant assessment of auditory

discrimination. Exp Neurol, 2004 Nov;190 (Suppl 1):544–51.

Craner SL. A developmental analysis of the organization of the

somatosensory cortices of the domestic pig. PhD Thesis. East Carolina

Univ., School of Medicine; 1988.

De Weerd AW. Atlas of EEG in the first months of life. New York:

Elsevier; 1995.

Eiselt M, Schindler J, Arnold M, Witte H, Zwiener U, Frenzel J. Functional

interaction within the newborn brain investigated by adaptive

coherence analysis of EEG. Clin Neurophysiol 2001;31:104–13.

Eramie U, Ringertz H. Normal width of cranial sutures in the neonate and

infant. Acta Radiol Diagn 1976;17:565–72.

Gevins A, Le J, Martin NK, Brickett P, Desmond J, Reutter B. High

resolution EEG: 124-channel recording, spatial deblurring and MRI

integration methods. Electroenceph Clin Neurophysiol 1994;90:

337–58.

Gevins A, Le J, Leong H, McEvoy LK, Smith ME. Deblurring. J Clin


Hansman CF. Growth of interorbital distance and skull thickness as

observed in roentgenographic measurements. Radiology 1966;86:

87–96.

Haueisen J, Ramon C, Eiselt M, Brauer H, Nowak H. Influence of tissue

resitivities on neuromegnetic fields and electric potentials studied with a

finite element model of the head. IEEE Trans Biomed Eng 1997a;44:

727–35.

Haueisen J, Bottner A, Funke M, Brauer H, Nowak H. The influence of

boundary element discretization on the forward and inverse problem in

electroencephalography and magnetoencephalography. Biomed Tech

1997b;42:240–8.

He B. Brain electric source imaging: scalp Laplacian mapping and cortical

imaging. Crit Rev Biomed Eng 1999;27(3–5):149–88.

Heasman BC, Valentin A, Alacron G, Garcia Seonane JJ, Binnie CD,

Guy CN. A hole in the skull distorts substantially the distribution of

extracranial electrical fields in an in vitro model. J clin Neurophysiol

2002;19(2):163–71.

Hennig J. Multiecho imaging sequence with low refocussing angles.

J Magn Reson 1988;78:397–407.

Hjorth B. An on-line transformation of EEG scalp potentials into

orthogonal source derivations. Electroenceph Clin Neurophysiol

1975;39:526–30.

Hoekema R, Wieneke GH, Leijten FS, van Veelen CW, van Rijen PC,

Huiskamp GJ, Ansems J, van Huffelen AC. Measurement of the

conductivity of skull, temporarily removed during epilepsy surgery.

Brain Topogr 2003;16:29–38.


Le J, Menon V, Gevins A. Local estimate of surface Laplacian derivation

on a realistically shaped scalp surface and its performance on noisy

data. Electroenceph Clin Neurophysiol 1994;92:433–41.

Nunez PL, Silberstein RB, Cadusch PJ, Wijesinghe RS, Westdorp AF,

Srinivasan RA. Theoretical and experimental study of high resolution

EEG based on surface Laplacians and cortical imaging. Electroenceph

Clin Neurophysiol 1994;90:40–57.

Okada YC, Huang J-C, Rice ME, Tranchina D, Nicholson C. Origin of the

apparent tissue conductivity in the molecular and granular layers of the

in vitro turtle cerebellum and the interpretation of current source–

density analysis. J Neurophysiol 1994;72:742–53.

Okada YC, Papuashvili NS, Xu C. What can we learn from MEG studies of

the somatosensory system of the swine?. In: Hashimoto I, Okada YC,

Ogawa S, editors. Visualization of information processing in the human

brain: recent advances in MEG and functional MRI (EEG. Clin Neurol

Suppl 47). Amsterdam: Elsevier; 1996.

Okada YC, Lahteenmaki A, Xu C. Comparison of MEG and EEG on the

basis of somatic evoked responses elicited by stimulation of the snout in

the juvenile swine. Clin Neurophysiol 1999a;110:214–29.

Okada YC, Lahteenmaki A, Xu C. Experimental analysis of distortion of

MEG signals by the skull. Electroenceph Clin Neurophysiol 1999b;110:

230–8.

Oostendorp TF, Delbeke J, Stegeman DF. The conductivity of the human

skull: results of in vivo and in vitro measurements. IEEE Trans Biomed

Eng 2000;11:1487–92.

Oostenveld R, Oostendorp TF. Validating the boundary element method for

forward and inverse EEG computations in the presence of a hole in the

skull. Hum Brain Mapp 2002;17:179–92.

Pihko E, Lauronen L, Wikstrom H, Taulu S, Nurminen J, Kivitie-Kallio S,

Okada Y. Somatosensory evoked potentials and magnetic fields elicited

by tactile stimulation of the hand during active and quiet sleep in

newborns. Clin Neurophysiol 2004;115:448–55.

Sunshine R. Epidemiology of perinatal asphyxia. In: Stevenson DK,

Sunshine P, editors. Fetal and neonatal brain injury: mechanisms,

management and the risks of practice. New York: Oxford University

Press; 1997. p. 3–23.

Taulu S, Kajola M, Simola J. Suppression of interference and artifacts by

the signal space separation method. Brain Topograph 2004;16:

269–75.

Tharp B. Use of the electroencephalogram in assessing acute brain damage

in the newborn. In: Stevenson DK, Sunshine P, editors. Fetal and

neonatal brain injury: mechanisms, management and the risks of

practice. New York: Oxford University Press; 1997. p. 287–301.

Van de Broek SP, Reinders F, Donderwinkel M, Peters MJ. Volume

conduction effects in the EEG and MEG. Electroenceph Clin


Vanrumste B, Van Hoesy G, Van de Walle R, D’Have M, Lemahieu I,

Boon P. Dipole location errors in electroencephalogram source analysis

due to volume conductor model errors. Med Biol Eng Comput 2000;38:

528–34.

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