Neuromagnetic biomarkers of visuocortical development in healthy children
Yangmei Chena,b, Jing Xianga,*, Elijah G. Kirtmana, Yingying Wanga, Rupesh Kotechaa, Yang Liua
aDepartment of Neurology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
bDepartment of Neurology, The Second Affiliated Hospital, Chongqing Medical University, 76 Lin Jiang Road, Chongqing 400010, China
a r t i c l ei n f o
Accepted 23 March 2010
Available online 14 April 2010
Visual evoked magnetic fields
a b s t r a c t
Objective: The objective of the present study was to investigate noninvasive biomarkers for visuocortical
development in healthy children.
Methods: Sixty healthy children and 20 adults were studied with a whole-head magnetoencephalogra-
phy (MEG) system. The adults were included to find out when the markers stabilize. Visual evoked mag-
netic fields (VEFs) were evoked with full-field pattern-reversal checks.
Results: Three response peaks were identified at 77 ± 8 ms (M75), 111 ± 9 ms (M100) and 150 ± 11 ms
(M145) for children. The latency of M75 and M100 decreased with age (p < 0.01). The amplitude ratio
of M100/M75 increased significantly with age (p < 0.001). The differences of MEG source images between
the left and right occipital cortices for M75 and M145 increased significantly with age (r = 0.47 and 0.46,
respectively, p < 0.01).
Conclusions: The latency of M75 and M100 and the amplitude ratio of M100/M75 are robust biomarkers
for the development of visual function in children.
Significance: The development of visual function in childhood is noninvasively measurable. The results
lay a foundation for quantitative identification of developmental delay and/or abnormalities of visual
function in children with brain disorders.
? 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights
Recent advances have found that noninvasive biomarkers are
critical to the study of functional brain maturation and develop-
mental delay in children (Lippe et al., 2007). Developmental
changes of brain responses to pattern-reversal visual stimulation
have been noted in many previous reports (Allison et al., 1984;
Crognale et al., 2001; Brecelj et al., 2002; Lippe et al., 2007). Pre-
term neonate studies with electroencephalogram (EEG) have
shown that a single latency negative peak (N75) and a positive
peak (P100) can be detected as early as 26–36 weeks gestational
age, respectively, with the positive peak’s latency decreasing with
increasing neonatal age (Ellingson et al., 1973; Taylor et al., 1987;
Tsuneishi and Casaer, 2000; Birch and O’Connor, 2001). The laten-
cies of all three components have been shown to decrease between
0 and 7 months following birth (Crognale et al., 2001). The latency
of P100 decreases with age in children aged 5–24 months,
1–5 years or as late as 20 years (Allison et al., 1983; Shaw, 1984;
McCulloch and Skarf, 1991; Emmerson-Hanover et al., 1994). A
study of visual evoked potentials (VEP) (Brecelj et al., 2002) has re-
vealed that the P100 amplitude is greatest between 6 and 11 years.
It has been noted that female adults have shorter latencies and
generate higher component amplitudes than males (Celesia et al.,
1987; Klistorner and Graham, 2001). In addition, it has been found
that the P100 characteristics exhibit age-related changes and that
these changes are greatest in males (Allison et al., 1984; Brecelj
et al., 2002; Lippe et al., 2007). Noticeably, previous reports on
VEPs in children mainly focused on the latency and amplitude of
P100 in VEPs. The middle latency component, N75, has rarely been
studied. In addition, the relative changes of P100 and N75 remain
unclear. Furthermore, the spatial characteristics of visual evoked
activation in the developing brain have not been reported.
Magnetoencephalography (MEG) is a new technology for
detecting neuromagnetic fields associated with electric brain activ-
ities. It is generally accepted that MEG has both a high spatial and
temporal resolution (Nakasato et al., 1996; Seki et al., 1996). Visual
evoked magnetic fields (VEFs) in the visual cortex in response to a
pattern-reversal visual stimulus have revealed several detectable
components. The most robust components have been identified
approximately at 75 ms (M75), 100 ms (M100) and 145 ms
(M145) (Moradi et al., 2003; Barnikol et al., 2006; Perfetti et al.,
2007). Fetal MEG studies have found that the latency of fetal VEFs
(fP200) begin to decrease as early as 28 weeks gestational age,
1388-2457/$36.00 ? 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
* Corresponding author. Address: Department of Neurology, MLC 2015, Cincin-
nati Children’s Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH 45220,
USA. Tel.: +1 513 636 303; fax: +1 513 636 1888.
E-mail address: firstname.lastname@example.org (J. Xiang).
Clinical Neurophysiology 121 (2010) 1555–1562
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journal homepage: www.elsevier.com/locate/clinph
approaching adult latency near 36 weeks gestational age (Eswaran
et al., 2002, 2005). Since Eswaran and colleagues measured the
photic evoked response to a flash stimulus (Eswaran et al., 2002,
2005), their results might be different from the VEFs evoked by
the reversing checkerboard stimulus, which is widely used in clin-
ical practice. Noteworthy, three components (M75, M100 and
M145) have been identified in VEFs. However, to our knowledge,
the maturational changes of these components in children aged
6–17 years old have not been well investigated with MEG.
Since visual evoked responses correlate to myelination and syn-
aptic transmission (Scherg and Picton, 1991; Tsuneishi and Casaer,
1997), it is more than likely that VEFs change with age. However,
due to the development of the brain, the size of the child’s head
varies with age. Consequently, the evoked potential map might
be distorted by the development of the skin, skull and other tis-
sues. It is well known that magnetic signals are not significantly af-
fected by the skull, skin and other tissues. However, an increase of
distance between the cerebral cortex and the MEG sensor arrays
caused by a change in the size of the head may decrease the abso-
lute value of the amplitude. According to our experience in clinical
practice, there is an urgent need to find to a new biomarker that is
not significantly affected by head size to more accurately charac-
terize the developmental patterns of VEFs. If such kind of noninva-
sive biomarker could be found for visuocortical development, it
would lay a foundation for the identification of aberrant VEFs in
children with various brain disorders. Importantly, noninvasive
biomarkers can also be used in identifying developmental delay
of visual function. Since recent advances in MEG methodology have
made it possible to estimate precisely the spatiotemporal signa-
tures of neuromagnetic activation, it is interesting and feasible to
systematically investigate the neuromagnetic biomarkers for
The primary objective of the present study was to determine if
there were any neuromagnetic biomarkers for the visuocortical
development for children. We consider that a biomarker may help
us to accurately identify developmental delays or abnormalities in
the pediatric population. To determine the most reliable age-
dependent VEF components, the data obtained from children were
compared to data recorded from adults with an identical stimula-
tion paradigm. We hypothesized that a comprehensive analysis of
M75, M100 and M145 would reveal at least one component that
changed significantly with age. To achieve this goal, this study fo-
cused on the latency, amplitude and source imaging of neuromag-
netic activation in the visual cortex evoked by pattern-reversal
stimulation. Although M100 is the dominant response in VEFs in
adults, our pilot data have revealed that M75 could be the domi-
nant response in VEFs in children. Thus, the present study analyzed
all three components in children. This study is different from the
previous reports that mainly focused on the response around
100 ms after stimulus presentation (Brecelj et al., 2002). Therefore,
the results of the present investigation may significantly advance
our knowledge about the functional development and matura-
tional changes of the visual cortex.
2. Materials and methods
Sixty healthy normal children (age: 6–17 years, mean age: 11;
30 female and 30 male) and 20 healthy normal adults (age: 19–
49 years, mean age: 30 years; 10 female and 10 male) were studied
with MEG. The children were recruited from the surrounding Cin-
cinnati area. Since these children were developmentally normal
and had no aberrant findings reported from MRI, we considered
that they were representative of the normal population. According
to our previous experience, children under 6 years old were unable
to keep still for 30 min. The children were divided into three
groups, with 20 children in each group: 6–9 years old, 10–13 years
old and 14–17 years old. An informed consent, approved by Insti-
tutional Review Board (IRB) at Cincinnati Children’s Hospital Med-
ical Center (CCHMC), was obtained from each adult subject or from
the parent/legal guardian of each child. Inclusion criteria for partic-
ipation were: (1) healthy, without history of neurological disorder,
psychiatric disease, or brain injury; (2) normal hearing, vision and
hand movement; (3) current age between 6 and 50 years old.
Exclusion criteria for participation: (1) subject could not keep still
or could fit his or her head all the way into the MEG helmet; (2)
subjects with learning and/or speech/language disability; (3) sub-
jects with unidentifiable magnetic noise; and (4) subjects with
claustrophobic tendencies or who were pregnant.
Visual stimuli were generated by BrainX (Xiang et al., 2001), a
program based on DirectX (version 9; Microsoft Inc., Redmond,
WA, USA). The visual stimulus was a black and white pattern rever-
sal checkerboard with a yellow dot fixated in the center. The visual
stimuli were projected through a small hole in the magnetically
shielded room via a XGA portable multimedia projector (model
PLC-XP41, Sanyo Electronics Ltd., Chatsworth, CA). The pattern
reversals were presented binocularly at a distance of 60 cm from
the subject’s eyes and subtended 30 ? 30? of visual angle. The vi-
sual angle of each square (the check) within the checkerboard
was 60 min. The luminance of the white areas was about
40 cd m2. To facilitate source estimation, reversal rate between
the white and black checker was 1 Hz.
2.3. MEG recordings
The MEG signals were recorded in a magnetically shielded room
using a whole-head CTF 275-Channel MEG system (VSM MedTech
Systems Inc., Coquitlam, BC, Canada) in the MEG Center at CCHMC.
Before data acquisition began, three electromagnetic coils were at-
tached to the nasion, left and right pre-auricular points of each
subject. These three coils were subsequently activated at different
frequencies for measuring each subject’s head position relative to
the MEG sensors. Each subject laid comfortably in the supine posi-
tion, his or her arms resting on either side, during the entire proce-
dure. The sampling rate of the MEG recording was 6000 Hz per
channel. (This high sampling rate was used to allow for high-fre-
quency analysis, which is currently being performed in our labora-
tory for another study. This study focused on the magnetic signals
in the 1–100 Hz band.) The data was recorded with a noise cancel-
lation of third order gradients and without on-line filtering. One
hundred trials of binocular presentation were recorded for each
subject. Subjects were asked to keep still. If the head movement
during one recording was beyond 5 mm, the dataset would be indi-
cated as bad and an additional trial would be recorded.
2.4. MRI scan
Three-dimensional Magnetization-Prepared Rapid Acquisition
Gradient Echo (MP_RAGE) sequences were obtained for all subjects
with a 3T scanner (Siemens Medical Solutions, Malvern, PA). Three
fiduciary points were placed in identical locations to the positions
of the three coils used in the MEG recordings, with the aid of digital
photographs, to allow for an accurate co-registration of the two
data sets. All anatomical landmarks digitized in the MEG study
were made identifiable in the magnetic resonance images (MRI).
Y. Chen et al./Clinical Neurophysiology 121 (2010) 1555–1562
2.5. Data analyses
VEFs were investigated via DataEditor (CTF Systems Inc.), a pro-
gram that enables visualization of MEG data. MEG data were aver-
aged and DC-offset corrected with respect to the pre-stimulus
baseline. All channels were overlapped together for identification
of evoked responses (see Fig. 1, for example). The waveform was
then visually inspected for the VEF components. The morphology
of the evoked magnetic responses was analyzed in two steps. The
first step was to identify the number of responses. The second step
was to analyze the shape of the waveforms. We described the
shape of the waveforms as sharp or smooth. The latency and
amplitude of each component were then measured with DataEdi-
tor. We took the peak latency and amplitude of each component
using overlapped waveforms instead of a single channel because
the relative position between the subject’s head and the MEG sen-
sor arrays might vary across subjects. In other words, the best
channel for measuring the peak latency and amplitude of a compo-
nent might vary across the subjects. The measurement with over-
lapped waveform avoided this problem because the DataEditor
automatically searched for the best channel. Latency was mea-
sured in milliseconds (ms) and amplitude in femtotesla (fT), and
both were recorded for each component and subject. Each subject’s
waveform was accompanied by a contour map that indicated the
location of respective responses according to head and MEG sensor
location. DataEditor parameters were set so each subject’s data
were averaged across all trials at a band pass filter of 1–50 Hz.
MEG Processor was used to estimate functional images from the
MEG signals (Xiang and Xiao, 2008). The magnetic signals were
considered to be generated by electrical neural activities, which
are ionic currents. Our wavelet-based beamformer was improved
for the detection of correlated sources. A 3D-head model was cre-
ated with each subject’s MRI. Magnetic sources were scanned at a
resolution of 2.5 mm. MEG results were co-registered to the MRI
data using three complementary fiducial markers with the Mag-
netic Source Locator (MSL) (Xiang et al., 2001).
2.6. Statistical analysis
Statistical comparisons between age groups in terms of re-
sponse latency and amplitudes were performed with the two-sam-
computed for age and the latency and amplitude of M75, M100
and M145 components. Developmental changes in response la-
tency, amplitude and neuromagnetic source activation were char-
acterized by using linear least squares regression analysis for both
the children and the adult group data. The latency ratio of M100/
M75, M100/145 and M75/M145 and the amplitude ratio of
M100/M75, M100/M145 and M75/M145 were also analyzed with
Student’s t-test as well as linear least squares regression analysis
with respect to age. The threshold of statistical significance for dif-
ferences was set at p < 0.01. For each comparison between two age
groups there were 12 measures being tested. Therefore, a Bonfer-
roni multiple comparisons correction was applied to the data to ac-
count for these multiple tests, more specifically, response latency
and amplitude, source localization and size of beamformer images.
MEG sourceestimation statistical
computing the distance between the sources. The Euclidean dis-
tance between two points (X1, Y1, Z1) and (X2, Y2, Z2) is
we determined that each coordinate could have as much as
0.25 U of noise associated with it. For example, the difference
between two X-coordinates could be as much as 0.5 U closer
than the raw difference would indicate. As a result, the
following conservative distance measure using this adjustment
for each ofthethree
tistical analyses were performed using SPSS version 15.0 for
Windows (SPSS Inc., Chicago, IL, USA) and SAS version 9.1 for
Windows (SAS Institute Inc., Cary, NC, USA).
ðX1? X2Þ2þ ðY1? Y2Þ2þ ðZ1? Z2Þ2
. In order to be conservative,
The waveforms revealed that at least three responses (deflec-
tions) were elicited by pattern-reversal stimulation. Fig. 1 shows
typical waveforms at four age groups. Small and sharp responses
in middle latencies were observed in the youngest age group
(6–9 years of age) but not in the older children or adults.
Three prominent neuromagnetic responses were identified at
77 ± 8 ms (M75), 111 ± 9 ms (M100) and 150 ± 11 ms (M145) for
children and 75 ± 7 ms (M75), 102 ± 9 ms (M100) and 153 ±
17 ms (M145) for adults. The results of the latencies of the three
components were summarized in Fig. 2. In the 60 children, the
latency of M100 decreased with age (p < 0.01). In addition, the
latency of M75 also decreased with age (p < 0.01). However,
the 20 adults did show a clear age-dependent decrease of latency.
Fig. 1. Representative MEG waveforms showing neuromagnetic components of
each age group. Each age group reveals all three components (M75, M100 and
M145). The amplitude is indicated with a scale (50 fT). The Y-axis indicates ages in
years; the X-axis indicates the latency in milliseconds (ms). Noticeably, the
amplitude and latency of the three components change with age significantly.
Y. Chen et al./Clinical Neurophysiology 121 (2010) 1555–1562
MEG data from children showed that the amplitude of M75 de-
creased with age (p < 0.01) while the amplitude of M100 increased
with age (p < 0.01). Strikingly, the amplitude of M145 did not line-
arly change with age. Instead, the amplitude of M145 increased
with age from 6 to 12 years of age and then decreased with age.
The MEG data from adults showed that M100 was consistently
the prominent response without a clear age-dependent change.
The developmental patterns of the amplitudes of the three compo-
nents are summarized in Fig. 3.
Fig. 2. Scatter plot of the peak latencies of the M75, M100 and M145 components
relative to chronological age of the children. Linear regression lines, using the least-
squares method, are also plotted to show general trends for each component. The
M100 components show a clear developmental change with the highest correlation
coefficient. The Y-axis indicates the latency of responses in milliseconds; the X-axis
indicates the age of children in years.
Fig. 3. Scatter plot of the peak amplitudes of the M75, M100 and M145 components
relative to chronological age of the children. General trends are also plotted for each
component. Noticeably, the amplitude of M75 and M100 changes with age linearly.
The amplitude of M145 changes with age nonlinearly and forms an ‘‘n-shaped”
pattern. The Y-axis indicates the amplitude of responses in milliseconds; the X-axis
indicates the age of children in years.
Y. Chen et al./Clinical Neurophysiology 121 (2010) 1555–1562
We analyzed the amplitude ratio for the three components. The
results revealed that the amplitude ratio of M100 to M75 (M100/
M75) strongly correlated with age (r = 0.61, p < 0.001). However,
there was no strong correlation between the amplitude ratio of
M100/M145 and M75/M145. The amplitude ratio of M100/ M75
is shown in Fig. 4. We also analyzed the latency ratio of M100/
M75, M100/M145 and M75/M145; however, the results did not
show a clear age-dependent change of latency ratio for children
(see Fig. 4).
3.4. Source localization
The results of source estimation revealed that the M75, M100
and M145 were generated in the left and right striate and extras-
triate cortex for children and adults. There was no age-dependent
change in terms of source localization in X-, Y- and Z-coordinates.
Magnetic source imaging from representative participants is
shown in Fig. 5. Since wavelet-based beamformer provided 3D
images about VEFs, we computed the dimensional differences be-
tween the MEG beamformer images in the left and right occipital
cortices. Although the dominant occipital cortex varied across chil-
dren, the results indicated that there was a significant age-depen-
dent increase of dimensional difference between the MEG
beamformer images in the left and right occipital cortices for
M75 and M145 (r = 0.47 and 0.46, respectively, p < 0.01). However,
there was no age-dependent dimensional change of the MEG
beamformer images for M100 (p > 0.05). The maturational changes
of beamformer images in the child’s brain are shown in Fig. 6.
This study investigated the visuocortical development through
VEFs. MEG has recently entered routine clinical applications in
pediatrics (Hari, 1996; Nakasato et al., 1996). Previous publications
have demonstrated that MEG is a reliable noninvasive technology
for the study of the development of brain function and/or the iden-
tification of functional impairment (Nakasato et al., 1996; Ander-
son et al., 1999). Dimensional estimation of brain activation with
wavelet-based beamformer is a relative new method (Xiang and
Xiao, 2008). However, previous investigations of brain function in
the somatosensory and auditory cortices have shown that wave-
let-based beamformer is a robust method (Kotecha et al., 2008,
2009). To analyze the developmental changes of VEFs from small
children to adolescent to adults, we included an adult group as a
matured control. According to previous reports and our data, VEFs
in adults aged 19–49 years are relatively stable (Nakasato et al.,
1996; Anderson et al., 1999). Consequently, the variation of VEFs
in adults and the effects of stimulation parameters on VEFs were
not addressed in this paper because this study focused on develop-
mental changes. We consider the results of the present study are
interesting and important for the understanding of the maturation
of visual function in children.
4.1. Morphology age-dependence
The results of the present study demonstrated that the VEFs in
children were distinctly different from those in adults. M100 was
the prominent response in adults; however, M100 could be very
small in children. Our results showed that in children, M75 or
M145 might be a more prominent indicator of visual function than
M100 in small children (<9 years old). This finding could poten-
tially affect the applications of MEG in research and clinical prac-
tice in at least two areas: (1) the M75/M145 response may in
fact be the most obvious and robust neuromagnetic markers in
the developing visual cortex; (2) it is probably more reliable to
use M75/ M145 instead of M100 for identifying visual develop-
mental delays and/or abnormalities in children younger than
9 years old. Thus, the results of the present study highlight the
importance of M75 and M145 in the clinical applications of MEG
4.2. Latency age-dependence
The present results suggest that the latency of the M100
changes with age. These results are strongly supported by previous
EEG studies (Brecelj et al., 2002). Brecelj and colleague have re-
vealed that the latency of VEP changes with age. It seems that chil-
dren show adult-like waveforms by the age of 17 years old, after
which developmental trends were not observed. Our results
highlight the potential for M75 and M145 to become accurate
indicators of visual function development. Although there was in-
ter-individual variation, there was a clear tendency of decreasing
latency in VEF responses. In other words, the visual responses
tended to get faster with age.
Fig. 4. Scatter plots of the latency ratio (LR) and the amplitude ratio (AR) of the M75
and M100 components relative to chronological age of the children. General trends
are also plotted for each component. Noticeably, the LR does not change with age
linearly. However, the AR changes with age linearly. The Y-axis indicates the ratio
(LR or AR) of the responses; the X-axis indicates the age of children in years.
Y. Chen et al./Clinical Neurophysiology 121 (2010) 1555–1562
Our results indicate that the visual pathway continues to ma-
ture from the age of 6 to 17 years. Previous VEP reports have re-
vealed the maturational changes in infants (Birch and O’Connor,
2001). The present study illustrates the maturational changes in
children and adolescents. These findings imply that visual pathway
maturation may take longer than suggested in some VEP studies.
Moskowitz and Sokol (1983) showed that P100 latency was
adult-like by about 1 year of age to large and to small checks by
5 years of age. McCulloch and Skarf (1991) reported even earlier
P100 maturation, by 5 months to large checks and by 2 years to
small checks. Allison et al. (1983) showed that P100 decreased
steadily until adulthood. Several other authors have also found that
P100 latency approaches the adult level by the age of about
20 years (Shaw, 1984; Allison et al., 1984; Emmerson-Hanover
et al., 1994). Therefore, the P100 latency decrease suggests that,
in clinical work, it is important to consider that the upper limit
of P100 latency is longer in school children than in adults. The mat-
urational patterns in the visual systems of children could be used
to identify developmental delay or impairments in the visual sys-
tem in pediatric populations.
4.3. Amplitude age-dependence
The amplitude of the M75, M100 and M145 changed with age.
However, the change patterns were different: the amplitude of
M75 decreased with age while the amplitude of M100 increased
with age. Interestingly, the amplitude of M145 showed a clear
‘‘n-shaped” pattern with a turning point around 9–13 years of
age (see Fig. 3). Although the underlying neural mechanisms
affecting this phenomenon remain unclear, the results indicate
that the visual cerebral cortex is developing from age 6 to age
17. Age-dependent amplitude changes are strongly supported by
previous VEP reports (Brecelj et al., 2002). It seems that age-
matched evaluation of VEFs in clinical work is important.
One of the novel findings in the present study was the ampli-
tude ratio of M100/M75. The amplitude ratio was very important
to us because we considered that it is not affected by head size.
Due to the development of the brain, the size of children’s heads
varies among age groups. To minimize this problem, amplitude ra-
tio is a reliably alternative method. It is well known that magnetic
signals are not significantly affected by the skull, skin and other tis-
Fig. 5. Magnetic source imaging (MSI) from representative children shows that the M75, M100 and M145 components are localized to subareas of the visual cortex. The
locations of M75 and M145 are far from the location of M100. In addition, the source dimension of M75 and M145 lateralizes with age. However, the dimension of
beamformer images of M100 seems symmetric across all age groups.
Y. Chen et al./Clinical Neurophysiology 121 (2010) 1555–1562
sues. Nevertheless, an increase of distance between the cerebral
cortex and the MEG sensor arrays caused by a change in the size
of the head may decrease the absolute value of the amplitude.
However, this linear change can be cancelled out by computing
the amplitude ratio because the changes in all the components
for a subject should be the same. Thus, we consider that the ampli-
tude ratio change of the VEFs is a robust biomarker for the matu-
ration of visual cortex. Our results are strongly supported by
several previous reports with alternative neuroimaging modalities.
Synaptic density and cortical extent were reported to reach adult
values by the age of 11 years (Huttenlocher et al., 1982; Garey de
Court, 1983). Studies with positron emission tomography (PET)
indicate that maturation of the human visual cortex is protracted,
even at the age of 16–18 years (Chugani et al., 1998). It seems
therefore, that our finding of maturation of VEFs correlates quite
well with the PET studies.
4.4. Source activation age-dependence
The present results have demonstrated that all three compo-
nents are probably generated from the occipital visual cortex.
However, M100 is probably generated from a subarea, which is dif-
ferent from that for M75 or M145. There was no developmental
change in terms of source localization of the three components.
This finding is consistent with many previous reports (Allison
et al., 1983; Shaw, 1984). Previous findings obtained from invasive
recordings in humans or in animal experiments have found that
M75 is generated by neurons around the calcarine fissures (Schroe-
der et al., 1991). Schroeder and colleagues have found that the
monkey’s N50 (which corresponds to human M75) is generated
primarily by current sinks in the lamina 4C of the striate cortex,
whereas the monkey’s P60 (which corresponds to human M100)
arises from the large current sources in the supragranular laminae.
Taken together, M75 and M100 are probably generated by different
subgroups of neurons in the occipital cortex and reflect different
responses to visual inputs.
Previous reports have shown that M100 (or P100 in VEP) is gen-
erated in the occipital cortex (Allison et al., 1983; Shaw, 1984).
However, the exact locations remain controversial. Barrett and col-
leagues consider that P100 is generated in the striate cortex (Bar-
rett et al., 1976; Haimovic and Pedley, 1982; Ducati et al., 1988)
while Lehmann and colleagues proposed that it originates in the
extrastriate cortex (Lehmann and Soukos, 1982). In our study,
M100 was localized in the cortex around the calcarine fissure. Our
results are consistent with the findings of the direct recording from
the human occipital cortex (Ducati et al., 1988; Noachtar et al.,
attention due to its small amplitude in adults. However, M145 was
found to be prominent in some children. The source localization of
M145 was considered as different from the M100 source. It is more
than likely that M145 was generated in the extrastriate cortex. This
current direction of the estimated dipoles of M145 was different
from that of M100 (Shigeto et al., 1998).
The most interesting finding in source localization was the lat-
eralization of the dimension of the MEG beamformer images in the
left and right visual cortices. It seems that the dimensional differ-
ences between the left and right occipital cortices for M75 and
M145 are potential biomarkers for the maturation of the visual
function. Although our data did not show consistent dominant
sides, the results did reveal that one visual cortex had more activa-
tion than the other did. Expanding our protocol to a greater num-
ber of children in each subgroup might help to clarify further these
more subtle developmental changes. In addition, an improved
stimulation paradigm such as a serially presented visual stimulus
may result in better results.
It is necessary to point it out that the correlation between func-
tional dimension determined by wavelet-based beamformer and
the true extent of activated cortex needs further investigation
and verification. The changes in source dimension estimated by
wavelet-based beamformer could be affected by signal-to-noise ra-
tio, source orientation as well as the correlated sources. To mini-
mize the effect of signal-to-noise ratio, the present study
excluded subjects with identifiable magnetic noise. In addition,
we obtained individual MRI’s from each participant to confirm that
the sources were localized in occipital cortex. If the signal-to-noise
ratio greatly affected the results, the source imaging would localize
randomly within or around the head. In the present study, the
dimensional estimation was restricted to neuromagnetic activa-
tion, which was consistently localized in the occipital cortex. To
address the source orientation issue, the present study used ‘‘real
head model” based on individual MRI with multiple local spheres.
Since a head can hardly be a perfect sphere, the orientation prob-
lem could be minimized. In addition, our data analysis used a time
window and multipolar sources (Jerbi et al., 2004). We hope those
approaches minimize the effects of source orientation. Impor-
tantly, the present study used a ‘‘whole-head” MEG system. There
Fig. 6. Scatter plots of the left and right (LR) dimensional differences of beamformer
images for M75 and M145 relative to chronological age of the children. The
dimensional differences are the differences of the estimated functional activation in
the left and right (‘‘LR”) occipital cortices. General trends are plotted for each
component. Noticeably, the dimensional differences of the two components change
with age linearly. The Y-axis indicates the dimensional differences; the X-axis
indicates the age of children.
Y. Chen et al./Clinical Neurophysiology 121 (2010) 1555–1562
were 275 sensors around the head. If a source was oriented radially Download full-text
to one group of sensors, the source must be tangential to others
sensors. More specifically, if a source was oriented radially to back
sensors, the source must be tangential to the top, left and right sen-
sors. To address the effect of correlated sources on wavelet-based
beamformer, auditory evoked magnetic fields have been studied
and reported (Kotecha et al., 2009). Since the present study focuses
on the applications of MEG in the study of visual functional devel-
opment, further discussion of those methodological issues might
be beyond the scope of this paper. Thus, dimension observed in
the beamformer images, as a separate measure of visual system
development, may not necessarily reflect the cortical extent of
the source activation.
In summary, our data suggest the maturation of the visual sys-
tem continues up to 17 years of age. The maturation changes of the
visual system can be found in the morphology, latency and ampli-
tude of the VEF waveforms as well as the dimension of MEG beam-
former images. The latency and amplitude ratio of M75, M100 and
M140 are potential biomarkers for the study of visual function in
the child’s brain. Our results lay a foundation for identification of
visual function deficits and developmental delay in the developing
brain with various disorders such as epilepsy.
This study was supported by a Trustee Grant to Dr. Jing Xiang
from Cincinnati Children’s Hospital Medical Center, Cincinnati,
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