To detect extremely small magnetic fields generated by the human brain, currently all commercial magnetoencephalography (MEG) systems are equipped with low-temperature (low-Tc) superconducting quantum interference device (SQUID) sensors that use liquid helium for cooling. The limited and increasingly expensive supply of helium, which has seen dramatic price increases recently, has become a real problem for such systems and the situation shows no signs of abating. MEG research in the long run is now endangered. In this study, we report a MEG source localization utilizing a single, highly sensitive SQUID cooled with liquid nitrogen only. Our findings confirm that localization of neuromagnetic activity is indeed possible using high-Tc SQUIDs. We believe that our findings secure the future of this exquisitely sensitive technique and have major implications for brain research and the developments of cost-effective multi-channel, high-Tc SQUID-based MEG systems.

5.
T. H.
Sander
,
J.
Preusser
,
R.
Mhaskar
,
J.
Kitching
,
L.
Trahms
, and
S.
Knappe
,
Biomed. Opt. Express
3
,
981
(
2012
).
6.
C.
Johnson
,
P. D. D.
Schwindt
, and
M.
Weisend
,
Appl. Phys. Lett.
97
,
243703
(
2010
).
7.
J.
Nenonen
,
J.
Montonen
, and
T.
Katila
,
Rev. Sci. Instrum.
67
,
2397
(
1996
).
8.
N.
Kasai
,
K.
Sasaki
,
S.
Kiryu
, and
Y.
Suzuki
,
Cryogenics
33
,
175
(
1993
).
9.
K.
Yokosawa
,
A.
Tsukamoto
,
D.
Suzuki
,
A.
Kandori
,
T.
Miyashita
,
K.
Ogata
,
Y.
Seki
, and
K.
Tsukada
,
Supercond. Sci. Technol.
16
,
1383
(
2003
).
10.
Y.
Zhang
,
N.
Wolters
,
D.
Lomparski
,
W.
Zander
,
M.
Banzet
,
J.
Schubert
,
H.-J.
Krause
, and
P.
VanLeeuwen
,
IEEE Trans. Appl. Supercond.
15
,
631
(
2005
).
11.
S. H.
Liao
,
S. C.
Hsu
,
C. C.
Lin
,
H. E.
Horng
,
J. C.
Chen
,
M. J.
Chen
,
C. H.
Wu
, and
H. C.
Yang
,
Supercond. Sci. Technol.
16
,
1426
(
2003
).
12.
X. H.
Zeng
,
H.
Soltner
,
D.
Selbig
,
M.
Bode
,
M.
Bick
,
F.
Rüders
,
J.
Schubert
,
W.
Zander
,
M.
Banzet
,
Y.
Zhang
,
H.
Bousack
, and
A. I.
Braginski
,
Meas. Sci. Technol.
9
,
1600
(
1998
).
13.
Y.
Zhang
,
Y.
Tavrin
,
M.
Mück
,
A. I.
Braginski
,
C.
Heiden
,
S.
Hampson
,
C.
Pantev
, and
T.
Elbert
,
Brain Topogr.
5
,
379
(
1993
).
14.
H.-J.
Barthelmess
,
M.
Halverscheid
,
B.
Schiefenhovel
,
E.
Heim
,
M.
Schilling
, and
R.
Zimmermann
,
IEEE Trans. Appl. Supercond.
11
,
657
(
2001
).
15.
F.
Öisjöen
,
J. F.
Schneiderman
,
G. A.
Figueras
,
M. L.
Chukharkin
,
A.
Kalabukhov
,
A.
Hedström
,
M.
Elam
, and
D.
Winkler
,
Appl. Phys. Lett.
100
,
132601
(
2012
).
16.
M. I.
Faley
,
U.
Poppe
,
R. E.
Dunin-Borkowski
,
M.
Schiek
,
F.
Boers
,
H.
Chocholacs
,
J.
Dammers
,
E.
Eich
,
N. J.
Shah
,
A. B.
Ermakov
,
V. Y.
Slobodchikov
,
Y. V.
Maslennikov
, and
V. P.
Koshelets
,
IEEE Trans. Appl. Supercond.
23
,
1600705
(
2013
).
17.
M.
Faley
,
U.
Poppe
,
R. D.
Borkowski
,
M.
Schiek
,
F.
Boers
,
H.
Chocholacs
,
J.
Dammers
,
E.
Eich
,
N.
Shah
,
A.
Ermakov
,
V.
Slobodchikov
,
Y.
Maslennikov
, and
V.
Koshelets
,
Physics Procedia
36
,
66
(
2012
).
18.
In order to calibrate the high-Tc SQUID signal output, we performed noise measurements of about 2 min duration using both low- and high-Tc SQUID systems, simultaneously. After downsampling to 60 Hz, correlation analysis was applied to signal recordings from the high- and low-Tc SQUID system. The low-Tc SQUID sensor (A5 at the top of the helmet), which was orientated similarly to the high-Tc SQUID sensor, revealed a correlation coefficient of about 0.99. From these measurements, the signal output of the high-Tc SQUID system translates to ≈1 pT/mV.
19.
Each high-Tc SQUID measurement location was defined by the location of the electrode position of the electroencephalography (EEG) cap from EASYCAP (EASYCAP GmbH, Berlin, Germany), which the subject was wearing without EEG electrodes. Before the measurement, the subject's head, including the electrode locations of the EEG cap, was digitized using a 3D digitizer (Polhemus, 3Space/Fastrak, USA) to define a head coordinate system. For a comparison of the source analysis between the two systems, coordinates from the high-Tc SQUID measurements were aligned with one of the low-Tc SQUID sensors. This was done by minimizing the distance between a line normal to the low-Tc SQUID sensor and the electrode location from the EEG cap where the high-Tc SQUID sensor was placed. To correct for the high-Tc SQUID sensor-to-head distance, each sensor coordinate was shifted in a normal direction by 20 mm (which was the approximate head to high-Tc SQUID sensor distance), assuming the electrode locations are distributed on a spherical surface. With this procedure, we derived a virtual sensor configuration comprising all high-Tc SQUID channel positions.
20.
TFA was applied using the Python derivate of the MNE toolbox (http://martinos.org/mne). Each period of the task “eyes open” and “eyes closed” was limited to 7 s; to avoid interference due to the instruction of the task change, 1 s at the beginning and one at the end of each block was skipped. For each condition (eyes open vs. eyes closed), a total of 9 epochs with 7 s duration were used to calculate an average spectrogram. For comparisons between the two systems, the MEG signals were normalized to unit variance prior to analysis.
21.
Artifacts in the signal of the high-Tc and low-Tc SQUID recordings were identified by using a peak-to-peak measure applied to the full data set using a sliding window of 200 ms length. With respect to the signals recorded with the whole head system, we used a peak-to-peak threshold of ≥8 pT, whereas a threshold of about 15pT(15mV) was used for the high-Tc SQUID recordings. The reason for the lower threshold used for the low-Tc SQUID system is that data recorded by that system include an online noise compensation. After artifact removal, MEG data from the auditory experiment were bandpass filtered from 3 to 30 Hz including a notch filter at the power line frequency of 50 Hz. Trials around stimulus onset were defined with 1 s length and a pre-stimulus time of 400 ms. On average, 293 and 294 trials were left after discarding trials with artifacts or unusually large amplitudes for the low- and high-Tc SQUID recordings, respectively.
22.
T.
Lypchuk
,
Dipole Fit Algorithms for MEG Analysis
(
Biomagnetic Technologies, Inc.
,
San Diego, USA
,
1990
).
23.
GoF=1(mmeasmfit)2/(mmeas)2.
24.
D.
Sheng
,
S.
Li
,
N.
Dural
, and
M. V.
Romalis
,
Phys. Rev. Lett.
110
,
160802
(
2013
).
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