Biomedizinische Technik, 46 Suppl. 2: 242-244.
Statistical discrimination of controls, schizophrenics, depressives and
alcoholics using local magnetoencephalographic frequency-related
Fehr T., Wienbruch C., Moratti S., Rockstroh B., and Elbert T.
University of Konstanz, Konstanz, Germany
. Multiple source activity in the slow wave and alpharange was detected by the minimum-norm method [6,7].
Atypically enhanced activity in the delta and theta EEGfrequency bands has frequently been reported for schizo-
phrenic patients, while alpha activity is often attenuatedin these patients [2,9,10,12]. MEG and EEG data provide
30 schizophrenic (predominantly paranoid or
an advanced approach to analyze complex brain
disorganized schizophrenia, 12 female, mean age
functioning and to examine differences between different
31.1±8.6 years, 25 right-handed, 5 left-handed, 24
psychiatric patient groups due to their brain activity. Past
medicated, 6 unmedicated), 10 depressive (7 female,
analyses using different physiological parameters to
mean age 47.5±7.6 years, 9 right-handed, 1 left-handed, 8
discriminate a psychiatric patient group from controls
medicated, 2 unmedicated) and 12 alcoholic patients (1
reached statistical correct classification rates of at
female, mean age 39.7±10.9 years, 11 right-handed, 1
maximum 80 percent. Results usually shifted to chance
left-handed) and 18 healthy controls (2 female, mean age
when adding a third group to the analysis. Winterer
31.7±12.4 years, all right-handed) served as subjects
(2000) , for example, could discriminate between
during a resting, a mental calculation and a mental
schizophrenic patients and controls with a correct
imagination condition (each in a 5 minute epoch).
classification rate of 77 percent when using delta power,
In the resting
period, subjects were asked to relax but
signal power at Cz and power values of the high alpha
stay awake and not to engage in any specific mental
range as variables in a discriminant analysis. Including a
activity; in the mental arithmetic
period, subjects were
group of depressive patients in the analysis reduced the
asked to translate the words of a common German
correct classification rate to 50 percent. Gallhofer (1991)
folksong letter by letter into numbers (´a´ corresponding
 used 50 topographical frequency-related EEG-para-
to 1, ´b´ = 2, ´c´ = 3 etc.) and total them up; in the mental
meters in a discriminant analysis with schizophrenic and
condition, subjects were asked to imagine as
depressive patients and controls. He classified 49 out of
vividly as possible walking a well-known and recently
strolled footpath, e.g. through the hospital area.
Strategies that try to describe the physiological substrate
Data were obtained from magnetoencephalographic re-
of psychiatric diseases with only a few parameters
cordings (148-channel whole-head neuromagnetometer,
possibly over-simplify the nature of the phenomenon [see
MAGNES WH 2500, 4D Neuroimaging, San Diego,
also 5]. More complex strategies are possibly more
USA) with a 678.17 Hz sampling rate, using a band-pass
adequate to describe complex phenomena such like
filter of 0.1-200 Hz. Subjects were asked to fixate on a
colored mark on the ceiling of the chamber in order to
The present study examined to what extent delta-, theta-
avoid eye- and head-movement. For artifact control, eye
and alpha-band-related source space activity can separate
movements (EOG) were recorded from four electrodes
controls, schizophrenics, depressives and alcoholics by
attached to the left and right outer canthus and above and
discriminant analysis. The analyses are meant as a first
below the right eye. The electrocardiogram (ECG) was
step towards an evaluation of a set of physiological
monitored via electrodes attached to the right collarbone
parameters that could possibly be representative of
certain psychiatric gross groups. In order to explore
For each of the measured epochs the data were band-pass
possible methods sensitive to these physiological
filtered in the delta [1.5-4.0 Hz], theta [4.0-8.0 Hz] and
parameters, different strategies of MEG source space
alpha [low: 8.0-10.5 Hz; high: 10.5-13.0 Hz] band, and
analysis and statistical procedures were performed on
the number of sample points was reduced by a factor of
data obtained during three different mental modalities
16 prior to further source analyses.
(rest, mental calculation and mental imagery).
The multiple source activity
was located employing sour-
Enhancement in focal  as well as in multiple  slow
ces by means of the minimum-norm
wave activity has been reported for schizophrenic
(L2-norm) [6,7] for the delta, theta and alpha range. Two
patients. A reduction of alpha activity has been reported
strategies were realized: MN1)
Over all data time points
for schizophrenic [10,12] and alcohol  patients as well.
with a global field power between 3000 and 18000 [ft]
For the analysis of focal sources we performed the dipole
that did not correlate with a prominent eye-blink pattern a
density method that has been shown as a valid tool in the
MMN solution was calculated. The solutions were then
vicinity of the detection of pathological attributed slow
averaged over all time points; MN2)
wave activity for example around tumors  or lesions
commonly occurring topographies (identified by a sepa-
Biomedizinische Technik, 46 Suppl. 2: 242-244.
rate correlational analysis - reported elsewhere - , only for
the delta and theta range): the analysis was repeated,
– delta and theta band (each 10 regions)
using only the 20 time points (topographies) with the
strongest GFP. The resulting MMN-Maps of both strate-
gies MN1 and MN2 were then divided in 10 regions (see
Focal slow wave activity
was determined by the dipole
(DD) for the delta and theta range.
Artifact-free time segments were determined by visual
inspection. Single equivalent current dipoles in a
homogeneous sphere were fitted for each time point in
– delta, theta and alpha*) band (each 10 regions)
the selected epochs. Only dipole fit solutions at time
points with a root mean square 100 fT <
i)2)) < 300 fT and with a goodness of fit
(GOF) greater than 0.90 were accepted for further
analysis. These restrictions should ensure that neither
artifacts nor small amplitude biological noise would
affect the results, and that only dipolar fields that were
generated by focal sources were analyzed. The
percentage of dipoles fitted per second in a particular areawas submitted to the statistical analyses. The source
Tab. 1: results of the discriminant analyses (first root of
space data of the DD were divided into 10 voxels, five in
the discriminant function) for the different combinations
each hemisphere: prefrontal, frontal, temporal, parietal
of the source related variables (see text); DD=dipole
density, MN1, MN2=minimum-norm strategy 1 and 2
Standard discriminant analyses were performed
(see text); *) alpha low and alpha high were calculated
separately for the slow wave related source values of each
only for MN1 and added to the slow wave related source
model (DD, MN1 and MN2) and condition (20 regional
variables of the models DD, MN1 and MN2.
source variables due to the delta and theta range). In a
discriminant functions ranged between 90 and 99 percent.
second step all the models were added up by the multiple
In a third step for all discriminant models the amount of
alpha source values (alpha low and high, each band 10
included variables were stepwise reduced. Only one
regional source variables) estimated by the MN1 strategy.
discriminant model could be improved by cancelation of
In a third step the amount of variables in each
discriminant model was stepwise reduced oriented on thepartial significance levels of the variables. The reductionended at that point when the models became worse (dueto their correct classification rates).
In a first step 20 frequency related regional sourcevariables (for the delta and theta frequency range) wereincluded in discriminant analyses for the different models(DD, MN1 and MN2, see methods) separately for eachcondition. The discriminant functions for the DD methoddid not reach significance (see table 1 for the results indetail) for all conditions. The discriminant function forthe MN1 and the MN2 methods reached significance forthe rest and the mental calculation condition and showeda trend for the imagination condition (see table 1). Thedifferent groups could be separated comparably well with
Fig. 1: plotted loadings of single subjects (see legend for
a correct overall classification rate about 70 percent.
group identification) on the different roots of a
In a second step all models were added up by 20 regional
discriminant function (1st vs 2nd root and 1st vs 3rd root)
source space variables of the lower and higher alpha band
including 32 frequency band related source variables
(model MN1, see methods). For the DD slow wave
(model MN1, see text) and the corresponding
variables in combination with the 20 MN1 alpha
variables the discriminant function for the rest conditionwas significant (see table 1 for the results in detail). For
A stepwise reduction of variables led to a model with 32
the multiple slow wave variables (MN1 as well as MN2)
variables estimated by the minimum-norm method (in the
in combination with the 20 MN1 alpha variables all
rest condition, model MN1) that discriminated all three
discriminant functions were significant (see table 1). The
patient groups and the controls with a correct
overall correct classification rates of the calculated
classification rate of 100 percent (see table 2 and figure
Biomedizinische Technik, 46 Suppl. 2: 242-244.
1). All regional delta (mainly left prefrontal, temporal and
left occipital) and theta (mainly left prefrontal, left andright temporal and right occipital) and some alpha low
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Tab. 2: results of a stepwise discriminant analysis (first
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root of the discriminant function) for 32 source related
Rockstroh, B. (2001): Source distribution of neuromagnetic
variables of model MN1 (see text).
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present study have to be interpreted carefully because of
 Winterer, G., Herrmann, W.M. (1995): Über das
the relatively small subject samples. The results should
Elektroenzephalogramm in der Psychiatrie: Eine kritische
be replicated with bigger patient groups. A next step
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would be another important aspect that has to beconsidered carefully in further research.
Research was supported by the Deutsche Forschungsgemein-
The present explorative work offers a set of physiological
schaft. We thank Drs. K. Pröpster, H. Watzl, W. Höcker, A.
variables that could be hypothetically tested in different
Schiller, B. Schuller and P. Rössner for accomplishing the
patient groups and provides a promising toolbox of
diagnostics and clinical status of the patients.
strategies for analyzing frequency-related data on thebasis of functional magnetic source imaging.
Correspondence: [email protected]
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