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because we cannot guarantee all curves have an
increase trend in reality. But more than half of curves
having the property is enough to draw the conclusion.
However, if we raise more strict constraint on /, e.g.,
/ [ 70 %, then some of seizures do not have an
increase trend based on this strict constraint. It should
be pointed out that the last segment of correlation or
phase synchrony curve is only approximately defined;
that is, there is no exact definition for the starting time
instant and the ending time instant (clinic seizure
onset) of the last segment, due to the complexity of
seizures. The general rule for selecting the starting
time instant is to make sure the last segment has an
obvious larger mean value than other segments of the
same length in the early time period. In this study, the
optimal channel of the same patient is same for all
possible macroseizures.
Now for more clearness we summarize the detailed
process in D: (1) Define the last segment of correlation
or phase synchrony curves; (2) check if there is an early
time period satisfying the two requirements in D for all
correlation or phase synchrony curves. If so for one
correlation or phase synchrony curve, then this curve
has an increase trend before the macroseizure onset. If
the ratio / C 50 % based on the optimal channel, then
the seizure has an increase trend before the macrosei-
zure onset for correlation or phase synchrony metric.
Results
In this section we present results for three representative
epilepsy patients in detail and make a summary of corre-
lations and phase synchronies of microwire iEEGs for 24
seizures from 8 epilepsy patients. All iEEG traces were
created using EEGLAB (Delorme and Makeig 2004).
Patient 1
For one seizure of Patient 1 we report the detailed results
including the description of the last segment. 50 s macro-
wire iEEGs and 100 s micro iEEGs are presented in
Fig. 1a, b respectively where the macroseizure onset is at
740 s of MacroMF3 and earlier microseizure activities can
be observed on MicroMT09–11. Figure 1c presents 16 ICs
by applying fastICA algorithm (Hyvarinen and Oja 2000)
to 16 microwire iEEGs in Fig. 1b. Earlier microseizure
activities on IC11 and IC15 are very clear. Correlations
(phase synchronies are very similar to correlations and
omitted here) between MacroPT3 with all other macrowire
channels in ripple band are plotted in Fig. 1d from which
one can find that all correlations decrease before the
macroseizure onset 740 s. The decrease trend for phase
synchrony before seizure onset in macro domain widely
exist (Mormann et al. 2003a, b). Correlations and phase
synchronies of MicroMT02 with other 8 microwire chan-
nels (MicroPF01–05, 07, 08, and 11) are presented in
Fig. 1e, f, respectively. All these curves satisfy the strict
criteria, that is, mean value of the defined last segment (see
Fig. 2a) covering 587–740 s (i.e., 153 s) for each curve is
greater than that of previous any segment of the length of
153 s ([100s) in the interval [0, 587] which is the early
time period (the ratio q = 587/153 = 3.84 [ 3, so the
early time period satisfies the requirements in D of Meth-
ods section and as a result, all these curves have an increase
trend). All other curves are not included in Fig. 1e, f
because they do not satisfy the strict criteria. Comparing
Fig. 1e, f, both of correlation and phase synchrony are very
similar and the only difference is that phase synchrony is
smoother than correlation. All these curves in Fig. 1e, f
have an increase trend before the macroseizure onset time
at 740 s. Since 8 curves among total 15 curves (so, the ratio
/ = 8/15 [ 50 %) have an increase trend before the sei-
zure onset time at 740 s, we can conclude that both of
correlation and phase synchrony have an increase trend
before the macroseizure onset time at 740 s in micro
domain. This finding of increase trend for correlation or
phase synchrony before the macroseizure onset is totally
different from the above result in macro domain. Figure 1g
presents correlation between IC7 and IC15 which follows
the same pattern as Fig. 1e. It shows that these two ICs are
two major sources causing the increase trend. So, the
increase trend demonstrates the progressive coalescence
(or spread process) from source IC15 to source IC7. It is
only when the seizure has recruited enough surrounding
brain tissue does the signal become strong enough to be
observed on the clinical macroelectrode. For this patient, it
is noted that microseizure activities start at 587 s on
Micro09–11 (omitted here) and cause that correlation or
phase synchrony starts to increase from 587 s.
Fig. 1 Patient 1: a A 50 s sample of macrowire iEEGs where the
macroseizure onset is at 740 s of macroMF3. b A 100 s sample of
microwire iEEGs where microMT9–11 have earlier microseizure
activities. c ICA generates 16 independent components, IC1-16 from
microwire iEEGs. d Correlations of macroPT3 with all other
macrochannels in ripple band. Before the seizure onset at 740 one
can see decrease trend which is a well-known result in macro domain.
e Correlations of microMT02 with other 8 microchannels (mi-
croPF01–05, 07, 08, and 11) in ripple band. f phase synchronies of
microMT02 with other microchannels (microPF01–05, 07, 08, and
11) in ripple band. It is clear that increase trend can be found before
the seizure onset at 740 s for both correlation and phase synchrony
which are similar. g Correlations between IC7 and IC15. One can see
the obvious increase trend before the seizure onset, which demon-
strates that these two ICs are two major sources causing increase
trend. ICA independent component analysis
c
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