DEVELOPMENTAL THETA RESPONSE
117
values of the identified extrema were stored.
This step is illustrated in Figure la where sev-
eral representative single sweeps are shown.
Figure Ic illustrates the detected points with
coded amplitudes presented without the sig-
nals along the time axis.
Second, a histogram of the number of phase-
locked single theta waves (single sweep wave
identification histogram, SSWI histogram) was
constructed. To perform data reduction, the
analysis epoch was divided into time intervals
of 20 ms. For each time interval the identified
coded extrema were summed across trials.
Thus, the number of the phase-locked waves in
the consecutive single sweeps for each 20-ms
interval was determined, and the obtained val-
ue was assigned to the corresponding histo-
gram bar (Fig. Id). Typical SSWI histograms
are shown also in Figure 4c.
Third, quantitative evaluation of single-
sweep phase-locking was performed. The
SSWI histogram was normalized by dividing
the bar values by the number of single sweeps
included. Ihe sum of absolute bar values of the
normalized SSWI histogram was calculated for
the time windows 0-300 and 300-600 ms post-
stimulus, thereby giving information about the
strength of single-sweep phase-locking in two
consecutive post-stimulus periods. Ihe sums
were computed for each subject, stimulus type,
and electrode site.
3) Single-sweep enhancement relative to pre-
stimulus activity was analyzed by calculat-
ing the enhancement factor EF (Ba⅞ar,
1982): For each single sweep N, the ratio of
the maximal response amplitude Rn to the
root mean square value rmsN of the ongoing
EEG amplitude prior to the stimulus (in the
time window -500,0 ms) was calculated ac-
cording to the formula:
EFn = 2^2^
The term 2 √2~ gives the relation between the
maximal amplitude and rms amplitude in case
they are equal. As tested experimentally, the
post-stimulus amplitude is enhanced if EF
> 1.5 (Ba⅞ar, 1982). EFs were calculated for the
early and late time windows. Thereafter, the
mean values for each subject, location, and
stimulus were obtained.
Statistical analysis
Each of the three parameters of single theta re-
sponses (individual means of the maximal
peak-to-peak theta amplitudes, integral values
of the normalized SSWI histograms, and indi-
vidual means of enhancement factors) was an-
alyzed separately for the passive, target, and
nontarget ERPs. Individual values were sub-
jected to repeated measures analysis of vari-
ance with one between subject variable, age (6
levels corresponding to each age group, 6,7,8,
9,10 years, and adults), and two within-subjects
variables, time window (early vs. late), and
electrode (Fz, Cz, and Pz). The same analysis
was performed for the maximal peak-to-peak
amplitudes of averaged filtered (4-7 Hz)
ERPs. The Greenhouse-Geisser correction was
applied to the analyses with repeated measures
factor electrode. The original df and the prob-
ability values from the reduced df are reported
here. Results from testing simple effects not
presented in tables are regarded as significant
only if the probability values P were smaller
than .05. In order to describe group specific dif-
ferences, post-hoc univariate ^-contrasts were
performed. The Bonferroni procedure was
used to correct the probability values for the
number of comparisons made. The corrected
probability values are reported in the results.
A two-way ANOVA (age × electrode) was
performed on the log-transformed absolute
theta-band power values of the prestimulus
EEG of the passive, target, and nontarget
ERPs, and one-way ANOVA (age) was per-
formed for reaction time and error rate data.
To analyze the relationship between prestimu-
lus theta activity and theta response, step-wise
multiple regression analyses were carried out
for the log-transformed absolute theta-band
power and single-response parameters. To
evaluate the relationship between RT and
event-related theta activity, Pearson correla-
tion coefficients were calculated for single the-
ta response parameters to targets at each lead
and RTs.
Results
Behavioral data
As indicated by the significance of the age fac-
tor (age: F(5,54) = 14.5, P < .001), children’s
RTs to targets decreased with increasing age