EEG correlates of spatial working memory deficits in ADHD:
vigilance, encoding and maintenance.
A. Lenartowicz12, A. Delorme345, P.D. Walshaw12, A.L. Cho12, R. M. Bilder12, J. McGough12, J.T.
McCracken12, S. Makeig3, S.K. Loo12
Channel vs. IC Space Analyses
While independent component analysis (ICA) of EEG data has been increasing in
prevalence within the literature, the unique assumptions of ICA warrant further treatment.
It is notable that the ICA decomposition results do not use any knowledge of the locations
of the scalp electrodes. They find a best-fitting purely statistical model. For these reasons,
we present here additional analyses to evaluate how the IC model presented in our primary
analyses relates to effects at individual channels.
Mid-Occipital Cluster vs. Channel Effects. To better understand how to interpret the IC
model with respect to the overlying scalp channel data, we performed two additional
analyses. First we assessed how much variance in selected scalp channel signals was
accounted for by the projection of the ICs in the medial occipital cluster. Here we evaluated
the mean variance across electrode channels Iz, O1 and O2, the three scalp channels
showing strongest group main effects. The ICs accounted for 29.0% (SE=2.6) of TD time
course variance and for 25.5% (SE=2.8) ADHD time course variance. While a significant
contribution, these results demonstrate the expected breadth of cortical contributions to
individual scalp electrode channels.
In a second analysis, we evaluated to what extent the clustered ICs captured the effects that
were present in the overlying channel data. For the average of the Iz, O1, and O2 channel
time series, we performed the same repeated-measure ANOVA (with GROUP and LOAD as
factors) as on the cluster ICs, first on the raw data and, second, after subtracting from these
channel signals the projections of the mid-occipital cluster ICs. If the cluster ICs account for
a significant amount of the effect, then removing their contribution from the channel data
should decrease the F statistic for each effect. The results are presented in Fig. S1a. For the
effects of LOAD and GROUP, we observed a decrease in the magnitude of the effect after
subtracting the mid-occipital cluster contribution from the channel data (FLOAD(1,69) = 8.6
vs. 2.72; FGROUP(1,69) = 9.5 vs. 7.7). The decrease indicates that the mid-occipital cluster
indeed accounted for part of the effect in the channel data.
Since the F statistic remained significant, however, we inferred that other source clusters
also accounted for some of these effects. We therefore in addition removed the
contributions of the bilateral occipital and mid-parietal clusters, and then also the bilateral
parietal and mid-central clusters. The first step eliminated the effect of LOAD (FLOAD(1,69) =
0.3), indicating that lateral occipital and superior occipital sources accounted for the
remainder of its variance. Similarly, these two steps reduced the effect of GROUP (from
FGROUP(1,69) = 7.2 to 5.1). However, the GROUP effect was still significant, suggesting that it
had contributions from other sources.
However, unlike in the IC data, the interaction between GROUP and LOAD was not
significant in the channel data, F(1,69) < 1, indicating that the effect was masked in the
scalp signals and was unmasked only by ICA source separation and clustering.
Figure S1. The contributions of the midoccipital and mid-frontal IC clusters to the
overlying electrode channel data were
evaluated by comparing F statistics for effects
of interest before and after the removal of
cluster ICs from the channel data. For an
occipital channel mean (Iz, O1, O2) (a), the F
statistics for the group (green dashed) and
load (brown solid trace) effects on encodingperiod alpha band ERD were attenuated but
not eliminated by removal of contributions
from the mid-occipital cluster. The effects
were reduced or eliminated by further
removing either the mid-parietal or the
lateral-occipital cluster ICs, consistent with
the observed multiple source contributions to
the channel data. Though group by load
interaction (dotted blue trace) was not
significant in the channel data, in the midoccipital IC source cluster itself (not shown) it
was significant. (b) For a frontal channel mean
(Fz, F3, F4), the F statistics for the group and
load effects on maintenance theta were
considerably reduced after removing the
contributions of the mid-frontal cluster,
consistent with this cluster accounting for the
majority of the theta-band effects observed in
the supervening channel data.
Mid-Frontal Cluster vs. Channel Effects. As for the mid-occipital cluster, we also assessed
the effects of the mid-frontal IC cluster contribution to overlying scalp channel data. First
we assessed how much variance in the most strongly projected scalp channel time series,
here electrode channel Fz, was accounted for by projections of the clustered IC processes.
For electrode channel Fz, the mid-frontal cluster ICs accounted for 30.4% (SE=2.0) of time
course variance in TD and for 34.4% (SE=2.2) time course variance in ADHD participants.
Next, as for the mid-occipital cluster, we performed the repeated-measure ANOVA (with
GROUP and LOAD as factors) on the average time series across frontocentral scalp channels
Fz, F3 and F4, first on the raw data and, second, after subtracting from these channels the
variance accounted for by the projected activities of the mid-frontal cluster ICs. The results
are presented in Fig. S1b. For the LOAD and GROUP effects, after subtracting the midfrontal cluster contribution from the channel data we observed a decrease in effect
magnitude (FLOAD(1,69) = 0.9 vs. 0.4; FGROUP(1,69) = 2.1 vs. 0.2). The F statistics were small
and not significant indicating that these effects were largely masked in the raw signal data
and unmasked by ICA source separation.
Discussion
The percent variance accounted for (pvaf) in the maximally-projected scalp channel data
by the clusters of interest confirms that the data recorded at scalp electrodes represent
additive mixtures of source signals. As shown in Figure 2, for instance, the “occipital”
cluster scalp maps (mid-, left-, right-occipital, parietal) clearly overlap, and this is
congruent with an apportioning of the scalp channel variance among sources and source
clusters. We show that the significant group differences are only present for one of the
occipital clusters -- this is also congruent with expecting weakened group effects at
individual scalp electrodes. In particular, signals (and thus, signal variance) at each
occipital electrode mixes effects from the mid-occipital ICs (which showed group effects)
and from lateral occipital ICs (which did not show group effects). The effects of additive
mixtures of source signals were also present in the frontocentral scalp channels, in which
significant effects were not reliable.