Statistical Analysis within the masked cortical source space
First, the oscillatory ssVEF responses between both pre-cue conditions
(attend the central fixation cross vs. attend the peripheral rings) were
compared using a non-parametric cluster-based permutation approach
(Nichols and Holmes 2002) restricted to the cortical sources that
oscillated at the stimulus driven frequencies significantly different
from noise (see Figure 1). From these sources the relative power of the
12 Hz and 15 Hz driving frequencies were extracted by dividing the power
values of interest by the mean power across the noise power bins (31
frequency bins between 17 Hz and 20 Hz in 0.1 Hz steps). Then, within
the cortical source mask (Figure 1) source clusters were formed when at
least one adjacent source neighbor indicated a significant difference
based on a dependent t-test (cluster alpha threshold of p = 0.025
testing for both directions). Then, the t-values were summed across the
cluster. Thereafter, 1000 random permutations between both pre-cue
conditions for each cortical source under the Null hypothesis of no
differences between attending the central fixation cross or the
peripheral rings were done. At each permutation step the same cluster
rule was applied and the maximum t cluster sum entered a permutation
distribution. Finally, the empirically observed t clusters obtained by
the first step (see above) with a sum exceeding the 97.5 percentile
(test in both directions) of the permutation distribution were
considered as significant. In order to test possible interactions of
cortical hemisphere, mean relative ssVEF power were extracted from the
resulting significant clusters (see Results) and compared with the mean
ssVEF activity in the homologous opposite hemisphere by using a repeated
measures ANOVA with within-subject factors pre-cue condition (fixation
cross and peripheral rings) and hemisphere (left and right).
Greenhouse-Geisser corrections were applied when necessary.
However, the main objective of this study was to characterize how
stimulus driven ssVEF responses are modulated by shifts of spatial
attention when spatial attention had been already directed towards the
peripheral or central visual field (rings vs. cross). Using the same
non-parametric cluster-based mass-univariate approach, the interaction
of relative ssVEF power changes between experimental phases (pre-cue
baseline, post-cue hemifield not attended or attended) and pre-cue
baseline conditions (attend central fixation cross or peripheral rings)
was assessed for the left and right visual hemifield stimulations,
separately. However, clusters were derived from a dependent F-test
(equivalent to a repeated measures ANOVA) comparing the differences in
relative ssVEF power between the pre-cue peripheral rings minus central
fixation condition, post-cue visual hemifield not attended when rings
were attended before minus visual hemifield not attended when central
fixation cross was attended before, and post-cue visual hemifield
attended when rings were attended before minus visual hemifield attended
when central fixation cross was attended before. Note, that the
comparison of these differences is equivalent to test the interaction
experimental phase by pre-cue condition. Source clusters were formed
when at least one adjacent source neighbor indicated a significant
interaction based on a dependent F-test (cluster alpha threshold of p =
0.05 testing for one direction). F-values were summed across the
cluster. Then, the same permutation approach as outlined above was
applied. However, the empirically observed F clusters with a sum
exceeding the 95 percentile (F test in only one direction) of the
permutation distribution were considered as significant. All
non-parametric cluster-based permutation tests were implemented using
the fieldtrip toolbox (Oostenveld et al., 2011;https://www.fieldtriptoolbox.org).
In order to test any interactions with hemisphere, mean relative ssVEF
power values of cortical source clusters of both hemispheres as obtained
by the permutation statistics were entered in a repeated measures ANOVA
with within-subject factors of pre-cue baseline, experimental phase and
hemisphere. Greenhouse-Geisser corrections were applied when necessary.