Behavior Analysis
The completereaction time information
of two subjects (one PD and one HC, sub-RC4114 and sub-RC4224) was
unavailable. We first aggregated the mean reaction time and accuracy
from the six combinations of cue type × flanker congruency conditions
for the remaining subjects. Reaction times lower than 200 ms or higher
than 2000 ms were excluded. Second, we calculated the three behavior
attention network scores for each subject of each session. Third, we
verified whether the alerting, orienting, and executive effects could be
found at the behavior level and whether there were significant
differences between PD and HC. Finally, we calculated the test-retest
reliability estimates for the behavior attentional network scores.
Reproducibility across
Sessions and Groups
We used the mixed-effects
multilevel analysis (3dMEMA ) (Chen et al. , 2012) within an
intersection mask to model the group mean activation for each session of
the two groups. To make an intersection mask, all subjects’
functional masks were intersected with a threshold that at least 75% of
the participants had valid values for each voxel. Consequently, we
acquire four group-level statistical maps (2 groups × 2 sessions)for each contrast (alerting, orienting, executive) and
subsequently derive the corresponding group-level statistical maps after
applying post-thresholding criteria (employing a voxel-wise 1-sided
threshold of 0.01 and a cluster extent of 40 voxels). Finally, the
3ddot command computed dice coefficients (Equation 1) to compare
spatial overlap across populations and sessions. We also calculated the
dice coefficients for varying statistical thresholds to examine the
influence of threshold.
\(\mathbf{Dice=\ }\frac{\mathbf{2*|X\cap Y|}}{\left|\mathbf{X}\right|\mathbf{+|Y|}}\mathbf{,}\)(Equation 1)
In addition, to better
illustrate the spatial overlap between sessions, we visualize the brain
activations on the cerebral surface according to the brain parcellation
atlas. The Schaefer-Yeo atlas of
200 parcellations (Schaefer et al. , 2018) was used to extract
mean contrast estimates from each atlas region (3dROIstats ).
Then, we used the ggseg package (Mowinckel & Vidal-Piñeiro,
2020) to visually compare the region-based activations across groups and
sessions (with a liberal threshold of 0.05).
Because the present study focused on reproducibility and reliability, we
did not report the group difference in brain activations.Moreover, the group differences have been examined by other
researchers. Interested readers might refer to two published papers on
the difference in functional activation between the patient and healthy
group (Madhyastha et al. , 2015; Boord et al. , 2017).
Test-retest Reliability of
fMRI measures
The voxel-wise test-retest reliability analysis was performed for each
attention network contrast using 3dICC (Chen et al. ,
2018). The ICC estimates for HC and PD were included in the
supplementary material. For
the region-level and network-level analyses , the mean contrast
estimates for each atlas region were fed into the rptR package
(Stoffel et al. , 2017). We reported the adjusted test-retest
reliability by regressing out the systematic effect due to group,
session, and their interaction. The ICC estimates were calculated
for the patient and healthy group separately . The ICC map was
visualized using ggseg (Mowinckel & Vidal-Piñeiro, 2020). In
addition, we also plot the ICC distribution according to the seven
networks defined by Yeo et al. (2011). Besides the region- and
network-level analyses based on the Schafer-Yeo atlas, we also performed
reliability analyses on basal ganglia (12 subregions) and thalamus (16
subregions) according to the Brainnetome atlas.