Schematic of experimental design. A. Two face stimuli were presented simultaneously in the left and right hemifield. After baseline, a directional cue indicated the location of the target. After a variable delay interval (1000-2000ms) the eye-gaze of each stimulus (independent of the other) shifted randomly to the right or left. Subjects had to indicate the direction of the target eye movement after the delay interval (the face images have been replaced by emojis for copy right purposes). B. Examples of visual stimuli for each of the four conditions C. Table with the labels of the four load/salience conditions.

Alpha power decreases contralaterally and increases ipsilaterally with respect to the cued hemifield. A. Time-frequency representations of power demonstrate the difference between attended right versus left trials (t = 0 indicate the target onset). B. Topographical plot of the relative difference between attend right versus left trials. Regions of Interest sensors (ROIs) are marked with white circles. C. The alpha band modulation (MI(α)) averaged over ROI sensors within the left and right hemispheres, respectively. The absolute MI(α) increased gradually during the delay interval until the onset of the target stimuli.

Hemispheric lateralization modulation (HLM(a)) grand average and basal ganglia volumes across all participants. A, The HLM(a) distribution across participants. While there was considerable variation across participants, we observed no hemispheric bias in lateralized modulation values across participants (p-value = 0.39). B, Histograms of the lateralization volumes of subcortical regions. We found that caudate nucleus was right lateralized (p-value = 0.021) whereas, putamen, nucleus accumbens and thalamus volumes showed left lateralization (p-value = 0.004, p-value < 0.001 and p-value < 0.001, respectively). Th = Thalamus, CN = Caudate nucleus, Put = Putamen, GP = Globus Pallidus, Hipp = Hippocampus, Amyg = Amygdala, Acc = Nucleus Accumbens.

Lateralization volume of thalamus, caudate nucleus and globus pallidus in relation to hemispheric lateralization modulation of alpha (HLM(α)) in the task. A, The beta coefficients for the best model (containing three regressors) associated with a generalized linear model (GLM) where lateralization volume (LV) values were defined as explanatory variables for HLM(α). The model significantly explained the HLM(α) (p-value = 0.0007). Error bars indicate standard errors of mean (SEM). Asterisks denote statistical significance; *p<0.05. B, Partial regression plot showing the association between LVTh and HLM(α) while controlling for LVGP and LVCN (p-value = 0.01). B, Partial regression plot showing the association between LVCN and HLM(α) while controlling for LVTh and LVGP (p-value = 0.008). D, Partial regression plot showing the association between LVGP and HLM(α) while controlling for LVTh and LVCN (p-value = 0.061) . Negative (or positive) LVs indices denote greater left (or right) volume for a given substructure; similarly negative HLM(α) values indicate stronger modulation of alpha power in the left compared with the right hemisphere, and vice versa. The dotted curves in B, C, and D indicate 95% confidence bounds for the regression line fitted on the plot in red.

Beta estimates of subcortical nuclei from a multivariate regression model predicting HLM(α) in the four perceptual load conditions. Here the HLM(α) values for the four load conditions are the dependent variables and the lateralization volume of subcortical structures are the explanatory variables. The model significantly explains HLM(α) variability (p-value = 0.001) in comparison with null model). Error bars indicate SEM. Asterisks denote statistical significance; *p-value < 0.05.