Neuronal synchronization reflected by oscillatory brain activity has been strongly implicated in the mechanisms supporting selective gating. We here aimed at identifying the anatomical pathways in humans supporting the top-down control of neuronal synchronization. We first collected diffusion imaging data using magnetic resonance imaging to identify the medial branch of the superior longitudinal fasciculus (SLF), a white-matter tract connecting frontal control areas to parietal regions. We then quantified the modulations in oscillatory activity using magnetoencephalography in the same subjects performing a spatial attention task. We found that subjects with a stronger SLF volume in the right compared to the left hemisphere (or vice versa) also were the subjects who had a better ability to modulate right compared to left hemisphere alpha and gamma band synchronization, with the latter also predicting biases in reaction time. Our findings implicate the medial branch of the SLF in mediating top-down control of neuronal synchronization in sensory regions that support selective attention.
Alpha modulation source maps (Fig 2C)
Nifti file containing a map of the grand average alpha modulation index scores from all 26 subjects, normalised to MNI space, as shown in Fig 2C. Note - in order to view this file correctly it is necessary to use a bidirectional colour map that can display positive and negative values using different colours, such as 'jet' or 'flow'.
alpha_mod_idx.nii
Gamma modulation source maps (Fig 2D)
Nifti file containing a map of the grand average gamma modulation index scores from all 26 subjects, normalised to MNI space, as shown in Fig 2D. Note - in order to view this file correctly it is necessary to use a bidirectional colour map that can display positive and negative values using different colours, such as 'jet' or 'flow'.
gamma_mod_idx.nii
Alpha modulation TFR - sensor level (Fig 2A/B)
Fieldtrip structure containing a time-frequency representation of the grand average alpha modulation index scores from all 26 subjects at the sensor level. The user will need to download and install the fieldtrip matlab toolbox (http://www.fieldtriptoolbox.org/) to visualise this data. The following matlab code will reproduce the bottom rows of Fig 2A and Fig 2B from this structure:
figure
cfg=[];
cfg.zlim=[-9 9];
cfg.channel={'MLO*'};
subplot(2,1,1),ft_singleplotTFR(cfg,amod_g);
cfg.channel={'MRO*'};
subplot(2,1,2),ft_singleplotTFR(cfg,amod_g);
alpha_TFR.mat
Gamma modulation TFR - sensor level (Fig 2A/B)
Fieldtrip structure containing a time-frequency representation of the grand average alpha modulation index scores from all 26 subjects at the sensor level. The user will need to download and install the fieldtrip matlab toolbox (http://www.fieldtriptoolbox.org/) to visualise this data. The following matlab code will reproduce the top rows of Fig 2A and Fig 2B from this structure:
figure
cfg=[];
cfg.zlim=[-1.5 1.5];
cfg.channel={'MLO*'};
subplot(2,1,1),ft_singleplotTFR(cfg,gmod_g);
cfg.channel={'MRO*'};
subplot(2,1,2),ft_singleplotTFR(cfg,gmod_g);
gamma_TFR.mat
SLF fiber tracts
Grand-averaged fiber tract maps of the SLF branches from all 26 subjects.
SLF_branches.zip
Statistical maps (Supplementary Figs 1,2)
Nifti files containing group statistical maps comparing alpha- and gamma-band power during 'attention left' and 'attention right' trials. 'Alpha_tmap' and 'Gamma_tmap' show whole-brain statistical maps. The other volumes are masked by cluster-based permutation test. Note - in order to view the t-maps correctly it is necessary to use a bidirectional colour map that can display positive and negative values using different colours, such as 'jet' or 'flow'.
source_statistical_maps.zip
Behavioural data (Fig 1B)
CSV sheet containing the data used in the behavioural analysis shown in figure 1B of the manuscript. Each row represents one subject. The column headings are as follows:
Column 1 - Accuracy on 'target left, cued' trials
Column 2 - Accuracy on 'target right, cued' trials
Column 3 - Accuracy on 'target left, uncued' trials
Column 4 - Accuracy on 'target right, uncued' trials
Column 5 - Reaction Time on 'target left, cued' trials
Column 6 - Reaction Time on 'target right, cued' trials
Column 7 - Reaction Time on 'target left, uncued' trials
Column 8 - Reaction Time on 'target right, uncued' trials
behav_csv.txt
Neural data (Figs 3,4,5,6)
CSV sheet containing the data used in the neural data analyses and brain-behaviour correlation analyses shown in figures 3, 4, 5, and 6 of the manuscript. Each row represents one subject. The column headings are as follows:
Column 1 - Volumetric asymmetry of SLF1
Column 2 - Volumetric asymmetry of SLF2
Column 3 - Volumetric asymmetry of SLF3
Column 4 - Alpha modulation asymmetry, occipital cortex
Column 5 - Alpha modulation asymmetry, frontal cortex, FEF ROI
Column 6 - Alpha modulation asymmetry, frontal cortex, ROI from Olesen et al
Column 7 - Gamma modulation asymmetry, occipital cortex
Column 8 - Gamma modulation asymmetry, frontal cortex, FEF ROI
Column 9 - Gamma modulation asymmetry, frontal cortex, ROI from Olesen et al
Column 10 - Asymmetry of cueing benefit, reaction times
Column 11 - Asymmetry of cueing benefit, accuracy
neur_csv.txt
