DOI: 10.5061/dryad.bt7v0
title: Data from: Frontoparietal structural connectivity mediates the top-down control of neuronal synchronization associated with selective attention

description: 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.
description: 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.niiGamma 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.niiAlpha 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.matGamma 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.matSLF fiber tractsGrand-averaged fiber tract maps of the SLF branches from all 26 subjects.SLF_branches.zipStatistical 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.zipBehavioural 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' trialsbehav_csv.txtNeural 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, accuracyneur_csv.txt