Overview of analysis pipeline for simulated neural activity and MEG data.

<p>After computing activity timecourses for each region, both simulated and real signals are processed through the same pipeline.</p

Total execution times (in log scale) of the bedpostX application in a single-core CPU and a Tesla C2050 GPU for the whole dataset (30 slices), as the number of fibres <i>L</i> is increased.

<p>Results are shown for different number <i>K</i> of gradient directions (64, 128 and 256) and when MCMC iterations were utilised (3000 burn-in iterations).</p

Balance of excitation and inhibition.

<p>(a) Magnitude of correlation between node strength and <b><i>c</i></b>_{<b><i>ie</i></b>} for a range of global couplings and delays. The red dot corresponds to the parameters shown in <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g005" target="_blank">Fig 5</a></b>. (b) <b><i>c</i></b>_{<b><i>ie</i></b>} values plotted against network node strength, for the parameters marked in panel (a) by the red dot, with a linear fit (red line).</p

Comparison between CPU and GPU model estimates for the diffusivity <i>d</i>, the baseline signal and the volume fraction of the first fibre , in different brain areas.

<p>(a) A corpus callosum voxel, (b) a centrum semiovale voxel and (c) a grey matter voxel. Each design was ran 1000 times on the same data and for each repeat the mean of the posterior distribution of the respective parameter was recorded. The histograms show the distributions of these means across all 1000 repeats. For each repeat, a burn-in period of 3000 iterations and a thinning period of 25 samples was used for the MCMC.</p

Alpha band functional connectivity profiles in data and model.

<p>Functional connectivity in (a,b) AEC, (c,d) PLV,and (e,f) PLI, shown in data, and in the model for the parameters marked by the red dot in <b>Figs <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g004" target="_blank">4</a>, <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g006" target="_blank">6</a></b> and <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g007" target="_blank">7</a></b>.</p

Synchrony and metastability.

<p>Alpha band synchrony (averaged over time) and metastability (standard deviation of synchrony), in the model (a,b) without ISP (c,d) with ISP. The red dot corresponds to the parameters shown in <b>Figs <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g005" target="_blank">5</a></b> and <b><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g007" target="_blank">7</a></b>.</p

Typical model neural activity.

<p>(a) Raw excitatory activity timecourse (blue) and corresponding orthogonalised alpha band envelope (red) for the left pericalcarine parcel, which is well correlated with the right pericalcarine as shown in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g005" target="_blank">Fig 5B</a>. The envelope timecourse in right pericalcarine (green) is strongly correlated with the envelope timecourse in left pericalcarine–these correlations correspond to the AEC reported in Figs <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g004" target="_blank">4</a> and <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.g005" target="_blank">5</a>. (b) Power spectrum of excitatory activity, averaged over all brain regions. The red bars show the position and size of the alpha band analysis window relative to the spectral peak.</p

Model local parameter values.

<p>Parameters are based on previous work by Deco et al. [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1006007#pcbi.1006007.ref012" target="_blank">12</a>].</p