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By shuffling the data this should destroy any correlations present and so the exponent of the shuffled data is expected to be approximately 0.5.
We further examined the effect of random changes of activity by shuffling the data specifically duration reactivations and then plotting the transient trajectories using sliding-window technique.
A total of 1,000 randomizations was done by shuffling the data of participants between groups.
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To test this hypothesis, we devised a method for finding precise repeats of activity and compared repeats found in the data to those found in surrogate datasets made by shuffling the original data.
The permutated sets were constructed by randomly assembling eight sets of LTR time series by shuffling the real data while keeping time points constant.
Since we needed more realistic null models to better discern features of real networks from the data, we decided to keep only the relevant links that would be sufficient to generate a single component network while generating randomized networks by shuffling the real data time points.
The Klijn et al. method (called KC-SMART) is implemented in the R/Bioconductor package [ 15] and the null hypothesis is obtained by shuffling the non-discretized data (log-ratio data) over the entire genome.
For each sample, a random data set was produced by shuffling the genomic positions of the data, and an identical search was conducted.
It was performed by shuffling the trials of LFP data to match original spike trains.
To account for these effects, it was suggested that the procedure be empirically validated by shuffling the social group membership data, and verifying that no significant species are identified.
Surrogate signals were generated from the nLFP data sets by shuffling the occurrence times of the different peaks, while keeping the same distribution of peak amplitudes.
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