A new method of detecting criticality from time-series data outperforms conventional metrics in the presence of variable noise levels for both simulated systems and real neural recordings.
A new method of detecting criticality from time-series data outperforms conventional metrics in the presence of variable noise levels for both simulated systems and real neural recordings.
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