Density-based clustering: A ‘landscape view’ of multi-channel neural data for inference and dynamic complexity analysis

@article{Baglietto2016DensitybasedCA,
  title={Density-based clustering: A ‘landscape view’ of multi-channel neural data for inference and dynamic complexity analysis},
  author={Gabriel Baglietto and Guido Gigante and Paolo Del Giudice},
  journal={PLoS ONE},
  year={2016},
  volume={12}
}
Simultaneous recordings from N electrodes generate N-dimensional time series that call for efficient representations to expose relevant aspects of the underlying dynamics. Binning the time series defines a sequence of neural activity vectors that populate the N-dimensional space as a density distribution, especially informative when the neural dynamics proceeds as a noisy path through metastable states (often a case of interest in neuroscience); this makes clustering in the N-dimensional space… 

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