A novel distance measure for the unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles

@article{Groberger2018AND,
  title={A novel distance measure for the unsupervised clustering of temporal patterns in high-dimensional neuronal ensembles},
  author={Lukas Gro{\ss}berger and Francesco Paolo Battaglia and Martin A. Vinck},
  journal={bioRxiv},
  year={2018},
  pages={252791}
}
Temporally ordered multi-neuron patterns likely encode information in the brain. We introduce an unsupervised method, SPOTDistClust (Spike Pattern Optimal Transport Distance Clustering), for their detection from high-dimensional neural ensembles. SPOTDistClust measures similarity between two ensemble spike patterns by determining the minimum transport cost of transforming their corresponding normalized cross-correlation matrices into each other (SPOTDist). Then, it performs density-based… 
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References

SHOWING 1-10 OF 82 REFERENCES
Discovery of Salient Low-Dimensional Dynamical Structure in Neuronal Population Activity Using Hopfield Networks
TLDR
A novel method by fitting large Hopfield networks to windowed, binned spiking activity in an unsupervised way using minimum probability flow parameter estimation and then collecting Hopfield memories over the raw data, which results in a drastic reduction of pattern counts and can be exploited to identify prominently recurring spatiotemporal patterns.
A combinatorial method for analyzing sequential firing patterns involving an arbitrary number of neurons based on relative time order.
TLDR
A combinatorial method for quantifying the degree of matching between a "reference sequence" of N distinct "letters" and an arbitrarily long "word" composed of any subset of those letters including repeats and can reduce the sample size problem associated with analyzing complex firing patterns.
Unsupervised Spike Detection and Sorting with Wavelets and Superparamagnetic Clustering
TLDR
A new method for detecting and sorting spikes from multiunit recordings that combines the wave let transform with super paramagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions is introduced.
Does the Cerebral Cortex Exploit High-Dimensional, Non-linear Dynamics for Information Processing?
TLDR
A framework is presented which establishes links between the various manifestations of cortical dynamics by assigning specific coding functions to low-dimensional dynamic features such as synchronized oscillations and phase shifts on the one hand and high-dimensional non-linear, non-stationary dynamics on the other.
Finding neural assemblies with frequent item set mining
TLDR
This work proposes a new assembly detection method based on frequent item set mining (FIM), which is able to reliably suppress false discoveries, while it is still very sensitive in discovering synchronous activity.
Unitary Events in Multiple Single-Neuron Spiking Activity: I. Detection and Significance
TLDR
A novel method to detect conspicuous patterns of coincident joint spike activity among simultaneously recorded single neurons, designed to deal with nonstationary firing rates is described.
Replay and Time Compression of Recurring Spike Sequences in the Hippocampus
TLDR
It is hypothesized that the endogenously expressed spike sequences during sleep reflect reactivation of the circuitry modified by previous experience and serve to consolidate information in neuronal networks.
A neuronal learning rule for sub-millisecond temporal coding
TLDR
A modelling study based on computer simulations of a neuron in the laminar nucleus of the barn owl shows that the necessary degree of coherence in the signal arrival times can be attained during ontogenetic development by virtue of an unsupervised hebbian learning rule.
Detecting cell assemblies in large neuronal populations
...
...