Methods for identification of spike patterns in massively parallel spike trains
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Publication:1799441
DOI10.1007/s00422-018-0755-0zbMath1400.92109OpenAlexW2797918600WikidataQ52590593 ScholiaQ52590593MaRDI QIDQ1799441
Sonja Grün, Vahid Rostami, Pietro Quaglio, Emiliano Torre
Publication date: 18 October 2018
Published in: Biological Cybernetics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00422-018-0755-0
Monte Carlo methodsdata miningspike synchronycorrelated point processesspatio-temporal spike patterns
Uses Software
Cites Work
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- Assessment of synchrony in multiple neural spike trains using loglinear point process models
- Evidence, information, and surprise
- Correlated input spike trains and their effects on the response of the leaky integrate-and-fire neuron
- Effect of cross-trial nonstationarity on joint-spike events
- Decomposition of neuronal assembly activity via empirical de-Poissonization
- Analysis of neural data
- NeuroXidence: reliable and efficient analysis of an excess or deficiency of joint-spike events
- Unitary Events in Multiple Single-Neuron Spiking Activity: II. Nonstationary Data
- Theory of the Snowflake Plot and Its Relations to Higher-Order Analysis Methods
- Detecting Synchronous Cell Assemblies with Limited Data and Overlapping Assemblies
- Information Theory and Statistical Mechanics
- Correlations and Population Dynamics in Cortical Networks
- Higher-Order Statistics of Input Ensembles and the Response of Simple Model Neurons
- A model of neocortex
- Impact of Spike Train Autostructure on Probability Distribution of Joint Spike Events
- Spike-Centered Jitter Can Mistake Temporal Structure
- Polychronization: Computation with Spikes
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