Unitary Events in Multiple Single-Neuron Spiking Activity: I. Detection and Significance

@article{Grn2002UnitaryEI,
  title={Unitary Events in Multiple Single-Neuron Spiking Activity: I. Detection and Significance},
  author={S. Gr{\"u}n and M. Diesmann and A. Aertsen},
  journal={Neural Computation},
  year={2002},
  volume={14},
  pages={43-80}
}
It has been proposed that cortical neurons organize dynamically into functional groups (cell assemblies) by the temporal structure of their joint spiking activity. Here, we describe a novel method to detect conspicuous patterns of coincident joint spike activity among simultaneously recorded single neurons. The statistical significance of these unitary events of coincident joint spike activity is evaluated by the joint-surprise. The method is tested and calibrated on the basis of simulated… Expand
Unitary Event Analysis
  • S. Grün
  • Computer Science
  • Encyclopedia of Computational Neuroscience
  • 2014
TLDR
This chapter reviews the basic components of UE analysis and explores its dependencies on parameters like the allowed temporal imprecision and features of the data like firing rate and coincidence rate, and concludes that the UE method is robust already in its basic form. Expand
Unitary Event Analysis
TLDR
This chapter reviews the basic components of UE analysis and explores its dependencies on parameters like the allowed temporal imprecision and features of the data like firing rate and coincidence rate, and concludes that the UE method is robust already in its basic form. Expand
Statistical Significance of Coincident Spikes: Count-Based Versus Rate-Based Statistics
TLDR
This work reformulated the statistical test underlying unitary-event analysis, using a coincidence count distribution based on empirical spike counts rather than on estimated spike probabilities, and demonstrates that the test power can be increased by a factor of two or more in physiologically realistic regimes. Expand
Serial Spike Time Correlations Affect Probability Distribution of Joint Spike Events
TLDR
Non-renewal processes with the inter-spike interval distribution model that incorporates spike-history dependence of individual neurons are investigated, and it is concluded that small differences in the exact autostructure of the point process can cause large Differences in the width of a coincidence distribution. Expand
Assembly Detection in Continuous Neural Spike Train Data
TLDR
This work presents a method based on modeling spikes by influence regions of a user-specified width around the exact spike times and a clustering-like grouping of similar spike trains that is able to cope with two core challenges of this complex task: temporal imprecision and selective participation. Expand
Detecting cell assemblies in large neuronal populations
TLDR
Three linear methods for the detection of cell assemblies in large neuronal populations that rely on principal and independent component analysis are reviewed and a modified framework that incorporates multiple features of these previous methods is proposed. Expand
On the statistical significance of temporal firing patterns in multi-neuronal spike trains
TLDR
This paper presents a method for assessing significance on simulated spike trains involving inhomogeneous Poisson processes with strong interactions, where the correlation counts are obtained using the two-tape algorithm. Expand
Detecting Multineuronal Temporal Patterns in Parallel Spike Trains
We present a non-parametric and computationally efficient method that detects spatiotemporal firing patterns and pattern sequences in parallel spike trains and tests whether the observed numbers ofExpand
Significance of joint-spike events based on trial-shuffling by efficient combinatorial methods
TLDR
A Monte-Carlo-based resampling procedure is suggested and it is demonstrated that the procedure yields an appropriate estimate of the distribution and reliable significance estimation and is able to systematically sample the coincidence counts from all trial combinations. Expand
Dynamical features of higher-order correlation events: impact on cortical cells
TLDR
This work simulated the dynamics of a population of 5000 neurons, controlling both their second order and higher-order correlation properties to reflect physiological data, and shows how these results affect sparseness of neuronal representations, tuning properties, and feature selectivity of cortical cells. Expand
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References

SHOWING 1-10 OF 121 REFERENCES
Detecting unitary events without discretization of time
TLDR
A new approach is presented, the 'multiple shift' method (MS), which overcomes the need for binning and treats the data in their ( original) high time resolution (typically 1 ms, or better) and enhances the sensitivity for coincidences with temporal jitter. Expand
Statistical Significance of Coincident Spikes: Count-Based Versus Rate-Based Statistics
TLDR
This work reformulated the statistical test underlying unitary-event analysis, using a coincidence count distribution based on empirical spike counts rather than on estimated spike probabilities, and demonstrates that the test power can be increased by a factor of two or more in physiologically realistic regimes. Expand
Significance of joint-spike events based on trial-shuffling by efficient combinatorial methods
TLDR
A Monte-Carlo-based resampling procedure is suggested and it is demonstrated that the procedure yields an appropriate estimate of the distribution and reliable significance estimation and is able to systematically sample the coincidence counts from all trial combinations. Expand
Stable propagation of synchronous spiking in cortical neural networks
TLDR
The results indicate that a combinatorial neural code, based on rapid associations of groups of neurons co-ordinating their activity at the single spike level, is possible within a cortical-like network. Expand
On the significance of correlations among neuronal spike trains
TLDR
It is possible to compare stimulus-locked, and therefore time dependent correlations for different stimuli and also for different times relative to stimulus onset, and to separate purely stimulus-induced correlation from intrinsic interneuronal correlation. Expand
Dynamical changes and temporal precision of synchronized spiking activity in monkey motor cortex during movement preparation
TLDR
Data indicate that not only the discharge rate is involved in preparatory processes, but also temporal aspects of neuronal activity as expressed in the precise synchronization of individual action potentials. Expand
Spike synchronization and rate modulation differentially involved in motor cortical function.
TLDR
Findings indicate that internally generated synchronization of individual spike discharges may subserve the cortical organization of cognitive motor processes. Expand
Dynamics of neuronal firing correlation: modulation of "effective connectivity".
TLDR
Adopting a model-based approach, this work develops procedures to quantify and properly normalize the classical joint peristimulus time scatter diagram and generalizes the classical measures for quantifying a direct interneuronal connection to include possible stimulus-locked time variations. Expand
Precise spike synchronization in monkey motor cortex involved in preparation for movement
TLDR
The findings indicate that the synchronization of individual action potentials and the modulation of the firing rate may serve different and complementary functions underlying the cortical organization of cognitive motor processes. Expand
Single-trial estimation of neuronal firing rates: From single-neuron spike trains to population activity
TLDR
A method to estimate the neuronal firing rate from single-trial spike trains, based on convolution of the spike train with a fixed kernel function, is presented and rules for the optimized use and performance of the kernel method are derived. Expand
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