Estimating membrane voltage correlations from extracellular spike trains.
@article{Dorn2003EstimatingMV,
title={Estimating membrane voltage correlations from extracellular spike trains.},
author={Jessy D. Dorn and Dario L. Ringach},
journal={Journal of neurophysiology},
year={2003},
volume={89 4},
pages={
2271-8
}
}The cross-correlation coefficient between neural spike trains is a commonly used tool in the study of neural interactions. Two well-known complications that arise in its interpretation are 1) modulations in the correlation coefficient may result solely from changes in the mean firing rate of the cells and 2) the mean firing rates of the neurons impose upper and lower bounds on the correlation coefficient whose absolute values differ by an order of magnitude or more. Here, we propose a model…
39 Citations
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References
SHOWING 1-10 OF 31 REFERENCES
Model Dependence in Quantification of Spike Interdependence by Joint Peri-Stimulus Time Histogram
- BiologyNeural Computation
- 2000
It is demonstrated that firing-rate modulations cannot be corrected for in a model-independent manner, and therefore the effective connectivity does not represent a universal characteristic that is independent of modulation of the firing rates.
Impact of Correlated Synaptic Input on Output Firing Rate and Variability in Simple Neuronal Models
- BiologyThe Journal of Neuroscience
- 2000
A simple random walk model in which the membrane potential of a target neuron fluctuates stochastically, driven by excitatory and inhibitory spikes arriving at random times, shows that, in the balanced regime, weak correlations caused by signals shared among inputs may have a multiplicative effect on the input-output rate curve of a postsynaptic neuron.
Neuronal spike trains and stochastic point processes. I. The single spike train.
- Computer ScienceBiophysical journal
- 1967
Dynamics of neuronal firing correlation: modulation of "effective connectivity".
- BiologyJournal of neurophysiology
- 1989
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.
Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains.
- BiologyBiophysical journal
- 1967
On the significance of correlations among neuronal spike trains
- BiologyBiological Cybernetics
- 2004
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.
Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior
- Psychology, BiologyThe Journal of Neuroscience
- 2001
The results strengthen the view that common input, common stimulus selectivity, and common noise are tightly linked in functioning cortical circuits.
Correlations between neural discharges are related to receptive field properties in cat primary auditory cortex
- Biology, PsychologyThe European journal of neuroscience
- 1999
Systematic relationships were found between correlation properties and the receptive field‐based organization of cortical processing, suggesting that similar general mechanisms are utilized in many parts of the sensory cortex.
Correlations Without Synchrony
- BiologyNeural Computation
- 1999
Two biologically plausible ways of departing from independence that are capable of generating peaks very similar to spike timing peaks are described here: covariations over trials in response latency and covariationsover trials in neuronal excitability.







