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Dynamics of neuronal firing correlation: modulation of "effective connectivity"

Journal of Neurophysiology · 1989 · Vol. 61(5) · pp. 900–917
A AertsenGeorge L. GersteinMuhammad HabibG. Palm

Abstract

1. We reexamine the possibilities for analyzing and interpreting the time course of correlation in spike trains simultaneously and separably recorded from two neurons. 2. We develop procedures to quantify and properly normalize the classical joint peristimulus time scatter diagram. These allow separation of the "raw" correlation into components caused by direct stimulus modulations of the single-neuron firing rates and those caused by various types of interaction between the two neurons. 3. A newly developed significance test ("surprise") is applied to evaluate such inferences. 4. Application of the new procedures to simulated spike trains allowed the recovery of the known circuitry. In particular, it proved possible to recover fast stimulus-locked modulations of "effective connectivity," even if they were masked by strong direct stimulus modulations of individual firing rates. These procedures thus present a clearly superior alternative to the commonly used "shift predictor." 5. Adopting a model-based approach, we generalize the classical measures for quantifying a direct interneuronal connection ("efficacy" and "contribution") to include possible stimulus-locked time variations. 6. Application of the new procedures to real spike trains from several different preparations showed that fast stimulus-locked modulations of "effective connectivity" also occur for real neurons.

Neural dynamics and brain functionNeuroscience and Neural Engineeringstochastic dynamics and bifurcationStimulus (psychology)Computer scienceCorrelationSurpriseNeuroscienceTrainArtificial intelligenceBiological systemCommunicationMathematics

MeSH terms

AnimalsMathematicsModels, NeurologicalNeural ConductionNeurons
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References
Neuronal Spike Trains and Stochastic Point Processes
Biophysical Journal · 1967 · 1,322 citations
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