- Oral presentation
- Open Access
Non-renewal spiking and neural dynamics - a simple theory of interspike-interval correlations in adapting neurons
© Schwalger and Lindner; licensee BioMed Central Ltd. 2013
- Published: 8 July 2013
- Firing Rate
- Correlation Structure
- Serial Correlation Coefficient
- Adaptation Current
- Correlation Pattern
There is accumulating evidence that the spiking of many neurons is not a renewal process but is characterized by correlations between interspike intervals (ISIs) . These correlations are crucial for understanding signal processing in single neurons, however, their origin and structure is still poorly understood theoretically. Here, we present a simple theory of correlations in neural oscillators with spike-triggered adaptation currents, which are a major source of non-renewal spiking. These currents mediate spike-frequency adaptation and are commonly believed to result in negative correlations between adjacent ISIs. For such adapting neurons, we show that the serial correlation coefficient (SCC) is fundamentally related to the neuron's phase response curve (PRC). The relation predicts possible correlation patterns that characterize how correlations depend on the lag between ISIs. Different patterns arise from the specific interplay between nonlinear neural dynamics and adaptation dynamics. In particular, the correlation structure can be determined by a single parameter that includes the shape of the PRC as well as the strength and time scale of the adaptation current (Fig.1).
This work is funded by the BMBF (FKZ: 01GQ1001A).
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