A model study for causal relationships between voltage and calcium dynamics
© Chamorro et al; licensee BioMed Central Ltd. 2011
Published: 18 July 2011
Intracellular mechanisms directly or indirectly, influence the electrical activity of neurons in different time scales. These subcellular processes play a crucial role in generating transient dynamics and may shape firing patterns of individual cells and circuit activity in the nervous system [1–3]. Slow dynamics can contain a short-term history of a neuron and predispose it to prior activity-dependent (or preferred input-output) responses . The precise temporal distribution of spiking activity can also have as a substrate the slow calcium dynamics .
We have addressed this question using conductance based models including a description of calcium dynamics. In order to explore their mutual interaction, we evaluated the strength of the causal relationships between the calcium concentration and the membrane potential with Granger Causality (GC). GC is an efficient way to investigate cause-effect relationships between time series, and is currently the state of the art method for this kind of analysis in neural data. For this study we applied Kernel Granger Causality (KGC), a recently proposed approach which allows a straightforward extension to the nonlinear case . The causality index was evaluated for several parameters of the model, such as the order of regression, the delay and the degree of nonlinearity. Given the oscillatory nature of the signals, we also employed a modified approach which allows evaluating causality between the phases of the oscillations.
The causal relationship between voltage and calcium was analyzed for different activity modes in the models, i.e., regular spiking, regular bursting, irregular spiking and irregular bursting. The results show several evolving asymmetries between the causality in the voltage -> calcium direction and the other way around. These asymmetries can be related to the different temporal structure of the spiking and spiking-bursting regimes.
This work was supported by grants MICINN BFU2009-08473 and TIN 2010-19607.
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