We experimentally demonstrate the use of continuous, time-delayed, feedback stimulation for controlling the synchronization of neuron action potentials. Phase-based models were experimentally constructed from a single synaptically isolated cultured hippocampal neuron. These models were used to determine the stimulation parameters necessary to produce the desired synchronization behavior in the action potentials of a pair of neurons coupled through a global time-delayed interaction. Measurements made using a dynamic clamp system confirm the generation of the synchronized states predicted by the experimentally constructed phase model. This model was then utilized to extrapolate the feedback stimulation parameters necessary to disrupt the action potential synchronization of a large population of globally interacting neurons.
"With the addition of AEC StdpC can now be applied in a majority of dynamic clamp applications that have previously been inaccessible to such experimentation due to the requirements of two independent electrodes. It also allows to reconfirm experiments of authors who have previously used dynamic clamp with single electrodes using only traditional compensation methods of bridge balance and capacitance compensation (Rothman et al., 2009; Rusin et al., 2011). "
[Show abstract][Hide abstract] ABSTRACT: Dynamic clamp is a powerful approach for electrophysiological investigations allowing researchers to introduce artificial electrical components into target neurons to simulate ionic conductances, chemical or electrotonic inputs or connections to other cells. Due to the rapidly changing and potentially large current injections during dynamic clamp, problematic voltage artifacts appear on the electrode used to inject dynamic clamp currents into a target neuron. Dynamic clamp experiments, therefore, typically use two separate electrodes in the same cell, one for recording membrane potential and one for injecting currents. The requirement for two independent electrodes has been a limiting factor for the use of dynamic clamp in applications where dual recordings of this kind are difficult or impossible to achieve. The recent development of an active electrode compensation (AEC) method has overcome some of these prior limitations, permitting artifact-free dynamic clamp experimentation with a single electrode. Here we describe an AEC method for the free dynamic clamp software StdpC. The AEC component of StdpC is the first such system implemented for the use of non-expert users and comes with a set of semi-automated configuration and calibration procedures that facilitate its use. We briefly introduce the AEC method and its implementation in StdpC and then validate it with an electronic model cell and in two different biological preparations.
[Show abstract][Hide abstract] ABSTRACT: A method of chaos synchronization and parameter identification is proposed in the paper. The synchronization controller and the parameter recognizer are designed. Two coupled map lattices with different structures are taken as examples to verify the effectiveness of the method. Simulation results show that the identification variables in the parameter recognizer can substitute for the unknown parameters in both target and response systems. Then global synchronization of the two uncertain coupled map lattices can be realized after the designed controller is added.
[Show abstract][Hide abstract] ABSTRACT: Large scale simulations of electrically coupled neuronal oscillators often employ the phase coupled oscillator paradigm to understand and predict network behavior. We study the nature of the interaction between such coupled oscillators using weakly coupled oscillator theory. By employing piecewise linear approximations for phase response curves and voltage time courses and parametrizing their shapes, we compute the interaction function for all such possible shapes and express it in terms of discrete Fourier modes. We find that reasonably good approximation is achieved with four Fourier modes that comprise of both sine and cosine terms.
Physical Review E 10/2013; 88(4-1):042704. DOI:10.1103/PhysRevE.88.042704 · 2.29 Impact Factor
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