Phase synchronization of coupled bursting neurons and the generalized Kuramoto model

Bursting neurons fire rapid sequences of action potential spikes followed by a quiescent period. The basic dynamical mechanism of bursting is the slow currents that modulate a fast spiking activity caused by rapid ionic currents. Minimal models of bursting neurons must include both effects. We considered one of these models and its relation with a generalized Kuramoto model, thanks to the definition of a geometrical phase for bursting and a corresponding frequency. We considered neuronal networks with different connection topologies and investigated the transition from a non-synchronized to a partially phase-synchronized state as the coupling strength is varied. The numerically determined critical coupling strength value for this transition to occur is compared with theoretical results valid for the generalized Kuramoto model.Comment: 31 pages, 5 figure

Homeostatic plasticity and external input shape neural network dynamics

In vitro and in vivo spiking activity clearly differ. Whereas networks in vitro develop strong bursts separated by periods of very little spiking activity, in vivo cortical networks show continuous activity. This is puzzling considering that both networks presumably share similar single-neuron dynamics and plasticity rules. We propose that the defining difference between in vitro and in vivo dynamics is the strength of external input. In vitro, networks are virtually isolated, whereas in vivo every brain area receives continuous input. We analyze a model of spiking neurons in which the input strength, mediated by spike rate homeostasis, determines the characteristics of the dynamical state. In more detail, our analytical and numerical results on various network topologies show consistently that under increasing input, homeostatic plasticity generates distinct dynamic states, from bursting, to close-to-critical, reverberating and irregular states. This implies that the dynamic state of a neural network is not fixed but can readily adapt to the input strengths. Indeed, our results match experimental spike recordings in vitro and in vivo: the in vitro bursting behavior is consistent with a state generated by very low network input (< 0.1%), whereas in vivo activity suggests that on the order of 1% recorded spikes are input-driven, resulting in reverberating dynamics. Importantly, this predicts that one can abolish the ubiquitous bursts of in vitro preparations, and instead impose dynamics comparable to in vivo activity by exposing the system to weak long-term stimulation, thereby opening new paths to establish an in vivo-like assay in vitro for basic as well as neurological studies.Comment: 14 pages, 8 figures, accepted at Phys. Rev.

Computational modeling of spike generation in serotonergic neurons of the dorsal raphe nucleu

We consider here a single-compartment model of these neurons which is capable of describing many of the known features of spike generation, particularly the slow rhythmic pacemaking activity often observed in these cells in a variety of species. Included in the model are ten kinds of voltage dependent ion channels as well as calcium-dependent potassium current. Calcium dynamics includes buffering and pumping. In sections 3-9, each component is considered in detail and parameters estimated from voltage clamp data where possible. In the next two sections simplified versions of some components are employed to explore the effects of various parameters on spiking, using a systematic approach, ending up with the following eleven components: a fast sodium current $I_{Na}$, a delayed rectifier potassium current $I_{KDR}$, a transient potassium current $I_A$, a low-threshold calcium current $I_T$, two high threshold calcium currents $I_L$ and $I_N$, small and large conductance potassium currents $I_{SK}$ and $I_{BK}$, a hyperpolarization-activated cation current $I_H$, a leak current $I_{Leak}$ and intracellular calcium ion concentration $Ca_i$. Attention is focused on the properties usually associated with these neurons, particularly long duration of action potential, pacemaker-like spiking and the ramp-like return to threshold after a spike. In some cases the membrane potential trajectories display doublets or have kinks or notches as have been reported in some experimental studies. The computed time courses of $I_A$ and $I_T$ during the interspike interval support the generally held view of a competition between them in influencing the frequency of spiking. Spontaneous spiking could be obtained with small changes in a few parameters from their values with driven spiking.Comment: The abstract has been truncate

In vivo measurements with robust silicon-based multielectrode arrays with extreme shaft lengths

In this paper, manufacturing and in vivo testing of extreme-long Si-based neural microelectrode arrays are presented. Probes with different shaft lengths (15–70 mm) are formed by deep reactive ion etching and have been equipped with platinum electrodes of various configurations. In vivo measurements on rats indicate good mechanical stability, robust implantation, and targeting capability. High-quality signals have been recorded from different locations of the cerebrum of the rodents. The accompanied tissue damage is characterized by histology