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It has been demonstrated using single-cell and multiunit electrophysiology in layer III entorhinal cortex and disinhibited hippocampal CA3 slices that the balancing of the up-down activity is characterized by both GABAA and GABAB mechanisms. Here we report novel results obtained using multi-electrode array (60 electrodes) simultaneous recordings from reverberating postnatal neocortical networks containing 19.2 ± 1.4% GABAergic neurons, typical of intact tissue. We observed that in each spontaneous active-state the total number of spikes in identified clusters of excitatory and inhibitory neurons is almost equal, thus suggesting a balanced average activity. Interestingly, in the active-state, the early phase is sustained by only 10% of the total spikes and the firing rate follows a sigmoidal regenerative mode up to peak at 35 ms with the number of excitatory spikes greater than inhibitory, therefore indicating an early unbalance. Concentration-response pharmacology of up- and down-state lifetimes in clusters of excitatory (n = 1067) and inhibitory (n = 305) cells suggests that, besides the GABAA and GABAB mechanisms, others such as GAT-1-mediated uptake, Ih, INaP and IM ion channel activity, robustly govern both up- and down-activity. Some drugs resulted to affect up- and/or down-states with different IC50s, providing evidence that various mechanisms are involved. These results should reinforce not only the role of synchrony in CNS networks, but also the recognized analogies between the Hodgkin–Huxley action potential and the population bursts as basic mechanisms for originating membrane excitability and CNS network synchronization, respectively.

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In this paper, we consider the problem of estimating the parameters in mathematical models of complex systems from experimental observations; the methods and procedures that we develop are general, but in this work we make specific reference to the problem of parameter estimation for multibody-based rotorcraft vehicle models from flight test data. We consider methods that are applicable to unstable systems, since rotorcraft vehicles are typically unstable at least in certain flight regimes. Unstable vehicles must be operated in closed-loop, and this must be explicitly accounted for when formulating parameter estimation methods. We describe two alternative classes of methods in the time domain, namely, the recursive filtering and the batch optimization methods. In the recursive approach, we formulate a novel version of the extended Kalman filter that accounts for the presence of unobservable states in the model. In the case of the batch optimization methods, we present a formulation based on a new single-multiple shooting approach, specifically designed for models with slow and fast solution components. We perform some initial steps toward the validation of the proposed procedures with the help of applications regarding manned and unmanned rotorcraft vehicles.

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