No abstract

Neuroadaptations in the nucleus accumbens (NAc) are associated with the development of drug addiction. Plasticity in synaptic strength and intrinsic excitability of NAc medium spiny neurons (MSNs) play critical roles in addiction induced by different classes of abused drugs. However, it is unknown whether morphine exposure influences synaptic strength, intrinsic excitability or both in NAc. Here we show that chronic withdrawal (10 days after the last injection) from repeated morphine exposure elicited potentiation in both glutamatergic synaptic strength and intrinsic excitability of MSNs in NAc shell (NAcSh). The potentiation of synaptic strength was demonstrated by an increase in the frequency of miniature excitatory postsynaptic currents (mEPSCs), a decrease in the paired-pulse ratio (PPR), and an increase in the ratio of α-amino-3-hydroxy-5-methyl-isoxazole propionic acid receptors (AMPAR)- to N-methyl-D-aspartate receptors (NMDAR)-mediated currents. The potentiation of intrinsic excitability was mediated by inhibition of the sustained potassium currents via extrasynaptic NMDAR activation. The function of the presynaptic group II metabotropic glutamate receptors (mGluR2/3) was downregulated, enhancing the probability of glutamate release on synaptic terminals during chronic morphine withdrawal. Pretreatment with the mGluR2/3 agonist LY379268 completely blocked potentiation of both synaptic strength and intrinsic excitability. These results suggest that chronic morphine withdrawal downregulates mGluR2/3 to induce potentiation of MSN glutamatergic synapse via increased glutamate release, leading to potentiation of intrinsic excitability. Such potentiation of both synaptic strength and intrinsic excitability might contribute to neuroadaptations induced by morphine application.

No abstract

No abstract

A derivative-free robust Kalman filter algorithm is proposed for nonlinear uncertain systems. The unscented transform (UT) is adopted instead of the linearization technique to obtain the solution of the H ∞ filter Riccati equation. A robust unscented Kalman filter (RUKF) is derived to guarantee an optimized upper bound on the estimation error covariance despite the model uncertainties and the approximation error of the UT. The proposed algorithm is applied to a satellite attitude determination system. Simulation results show that the RUKF is more effective than the unscented Kalman filter (UKF) in cases where alignment errors are present.