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In this paper, we investigate the dynamical behaviors of a Morris-Lecar neuron model. By using bifurcation methods and numerical simulations, we examine the global structure of bifurcations of the model. Results are summarized in various two-parameter bifurcation diagrams with the stimulating current as the abscissa and the other parameter as the ordinate. We also give the one-parameter bifurcation diagrams and pay much attention to the emergence of periodic solutions and bistability. Different membrane excitability is obtained by bifurcation analysis and frequency-current curves. The alteration of the membrane properties of the Morris-Lecar neurons is discussed.

Utilizing NNC 26-9100 (11) as a structural lead, a variety of nonpeptide derivatives of somatostatin were synthesized and evaluated for sst2 and sst4 receptor binding affinity. A novel thiourea scaffold was utilized to attach (1) a heteroaromatic nucleus to mimic the Trp8 residue, (2) a nonheteroaromatic nucleus to mimic Phe7, and (3) a primary amine or other basic group to mimic the Lys9 residue of somatostatin. Displacement studies were carried out using membranes from cell lines expressing ssts [BHK cells (sst4) and HEK 293 cells (sst2)] utilizing [125I]Tyr11-SRIF as the radioligand. Several thioureas (11, 38, 39, 41, and 42) and the urea 66 exhibited Ki values of less than 100 nM. The thioureas 11 (Ki = 6 nM) and 41 (Ki = 16 nM) and the urea 66 (Ki = 14 nM) are believed to be the most potent nonpeptide sst4 agonists known. Since the thiourea 11 and the urea 66 exhibit high sst4 selectivity, these novel nonpeptide derivatives may be useful tools for studying the sst4 receptor. Studies are currently in progress to evaluate the therapeutic potential of NNC 26-9100 (11) in the treatment of glaucoma.

Summary The prefrontal cortex (PFC) plays a prominent role in performing flexible cognitive functions and working memory, yet the underlying computational principle remains poorly understood. Here, we trained a rate-based recurrent neural network (RNN) to explore how the context rules are encoded, maintained across seconds-long mnemonic delay, and subsequently used in a context-dependent decision-making task. The trained networks replicated key experimentally observed features in the PFC of rodent and monkey experiments, such as mixed selectivity, neuronal sequential activity, and rotation dynamics. To uncover the high-dimensional neural dynamical system, we further proposed a geometric framework to quantify and visualize population coding and sensory integration in a temporally defined manner. We employed dynamic epoch-wise principal component analysis (PCA) to define multiple task-specific subspaces and task-related axes, and computed the angles between task-related axes and these subspaces. In low-dimensional neural representations, the trained RNN first encoded the context cues in a cue-specific subspace, and then maintained the cue information with a stable low-activity state persisting during the delay epoch, and further formed line attractors for sensor integration through low-dimensional neural trajectories to guide decision-making. We demonstrated via intensive computer simulations that the geometric manifolds encoding the context information were robust to varying degrees of weight perturbation in both space and time. Overall, our analysis framework provides clear geometric interpretations and quantification of information coding, maintenance, and integration, yielding new insight into the computational mechanisms of context-dependent computation.

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A novel solution to integrating offshore wind power via the Fractional Frequency Transmission System (FFTS) is introduced in this paper. The basic idea of FFTS is to improve the technical and economic performance of AC transmission systems by lowering the grid frequency. FFTS is especially suitable for transmitting offshore wind power because the low frequency dramatically reduces the charging current in the cable. In addition, as a novel AC transmission system, FFTS performs much better than HVDC in constructing a multi-terminal (MT) grid. The basic structures and characteristics of a typical PMSG-based FFTS offshore wind power system and a MT-FFTS offshore grid are described first. Then two offshore wind power cases are used to compare the technical and economical pros and cons of the FFTS solution with the conventional solutions: HVAC and HVDC. The feasibility studies show that the performance of FFTS offshore wind power system is superior to that of HVAC and HVDC in both point-to-point (PP) and multi-terminal cases. The uniform annual value of PP-FFTS and MT-FFTS are 5.01% and 5.07% cheaper than PP-HVDC and MT-HVDC. Therefore, FFTS is a promising solution to offshore wind power integration and building offshore grids.Index Terms-Feasibility study; fractional frequency transmission system; offshore grid; offshore wind power integration

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