Bidirectional Coupling between Astrocytes and Neurons Mediates Learning and Dynamic Coordination in the Brain: A Multiple Modeling Approach

In recent years research suggests that astrocyte networks, in addition to nutrient and waste processing functions, regulate both structural and synaptic plasticity. To understand the biological mechanisms that underpin such plasticity requires the development of cell level models that capture the mutual interaction between astrocytes and neurons. This paper presents a detailed model of bidirectional signaling between astrocytes and neurons (the astrocyte-neuron model or AN model) which yields new insights into the computational role of astrocyte-neuronal coupling. From a set of modeling studies we demonstrate two significant findings. Firstly, that spatial signaling via astrocytes can relay a “learning signal” to remote synaptic sites. Results show that slow inward currents cause synchronized postsynaptic activity in remote neurons and subsequently allow Spike-Timing-Dependent Plasticity based learning to occur at the associated synapses. Secondly, that bidirectional communication between neurons and astrocytes underpins dynamic coordination between neuron clusters. Although our composite AN model is presently applied to simplified neural structures and limited to coordination between localized neurons, the principle (which embodies structural, functional and dynamic complexity), and the modeling strategy may be extended to coordination among remote neuron clusters

Real time adaptive relay settings for Microgrid protection verified using Hardware in Loop

Microgrids with penetration of renewables is imposing new challenges for system protection. Renewables are characterized with high source impedance which limit the short circuit current. The value of short-circuit current is limited due to converters used which limit the current to a maximum of 1.1 to 1.5 times maximum rated load current. This can result in faults during the islanded mode of microgrid to go unnoticed if the relay settings are not adapted to account for it. The presence of such uncleared faults in the microgrid can result in exposing it to overcurrent for a long time which can damage the equipment. One solution is to have different protection element pickup settings for different modes of operation. This report discusses the development of an algorithm to switch these settings upon microgrid state changes and test the algorithm using OPAL-RT hardware in loop real-time testing with SEL-351S relay as the hardware

The Critical Role of Golgi Cells in Regulating Spatio-Temporal Integration and Plasticity at the Cerebellum Input Stage

The discovery of the Golgi cell is bound to the foundation of the Neuron Doctrine. Recently, the excitable mechanisms of this inhibitory interneuron have been investigated with modern experimental and computational techniques raising renewed interest for the implications it might have for cerebellar circuit functions. Golgi cells are pacemakers with preferential response frequency and phase-reset in the theta-frequency band and can therefore impose specific temporal dynamics to granule cell responses. Moreover, through their connectivity, Golgi cells determine the spatio-temporal organization of cerebellar activity. Finally, Golgi cells, by controlling granule cell depolarization and NMDA channel unblock, regulate the induction of long-term synaptic plasticity at the mossy fiber – granule cell synapse. Thus, the Golgi cells can exert an extensive control on spatio-temporal signal organization and information storage in the granular layer playing a critical role for cerebellar computation

The Critical Role of Golgi Cells in Regulating Spatio-Temporal Integration and Plasticity at the Cerebellum Input Stage

The discovery of the Golgi cell is bound to the foundation of the Neuron Doctrine. Recently, the excitable mechanisms of this inhibitory interneuron have been investigated with modern experimental and computational techniques raising renewed interest for the implications it might have for cerebellar circuit functions. Golgi cells are pacemakers with preferential response frequency and phase-reset in the theta-frequency band and can therefore impose specific temporal dynamics to granule cell responses. Moreover, through their connectivity, Golgi cells determine the spatio-temporal organization of cerebellar activity. Finally, Golgi cells, by controlling granule cell depolarization and NMDA channel unblock, regulate the induction of long-term synaptic plasticity at the mossy fiber – granule cell synapse. Thus, the Golgi cells can exert an extensive control on spatio-temporal signal organization and information storage in the granular layer playing a critical role for cerebellar computation

Controller with Vehicular Communication Design for Vehicular Platoon System

PhD ThesisTracked Electric Vehicles (TEV) which is a new mass-transport system. It aims to provide a safe, efficient and coordinated traffic system. In TEV, the inter-vehicular distance is reduced to only a quarter of the regular car length and where drive at 200km/h enabling mass transport at uniform speed. Under this requirement, the design of the controller is particularly important. This thesis first developed an innovative approach using adaptive Proportion, integral and derivation (PID) controller using fuzzy logic theory to keep variable time-gap between dynamic cars for platooning system with communication delay. The simulation results presented show a significant improvement in keeping time-gap variable between the cars enabling a safe and efficient flow of the platooning system. Secondly, this thesis investigates the use of Slide Mode Control (SMC) for TEV. It studies different V2V communication topology structures using graph theory and proposes a novel SMC design with and without global dynamic information. The Lyapunov candidate function was chosen to study the impact which forms an integral part for current and future research. The simulation results show that this novel SMC has a tolerance ability for communication delay. In order to present the real time TEV platoon system, a similar PI controller has been utilized in a novel automated vehicle, based on Raspberry Pi, multi-sensors and the designed Remote Control (RC) car. Thirdly, in order to obtain precise positioning information for vehicles in platoon system, this thesis describes Inertial Measurement Unit (IMU)/Global Navigation Satellite System (GNSS) data fusion to achieve a highly precise positioning solution. The results show that the following vehicles can reach the same velocity and acceleration as the leading vehicle in 5 seconds and the spacing error is less than 0.1m. The practical results are in line with those from the simulated experiment