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In this paper, we analyze the spatiotemporal mean field model developed by Liley et al. [1] in order to advance our understanding of the wide effects of pharmacological agents and anesthetics. Specifically, we use the spatiotemporal mean field model in [1] for capturing the electrical activity in the neocortex to computationally study the emergence of α- and gamma-band rhythmic activity in the brain. We show that a oscillations in the solutions of the model appear globally across the neocortex, whereas gamma oscillations can emerge locally as a result of a bifurcation in the dynamics of the model. We solve the dynamic equations of the model using a finite element solver package and show that our results verify the predictions made by bifurcation analysis. 

In this paper, we develop a learning-based secure control framework for cyber-physical systems in the presence of sensor attacks. Specifically, we use several observer-based estimators to detect the attacks while also introducing a threat detection level function. We then solve the underlying joint state estimation and attack mitigation problems by using a reinforcement learning algorithm. Finally, an illustrative numericalexampleisprovidedtoshowtheefficacyoftheproposed framework. 

Summary In this paper, we develop an adaptive control algorithm for addressing security for a class of networked vehicles that comprise a formation ofhuman‐driven vehicles sharing kinematic data and an autonomous vehicle in the aft of the vehicle formation receiving data from the preceding vehicles through wireless vehicle‐to‐vehicle communication devices. Specifically, we develop an adaptive controller for mitigating time‐invariant state‐dependent adversarial sensor and actuator attacks while guaranteeing uniform ultimate boundedness of the closed‐loop networked system. Furthermore, an adaptive learning framework is presented for identifying the state space model parameters based on input‐output data. This learning technique utilizes previously stored data as well as current data to identify the system parameters using a relaxed persistence of excitation condition. The effectiveness of the proposed approach is demonstrated by an illustrative numerical example involving a platoon of connected vehicles.