Relating Spontaneous Activity and Cognitive States via NeuroDynamic Modeling

Stimulus-free brain dynamics form the basis of current knowledge concerning functional integration and segregation within the human brain. These relationships are typically described in terms of resting-state brain networks—regions which spontaneously coactivate. However, despite the interest in the anatomical mechanisms and biobehavioral correlates of stimulus-free brain dynamics, little is known regarding the relation between spontaneous brain dynamics and task-evoked activity. In particular, no computational framework has been previously proposed to unite spontaneous and task dynamics under a single, data-driven model. Model development in this domain will provide new insight regarding the mechanisms by which exogeneous stimuli and intrinsic neural circuitry interact to shape human cognition. The current work bridges this gap by deriving and validating a new technique, termed Mesoscale Individualized NeuroDynamic (MINDy) modeling, to estimate large-scale neural population models for individual human subjects using resting-state fMRI. A combination of ground-truth simulations and test-retest data are used to demonstrate that the approach is robust to various forms of noise, motion, and data processing choices. The MINDy formalism is then extended to simultaneously estimating neural population models and the neurovascular coupling which gives rise to BOLD fMRI. In doing so, I develop and validate a new optimization framework for simultaneously estimating system states and parameters. Lastly, MINDy models derived from resting-state data are used to predict task-based activity and remove the effects of intrinsic dynamics. Removing the MINDy model predictions from task fMRI, enables separation of exogenously-driven components of activity from their indirect consequences (the model predictions). Results demonstrate that removing the predicted intrinsic dynamics improves detection of event-triggered and sustained responses across four cognitive tasks. Together, these findings validate the MINDy framework and demonstrate that MINDy models predict brain dynamics across contexts. These dynamics contribute to the variance of task-evoked brain activity between subjects. Removing the influence of intrinsic dynamics improves the estimation of task effects

非線形システムに対する制御系設計と外乱抑制のための積分型リアプノフ関数アプローチ

電気通信大学202

Cooperative Strategies for Management of Power Quality Problems in Voltage-Source Converter-based Microgrids

The development of cooperative control strategies for microgrids has become an area of increasing research interest in recent years, often a result of advances in other areas of control theory such as multi-agent systems and enabled by emerging wireless communications technology, machine learning techniques, and power electronics. While some possible applications of the cooperative control theory to microgrids have been described in the research literature, a comprehensive survey of this approach with respect to its limitations and wide-ranging potential applications has not yet been provided. In this regard, an important area of research into microgrids is developing intelligent cooperative operating strategies within and between microgrids which implement and allocate tasks at the local level, and do not rely on centralized command and control structures. Multi-agent techniques are one focus of this research, but have not been applied to the full range of power quality problems in microgrids. The ability for microgrid control systems to manage harmonics, unbalance, flicker, and black start capability are some examples of applications yet to be fully exploited. During islanded operation, the normal buffer against disturbances and power imbalances provided by the main grid coupling is removed, this together with the reduced inertia of the microgrid (MG), makes power quality (PQ) management a critical control function. This research will investigate new cooperative control techniques for solving power quality problems in voltage source converter (VSC)-based AC microgrids. A set of specific power quality problems have been selected for the application focus, based on a survey of relevant published literature, international standards, and electricity utility regulations. The control problems which will be addressed are voltage regulation, unbalance load sharing, and flicker mitigation. The thesis introduces novel approaches based on multi-agent consensus problems and differential games. It was decided to exclude the management of harmonics, which is a more challenging issue, and is the focus of future research. Rather than using model-based engineering design for optimization of controller parameters, the thesis describes a novel technique for controller synthesis using off-policy reinforcement learning. The thesis also addresses the topic of communication and control system co-design. In this regard, stability of secondary voltage control considering communication time-delays will be addressed, while a performance-oriented approach to rate allocation using a novel solution method is described based on convex optimization

Second International Workshop on Harmonic Oscillators

The Second International Workshop on Harmonic Oscillators was held at the Hotel Hacienda Cocoyoc from March 23 to 25, 1994. The Workshop gathered 67 participants; there were 10 invited lecturers, 30 plenary oral presentations, 15 posters, and plenty of discussion divided into the five sessions of this volume. The Organizing Committee was asked by the chairman of several Mexican funding agencies what exactly was meant by harmonic oscillators, and for what purpose the new research could be useful. Harmonic oscillators - as we explained - is a code name for a family of mathematical models based on the theory of Lie algebras and groups, with applications in a growing range of physical theories and technologies: molecular, atomic, nuclear and particle physics; quantum optics and communication theory