W9: Neurotechnologies and closed-loop control of neurodynamics (0099)

Erfan Nozari, Fabio Pasqualetti, Sérgio Pequito

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Recent years have witnessed an unprecedented demand within cognitive sciences (neuroscience, psychology, psychiatry, and beyond) for theoretical and computational tools from mathematics and engineering. This demand is evident, e.g., from the latest Technology Roadmap White Paper produced by the IEEE Brain Society on November 2019 titled \Future Neural Therapeutics: Closed-Loop Control of Neural Activity". There is now little doubt that these tools are critical to complement the classical, experimental and statistical methods in cognitive sciences and tackle the various outstanding problems related to our understanding of the brain and mind. The cross-disciplinary efforts needed to bridge between these fields and enable constructive dialogue between experts from traditionally distant domains are the main focus of this workshop and have tremendous potential to enhance translational research and contribute to various societal problems associated with neurocognitive health. This workshop is in absolute synergy not only with the BRAIN Initiative but also has a particular focus on neurotechnologies. Therefore, this workshop aims to “fill major gaps in our current knowledge and provide unprecedented opportunities for exploring exactly how the brain enables the human body to record, process, utilize, store, and retrieve vast quantities of information", and also develop the next generation of neurowearables and neurostimulators.

The past decade has witnessed an unprecedented and growing interest in interdisciplinary works that use the wealth of theories and tools in mathematics and engineering to solve outstanding problems in neuroscience. It is now widely believed that traditional experimentation and statistical analysis are not sufficient for solving the complex mysteries of the brain (the neural code, e.g.), but should rather be combined with rigorous and abstract mathematical analysis and engineering design [1]. Bridging the rather large gap between neuroscience and mathematics/engineering, however, involves great challenges such as differences in language and terminology, scientific training, methodological limitations, and publication practices, to name a few. It is therefore imperative to dedicate targeted effort and organization to address these challenges and, in doing so, scientific conferences hold a unique position. Among the various recent areas in computational and theoretical neuroscience, dynamical models have been proposed and increasingly sought to describe brain activity and ultimately develop systematically designed and theoretically informed intervention techniques to treat neurocognitive disorders such as Parkinson's disease, epilepsy, spinal cord injury, and major depressive disorder given the dynamical, uncertain, and large-scale nature of brain processes. Here, control theorists and engineers have the unique opportunity and capabilities to contribute to this important research effort demanded by the BRAIN Initiative. Indeed, the demand for these tools is evident from the latest Technology Roadmap White Paper produced by the IEEE Brain Society on November 2019 titled \Future Neural Therapeutics: Closed-Loop Control of Neural Activity".

The “Neurotechnologies and closed-loop control of neurodynamics" workshop will bring together researchers from different backgrounds to demonstrate how the theory of dynamical systems and control engineering successfully enables new insights in neuroscience and emerging neurotechnologies. More specifically, the scope of the talks will cover:

  • mathematical modeling of neurodynamics at different spatio-temporal scales;
  • theoretical and computational methods of analyzing the dynamics of these models and how they relate to behavior;
  • state of the art neurotechnologies for sensing and actuation;
  • the motor system, brain-machine interfaces, and rehabilitation;
  • identification of pathological activity in models of neurodynamics and the design of closed-loop control strategies for mitigating them; and
  • synchronization and synchronizability of global brain activity.

For up-to-date information regarding this workshop please link to


Topic 1. Brain modeling for control

  • Neuroscience experts: Dr. Danielle Bassett (University of Pennsylvania)
  • Control experts: Dr. ShiNung Ching (Washington University in St. Louis)

Topic 2. Epilepsy and seizure control

  • Neuroscience experts: Dr. Steven Schi_ (Pennsylvania State University)
  • Control experts: Dr. Sridevi Sarma (Johns Hopkins University)

Topic 3. Brain Machine Interfaces and motor control

  • Neuroscience experts: Dr. Cindy Chestek (University of Michigan)
  • Control experts: Dr. Maryam Shanechi (University of Southern California)


Erfan Nozari

Department of Mechanical Engineering, University of California at Riverside

Fabio Pasqualetti

Department of Mechanical Engineering, University of California at Riverside

Sérgio Pequito

Delft Center for Systems & Control, Delft University of Technology

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