Jeffrey Herron

Kinematic Adaptive Deep Brain Stimulation for Resting Tremor in Parkinson's Disease.

Alessio Di Fonzo, MD, PhD, Gianluca Ardolino, MD, Lorena Airaghi, MD, Piero Biondetti, MD, and Nereo Bresolin, MD Department of Neuroscience and Mental Health, IRCCS C a Granda-Ospedale Maggiore Policlinico Foundation, University of Milan, Milan, Italy Excellence Center for Advanced MR Studies, IRCCS C a Granda-Ospedale Maggiore Policlinico Foundation, Milan, Italy Department of Internal Medicine, IRCCS C a Granda-Ospedale Maggiore Policlinico Foundation, University of Milan, Milan, Italy Radiology Unit, IRCCS C a Granda-Ospedale Maggiore Policlinico Foundation, Milan, Italy

Proceedings of the Third Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

The proceedings of the 3rd Annual Deep Brain Stimulation Think Tank summarize the most contemporary clinical, electrophysiological, imaging, and computational work on DBS for the treatment of neurological and neuropsychiatric disease. Significant innovations of the past year are emphasized. The Think Tanks contributors represent a unique multidisciplinary ensemble of expert neurologists, neurosurgeons, neuropsychologists, psychiatrists, scientists, engineers, and members of industry. Presentations and discussions covered a broad range of topics, including policy and advocacy considerations for the future of DBS, connectomic approaches to DBS targeting, developments in electrophysiology and related strides toward responsive DBS systems, and recent developments in sensor and device technologies.

Chronic electrocorticography for sensing movement intention and closed-loop deep brain stimulation with wearable sensors in an essential tremor patient

Deep brain stimulation (DBS) has become a widespread and valuable treatment for patients with movement disorders such as essential tremor (ET). However, current DBS treatment constantly delivers stimulation in an open loop, which can be inefficient. Closing the loop with sensors to provide feedback may increase power efficiency and reduce side effects for patients. New implantable neuromodulation platforms, such as the Medtronic Activa PC+S DBS system, offer important data sources by providing chronic neural sensing capabilities and a means of investigating dynamic stimulation based on symptom measurements. The authors implanted in a single patient with ET an Activa PC+S system, a cortical strip of electrodes on the hand sensorimotor cortex, and therapeutic electrodes in the ventral intermediate nucleus of the thalamus. In this paper they describe the effectiveness of the platform when sensing cortical movement intentions while the patient actually performed and imagined performing movements. Additionally, they demonstrate dynamic closed-loop DBS based on several wearable sensor measurements of tremor intensity.

Prototype closed-loop deep brain stimulation systems inspired by Norbert Wiener

Implantable neurostimulators have rapidly become established methods of treating a variety of neurological disor-ders. The development of implantable neural interfaces enable the testing of Norbert Wieners hypotheses regarding neural disorders and their relationship to ideas of cybernetics. However, currently deployed medical devices of this kind are open-loop. For example, DBS for treatment of tremor does not take into account the variable and intermittent nature of the tremor. Closing the loop through sensors and real-time communication to the implanted neurostimulator could result in lower average power dissipation and reduced side effects from unneeded stimulation. In this paper we present a closed-loop DBS platform for investigating control strategies for the management of essential tremor. We demonstrate a system capable using a variety of sensors including inertial measurements, electromyography and neurostimulator electrode readings. This sensed data is used to modify stimulation (within limits pre-set by a clinician), thus resulting in a closed-loop system.

Closed-loop DBS with movement intention

In this paper we present a prototype proof-of-concept for a closed-loop deep brain stimulation system for patients with essential tremor. This system makes use of sensed movement intentions via EEG to determine when stimulation is required and automatically enables stimulation only when needed. We demonstrate this system using a healthy subject and a benchtop experimental prototype. By limiting stimulation to only when it is therapeutically required, implanted neurostimulators can be more power efficient and potentially limit the period where patients experience side-effects to only the time when therapy is needed.

Securing the exocortex: A twenty-first century cybernetics challenge

An exocortex is a wearable (or implanted) computer, used to augment a brains biological high-level cognitive processes and inform a users decisions and actions. In this paper, we focus on Brain-Computer Interfaces (BCIs), a special type of exocortex used to interact with the environment via neural signals. BCI use ranges from medical applications and rehabilitation to operation of assistive devices. They can also be used for marketing, gaming, and entertainment, where BCIs are used to provide users with a more personalized experience. BCI-enabled technology carries a great potential to improve and enhance the quality of human lives. This technology, however, is not without risk. In this paper, we address a specific class of privacy issues, brain spyware, shown to be feasible against currently available non-invasive BCIs. We show this attack can be mapped into a communication-theoretic setting. We then show that the problem of preventing it is similar to the problem of information hiding in communications. We address it in an information-theoretic framework. Finally, influenced by Professor Wieners computer ethics work, we propose a set of principles regarding appropriate use of exocortex.

Controlling our brains – a case study on the implications of brain-computer interface-triggered deep brain stimulation for essential tremor

AbstractDeep brain stimulators (DBS) are a neurotechnological means of treating a variety of movement disorders, including essential tremor (ET). Current stimulation systems apply an electrical current to targets in the brain at a constant rate for as long as they are implanted and activated – treating symptoms but causing uncomfortable side-effects and inefficient power usage. Some users feel estranged or isolated for various reasons. Next-generation DBS systems could use the patient’s self-modulated neural signals to trigger stimulation. These brain-computer interface-triggered DBS (BCI-DBS) systems would give the user the ability to moderate side-effects and reduce battery power consumption. It’s not yet clear, however, whether neural control will alleviate or exacerbate psychosocial problems. To explore these concerns, we conducted interviews with an ET patient using an experimental BCI-DBS platform. Our interviews offer preliminary insights about what problems ET patients may face while using BCI-DBS.

Securing the Exocortex: A Twenty-First Century Cybernetics Challenge

An exocortex is a wearable (or implanted) computer, used to augment a brains biological high-level cognitive processes and inform a users decisions and actions. In this paper, we focus on Brain-Computer Interfaces (BCIs), a special type of exocortex used to interact with the environment via neural signals. BCI use ranges from medical applications and rehabilitation to operation of assistive devices. They can also be used for marketing, gaming, and entertainment, where BCIs are used to provide users with a more personalized experience. BCI-enabled technology carries a great potential to improve and enhance the quality of human lives. This technology, however, is not without risk. In this paper, we address a specific class of privacy issues, brain spyware, shown to be feasible against currently available non-invasive BCIs. We show this attack can be mapped into a communication-theoretic setting. We then show that the problem of preventing it is similar to the problem of information hiding in communications. We address it in an information-theoretic framework. Finally, influenced by Professor Wieners computer ethics work, we propose a set of principles regarding appropriate use of exocortex.

Cortical Brain–Computer Interface for Closed-Loop Deep Brain Stimulation

Essential tremor is the most common neurological movement disorder. This progressive disease causes uncontrollable rhythmic motions—most often affecting the patient’sdominant upper extremity—thatoccur during volitional movement and make it difficult for the patient to perform everyday tasks. Medication may also become ineffective as the disorder progresses. For many patients, deep brain stimulation (DBS) of the thalamus is an effective means of treating this condition when medication fails. In current use, however, clinicians set the patient’s stimulator to apply stimulation at all times—whether it is needed or not. This practice leads to excess power use, and more rapid depletion of batteries that require surgical replacement. In this paper, for the first time, neural sensing of movement (using chronically implanted cortical electrodes) is used to enable or disable stimulation for tremor. Therapeutic stimulation is delivered onlywhen the patient is actively using their effected limb, thereby reducing the total stimulation applied, and potentially extending the lifetime of surgically implanted batteries. This paper, which involves both implanted and external subsystems, paves the way for fully-implanted closed-loop DBS in the future.

Designing Neuromodulation Devices for Feedback Control

Abstract This chapter focuses on neuromodulation systems that leverage feedback control to adjust stimulation properties automatically. Most current neuromodulation systems provide open-loop stimulation, wherein stimulation parameters are static and unaffected by changes in symptoms or disease. In contrast, closed-loop systems adapt therapy in response to physiological changes and may provide more effective and efficient therapy. Closed-loop systems have already begun to appear in clinical practice. The chapter introduces the scientific background and technology landscape for three therapy areas that are using closed-loop control: spinal cord stimulation, vagal nerve stimulation, and deep brain stimulation. A review of general design strategies and practical considerations for the development of neuromodulation systems that leverage principles of feedback control to deliver therapy is presented.