An implantable Bi-directional brain-machine interface system for chronic neuroprosthesis research

Stanslaski, Scott; Cong, Peng; Carlson, David; Santa, W.; Jensen, Randy M.; Molnar, Greg; Marks, William J.; Shafquat, Afsah; Denison, Timothy

doi:10.1109/iembs.2009.5334562

Cited by 34 publications

(38 citation statements)

References 5 publications

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“…pacemakers and defibrillators), which can directly measure and report the effects of stimulation on the target organ, the present generation of neurostimulators does not have the capability to record physiologic signals from implanted leads. We report here the first chronic evaluation, in a large animal model, of a new DBS hardware platform designed to permit long-term recording of electrical brain activity [17], and to thereby directly examine the effects of DBS on specific neural networks. …”

Section: Introductionmentioning

confidence: 99%

Chronic Evaluation of a Clinical System for Deep Brain Stimulation and Recording of Neural Network Activity

Stypulkowski¹,

Stanslaski²,

Denison³

et al. 2013

Stereotact Funct Neurosurg

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Background/Aims: In conjunction with therapeutic stimulation, next-generation deep brain stimulation (DBS) devices may offer the ability to record and analyze neural signals, providing for unprecedented insight into DBS effects on neural networks. This work was conducted to evaluate an implantable, clinical-grade system that permits concurrent stimulation and recording using a large animal (ovine) model recently developed to study DBS for epilepsy. Methods: Following anesthesia and 1.5-tesla MRI acquisition, unilateral anterior thalamic and hippocampal DBS leads were implanted (n = 3) using a frameless stereotactic system. Chronic, awake recordings of evoked potentials (EPs) and local field potentials were collected with the implanted device and analyzed off-line. Results: Hippocampal EPs were stable over long-term (>1 year) recording and consistent in morphology and latency with prior acute results. Thalamic and hippocampal DBS produced both excitatory and inhibitory network effects that were stimulation site and parameter dependent. Free roaming recordings illustrated periods of highly correlated activity between these two structures within the circuit of Papez. Conclusions: These results provide further insight into mechanisms of DBS therapy for epilepsy and an encouraging demonstration of the capabilities of this new technology, which in the future, may afford unique opportunities to study human brain function and neuromodulation mechanism of action.

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Section: Introductionmentioning

confidence: 99%

Chronic Evaluation of a Clinical System for Deep Brain Stimulation and Recording of Neural Network Activity

Stypulkowski¹,

Stanslaski²,

Denison³

et al. 2013

Stereotact Funct Neurosurg

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“…Currently, in standard DBS systems, the stimulation parameters setting is done either by neurologist or trained physician according to gaits. The stimulation parameter adjustment by the clinician is not in real-time and automated, meaning that such systems are not closed loop systems [9]. Standard OLDBS systems suffer from some limitations including: having no effect on some symptoms, deteriorating certain conditions, causing some side effects, becoming less effective with time, causing speech impairment, increasing the cost of therapy, applying the same stimulation signal regardless of the state of patient, and so on [10].…”

Section: Introductionmentioning

confidence: 99%

Closed loop deep brain stimulation: an evolving technology

Hosain

Kouzani

Tye

2014

Australas Phys Eng Sci Med

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Deep brain stimulation is an effective and safe medical treatment for a variety of neurological and psychiatric disorders including Parkinson's disease, essential tremor, dystonia, and treatment resistant obsessive compulsive disorder. A closed loop deep brain stimulation (CLDBS) system automatically adjusts stimulation parameters by the brain response in real time. The CLDBS continues to evolve due to the advancement in the brain stimulation technologies. This paper provides a study on the existing systems developed for CLDBS. It highlights the issues associated with CLDBS systems including feedback signal recording and processing, stimulation parameters setting, control algorithm, wireless telemetry, size, and power consumption. The benefits and limitations of the existing CLDBS systems are also presented. Whilst robust clinical proof of the benefits of the technology remains to be achieved, it has the potential to offer several advantages over open loop DBS. The CLDBS can improve efficiency and efficacy of therapy, eliminate lengthy start-up period for programming and adjustment, provide a personalized treatment, and make parameters setting automatic and adaptive.

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“…The capacity to simultaneously sense and stimulate is highly desirable, as it enables well-tailored, prompt adaptive therapeutics and contributes to our understanding of natural and evoked neural activity [68]. However, in practice, the ability of closed loop neuromodulation devices to detect brain signals is limited, due relatively high amplitude of the stimulation potential compared to the field potential signals used to sense brain activity [50].…”

Section: Typical Requirements Of Implant Systemsmentioning

confidence: 99%

“…In themselves, complex algorithms may lead to noncapture or oversensing of biological signals, potentially resulting in under or incorrect diagnosis [63,70]. As a result, concurrent sensing and stimulation is often foregone if favor of detecting and recording data regarding the immediate actuation performance, reducing neuromodulation treatment to rigid stimulation system that relies heavily on the symptomatic assessment and actuation tuning by the medical practitioner [55,68]. Although certain combinations of indwelling hardware, e.g., high performance amplifiers, stimulation parameters and interpretation algorithms can minimize residual stimulation disturbances, further research in this area is required [50].…”

Section: Typical Requirements Of Implant Systemsmentioning

confidence: 99%

Implantable Devices: Issues and Challenges

2012

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Ageing population and a multitude of neurological and cardiovascular illnesses that cannot be mitigated by medication alone have resulted in a significant growth in the number of patients that require implantable electronic devices. These range from sensors, gastric and cardiac pacemakers, cardioverter defibrillators, to deep brain, nerve, and bone stimulators. Long-term implants present specific engineering challenges, including low energy consumption and stable performance. Resorbable electronics may offer excellent short-term performance without the need for surgical removal. However, most electronic materials have poor bio-and cytocompatibility, resulting in immune reactions and infections. This paper reviews the current situation and highlights challenges for future advancements.

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An implantable Bi-directional brain-machine interface system for chronic neuroprosthesis research

Cited by 34 publications

References 5 publications

Chronic Evaluation of a Clinical System for Deep Brain Stimulation and Recording of Neural Network Activity

Chronic Evaluation of a Clinical System for Deep Brain Stimulation and Recording of Neural Network Activity

Closed loop deep brain stimulation: an evolving technology

Implantable Devices: Issues and Challenges

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