A flexible algorithm framework for closed-loop neuromodulation research systems

Carlson, David; Linde, Dave; Isaacson, Ben; Afshar, Puya; Bourget, Duane; Stanslaski, Scott; Stypulkowski, Paul H.; Denison, Timothy

doi:10.1109/embc.2013.6610956

Cited by 6 publications

(4 citation statements)

References 11 publications

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“…Other programmable stimulation platforms motivated by a dynamic control framework have previously been proposed [6, 7]. However, despite examples of responsive electrical stimulation in people and animals, we did not find a reported system in literature with the low latency, high channel throughput and sampling rate, and suitability for inpatient testing that characterizes our system.…”

Section: Discussionmentioning

confidence: 86%

“…Programmable, dynamic control approaches to brain stimulation and seizure control have been proposed, but have not been translated to human research participants [5–7]. Cortical stimulation has been used to probe neural dynamics during interictal states in people with epilepsy, as an active assessment of the susceptibility of brain network dynamics to electrical pulse propagation, and by extension, seizures [8].…”

Section: Introductionmentioning

confidence: 99%

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A modular, closed-loop platform for intracranial stimulation in people with neurological disorders

Sarma

Crocker

Cash

et al. 2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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Neuromodulation systems based on electrical stimulation can be used to investigate, probe, and potentially treat a range of neurological disorders. The effects of ongoing neural state and dynamics on stimulation response, and of stimulation parameters on neural state, have broad implications for the development of closed-loop neuromodulation approaches. We describe the development of a modular, low-latency platform for pre-clinical, closed-loop neuromodulation studies with human participants. We illustrate the uses of the platform in a stimulation case study with a person with epilepsy undergoing neuro-monitoring prior to resective surgery. We demonstrate the efficacy of the system by tracking interictal epileptiform discharges in the local field potential to trigger intracranial electrical stimulation, and show that the response to stimulation depends on the neural state.

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Section: Discussionmentioning

confidence: 86%

Section: Introductionmentioning

confidence: 99%

A modular, closed-loop platform for intracranial stimulation in people with neurological disorders

Sarma

Crocker

Cash

et al. 2016

2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

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“…The Medtronic PC+S/RC+S was developed as an open platform for chronic, adaptive brain stimulation, and has been used in a wide range of pre-clinical and clinical applications (Stanslaski et al, 2012 ; Carlson et al, 2013 ; Stypulkowski et al, 2013 ). These include, for example, developing a brain-computer interface in a locked-in patient with amyotrophic lateral sclerosis (Vansteensel et al, 2016 ), tremor control linked to a wearable device (Herron et al, 2017 ), brain stimulation for epilepsy (Stypulkowski et al, 2014 ), and recording biomarkers while stimulating in Parkinson's disease (Quinn et al, 2015 ; Neumann et al, 2016 ; Blumenfeld et al, 2017 ).…”

Section: Adaptive and Closed-loop Controlmentioning

confidence: 99%

Biomarkers and Stimulation Algorithms for Adaptive Brain Stimulation

et al. 2017

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The goal of this review is to describe in what ways feedback or adaptive stimulation may be delivered and adjusted based on relevant biomarkers. Specific treatment mechanisms underlying therapeutic brain stimulation remain unclear, in spite of the demonstrated efficacy in a number of nervous system diseases. Brain stimulation appears to exert widespread influence over specific neural networks that are relevant to specific disease entities. In awake patients, activation or suppression of these neural networks can be assessed by either symptom alleviation (i.e., tremor, rigidity, seizures) or physiological criteria, which may be predictive of expected symptomatic treatment. Secondary verification of network activation through specific biomarkers that are linked to symptomatic disease improvement may be useful for several reasons. For example, these biomarkers could aid optimal intraoperative localization, possibly improve efficacy or efficiency (i.e., reduced power needs), and provide long-term adaptive automatic adjustment of stimulation parameters. Possible biomarkers for use in portable or implanted devices span from ongoing physiological brain activity, evoked local field potentials (LFPs), and intermittent pathological activity, to wearable devices, biochemical, blood flow, optical, or magnetic resonance imaging (MRI) changes, temperature changes, or optogenetic signals. First, however, potential biomarkers must be correlated directly with symptom or disease treatment and network activation. Although numerous biomarkers are under consideration for a variety of stimulation indications the feasibility of these approaches has yet to be fully determined. Particularly, there are critical questions whether the use of adaptive systems can improve efficacy over continuous stimulation, facilitate adjustment of stimulation interventions and improve our understanding of the role of abnormal network function in disease mechanisms.

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“…Thus, the experience in DBS is highly relevant to our discussion of implantable BCI research. Indeed, DBS platforms appear to be a promising approach to early candidates for implantable BCI devices (Carlson et al 2013). Though some early investigators in implantable BCI research have begun to develop and share informed consent processes (Collinger et al 2014) This paper focuses on identifying research risks associated with implantable BCI.…”

Section: Introductionmentioning

confidence: 99%