scholarly journals Optimal Closed-loop Deep Brain Stimulation with Multi-Contact Electrodes

2020 ◽  
Author(s):  
Gihan Weerasinghe ◽  
Benoit Duchet ◽  
Christian Bick ◽  
Rafal Bogacz
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Brain Activity ◽  
Neural Populations ◽  
Multiple Regions ◽  
Analytical Expressions ◽  
Contact Electrodes ◽  
Coupled Oscillator Model ◽  
Deep Brain

AbstractDeep brain stimulation (DBS) is a well-established treatment option for a variety of neurological disorders, including Parkinson’s disease (PD) and essential tremor (ET). It is widely believed that the efficacy, efficiency and side-effects of the treatment can be improved by stimulating ‘closed-loop’, according to the symptoms of a patient. Multi-contact electrodes powered by independent current sources are a recent development in DBS technology which allow for greater precision when targeting one or more pathological regions but, in order to realise the potential of such systems, algorithms must be developed to deal with their increased complexity. This motivates the need to understand how applying DBS to multiple regions (or neural populations) can affect the efficacy and efficiency of the treatment. On the basis of a theoretical model, our paper aims to address the question of how to best apply DBS to multiple neural populations to maximally desynchronise brain activity. Using a coupled oscillator model, we derive analytical expressions which predict how the symptom severity should change as a result of applying stimulation. On the basis of these expressions we derive an algorithm describing when the stimulation should be delivered to individual contacts. Remarkably, these expressions also allow us to determine the conditions for when stimulation using information from individual contacts is likely to be advantageous. Using numerical simulation, we demonstrate that our methods have the potential to be both more effective and efficient than existing methods found in the literature.

scholarly journals Optimal closed-loop deep brain stimulation using multiple independently controlled contacts

2021 ◽  
Vol 17 (8) ◽  
pp. e1009281
Author(s):  
Gihan Weerasinghe ◽  
Benoit Duchet ◽  
Christian Bick ◽  
Rafal Bogacz
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Brain Activity ◽  
Neural Populations ◽  
Multiple Regions ◽  
Analytical Expressions ◽  
The Brain ◽  
Coordinated Reset ◽  
Deep Brain

Deep brain stimulation (DBS) is a well-established treatment option for a variety of neurological disorders, including Parkinson’s disease and essential tremor. The symptoms of these disorders are known to be associated with pathological synchronous neural activity in the basal ganglia and thalamus. It is hypothesised that DBS acts to desynchronise this activity, leading to an overall reduction in symptoms. Electrodes with multiple independently controllable contacts are a recent development in DBS technology which have the potential to target one or more pathological regions with greater precision, reducing side effects and potentially increasing both the efficacy and efficiency of the treatment. The increased complexity of these systems, however, motivates the need to understand the effects of DBS when applied to multiple regions or neural populations within the brain. On the basis of a theoretical model, our paper addresses the question of how to best apply DBS to multiple neural populations to maximally desynchronise brain activity. Central to this are analytical expressions, which we derive, that predict how the symptom severity should change when stimulation is applied. Using these expressions, we construct a closed-loop DBS strategy describing how stimulation should be delivered to individual contacts using the phases and amplitudes of feedback signals. We simulate our method and compare it against two others found in the literature: coordinated reset and phase-locked stimulation. We also investigate the conditions for which our strategy is expected to yield the most benefit.

scholarly journals Applying a Sensing-Enabled System for Ensuring Safe Anterior Cingulate Deep Brain Stimulation for Pain

2019 ◽  
Vol 9 (7) ◽  
pp. 150 ◽  
Author(s):  
Yongzhi Huang ◽  
Binith Cheeran ◽  
Alexander L. Green ◽  
Timothy J. Denison ◽  
Tipu Z. Aziz
Keyword(s):  
Deep Brain Stimulation ◽  
Pain Relief ◽  
Brain Stimulation ◽  
Brain Activity ◽  
Anterior Cingulate ◽  
Chronic Therapy ◽  
Provide Pain Relief ◽  
Surgical Options ◽  
Effective Pain Relief ◽  
Deep Brain

Deep brain stimulation (DBS) of the anterior cingulate cortex (ACC) was offered to chronic pain patients who had exhausted medical and surgical options. However, several patients developed recurrent seizures. This work was conducted to assess the effect of ACC stimulation on the brain activity and to guide safe DBS programming. A sensing-enabled neurostimulator (Activa PC + S) allowing wireless recording through the stimulating electrodes was chronically implanted in three patients. Stimulation patterns with different amplitude levels and variable ramping rates were tested to investigate whether these patterns could provide pain relief without triggering after-discharges (ADs) within local field potentials (LFPs) recorded in the ACC. In the absence of ramping, AD activity was detected following stimulation at amplitude levels below those used in chronic therapy. Adjustment of stimulus cycling patterns, by slowly ramping on/off (8-s ramp duration), was able to prevent ADs at higher amplitude levels while maintaining effective pain relief. The absence of AD activity confirmed from the implant was correlated with the absence of clinical seizures. We propose that AD activity in the ACC could be a biomarker for the likelihood of seizures in these patients, and the application of sensing-enabled techniques has the potential to advance safer brain stimulation therapies, especially in novel targets.

Closed-loop programming using external responses for deep brain stimulation in Parkinson's disease

2021 ◽  
Vol 84 ◽  
pp. 47-51
Author(s):  
Fuyuko Sasaki ◽  
Genko Oyama ◽  
Satoko Sekimoto ◽  
Maierdanjiang Nuermaimaiti ◽  
Hirokazu Iwamuro ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Deep Brain

scholarly journals Conceptualization and validation of an open-source closed-loop deep brain stimulation system in rat

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Hemmings Wu ◽  
Hartwin Ghekiere ◽  
Dorien Beeckmans ◽  
Tim Tambuyzer ◽  
Kris van Kuyck ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Deep Brain Stimulation ◽  
Open Source ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Symptom Control ◽  
Theta Oscillations ◽  
Open Source Hardware ◽  
Hippocampal Theta ◽  
Deep Brain

Abstract Conventional deep brain stimulation (DBS) applies constant electrical stimulation to specific brain regions to treat neurological disorders. Closed-loop DBS with real-time feedback is gaining attention in recent years, after proved more effective than conventional DBS in terms of pathological symptom control clinically. Here we demonstrate the conceptualization and validation of a closed-loop DBS system using open-source hardware. We used hippocampal theta oscillations as system input and electrical stimulation in the mesencephalic reticular formation (mRt) as controller output. It is well documented that hippocampal theta oscillations are highly related to locomotion, while electrical stimulation in the mRt induces freezing. We used an Arduino open-source microcontroller between input and output sources. This allowed us to use hippocampal local field potentials (LFPs) to steer electrical stimulation in the mRt. Our results showed that closed-loop DBS significantly suppressed locomotion compared to no stimulation and required on average only 56% of the stimulation used in open-loop DBS to reach similar effects. The main advantages of open-source hardware include wide selection and availability, high customizability and affordability. Our open-source closed-loop DBS system is effective and warrants further research using open-source hardware for closed-loop neuromodulation.

scholarly journals Differential effects of deep brain stimulation and levodopa on brain activity in Parkinson’s disease

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Karsten Mueller ◽  
Dušan Urgošík ◽  
Tommaso Ballarini ◽  
Štefan Holiga ◽  
Harald E Möller ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Deep Brain Stimulation ◽  
Functional Mri ◽  
Brain Stimulation ◽  
Significant Interaction ◽  
Brain Activity ◽  
Finger Tapping ◽  
Levodopa Treatment ◽  
Deep Brain

Abstract Levodopa is the first-line treatment for Parkinson’s disease, although the precise mechanisms mediating its efficacy remain elusive. We aimed to elucidate treatment effects of levodopa on brain activity during the execution of fine movements and to compare them with deep brain stimulation of the subthalamic nuclei. We studied 32 patients with Parkinson’s disease using functional MRI during the execution of finger-tapping task, alternating epochs of movement and rest. The task was performed after withdrawal and administration of a single levodopa dose. A subgroup of patients (n = 18) repeated the experiment after electrode implantation with stimulator on and off. Investigating levodopa treatment, we found a significant interaction between both factors of treatment state (off, on) and experimental task (finger tapping, rest) in bilateral putamen, but not in other motor regions. Specifically, during the off state of levodopa medication, activity in the putamen at rest was higher than during tapping. This represents an aberrant activity pattern probably indicating the derangement of basal ganglia network activity due to the lack of dopaminergic input. Levodopa medication reverted this pattern, so that putaminal activity during finger tapping was higher than during rest, as previously described in healthy controls. Within-group comparison with deep brain stimulation underlines the specificity of our findings with levodopa treatment. Indeed, a significant interaction was observed between treatment approach (levodopa, deep brain stimulation) and treatment state (off, on) in bilateral putamen. Our functional MRI study compared for the first time the differential effects of levodopa treatment and deep brain stimulation on brain motor activity. We showed modulatory effects of levodopa on brain activity of the putamen during finger movement execution, which were not observed with deep brain stimulation.

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