Oscillation suppression effects of intermittent noisy deep brain stimulation induced by coordinated reset pattern based on a computational model

2022 ◽  
Vol 73 ◽  
pp. 103466
Author(s):  
Chen Liu ◽  
Yutong Yao ◽  
Jiang Wang ◽  
Huiyan Li ◽  
Hao Wu ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Computational Model ◽  
Brain Stimulation ◽  
Oscillation Suppression ◽  
Coordinated Reset ◽  
Suppression Effects ◽  
Deep Brain

New insights offered by a computational model of deep brain stimulation

2007 ◽  
Vol 101 (1-3) ◽  
pp. 56-63 ◽  
Author(s):  
J. Modolo ◽  
E. Mosekilde ◽  
A. Beuter
Keyword(s):  
Deep Brain Stimulation ◽  
Computational Model ◽  
Brain Stimulation ◽  
Deep Brain

scholarly journals Low-frequency oscillation suppression in dystonia: Implications for adaptive deep brain stimulation

2020 ◽  
Vol 79 ◽  
pp. 105-109
Author(s):  
D. Piña-Fuentes ◽  
M. Beudel ◽  
J.C. Van Zijl ◽  
M.E. Van Egmond ◽  
D.L.M. Oterdoom ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Brain Stimulation ◽  
Low Frequency ◽  
Frequency Oscillation ◽  
Low Frequency Oscillation ◽  
Oscillation Suppression ◽  
Deep Brain

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 Thalamocortical Relay Fidelity Varies Across Subthalamic Nucleus Deep Brain Stimulation Protocols in a Data-Driven Computational Model

2008 ◽  
Vol 99 (3) ◽  
pp. 1477-1492 ◽  
Author(s):  
Yixin Guo ◽  
Jonathan E. Rubin ◽  
Cameron C. McIntyre ◽  
Jerrold L. Vitek ◽  
David Terman
Keyword(s):  
Deep Brain Stimulation ◽  
Basal Ganglia ◽  
Computational Model ◽  
Subthalamic Nucleus ◽  
Brain Stimulation ◽  
Relay Cell ◽  
Heterogeneous Model ◽  
Normal Case ◽  
Stn Dbs ◽  
Deep Brain

The therapeutic effectiveness of deep brain stimulation (DBS) of the subthalamic nucleus (STN) may arise through its effects on inhibitory basal ganglia outputs, including those from the internal segment of the globus pallidus (GPi). Changes in GPi activity will impact its thalamic targets, representing a possible pathway for STN-DBS to modulate basal ganglia-thalamocortical processing. To study the effect of STN-DBS on thalamic activity, we examined thalamocortical (TC) relay cell responses to an excitatory input train under a variety of inhibitory signals, using a computational model. The inhibitory signals were obtained from single-unit GPi recordings from normal monkeys and from monkeys rendered parkinsonian through arterial 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine injection. The parkinsonian GPi data were collected in the absence of STN-DBS, under sub-therapeutic STN-DBS, and under therapeutic STN-DBS. Our simulations show that inhibition from parkinsonian GPi activity recorded without DBS-compromised TC relay of excitatory inputs compared with the normal case, whereas TC relay fidelity improved significantly under inhibition from therapeutic, but not sub-therapeutic, STN-DBS GPi activity. In a heterogeneous model TC cell population, response failures to the same input occurred across multiple TC cells significantly more often without DBS than in the therapeutic DBS case and in the normal case. Inhibitory signals preceding successful TC relay were relatively constant, whereas those before failures changed more rapidly. Computationally generated inhibitory inputs yielded similar effects on TC relay. These results support the hypothesis that STN-DBS alters parkinsonian GPi activity in a way that may improve TC relay fidelity.

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