scholarly journals Closed‐Loop Deep Brain Stimulation for Essential Tremor Based on Thalamic Local Field Potentials

2021 ◽  
Vol 36 (4) ◽  
pp. 863-873
Author(s):  
Shenghong He ◽  
Fahd Baig ◽  
Abteen Mostofi ◽  
Alek Pogosyan ◽  
Jean Debarros ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Essential Tremor ◽  
Local Field ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Deep Brain

scholarly journals Acute effects of thalamic deep brain stimulation and thalamotomy on sensorimotor cortex local field potentials in essential tremor

2012 ◽  
Vol 123 (11) ◽  
pp. 2232-2238 ◽  
Author(s):  
Ellen L. Air ◽  
Elena Ryapolova-Webb ◽  
Coralie de Hemptinne ◽  
Jill L. Ostrem ◽  
Nicholas B. Galifianakis ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Essential Tremor ◽  
Local Field ◽  
Brain Stimulation ◽  
Sensorimotor Cortex ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Acute Effects ◽  
Deep Brain

scholarly journals Bilateral double beta peaks in a PD patient with STN electrodes

2020 ◽  
Vol 163 (1) ◽  
pp. 205-209 ◽  
Author(s):  
Thomas Koeglsperger ◽  
Jan H. Mehrkens ◽  
Kai Bötzel
Keyword(s):  
Physical Activity ◽  
Deep Brain Stimulation ◽  
Local Field ◽  
Brain Stimulation ◽  
Closed Loop ◽  
Local Field Potentials ◽  
Beta Activity ◽  
Field Potentials ◽  
Beta Band ◽  
Deep Brain

AbstractSubthalamic local field potentials in the beta band are considered as potential biomarkers for closed-loop deep brain stimulation. To investigate the subthalamic beta band peak amplitudes in a Parkinson’s disease patient over an extended period of time by using a novel and commercially available neurostimulator with permanent sensing capability. We recorded local field potentials of the subthalamic nucleus using the Medtronic Percept™ implantable neurostimulator at rest and during physical activity (gait) with and in response to deep brain stimulation. We found a double-peaked beta activity on both sides. Increasing stimulation and physical activity resulted in a decreased beta band amplitude, but was accompanied by the appearance of a second, and previously unrecognized peak at 13 Hz in the right hemisphere. Our results will support the investigation of distinct different peaks in the beta band and their relevance and usefulness as closed-loop biomarkers.

Basal ganglia local field potentials: applications in the development of new deep brain stimulation devices for movement disorders

2007 ◽  
Vol 4 (5) ◽  
pp. 605-614 ◽  
Author(s):  
Sara Marceglia ◽  
Lorenzo Rossi ◽  
Guglielmo Foffani ◽  
AnnaMaria Bianchi ◽  
Sergio Cerutti ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Basal Ganglia ◽  
Local Field ◽  
Brain Stimulation ◽  
Movement Disorders ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Deep Brain

scholarly journals Characteristics of local field potentials correlate with pain relief by deep brain stimulation

2016 ◽  
Vol 127 (7) ◽  
pp. 2573-2580 ◽  
Author(s):  
Yongzhi Huang ◽  
Huichun Luo ◽  
Alexander L. Green ◽  
Tipu Z. Aziz ◽  
Shouyan Wang
Keyword(s):  
Deep Brain Stimulation ◽  
Pain Relief ◽  
Local Field ◽  
Brain Stimulation ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Deep Brain

A Method for Removal of Deep Brain Stimulation Artifact From Local Field Potentials

2017 ◽  
Vol 25 (12) ◽  
pp. 2217-2226 ◽  
Author(s):  
Xing Qian ◽  
Yue Chen ◽  
Yuan Feng ◽  
Bozhi Ma ◽  
Hongwei Hao ◽  
...  
Keyword(s):  
Deep Brain Stimulation ◽  
Local Field ◽  
Brain Stimulation ◽  
Local Field Potentials ◽  
Field Potentials ◽  
Deep Brain

scholarly journals Biophysical basis of subthalamic local field potentials recorded from deep brain stimulation electrodes

2018 ◽  
Vol 120 (4) ◽  
pp. 1932-1944 ◽  
Author(s):  
Nicholas Maling ◽  
Scott F. Lempka ◽  
Zack Blumenfeld ◽  
Helen Bronte-Stewart ◽  
Cameron C. McIntyre
Keyword(s):  
Deep Brain Stimulation ◽  
Local Field ◽  
Brain Stimulation ◽  
Local Field Potentials ◽  
Patient Specific ◽  
Beta Activity ◽  
Field Potentials ◽  
Clinical Biomarkers ◽  
Scientific Platform ◽  
Deep Brain

Clinical deep brain stimulation (DBS) technology is evolving to enable chronic recording of local field potentials (LFPs) that represent electrophysiological biomarkers of the underlying disease state. However, little is known about the biophysical basis of LFPs, or how the patient’s unique brain anatomy and electrode placement impact the recordings. Therefore, we developed a patient-specific computational framework to analyze LFP recordings within a clinical DBS context. We selected a subject with Parkinson’s disease implanted with a Medtronic Activa PC+S DBS system and reconstructed their subthalamic nucleus (STN) and DBS electrode location using medical imaging data. The patient-specific STN volume was populated with 235,280 multicompartment STN neuron models, providing a neuron density consistent with histological measurements. Each neuron received time-varying synaptic inputs and generated transmembrane currents that gave rise to the LFP signal recorded at DBS electrode contacts residing in a finite element volume conductor model. We then used the model to study the role of synchronous beta-band inputs to the STN neurons on the recorded power spectrum. Three bipolar pairs of simultaneous clinical LFP recordings were used in combination with an optimization algorithm to customize the neural activity parameters in the model to the patient. The optimized model predicted a 2.4-mm radius of beta-synchronous neurons located in the dorsolateral STN. These theoretical results enable biophysical dissection of the LFP signal at the cellular level with direct comparison to the clinical recordings, and the model system provides a scientific platform to help guide the design of DBS technology focused on the use of subthalamic beta activity in closed-loop algorithms. NEW & NOTEWORTHY The analysis of deep brain stimulation of local field potential (LFP) data is rapidly expanding from scientific curiosity to the basis for clinical biomarkers capable of improving the therapeutic efficacy of stimulation. With this growing clinical importance comes a growing need to understand the underlying electrophysiological fundamentals of the signals and the factors contributing to their modulation. Our model reconstructs the clinical LFP from first principles and highlights the importance of patient-specific factors in dictating the signals recorded.

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