TY  - JOUR
AU  - Payonk, Jan Philipp
AU  - Bathel, Henning
AU  - Arbeiter, Nils
AU  - Kober, Maria
AU  - Fauser, Mareike
AU  - Storch, Alexander
AU  - van Rienen, Ursula
AU  - Zimmermann, Julius
TI  - Improving computational models of deep brain stimulation through experimental calibration.
JO  - Journal of neuroscience methods
VL  - 414
SN  - 0165-0270
CY  - Amsterdam [u.a.]
PB  - Elsevier Science
M1  - DZNE-2024-01415
SP  - 110320
PY  - 2025
AB  - Deep brain stimulation has become a well-established clinical tool to treat movement disorders. Nevertheless, the knowledge of processes initiated by the stimulation remains limited. To address this knowledge gap, computational models are developed to gain deeper insight. However, their predictive power remains constrained by model uncertainties and a lack of validation and calibration.Exemplified with rodent microelectrodes, we present a workflow for validating electrode model geometry using microscopy and impedance spectroscopy in vitro before implantation. We address uncertainties in the tissue distribution and dielectric properties and outline a concept for calibrating the computational model based on in vivo impedance spectroscopy measurements.The standard deviation of the volume of tissue activated across the 18 characterized electrodes was approximately 32.93
KW  - Deep Brain Stimulation: methods
KW  - Deep Brain Stimulation: standards
KW  - Animals
KW  - Calibration
KW  - Computer Simulation
KW  - Microelectrodes
KW  - Rats
KW  - Dielectric Spectroscopy: methods
KW  - Electrodes, Implanted: standards
KW  - Male
KW  - Brain: physiology
KW  - Models, Neurological
KW  - Computational modeling (Other)
KW  - Deep brain stimulation (Other)
KW  - Dielectric properties (Other)
KW  - Encapsulation tissue (Other)
KW  - Impedance spectroscopy (Other)
KW  - Uncertainty quantification (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:39549963
DO  - DOI:10.1016/j.jneumeth.2024.110320
UR  - https://pub.dzne.de/record/273941
ER  -