1
|
Spiliotis K, Appali R, Fontes Gomes AK, Payonk JP, Adrian S, van Rienen U, Starke J, Köhling R. Utilising activity patterns of a complex biophysical network model to optimise intra-striatal deep brain stimulation. Sci Rep 2024; 14:18919. [PMID: 39143173 PMCID: PMC11324959 DOI: 10.1038/s41598-024-69456-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 08/05/2024] [Indexed: 08/16/2024] Open
Abstract
A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin-Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies.
Collapse
Affiliation(s)
- Konstantinos Spiliotis
- Institute of Mathematics, University of Rostock, Rostock, Germany.
- Laboratory of Mathematics and Informatics (ISCE), Department of Civil Engineering, Democritus University of Thrace, Xanthi, Greece.
| | - Revathi Appali
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
| | | | - Jan Philipp Payonk
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
| | - Simon Adrian
- Faculty of Computer Science and Electrical Engineering, University of Rostock, Rostock, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany
- Department of Life, Light and Matter, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
| | - Jens Starke
- Institute of Mathematics, University of Rostock, Rostock, Germany
| | - Rüdiger Köhling
- Department of Life, Light and Matter, University of Rostock, Rostock, Germany
- Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany
- Oscar-Langendorff-Institute of Physiology, Rostock University Medical Center, Rostock, Germany
| |
Collapse
|
2
|
Criswell SR, Nielsen SS, Faust IM, Shimony JS, White RL, Lenox-Krug J, Racette BA. Neuroinflammation and white matter alterations in occupational manganese exposure assessed by diffusion basis spectrum imaging. Neurotoxicology 2023; 97:25-33. [PMID: 37127223 PMCID: PMC10524700 DOI: 10.1016/j.neuro.2023.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 04/04/2023] [Accepted: 04/28/2023] [Indexed: 05/03/2023]
Abstract
OBJECTIVE To evaluate in-vivo neuroinflammation and white matter (WM) microstructural integrity in occupational manganese (Mn) exposure. METHODS We assessed brain inflammation using Diffusion Basis Spectrum Imaging (DBSI) in 26 Mn-exposed welders, 17 Mn-exposed workers, and 26 non-exposed participants. Cumulative Mn exposure was estimated from work histories and the Unified Parkinson's Disease Rating Scale motor subsection 3 (UPDRS3) scores were completed by a movement specialist. Tract-based Spatial Statistics allowed for whole-brain voxel-wise WM analyses to compare WM DBSI-derived measures between the Mn-exposed and non-exposed groups. Exploratory grey matter region of interest (ROI) analyses examined the presence of similar alterations in the basal ganglia. We used voxelwise general linear modeling and linear regression to evaluate the association between cumulative Mn exposure, WM or basal ganglia DBSI metrics, and UPDRS3 scores, while adjusting for age. RESULTS Mn-exposed welders had higher DBSI-derived restricted fraction (DBSI-RF), higher DBSI-derived nonrestricted fraction (DBSI-NRF), and lower DBSI-derived fiber fraction (DBSI-FF) in multiple WM tracts (all p < 0.05) in comparison to less-exposed workers and non-exposed participants. Basal ganglia ROI analyses revealed higher average caudate DBSI-NRF and DBSI-derived radial diffusion (DBSI-RD) values in Mn-exposed welders relative to non-exposed participants (p < 0.05). Caudate DBSI-NRF was also associated with greater cumulative Mn exposure and higher UPRDS3 scores. CONCLUSIONS Mn-exposed welders demonstrate greater DBSI-derived indicators of neuroinflammation-related cellularity (DBSI-RF), greater extracellular edema (DBSI-NRF), and lower apparent axonal density (DBSI-FF) in multiple WM tracts suggesting a neuroinflammatory component in the pathophysiology of Mn neurotoxicity. Caudate DBSI-NRF was positively associated with both cumulative Mn exposure and clinical parkinsonism, indicating a possible dose-dependent effect on extracellular edema with associated motor effects.
Collapse
Affiliation(s)
- Susan R Criswell
- Department of Neurology, Barrow Neurological Institute, 2910 N. 3rd Ave, Phoenix, AZ 85013, USA; Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA.
| | - Susan Searles Nielsen
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Irene M Faust
- Department of Neurology, Barrow Neurological Institute, 2910 N. 3rd Ave, Phoenix, AZ 85013, USA; Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Joshua S Shimony
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA; Mallinckrodt Institute of Radiology, Washington University School of Medicine, 510 S. Kingshighway Blvd, St. Louis, MO 63110, USA
| | - Robert L White
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA; John Cochran Division, St. Louis VA Medical Center, Neurology Section, 915 N. Grand Blvd, St. Louis, MO 63106, USA
| | - Jason Lenox-Krug
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA
| | - Brad A Racette
- Department of Neurology, Barrow Neurological Institute, 2910 N. 3rd Ave, Phoenix, AZ 85013, USA; Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO 63110, USA; School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, 27 Andrews Rd, Parktown 2193, South Africa
| |
Collapse
|