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Publikation Probabilistic maps for deep brain stimulation – Impact of methodological differences(Elsevier, 2022) Nordin, Teresa; Vogel, Dorian; Osterlund, Erik; Johansson, Johannes; Fytagoridis, Anders; Blomstedt, Patric; Hemm-Ode, Simone; Wardell, KarinBackground Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations. Objective To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters. Methods Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function. Results Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters. Conclusion The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Deep brain stimulation: emerging tools for simulation, data analysis, and visualization(Frontiers, 11.04.2022) Wårdell, Karin; Nordin, Teresa; Zsigmond, Peter; Westin, Carl-Fredrik; Hariz, Marwan; Vogel, Dorian; Hemm-Ode, SimoneDeep brain stimulation (DBS) is a well-established neurosurgical procedure for movement disorders that is also being explored for treatment-resistant psychiatric conditions. This review highlights important consideration for DBS simulation and data analysis. The literature on DBS has expanded considerably in recent years, and this article aims to identify important trends in the field. During DBS planning, surgery, and follow up sessions, several large data sets are created for each patient, and it becomes clear that any group analysis of such data is a big data analysis problem and has to be handled with care. The aim of this review is to provide an update and overview from a neuroengineering perspective of the current DBS techniques, technical aids, and emerging tools with the focus on patient-specific electric field (EF) simulations, group analysis, and visualization in the DBS domain. Examples are given from the state-of-the-art literature including our own research. This work reviews different analysis methods for EF simulations, tractography, deep brain anatomical templates, and group analysis. Our analysis highlights that group analysis in DBS is a complex multi-level problem and selected parameters will highly influence the result. DBS analysis can only provide clinically relevant information if the EF simulations, tractography results, and derived brain atlases are based on as much patient-specific data as possible. A trend in DBS research is creation of more advanced and intuitive visualization of the complex analysis results suitable for the clinical environment.01A - Beitrag in wissenschaftlicher ZeitschriftPublikation Heading direction is significantly biased by preceding whole-body roll-orientation while lying(Frontiers, 18.04.2022) Tarnutzer, Alexander Andrea; Duarte da Costa, Vasco; Baumann, Denise; Hemm-Ode, SimoneBackground: After a prolonged static whole-body roll-tilt, a significant bias of the internal estimates of the direction of gravity has been observed when assessing the subjective visual vertical. Objective: We hypothesized that this post-tilt bias represents a more general phenomenon, broadly affecting spatial orientation and navigation. Specifically, we predicted that after the prolonged roll-tilt to either side perceived straight-ahead would also be biased. Methods: Twenty-five healthy participants were asked to rest in three different lying positions (supine, right-ear-down, and left-ear-down) for 5 min (“adaptation period”) prior to walking straight-ahead blindfolded for 2 min. Walking was recorded with the inertial measurement unit sensors attached to different body locations and with sensor shoe insoles. The raw data was segmented with a gait–event detection method. The Heading direction was determined and linear mixed-effects models were used for statistical analyses. Results: A significant bias in heading into the direction of the previous roll-tilt position was observed in the post-adaptation trials. This bias was identified in both measurement systems and decreased again over the 2-min walking period. Conclusions: The bias observed further confirms the influence of prior knowledge on spatial orientation and navigation. Specifically, it underlines the broad impact of a shifting internal estimate of direction of gravity over a range of distinct paradigms, illustrating similar decay time constants. In the broader context, the observed bias in perceived straight-ahead emphasizes that getting up in the morning after a good night's sleep is a vulnerable period, with an increased risk of falls and fall-related injuries due to non-availability of optimally tuned internal estimates of the direction of gravity and the direction of straight-ahead.01A - Beitrag in wissenschaftlicher Zeitschrift