Nico Golfrè Andreasi

Background/Objectives: Subcortical local field potentials (LFPs) provide a valuable in vivo window into the neurophysiology of the dystonia network. These signals can be recorded through Deep Brain Stimulation (DBS) devices and combined with whole-head techniques such as magnetoencephalography (MEG) to study cortical–subcortical interactions. However, simultaneous LFP-MEG acquisition poses challenges, including interference from the DBS device and synchronization issues. We present preliminary data on the feasibility and signal quality of concurrent LFP and MEG recordings in dystonia patients. Methods: We assessed simultaneous MEG-LFP recordings in 11 patients with inherited or idiopathic dystonia who underwent bilateral DBS lead implantation in the Globus Pallidus Internus (GPi). Two synchronization strategies were tested: (1) the Tapping method, using an accelerometer placed on the DBS device, and (2) the Stimulation method, which generated detectable artifacts during sham stimulation. Results: Both methods successfully aligned MEG and LFP signals with a mean temporal delay of 91 ± 22 ms for the Tapping method and 288 ± 166 ms for the Stimulation method. Post-implantation signal-to-noise ratio analysis revealed slight degradation but no significant impact on MEG quality (gradiometers: −0.12 ± 1.85 dB; magnetometers: −0.47 ± 2.03 dB). Conclusions: Simultaneous MEG-LFP recordings in dystonic patients are feasible, yielding high-quality signals, and reliable synchronization. Temporal alignment improved with practice, suggesting a short learning curve. This method opens new opportunities to study cortical-subcortical dynamics and strengthens the potential of combining MEG-LFP approaches for investigating dystonia.

Microelectrode recording (MER) is commonly used to validate preoperative targeting during subthalamic nucleus (STN) deep brain stimulation (DBS) surgery for Parkinson’s Disease (PD). Although machine learning (ML) has been used to improve STN localization using MER data, the impact of preprocessing steps on the accuracy of classifiers has received little attention. We evaluated 24 distinct preprocessing pipelines combining four artifact removal strategies, three outlier handling methods, and optional feature normalization. The effect of each data processing procedure’s component of interest was evaluated in function of the performance obtained using three ML models. Artifact rejection methods (i.e., unsupervised variance-based algorithm (COV) and background noise estimation (BCK)), combined with optimized outlier management (i.e., statistical outlier identification per hemisphere (ORH)) consistently improved classification performance. In contrast, applying hemisphere-specific feature normalization prior to classification led to performance degradation across all metrics. SHAP (SHapley Additive exPlanations) analysis, performed to determine feature importance across pipelines, revealed stable agreement with regard to influential features across diverse preprocessing configurations. In conclusion, optimal artifact rejection and outlier treatment are essential in preprocessing MER for STN identification in DBS, whereas preliminary feature normalization strategies may impair model performance. Overall, the best classification performance was obtained by applying the Random Forest model to the dataset treated using COV artifact rejection and ORH outlier management (accuracy = 0.945). SHAP-based interpretability offers valuable guidance for refining ML pipelines. These insights can inform robust protocol development for MER-guided DBS targeting.

Background: Micro-electrode recording (MER) is one of the modalities used to confirm pre-operative planning during Deep Brain Stimulation (DBS) surgery of the subthalamic nucleus (STN) for the symptomatic treatment of Parkinson’s Disease. MER signals have been widely used in combination with machine learning (ML) techniques to improve STN functional localization. However, the impact of data processing and preparation has mostly been overlooked. Methods: A total of twenty-four combinations of processing approaches have been implemented with the aim of exploring the impact of data processing pipelines on the performance of feature-based ML classifiers. These comprise four signal artefact treatments, three outlier management procedures, and an option to standardize or not the feature sets. The effects of the implemented pipeline on the classification results were evaluated by training and testing three classifiers, both with and without feature selection. A final fundamental step to explore the feature importance using SHAP approach has also been implemented. Results: Improvements in performance metrics have been noticed after implementing approaches to artefact rejection and optimal outlier management, while the preliminary features standardization based on single patient and brain hemisphere data reduce all the performance metrics (accuracy, F1-score, recall, precision and area under the curve (AUC)). Interestingly, feature importance analysis through SHAP approach highlighted a good agreement between features contributing to classification across most of the implemented pipelines. Conclusions: Proper identification and rejection of artefacts combined with appropriate outlier management are crucial steps during MER processing pipelines for STN identification, while pre-normalization of features based on data from single patient and brain hemisphere may lead to overall performance degradation. In addition, the SHAP approach may represent an adjunctive useful tool to guide and improve the implementation of future algorithms.

Objective: Genetic dystonia is a complex movement disorder with diverse clinical manifestations resulting from pathogenic mutations in associated genes. A recent paradigm shift emphasizes the functional convergence among dystonia genes, hinting at a shared pathomechanism. However, the neural dynamics supporting this convergence remain largely unexplored.Methods: Herein, we analyzed microelectrode recordings acquired during pallidal deep brain stimulation surgery from 31 dystonia patients with pathogenic mutations in the AOPEP, GNAL, KMT2B, PANK2, PLA2G6, SGCE, THAP1, TOR1A, and VPS16 genes. We identified 1,694 single units whose activity was characterized by a broad set of neural features.Results: AOPEP, PANK2, and THAP1 displayed higher firing regularity, whereas GNAL, PLA2G6, KMT2B, and SGCE shared a large fraction of bursting neurons (> 26.6%), significantly exceeding the rate in other genes. TOR1A and VPS16 genes constituted an intermediate group, bridging these 2 groups, due to having the highest degree of spiking irregularity. Hierarchical clustering algorithms based on these dynamics confirmed the results obtained with first‐order comparisons.Interpretation: Despite lacking common molecular pathways, dystonia genes share largely overlapping structures of neural patterns, in particular the degree of pallidal spiking regularity and bursting activity. We propose that the degree of desynchronization facilitated by pallidal neural bursts may explain the variability in deep brain stimulation (DBS) of the globus pallidus internus (GPi) surgery outcomes across genetic dystonia syndromes. Lastly, investigating the effects of genetic mutations on low‐frequency pallidal activity could optimize personalized adaptive DBS treatments in patients with genetic dystonia. ANN NEUROL 2025;97:826–844

Background: Magnetic resonance–guided focused ultrasound (MRgFUS) thalamotomy of ventral intermediate (Vim) nucleus is useful to treat drug‐resistant tremor‐dominant Parkinson's disease (TdPD), but tremor relapse may occur. Predictors of relapse have been poorly investigated so far.Objective: The aim of this study is to evaluate the role of clinico‐demographic, procedural, and neuroradiological variables in determining clinical response, relapse, and adverse events (AEs) in TdPD after MRgFUS Vim‐thalamotomy.Methods: Fifty‐two TdPD patients who consecutively underwent unilateral MRgFUS Vim‐thalamotomy were prospectively evaluated at baseline and after 24 hours, 1 month, 6 months, and 12 months using MDS‐UPDRS‐III in off and on medication conditions. AEs were collected at each evaluation. Lesion volume was calculated at 24‐hour magnetic resonance imaging (MRI). Patients with tremor improvement 30% at 24 hours. Tremor relapse occurred in 12 patients (23%), exclusively during the first month after thalamotomy. Relapse was associated with younger age (P = 0.030) and smaller lesion volume (P = 0.030). At 1 month, 22 patients (42%) had AEs; at 6 and 12 months, AEs persisted in 19% and 6% of cases. AEs at 6 months were associated with larger lesions (P = 0.018). All AEs were mild.Conclusions: MRgFUS Vim‐thalamotomy is effective in treating tremor in TdPD. Relapse is associated with younger age and smaller lesion volume, but larger lesions make AEs more likely to persist. We suggest that a lesion volume between 145 and 220 mm³ on T1‐weighted MRI may be the therapeutic window that ensures tremor control without long‐lasting AEs. © 2025 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Background: Magnetic resonance‐guided focused ultrasound (MRgFUS) targeting the thalamic ventral intermediate nucleus (VIM) is an innovative treatment for drug‐refractory essential tremor (ET). The relationship between lesion characteristics, dentate‐rubro‐thalamic‐tract (DRTT) involvement and clinical benefit remains unclear.Objectives: To investigate whether clinical outcome is related to lesion volume and/or its overlap with the DRTT. To compare the reliability of probabilistic versus deterministic tractography in reconstructing the DRTT and improving VIM targeting.Methods: Forty ET patients who underwent MRgFUS thalamotomy between 2019 and 2022 were retrospectively analyzed. Clinical outcomes and adverse effects were recorded at 1/6/12 months after the procedure. The DRTT was generated using deterministic and probabilistic tractography on preoperative diffusion‐tensor 3 T‐images and location and volume of the lesion were calculated.Results: Probabilistic tractography identified both decussating (d‐DRTT) and non‐decussating (nd‐DRTT) components of the DRTT, whereas the deterministic approach only identified one component overlapping with the nd‐DRTT. Despite the lesions predominantly intersecting the medial portion of the d‐DRTT, with a significantly greater overlap in responder patients, we observed only a non‐significant correlation between tremor improvement and increased d‐DRTT‐lesion overlap (r = 0.22, P = 0.20). The lesion volume demonstrated a significant positive correlation with clinical improvement at 1‐day MRI (r = 0.42, P < 0.01).Conclusion: Variability in the reconstructed DRTT position relative to the lesion center of mass, even among good responders, suggests that this fiber bundle is unlikely to be considered the sole target for a successful MRgFUS thalamotomy in ET. Indirect individualized targeting allows for more precise and reproducible identification of actual treatment coordinates than the direct method.

This study aimed to evaluate the intensity of head pain associated with sonication. In particular, we were interested in identifying predictive factors of high-intensity head pain as it could be a source of interference with the procedure. Furthermore, we explored eventual dissociative or post-traumatic consequences related to high-intensity pain during MRgFUS.

Background: Magnetic resonance‐guided focused ultrasound (MRgFUS) thalamotomy is increasingly used to treat drug‐resistant essential tremor (ET). Data on MRgFUS thalamotomy in dystonic tremor (DT) are anecdotal.Objectives: To investigate efficacy, safety, and differences in target coordinates of MRgFUS thalamotomy in DT versus ET.Methods: Ten patients with DT and 35 with ET who consecutively underwent MRgFUS thalamotomy were followed for 12 months. Although in both groups the initial surgical planning coordinates corresponded to the ventralis intermediate (Vim), the final target could be modified intraoperatively based on clinical response.Results: Tremor significantly improved in both groups. The thalamic lesion was significantly more anterior in DT than ET. Considering both ET and DT groups, the more anterior the lesion, the lower the odds ratio for adverse events.Conclusions: MRgFUS thalamotomy is safe and effective in DT and ET. Compared to classical Vim coordinates used for ET, more anterior targeting should be considered for DT.

Background: Magnetic resonance–guided focused ultrasound (MRgFUS) thalamotomy is a safe and effective procedure for drug‐resistant tremor in Parkinson's disease (PD).Objective: The aim of this study was to demonstrate that MRgFUS ventralis intermedius thalamotomy in early‐stage tremor‐dominant PD may prevent an increase in dopaminergic medication 6 months after treatment compared with matched PD control subjects on standard medical therapy.Methods: We prospectively enrolled patients with early‐stage PD who underwent MRgFUS ventralis intermedius thalamotomy (PD‐FUS) and patients treated with oral dopaminergic therapy (PD‐ODT) with a 1:2 ratio. We collected demographic and clinical data at baseline and 6 and 12 months after thalamotomy.Results: We included 10 patients in the PD‐FUS group and 20 patients in the PD‐ODT group. We found a significant increase in total levodopa equivalent daily dose and levodopa plus monoamine oxidase B inhibitors dose in the PD‐ODT group 6 months after thalamotomy.Conclusions: In early‐stage tremor‐dominant PD, MRgFUS thalamotomy may be useful to reduce tremor and avoid the need to increase dopaminergic medications. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society