Luka Milosevic

Essential Tremor (ET) is the most common movement disorder. Magnetic Resonance-guided Focused Ultrasound (MRgFUS), an incisionless surgery involving thermal ablation of targeted brain regions, like the Ventral Intermediate Nucleus of the Thalamus (VIM) and surrounding white matter tracts, is an effective treatment option. Fractional Anisotropy (FA), a metric of diffusion tensor imaging, can be used to determine white matter structural integrity and their changes following MRgFUS. This study investigates white matter and morphological brain remodeling after MRgFUS VIM thalamotomy and its association with tremor improvement, assessed by the Clinical Rating Scale for Tremor (CRST), over the first postoperative year. We retrospectively analyzed 56 ET patients who underwent unilateral MRgFUS VIM thalamotomy. Subjects’ CRST scores, T1-weighted MRI scans, and diffusion-weighted imaging (DWI) scans were acquired pre-operatively and at three and twelve months post-operatively. FA maps were generated and registered to a standard space. Voxel clusters that exhibited significant change in FA over time were identified using FSL’s cluster tool (p<0.001) and their change in FA value over time was Spearman correlated with relative change in CRST score. Deformation-Based Morphometry of T1-weighted images evaluated changes in structural volume, and a linear mixed-effects model was applied. We permuted these values 1000 times randomly to isolate significant (p<0.01) clusters related to the interaction between time and outcome and Spearman correlated them with relative improvement in CRST. Four main FA clusters demonstrated strong associations between CRST score and time. The insula produced consistent positive correlations at three (R=0.32, p=0.04) and twelve months (R=0.29, p=0.11). Yet, the visual cortex exhibited no significant association at three months (R=0.11, p=0.46), but did at twelve months (R=0.35, p=0.05), suggesting malleable white matter remodeling. Our morphometry analysis revealed two primary clusters located in the pre-supplementary motor area (pre-SMA) and visual cortex. The pre-SMA exhibited the strongest correlations at three months (three months: R=0.34, p=0.03, twelve months: R=0.17, p=0.36), while the visual cortex displayed a similar strength throughout (three months: R=0.20, p=0.18, twelve months: R=-0.22, p=0.23). These findings suggest that MRgFUS VIM thalamotomy is associated with broad structural tract and volumetric changes that extend beyond motor networks. Both analyses demonstrated post-treatment volume growth and increased tract structure in visual and cognitive regions. Correlation with tremor improvement indicates many of these changes may contribute to individual outcomes during the first post-operative year.

The dynamic modulation of large-scale network activity, which is inherent to cognitive processes, is disrupted in Parkinson’s disease. Subthalamic deep brain stimulation can either improve or deteriorate cognition, particularly executive function, with these effects often going unnoticed during acute parameter optimization. This highlights the need for longer stimulation periods and more focused research on the underlying cortical mechanisms, which remain underexplored. This study was a prospective clinical trial involving nineteen people with Parkinson’s disease, who were evaluated off their medication at preoperative baseline and 6 months after deep brain stimulation implantation. Brain activity related to verbal and visuospatial working memory tasks was recorded using electroencephalography at both baseline and during follow-up evaluations conducted under stimulation. The follow-up assessments were carried out following 3-week periods of either omnidirectional or directional stimulation, applied in a randomized, double-blind, crossover design. Average postoperative working memory performance remained stable at the group level regardless of the stimulation condition for both verbal and visuospatial working memory tasks. However, at the individual level, higher alpha and beta power at baseline was associated with slower visuospatial working memory reaction time at follow-up. Additionally, reductions in theta and beta power during stimulation at follow-up correlated with better verbal working memory accuracy during the task and compared with baseline, respectively. These findings suggest that task-related electroencephalography may provide candidate physiological markers of individual working memory trajectories after subthalamic deep brain stimulation. Oscillatory brain activity may help to characterize stimulation-related cognitive variability beyond motor outcomes, but these exploratory findings require validation in larger cohorts before they can inform stimulation programming or closed-loop treatment strategies. Registration: ClinicalTrials.gov: NCT03548506

Deep brain stimulation (DBS) has been demonstrated to be a successful therapeutic intervention for neurological disorders, yet the mechanisms underlying its effects on neuronal circuits remain incompletely understood. In this study, we propose a comprehensive phenomenological computational model that accounts for the impact of electrical stimulation parameters on neuronal circuits while incorporating experimentally-validated synaptic and cellular constraints. We investigate how DBS pulses modulate spiking activity in populations of homogeneous neurons representing stimulated nuclei, systematically examining the influence of circuitry architecture, including synaptic connectivity strength (weak vs. strong) and organization (sparse vs. rich). To characterize how DBS-modulated neuronal activity propagates through downstream networks, we develop a simple encoder that reveals distinct encoding patterns arising from different architectural configurations of stimulated nuclei. Furthermore, by connecting stimulated nuclei to recurrently connected neuronal populations, we examine the propagation of DBS-modulated neuronal synchrony across various circuit motifs. Our results demonstrate that three critical factors shape DBS-modulated neuronal activity: (a) the intrinsic synaptic and cellular properties of stimulated nuclei, (b) the architectural organization of stimulated nuclei in terms of synaptic strength and connectivity density, and (c) the circuit motifs formed by postsynaptic targets of stimulated nuclei. This unified model provides a mechanistic framework for understanding DBS representation and propagation in neuronal networks, offering insights that may inform optimization of stimulation parameters for clinical applications. Author summary: Computational models of deep brain stimulation have proven to be supremely useful in disentangling the clinical benefits and adverse effects observed in the treatment of a variety of conditions. Despite this, the capacity for many of the existent computational models to account for micro/meso-circuit activation remains limited, as the major techniques rely on detailed characterization of tracts surrounding the DBS electrode, or depend on an non-physiologically constrained injected current intending to mimic the influence of electrical stimulation. The tract based methods only work for tracts that we have detailed characterization of, which are missing for many of the target structures, such as the basal ganglia. Given the restrictions of current methods we set out to define a phenomenological method that is applicable to as many simulation methods as possible, including those with missing details on tractography, while being able to readily integrate results of detailed simulations when available. Our approach is extensible and has examples implemented in some of the most popular computational neuroscience toolkits allowing for ready integration into existing network simulations. Further we demonstrate how this methodology supports interrogation of networks both for physiological responses but also computational dynamics, such as information multiplexing and delayed local evoked potentials.

Introduction: Stimulation-evoked potentials (SEPs), recorded both during and after deep brain stimulation (DBS) surgery, have shown promise for guiding DBS targeting and programming. However, filtering protocols applied to stimulation trains produce an artifact we call a filter-induced oscillation (FIO) which closely mimics physiological SEPs. Hence, we outline the mechanistic origins of this distortion and describe a means of differentiating it from valid SEP activity. Methods: We recorded in 18 patients undergoing DBS surgery targeting the subthalamic nucleus or globus pallidus internus. We stimulated target nuclei with cathode-first (CF) and anode-first (AF) pulses to record native SEPs, and in white matter tracts (null condition). Recordings were subsequently filtered to illustrate FIO. Next, we filtered harmonic frequencies of an artificial stimulation train to demonstrate FIO origins. Finally, FIO was deliberately generated in white matter recordings with a notch filter, and its behaviour contrasted with SEPs during AF and CF stimulation. Results: Filtering stimulation trains produced FIOs that depended on filter order and corner frequency. We also showed that FIO emerges from filter-induced attenuations of harmonic frequencies which compose stimulation trains, producing oscillations of like frequency around pulses. Finally, FIOs reverse in polarity depending on AF or CF stimulation, whereas SEPs do not. Conclusions: Given the potential for widespread adoption of SEPs in DBS targeting and programming, safe analytical protocols are imperative to avoid the induction of processing-related artifacts which can be misinterpreted as biological signals. Here we establish the necessary theory for identifying FIOs and tuning analytical pipelines to avoid their generation.

Parkinson’s disease (PD) is a movement disorder characterized by alpha-synuclein (a-Syn) aggregation, dopaminergic degeneration, and pathological beta oscillations (13–30 Hz) in the basal ganglia circuit. Deep brain stimulation (DBS) is an effective neurosurgical treatment for the motor symptoms of PD. However, the extent to which mitigation of beta oscillations mediates DBS therapeutic effects remains uncertain. Using an adeno-associated virus-mediated nigral A53T a-Syn overexpression rat model, we examined basal ganglia-thalamo-cortical electrophysiology and the model’s responsiveness to DBS. In vivo recordings revealed early beta emergence in the motor cortex (MCx), spreading to the subthalamic nucleus (STN) and entopeduncular nucleus (EP) with neurodegeneration. This was accompanied by alterations in STN and EP single-unit activity. Awake-state beta oscillations manifested as transient bursts. Low- and high-frequency DBS differentially modulated beta bursts and motor performance. Our results demonstrate that the A53T a-Syn model replicates key PD-like electrophysiological features, providing a platform to investigate DBS mechanisms and optimize therapies targeting aberrant beta activity.

Background Deep brain stimulation (DBS) is used to treat neurological and psychiatric disorders by modulating neuronal circuits. However, other mechanisms of DBS, such as the effects of electrical stimulation on the neurovascular unit remain poorly understood due to limitations of capturing microvascular changes near implanted leads. This motivated us to investigate electrophysiological surrogates of vascular dynamics in response to intraoperative microstimulation. Methods Microelectrode recordings (n = 193; 108 patients) were obtained during DBS implantation surgery from two electrodes (∼600 µm apart) before and after microstimulation through one electrode. Linear mixed models assessed cardioballistic waveform (CBW) amplitude changes following low-frequency (LFS, 1 Hz) or high-frequency stimulation (HFS, 100 Hz), with comparisons across basal ganglia regions and in white matter. An analytical model interpreted CBW amplitudes as pressure-driven vessel wall expansion, enabling estimation of stimulation-evoked vasodilation and cerebral blood flow. Results CBW amplitudes increased significantly after HFS at the stimulating electrode, but not at the non-stimulating electrode or after LFS. Significant region-specific effects were observed in the ventral intermediate nucleus (Vim; 107 ± 13%), subthalamic nucleus (STN; 79 ± 7%), and globus pallidus internus (GPi; 78 ± 8%), but not in white matter (50 ± 14%) or substantia nigra (45 ± 8%). Modelling showed that the mean 88% CBW increase across Vim, STN, and GPi corresponds to an acute increase in cerebral blood flow. Conclusion Intracranial CBW recordings reveal that high-frequency DBS evokes region-specific vascular responses which can be modelled as substantial increases in local blood flow, establishing CBW amplitude as a novel biomarker of subcortical hemodynamics, and a potential therapeutic modality.

Parkinson's disease is characterized, in part, by hypoactivity of direct pathway inhibitory projections from striatum to the globus pallidus internus (GPi) and indirect pathway inhibitory projections from globus pallidus externus (GPe) to the subthalamic nucleus (STN). In people with Parkinson's disease (n = 32), we explored the potential use of intracranial stimulation for eliciting long-term potentiation (LTP) of these underactive pathways to produce improvement of symptoms that persist beyond stimulation cessation. During GPi deep brain stimulation (DBS) surgery, we found strong evidence (P < 0.05; BF10 > 10) of increased amplitudes of hand movements and striato-GPi evoked potentials before versus after high-frequency microstimulation. In a small sample of outpatients with sensing-enabled GPi-DBS, we found anecdotal evidence (P < 0.10; BF10 > 1) of improved hand movements and attenuated beta frequency oscillations. In STN, enduring behavioural effects, potentiation of GPe-STN projections (intraoperative), and decreases to beta oscillations (extraoperative) were not observed. Our findings support that LTP-like effects in GPi may produce motor improvements that extend beyond stimulation cessation, while the lack of effects in STN suggests the need for optimizing stimulation paradigms for effective LTP induction. These findings nevertheless highlight the potential of LTP-based strategies for sustained therapeutic benefits, which may be useful for mitigating DBS side-effects and optimizing battery usage.