More than meets the eye-myelinated axons crowd the subthalamic nucleus

Efficient, Robust, and Accurate CNN Predictor for Neuronal Activation in Directional Deep Brain Stimulation

The programming of clinical deep brain stimulation (DBS) systems involves numerous combinations of stimulation parameters, such as stimulus amplitude, pulse width, and frequency. As more complex electrode designs, such as directional electrodes, are introduced, the traditional trial-and-error approach to manual DBS programming becomes increasingly impractical. Visualization of the volume of tissue activated (VTA) can assist in selecting stimulation parameters by showing the direct effects of DBS on neural tissue. However, the standard method for VTA calculation, which involves modeling biological nerve fibers, is highly time-consuming and limits clinical applicability. In this study, we used finite element models (FEM) of implanted DBS systems to compute electric fields and obtained a large dataset of axonal responses under electrical stimulation using multicompartment cable models. We then trained a convolutional neural network (CNN) to replace the cable models. The CNN model's performance in calculating VTA was evaluated across various electrode configurations and stimulation parameters, and compared with existing activation function (AF) methods. The CNN model achieved a mean absolute error (MAE) of 0.032V in predicting nerve fiber activation thresholds, demonstrating greater stability and accuracy in VTA prediction compared to the AF method. Additionally, the CNN reduced computation time by five orders of magnitude compared to standard axonal modeling methods. We demonstrate that the CNN-based neural fiber predictor can quickly, accurately, and robustly predict neural activation responses to DBS, thereby improving the efficiency of DBS programming.

Deep brain stimulation of symptom-specific networks in Parkinson's disease

Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.

Towards an optimised deep brain stimulation using a large-scale computational network and realistic volume conductor model

Objective. Constructing a theoretical framework to improve deep brain stimulation (DBS) based on the neuronal spatiotemporal patterns of the stimulation-affected areas constitutes a primary target.Approach. We develop a large-scale biophysical network, paired with a realistic volume conductor model, to estimate theoretically efficacious stimulation protocols. Based on previously published anatomically defined structural connectivity, a biophysical basal ganglia-thalamo-cortical neuronal network is constructed using Hodgkin-Huxley dynamics. We define a new biomarker describing the thalamic spatiotemporal activity as a ratio of spiking vs. burst firing. The per cent activation of the different pathways is adapted in the simulation to minimise the differences of the biomarker with respect to its value under healthy conditions.Main results.This neuronal network reproduces spatiotemporal patterns that emerge in Parkinson's disease. Simulations of the fibre per cent activation for the defined biomarker propose desensitisation of pallido-thalamic synaptic efficacy, induced by high-frequency signals, as one possible crucial mechanism for DBS action. Based on this activation, we define both an optimal electrode position and stimulation protocol using pathway activation modelling.Significance. A key advantage of this research is that it combines different approaches, i.e. the spatiotemporal pattern with the electric field and axonal response modelling, to compute the optimal DBS protocol. By correlating the inherent network dynamics with the activation of white matter fibres, we obtain new insights into the DBS therapeutic action.

Apathy following deep brain stimulation in Parkinson's disease visualized by 7-Tesla MRI subthalamic network analysis

BACKGROUND

Apathy is reported after subthalamic nucleus deep brain stimulation (STN DBS) and associated with a decreased quality of life in Parkinson's disease (PD) patients. Recent studies hypothesized that the location of active DBS contact point relative to the STN subdivisions (motor, associative and limbic) could be related to an increase of apathy.

METHODS

22 PD-patients that underwent STN DBS between January 2019 and February 2020 were divided in an apathy and non-apathy group using the change in the Starkstein Apathy Scale (SAS) after six months of DBS. For both groups the location of DBS electrodes was determined based on 7T MRI subthalamic network analysis, enabling visualization of the subdivisions and their projections relative to the active contact point. MDS-UPDRS III scores were included to evaluate DBS effect.

RESULTS

In six patients a post-DBS increase in apathy score was assessed, versus 16 non-apathy patients. Network analysis showed that active contacts in apathy patients were more often positioned in or close to the area within the STN with high density of surrounding projections to associative cortex areas than in non-apathy patients; 63% apathy versus 42% (P = 0.02). The density of surrounding motor projections was lower in the group with increased apathy (18%) than in the group without increased apathy (38%, P = 0.01). Motor UPDRS improvement for the apathy group was 39% and for the non-apathy group 58% (n.s.) CONCLUSION: This new approach in patient-specific subthalamic 7T MRI network analysis visualized an anatomical connectivity substrate for apathy in DBS, with active electrode contacts predominantly in the associative STN.

Deep Brain Stimulation: Emerging Tools for Simulation, Data Analysis, and Visualization

Deep 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.

Estimation of electric field impact in deep brain stimulation from axon diameter distribution in the human brain

Objective.Finite element method (FEM) simulations of the electric field magnitude (EF) are commonly used to estimate the affected tissue surrounding the active contact of deep brain stimulation (DBS) leads. Previous studies have found that DBS starts to noticeably activate axons at approximately 0.2 V mm^-1, corresponding to activation of 3.4μm axons in simulations of individual axon triggering. Most axons in the brain are considerably smaller however, and the effect of the electric field is thus expected to be stronger with increasing EF as more and more axons become activated. The objective of this study is to estimate the fraction of activated axons as a function of electric field magnitude.Approach. The EF thresholds required for axon stimulation of myelinated axon diameters between 1 and 5μm were obtained from a combined cable and Hodgkin-Huxley model in a FEM-simulated electric field from a Medtronic 3389 lead. These thresholds were compared with the average axon diameter distribution from literature from several structures in the human brain to obtain an estimate of the fraction of axons activated at EF levels between 0.1 and 1.8 V mm^-1.Main results. The effect of DBS is estimated to be 47·EF-8.8% starting at a threshold levelEF_t0 = 0.19 V mm^-1.Significance. The fraction of activated axons from DBS in a voxel is estimated to increase linearly with EF above the threshold level of 0.19 V mm^-1. This means linear regression between EF above 0.19 V mm^-1and clinical outcome is a suitable statistical method when doing improvement maps for DBS.

Diverging prefrontal cortex fiber connection routes to the subthalamic nucleus and the mesencephalic ventral tegmentum investigated with long range (normative) and short range (ex-vivo high resolution) 7T DTI

Uncertainties concerning anatomy and function of cortico-subcortical projections have arisen during the recent years. A clear distinction between cortico-subthalamic (hyperdirect) and cortico-tegmental projections (superolateral medial forebrain bundle, slMFB) so far is elusive. Deep Brain Stimulation (DBS) of the slMFB (for major depression, MD and obsessive compulsive disorders, OCD) has on the one hand been interpreted as actually involving limbic (prefrontal) hyperdirect pathways. On the other hand slMFB’s stimulation region in the mesencephalic ventral tegmentum is said to impact on other structures too, going beyond the antidepressant (or anti OCD) efficacy of sole modulation of the cortico-tegmental reward-associated pathways. We have here used a normative diffusion MRT template (HCP, n = 80) for long-range tractography and augmented this dataset with ex-vivo high resolution data (n = 1) in a stochastic brain space. We compared this data with histological information and used the high resolution ex-vivo data set to scrutinize the mesencephalic tegmentum for small fiber pathways present. Our work resolves an existing ambiguity between slMFB and prefrontal hyperdirect pathways which—for the first time—are described as co-existent. DBS of the slMFB does not appear to modulate prefrontal hyperdirect cortico-subthalamic but rather cortico-tegmental projections. Smaller fiber structures in the target region—as far as they can be discerned—appear not to be involved in slMFB DBS. Our work enfeebles previous anatomical criticism and strengthens the position of the slMFB DBS target for its use in MD and OCD.

Selection of deep brain stimulation contacts using volume of tissue activated software following subthalamic nucleus stimulation

OBJECTIVE

High-frequency deep brain stimulation (DBS) of the subthalamic nucleus (STN) is effective in the treatment of motor symptoms of Parkinson's disease. Using a patient-specific lead and volume of tissue activated (VTA) software, it is possible to visualize contact positions in the context of the patient's own anatomy. In this study, the authors' aim was to demonstrate that VTA software can be used in clinical practice to help determine the clinical effectiveness of stimulation in patients with Parkinson's disease undergoing DBS of the STN.

METHODS

Brain images of 26 patients undergoing STN DBS were analyzed using VTA software. Preoperative clinical and neuropsychological data were collected. Contacts were chosen by two experts in DBS blinded to the clinical data. A therapeutic window of amplitude was determined. These results were compared with the parameter settings for each patient. Data were obtained at 3 months and 1 year postsurgery.

RESULTS

In 90.4% (95% CI 82%-98%) of the patients, the contacts identified by the VTA software were concordant with the clinically effective contacts or with an effective contact in contact-by-contact testing. The therapeutic window of amplitude selected virtually included 81.3% of the clinical amplitudes.

CONCLUSIONS

VTA software appears to present significant concordance with clinical data for selecting contacts and stimulation parameters that could help in postoperative follow-up and programming.

Comparison between patient-specific deep brain stimulation simulations and commercial system SureTune3

Objective. Software to visualize estimated volume of tissue activated (VTA) in deep brain stimulation assuming a homogeneous tissue surrounding such as SureTune3 has recently become available for clinical use. The objective of this study is to compare SureTune3 with homogeneous and heterogeneous patient-specific finite element method (FEM) simulations of the VTA to elucidate how well they coincide in their estimates.Approach. FEM simulations of the VTA were performed in COMSOL Multiphysics and compared with VTA from SureTune3 with variation of voltage and current amplitude, pulse width, axon diameter, number of active contacts, and surrounding homogeneous grey or white matter. Patient-specific simulations with heterogeneous tissue were also performed.Main results. The VTAs corresponded well for voltage control in homogeneous tissue, though with the smallest VTAs being slightly larger in SureTune3 and the largest VTAs being slightly larger in the FEM simulations. In current control, FEM estimated larger VTAs in white matter and smaller VTAs in grey matter compared to SureTune3 as grey matter has higher electric conductivity than white matter and requires less voltage to reach the same current. The VTAs also corresponded well in the patient-specific cases except for one case with a cyst of highly conductive cerebrospinal fluid (CSF) near the active contacts.Significance. The VTA estimates without taking the surrounding tissue into account in SureTune3 are in good agreement with patient-specific FEM simulations when using voltage control in the absence of CSF-filled cyst. In current control or when CSF is present near the active contacts, the tissue characteristics are important for the VTA and needs consideration.Clinical. trial ethical approval: Local ethics committee at Linköping University (2012/434-31).

To stage, or not to stage

Staging of neurodegenerative diseases is based chiefly on the topographical or anatomical extent of aggregated proteinaceous inclusions, and the density or severity of the lesions in a given region is usually assessed semiquantitatively. Associated phenomena, such as cell loss and synapse loss, are evaluated but not staged. This article reviews the development of neuropathological staging of the sporadic Alzheimer's and sporadic Parkinson's diseases. It considers challenges for staging systems, and it poses the question whether neuropathological staging as practiced up to now is still relevant.

Clinical deep brain stimulation strategies for orientation-selective pathway activation

OBJECTIVE

This study investigated stimulation strategies to increase the selectivity of activating axonal pathways within the brain based on their orientations relative to clinical deep brain stimulation (DBS) lead implants.

APPROACH

Previous work has shown how varying electrode shape and controlling the primary electric field direction through preclinical electrode arrays can produce orientation-selective axonal stimulation. Here, we significantly extend those results using computational models to evaluate the degree to which clinical DBS leads can direct stimulus-induced electric fields and generate orientation-selective activation of fiber pathways in the brain. Orientation-selective pulse paradigms were evaluated in conceptual models and in patient-specific models of subthalamic nucleus (STN)-DBS for treating Parkinson's disease.

MAIN RESULTS

Single-contact monopolar or two-contact bipolar stimulation through clinical DBS leads with cylindrical electrodes primarily activated axons orientated parallel to the lead. Conversely, multi-contact monopolar stimulation with a cathode-leading pulse waveform selectively activated axons perpendicular to the DBS lead. Clinical DBS leads with segmented rows of electrodes and a single current source provided additional angular resolution for activating axons oriented 0°, ±22.5°, ±45°, ±67.5°, or 90° relative to the lead shaft. Employing multiple independent current sources to deliver unequal amounts of current through these leads further increased the angular resolution of activation relative to the lead shaft. The patient-specific models indicated that multi-contact cathode configurations, which are rarely used in clinical practice, could increase activation of the hyperdirect pathway collaterals projecting into STN (a putative therapeutic target), while minimizing direct activation of the corticospinal tract of internal capsule, which can elicit sensorimotor side-effects when stimulated.

SIGNIFICANCE

When combined with patient-specific tissue anisotropy and patient-specific anatomical morphologies of neural pathways responsible for therapy and side effects, orientation-selective DBS approaches show potential to significantly improve clinical outcomes of DBS therapy for a range of existing and investigational clinical indications.

Action potential initiation, propagation, and cortical invasion in the hyperdirect pathway during subthalamic deep brain stimulation

BACKGROUND

High frequency (∼130 Hz) deep brain stimulation (DBS) of the subthalamic region is an established clinical therapy for the treatment of late stage Parkinson's disease (PD). Direct modulation of the hyperdirect pathway, defined as cortical layer V pyramidal neurons that send an axon collateral to the subthalamic nucleus (STN), has emerged as a possible component of the therapeutic mechanisms. However, numerous questions remain to be addressed on the basic biophysics of hyperdirect pathway stimulation.

OBJECTIVE

Quantify action potential (AP) initiation, propagation, and cortical invasion in hyperdirect neurons during subthalamic stimulation.

METHODS

We developed an anatomically and electrically detailed computational model of hyperdirect neuron stimulation with explicit representation of the stimulating electric field, axonal response, AP propagation, and synaptic transmission.

RESULTS

We found robust AP propagation throughout the complex axonal arbor of the hyperdirect neuron. Even at therapeutic DBS frequencies, stimulation induced APs could reach all of the intracortical axon terminals with ∼100% fidelity. The functional result of this high frequency axonal driving of the thousands of synaptic connections made by each directly stimulated hyperdirect neuron is a profound synaptic suppression that would effectively disconnect the neuron from the cortical circuitry.

CONCLUSIONS

The synaptic suppression hypothesis integrates the fundamental biophysics of electrical stimulation, axonal transmission, and synaptic physiology to explain a generic mechanism of DBS.

Creating and parameterizing patient-specific deep brain stimulation pathway-activation models using the hyperdirect pathway as an example

BACKGROUND

Deep brain stimulation (DBS) is an established clinical therapy and computational models have played an important role in advancing the technology. Patient-specific DBS models are now common tools in both academic and industrial research, as well as clinical software systems. However, the exact methodology for creating patient-specific DBS models can vary substantially and important technical details are often missing from published reports.

OBJECTIVE

Provide a detailed description of the assembly workflow and parameterization of a patient-specific DBS pathway-activation model (PAM) and predict the response of the hyperdirect pathway to clinical stimulation.

METHODS

Integration of multiple software tools (e.g. COMSOL, MATLAB, FSL, NEURON, Python) enables the creation and visualization of a DBS PAM. An example DBS PAM was developed using 7T magnetic resonance imaging data from a single unilaterally implanted patient with Parkinson's disease (PD). This detailed description implements our best computational practices and most elaborate parameterization steps, as defined from over a decade of technical evolution.

RESULTS

Pathway recruitment curves and strength-duration relationships highlight the non-linear response of axons to changes in the DBS parameter settings.

CONCLUSION

Parameterization of patient-specific DBS models can be highly detailed and constrained, thereby providing confidence in the simulation predictions, but at the expense of time demanding technical implementation steps. DBS PAMs represent new tools for investigating possible correlations between brain pathway activation patterns and clinical symptom modulation.

Relationship between neural activation and electric field distribution during deep brain stimulation

Models and simulations are commonly used to study deep brain stimulation (DBS). Simulated stimulation fields are often defined and visualized by electric field isolevels or volumes of tissue activated (VTA). The aim of the present study was to evaluate the relationship between stimulation field strength as defined by the electric potential V, the electric field E, and the divergence of the electric field ∇(2) V, and neural activation. Axon cable models were developed and coupled to finite-element DBS models in three-dimensional (3-D). Field thresholds ( VT , ET, and ∇(2) VT ) were derived at the location of activation for various stimulation amplitudes (1 to 5 V), pulse widths (30 to 120 μs), and axon diameters (2.0 to 7.5 μm). Results showed that thresholds for VT and ∇(2) VT were highly dependent on the stimulation amplitude while ET were approximately independent of the amplitude for large axons. The activation field strength thresholds presented in this study may be used in future studies to approximate the VTA during model-based investigations of DBS without the need of computational axon models.

Brain tissue properties differentiate between motor and limbic basal ganglia circuits

Despite advances in understanding basic organizational principles of the human basal ganglia, accurate in vivo assessment of their anatomical properties is essential to improve early diagnosis in disorders with corticosubcortical pathology and optimize target planning in deep brain stimulation. Main goal of this study was the detailed topological characterization of limbic, associative, and motor subdivisions of the subthalamic nucleus (STN) in relation to corresponding corticosubcortical circuits. To this aim, we used magnetic resonance imaging and investigated independently anatomical connectivity via white matter tracts next to brain tissue properties. On the basis of probabilistic diffusion tractography we identified STN subregions with predominantly motor, associative, and limbic connectivity. We then computed for each of the nonoverlapping STN subregions the covariance between local brain tissue properties and the rest of the brain using high‐resolution maps of magnetization transfer (MT) saturation and longitudinal (R1) and transverse relaxation rate (R2*). The demonstrated spatial distribution pattern of covariance between brain tissue properties linked to myelin (R1 and MT) and iron (R2*) content clearly segregates between motor and limbic basal ganglia circuits. We interpret the demonstrated covariance pattern as evidence for shared tissue properties within a functional circuit, which is closely linked to its function. Our findings open new possibilities for investigation of changes in the established covariance pattern aiming at accurate diagnosis of basal ganglia disorders and prediction of treatment outcome. Hum Brain Mapp 35:5083–5092, 2014. © 2014 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Neural circuit modulation during deep brain stimulation at the subthalamic nucleus for Parkinson's disease: what have we learned from neuroimaging studies?

Deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) represents a powerful clinical tool for the alleviation of many motor symptoms that are associated with Parkinson's disease. Despite its extensive use, the underlying therapeutic mechanisms of STN-DBS remain poorly understood. In the present review, we integrate and discuss recent literature examining the network effects of STN-DBS for Parkinson's disease, placing emphasis on neuroimaging findings, including functional magnetic resonance imaging, positron emission tomography, and single-photon emission computed tomography. These techniques enable the noninvasive detection of brain regions that are modulated by DBS on a whole-brain scale, representing a key experimental strength given the diffuse and far-reaching effects of electrical field stimulation. By examining these data in the context of multiple hypotheses of DBS action, generally developed through clinical and physiological observations, we define a multitude of consistencies and inconsistencies in the developing literature of this rapidly moving field.

Closing the loop of deep brain stimulation

High-frequency deep brain stimulation is used to treat a wide range of brain disorders, like Parkinson's disease. The stimulated networks usually share common electrophysiological signatures, including hyperactivity and/or dysrhythmia. From a clinical perspective, HFS is expected to alleviate clinical signs without generating adverse effects. Here, we consider whether the classical open-loop HFS fulfills these criteria and outline current experimental or theoretical research on the different types of closed-loop DBS that could provide better clinical outcomes. In the first part of the review, the two routes followed by HFS-evoked axonal spikes are explored. In one direction, orthodromic spikes functionally de-afferent the stimulated nucleus from its downstream target networks. In the opposite direction, antidromic spikes prevent this nucleus from being influenced by its afferent networks. As a result, the pathological synchronized activity no longer propagates from the cortical networks to the stimulated nucleus. The overall result can be described as a reversible functional de-afferentation of the stimulated nucleus from its upstream and downstream nuclei. In the second part of the review, the latest advances in closed-loop DBS are considered. Some of the proposed approaches are based on mathematical models, which emphasize different aspects of the parkinsonian basal ganglia: excessive synchronization, abnormal firing-rate rhythms, and a deficient thalamo-cortical relay. The stimulation strategies are classified depending on the control-theory techniques on which they are based: adaptive and on-demand stimulation schemes, delayed and multi-site approaches, stimulations based on proportional and/or derivative control actions, optimal control strategies. Some of these strategies have been validated experimentally, but there is still a large reservoir of theoretical work that may point to ways of improving practical treatment.