Subcallosal cingulate deep brain stimulation evokes two distinct cortical responses via differential white matter activation.

Subcallosal cingulate (SCC) deep brain stimulation (DBS) is an emerging therapy for refractory depression. Good clinical outcomes are associated with the activation of white matter adjacent to the SCC. This activation produces a signature cortical evoked potential (EP), but it is unclear which of the many pathways in the vicinity of SCC is responsible for driving this response.

Role of the volume conductor on simulations of local field potential recordings from deep brain stimulation electrodes.

Objective: Local field potential (LFP) recordings from deep brain stimulation (DBS) electrodes are commonly used in research analyses, and are beginning to be used in clinical practice. Computational models of DBS LFPs provide tools for investigating the biophysics and neural synchronization that underlie LFP signals. However, technical standards for DBS LFP model parameterization remain to be established.

Mitigating Mismatch Compression in Differential Local Field Potentials.

Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC).

Time-frequency signatures evoked by single-pulse deep brain stimulation to the subcallosal cingulate.

Precision targeting of specific white matter bundles that traverse the subcallosal cingulate (SCC) has been linked to efficacy of deep brain stimulation (DBS) for treatment resistant depression (TRD). Methods to confirm optimal target engagement in this heterogenous region are now critical to establish an objective treatment protocol. As yet unexamined are the time-frequency features of the SCC evoked potential (SCC-EP), including spectral power and phase-clustering.

Isolating two sources of variability of subcortical stimulation to quantify fluctuations of corticospinal tract excitability.

Objective: Investigate the variability previously found with cortical stimulation and handheld transcranial magnetic stimulation (TMS) coils, criticized for its high potential of coil position fluctuations, bypassing the cortex using deep brain electrical stimulation (DBS) of the corticospinal tract with fixed electrodes where both latent variations of the coil position of TMS are eliminated and cortical excitation fluctuations should be absent.

Methods: Ten input-output curves were recorded from five anesthetized cats with implanted DBS electrodes targeting the corticospinal tract. Goodness of fit of regressions with a conventional single variability source as well as a dual variability source model was quantified using a Schwarz Bayesian Information approach to avoid overfitting.

Comparison of methodologies for modeling directional deep brain stimulation electrodes.

Deep brain stimulation (DBS) is an established clinical therapy, and directional DBS electrode designs are now commonly used in clinical practice. Directional DBS leads have the ability to increase the therapeutic window of stimulation, but they also increase the complexity of clinical programming. Therefore, computational models of DBS have become available in clinical software tools that are designed to assist in the identification of therapeutic settings.

Image-based biophysical modeling predicts cortical potentials evoked with subthalamic deep brain stimulation.

Background: Subthalamic deep brain stimulation (DBS) is an effective surgical treatment for Parkinson's disease and continues to advance technologically with an enormous parameter space. As such, in-silico DBS modeling systems have become common tools for research and development, but their underlying methods have yet to be standardized and validated.

Objective: Evaluate the accuracy of patient-specific estimates of neural pathway activations in the subthalamic region against intracranial, cortical evoked potential (EP) recordings.

StimVision v2: Examples and Applications in Subthalamic Deep Brain Stimulation for Parkinson's Disease.

Objective: Subthalamic deep brain stimulation (DBS) is an established therapy for Parkinson's disease. Connectomic DBS modeling is a burgeoning subfield of research aimed at characterizing the axonal connections activated by DBS. This article describes our approach and methods for evolving the StimVision software platform to meet the technical demands of connectomic DBS modeling in the subthalamic region.

Feasibility of Interferential and Pulsed Transcranial Electrical Stimulation for Neuromodulation at the Human Scale.

Objectives: Transcranial electrical stimulation (tES) is a promising tool for modulating neural activity, but tES has poor penetrability and spatiotemporal resolution compared to invasive techniques like deep brain stimulation (DBS). Interferential strategies for alternating-current stimulation (IF-tACS) and pulsed/intersectional strategies for transcranial direct-current stimulation (IS-tDCS) address some of the limitations of tES, but the comparative advantages and disadvantages of these new techniques is not well understood. This study's objective was to evaluate the suprathreshold and subthreshold membrane dynamics of neurons in response to IF-tACS and IS-tDCS.

Field potential 1/ activity in the subcallosal cingulate region as a candidate signal for monitoring deep brain stimulation for treatment-resistant depression.

Subcallosal cingulate cortex deep brain stimulation (SCC-DBS) is an experimental therapy for treatment-resistant depression (TRD). Refinement and optimization of SCC-DBS will benefit from increased study of SCC electrophysiology in context of ongoing high-frequency SCC-DBS therapy. The study objective was a 7-mo observation of frequency-domain 1/ slope in off-stimulation local field potentials (SCC-LFPs) alongside standardized measurements of depression severity in 4 patients undergoing SCC-DBS.

A Driving-Force Predictor for Estimating Pathway Activation in Patient-Specific Models of Deep Brain Stimulation.

Objective: Detailed biophysical modeling of deep brain stimulation (DBS) provides a theoretical approach to quantify the cellular response to the applied electric field. However, the most accurate models for performing such analyses, patient-specific field-cable (FC) pathway-activation models (PAMs), are so technically demanding to implement that their use in clinical research is greatly limited. Predictive algorithms can simplify PAM calculations, but they generally fail to reproduce the output of FC models when evaluated over a wide range of clinically relevant stimulation parameters.

Quantifying the axonal pathways directly stimulated in therapeutic subcallosal cingulate deep brain stimulation.

Deep brain stimulation (DBS) of the subcallosal cingulate (SCC) is an emerging experimental therapy for treatment-resistant depression. New developments in SCC DBS surgical targeting are focused on identifying specific axonal pathways for stimulation that are estimated from patient-specific computational models. This connectomic-based biophysical modeling strategy has proven successful in improving the clinical response to SCC DBS therapy, but the DBS models used to date have been relatively simplistic, limiting the precision of the pathway activation estimates.

Test-retest reliability of a stimulation-locked evoked response to deep brain stimulation in subcallosal cingulate for treatment resistant depression.

Deep brain stimulation (DBS) to the subcallosal cingulate cortex (SCC) is an emerging therapy for treatment resistant depression. Precision targeting of specific white matter fibers is now central to the model of SCC DBS treatment efficacy. A method to confirm SCC DBS target engagement is needed to reduce procedural variance across treatment providers and to optimize DBS parameters for individual patients.

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.

Characterization of the stimulus waveforms generated by implantable pulse generators for deep brain stimulation.

Objective: To determine the circuit elements required to theoretically describe the stimulus waveforms generated by an implantable pulse generator (IPG) during clinical deep brain stimulation (DBS).

Methods: We experimentally interrogated the Medtronic Activa PC DBS IPG and defined an equivalent circuit model that accurately captured the output of the IPG. We then compared the detailed circuit model of the clinical stimulus waveforms to simplified representations commonly used in computational models of DBS.

Quantifying axonal responses in patient-specific models of subthalamic deep brain stimulation.

Medical imaging has played a major role in defining the general anatomical targets for deep brain stimulation (DBS) therapies. However, specifics on the underlying brain circuitry that is directly modulated by DBS electric fields remain relatively undefined. Detailed biophysical modeling of DBS provides an approach to quantify the theoretical responses to stimulation at the cellular level, and has established a key role for axonal activation in the therapeutic mechanisms of DBS.

Stimulation Efficiency With Decaying Exponential Waveforms in a Wirelessly Powered Switched-Capacitor Discharge Stimulation System.

The purpose of this study was to test the feasibility of using a switched-capacitor discharge stimulation (SCDS) system for electrical stimulation, and, subsequently, determine the overall energy saved compared to a conventional stimulator. We have constructed a computational model by pairing an image-based volume conductor model of the cat head with cable models of corticospinal tract (CST) axons and quantified the theoretical stimulation efficiency of rectangular and decaying exponential waveforms, produced by conventional and SCDS systems, respectively. Subsequently, the model predictions were tested in vivo by activating axons in the posterior internal capsule and recording evoked electromyography (EMG) in the contralateral upper arm muscles.

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.

Role of Soft-Tissue Heterogeneity in Computational Models of Deep Brain Stimulation.

Background: Bioelectric field models of deep brain stimulation (DBS) are commonly utilized in research and industrial applications. However, the wide range of different representations used for the human head in these models may be responsible for substantial variance in the stimulation predictions.

Objective: Determine the relative error of ignoring cerebral vasculature and soft-tissue heterogeneity outside of the brain in computational models of DBS.

Analyzing the tradeoff between electrical complexity and accuracy in patient-specific computational models of deep brain stimulation.

Objective: Deep brain stimulation (DBS) is an adjunctive therapy that is effective in treating movement disorders and shows promise for treating psychiatric disorders. Computational models of DBS have begun to be utilized as tools to optimize the therapy. Despite advancements in the anatomical accuracy of these models, there is still uncertainty as to what level of electrical complexity is adequate for modeling the electric field in the brain and the subsequent neural response to the stimulation.

Effects of frequency-dependent membrane capacitance on neural excitability.

Objective: Models of excitable cells consider the membrane specific capacitance as a ubiquitous and constant parameter. However, experimental measurements show that the membrane capacitance declines with increasing frequency, i.e.

Design and in vivo evaluation of more efficient and selective deep brain stimulation electrodes.

Objective: Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, the efficiency and selectivity of DBS can be improved. Our objective was to design electrode geometries that increased the efficiency and selectivity of DBS.

Evaluation of intradural stimulation efficiency and selectivity in a computational model of spinal cord stimulation.

Spinal cord stimulation (SCS) is an alternative or adjunct therapy to treat chronic pain, a prevalent and clinically challenging condition. Although SCS has substantial clinical success, the therapy is still prone to failures, including lead breakage, lead migration, and poor pain relief. The goal of this study was to develop a computational model of SCS and use the model to compare activation of neural elements during intradural and extradural electrode placement.

Evaluation of high-perimeter electrode designs for deep brain stimulation.

Objective: Deep brain stimulation (DBS) is an effective treatment for movement disorders and a promising therapy for treating epilepsy and psychiatric disorders. Despite its clinical success, complications including infections and mis-programing following surgical replacement of the battery-powered implantable pulse generator adversely impact the safety profile of this therapy. We sought to decrease power consumption and extend battery life by modifying the electrode geometry to increase stimulation efficiency.

Influences of interpolation error, electrode geometry, and the electrode-tissue interface on models of electric fields produced by deep brain stimulation.

Deep brain stimulation (DBS) is an established therapy for movement disorders, but the fundamental mechanisms by which DBS has its effects remain unknown. Computational models can provide insights into the mechanisms of DBS, but to be useful, the models must have sufficient detail to predict accurately the electric fields produced by DBS. We used a finite-element method model of the Medtronic 3387 electrode array, coupled to cable models of myelinated axons, to quantify how interpolation errors, electrode geometry, and the electrode-tissue interface affect calculation of electrical potentials and stimulation thresholds for populations of model nerve fibers.