Realistic anatomically detailed open-source spinal cord stimulation (RADO-SCS) model

Computational Models of High-Definition Electroconvulsive Therapy for Focal or Multitargeting Treatment

ABSTRACT

Attempts to dissociate electroconvulsive therapy (ECT) therapeutic efficacy from cognitive side effects of ECT include modifying electrode placement, but traditional electrode placements employing 2 large electrodes are inherently nonfocal, limiting the ability to selectively engage targets associated with clinical benefit while avoiding nontargets associated with adverse side effects. Limited focality represents a technical limitation of conventional ECT, and there is growing evidence that the spatial distribution of the ECT electric fields induced in the brain drives efficacy and side effects. Computational models can be used to predict brain current flow patterns for existing and novel ECT montages. Using finite element method simulations (under quasi-static, nonadaptive assumptions, 800-mA total current), the electric fields generated in the superficial cortex and subcortical structures were predicted for the following traditional ECT montages (bilateral temporal, bifrontal, right unilateral) and experimental montages (focal electrically administered seizure therapy, lateralized high-definition [HD]-ECT, unilateral 4 × 1-ring HD-ECT, bilateral 4 × 1-ring HD-ECT, and a multipolar HD-ECT). Peak brain current density in regions of interest was quantified. Conventional montages (bilateral bifrontal, right unilateral) each produce distinct but diffuse and deep current flow. Focal electrically administered seizure therapy and lateralized HD-ECT produce unique, lateralized current flow, also impacting specific deep regions. A 4 × 1-ring HD-ECT restricts current flow to 1 (unilateral) or 2 (bilateral) cortical regions. Multipolar HD-ECT shows optimization to a specific target set. Future clinical trials are needed to determine whether enhanced control over current distribution is achieved with these experimental montages, and the resultant seizures, improve the risk/benefit ratio of ECT.

A Visual and Narrative Timeline Review of Spinal Cord Stimulation Technology and US Food and Drug Administration Milestones

OBJECTIVES

The aim of this study was to present key technologic and regulatory milestones in spinal cord stimulation (SCS) for managing chronic pain on a narrative timeline with visual representation, relying on original sources to the extent possible.

MATERIALS AND METHODS

We identified technical advances in SCS that facilitated and enhanced treatment on the basis of scientific publications and approvals from the United States (US) Food and Drug Administration (FDA). We presented milestones limited to first use in key indications and in the context of new technology validation. We focused primarily on pain management, but other indications (eg, motor disorder in multiple sclerosis) were included when they affected technology development.

RESULTS

We developed a comprehensive visual and narrative timeline of SCS technology and US FDA milestones. Since its conception in the 1960s, the science and technology of SCS neuromodulation have continuously evolved. Advances span lead design (from paddle-type to percutaneous, and increased electrode contacts) and stimulator technology (from wireless power to internally powered and rechargeable, with miniaturized components, and programmable multichannel devices), with expanding stimulation program flexibility (such as burst and kilohertz stimulation frequencies), as well as usage features (such as remote programming and magnetic resonance imaging conditional compatibility).

CONCLUSIONS

This timeline represents the evolution of SCS technology alongside expanding FDA-approved indications for use.

Quasistatic approximation in neuromodulation

We define and explain the quasistatic approximation (QSA) as applied to field modeling for electrical and magnetic stimulation. Neuromodulation analysis pipelines include discrete stages, and QSA is applied specifically when calculating the electric and magnetic fields generated in tissues by a given stimulation dose. QSA simplifies the modeling equations to support tractable analysis, enhanced understanding, and computational efficiency. The application of QSA in neuromodulation is based on four underlying assumptions: (A1) no wave propagation or self-induction in tissue, (A2) linear tissue properties, (A3) purely resistive tissue, and (A4) non-dispersive tissue. As a consequence of these assumptions, each tissue is assigned a fixed conductivity, and the simplified equations (e.g. Laplace's equation) are solved for the spatial distribution of the field, which is separated from the field's temporal waveform. Recognizing that electrical tissue properties may be more complex, we explain how QSA can be embedded in parallel or iterative pipelines to model frequency dependence or nonlinearity of conductivity. We survey the history and validity of QSA across specific applications, such as microstimulation, deep brain stimulation, spinal cord stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. The precise definition and explanation of QSA in neuromodulation are essential for rigor when using QSA models or testing their limits.

Postural Changes in Spinal Cord Stimulation Thresholds: Current and Voltage Sources

OBJECTIVE

Spinal cord stimulation (SCS) thresholds are known to change with body position; however, these changes have not been fully characterized for both "constant-voltage" and "constant-current" pulse generators. This study aimed to evaluate and quantify changes in psychophysical thresholds resulting from postural changes that may affect both conventional paresthesia-based SCS and novel paresthesia-free SCS technologies.

MATERIALS AND METHODS

We measured perceptual, usage, and discomfort thresholds in four body positions (prone, supine, sitting, standing) in 149 consecutive patients, with temporary lower thoracic percutaneous epidural electrodes placed for treating persistent low back and leg pain. We trialed 119 patients with constant-voltage stimulators and 30 patients with constant-current stimulators.

RESULTS

Moving from supine to the sitting, standing, or prone positions caused all three thresholds (perceptual, usage, and discomfort) to increase by 22% to 34% for constant-voltage stimulators and by 44% to 82% for constant-current stimulators. Changing from a seated to a supine position caused stimulation to exceed discomfort threshold significantly more often for constant-current (87%) than for constant-voltage (63%) stimulators (p = 0.01).

CONCLUSIONS

Posture-induced changes in SCS thresholds occurred consistently as patients moved from lying (supine or prone) to upright (standing or sitting) positions. These changes were more pronounced for constant-current than for constant-voltage pulse generators and more often led to stimulation-evoked discomfort. These observations are consistent with postural changes in spinal cord position measured in imaging studies, and with computer model predictions of neural recruitment for these different spinal cord positions. These observations have implications for the design, implantation, and clinical application of spinal cord stimulators, not only for conventional paresthesia-based SCS but also for paresthesia-free SCS.

A systematic review of computational models for the design of spinal cord stimulation therapies: from neural circuits to patient-specific simulations

Seventy years ago, Hodgkin and Huxley published the first mathematical model to describe action potential generation, laying the foundation for modern computational neuroscience. Since then, the field has evolved enormously, with studies spanning from basic neuroscience to clinical applications for neuromodulation. Computer models of neuromodulation have evolved in complexity and personalization, advancing clinical practice and novel neurostimulation therapies, such as spinal cord stimulation. Spinal cord stimulation is a therapy widely used to treat chronic pain, with rapidly expanding indications, such as restoring motor function. In general, simulations contributed dramatically to improve lead designs, stimulation configurations, waveform parameters and programming procedures and provided insight into potential mechanisms of action of electrical stimulation. Although the implementation of neural models are relentlessly increasing in number and complexity, it is reasonable to ask whether this observed increase in complexity is necessary for improved accuracy and, ultimately, for clinical efficacy. With this aim, we performed a systematic literature review and a qualitative meta-synthesis of the evolution of computational models, with a focus on complexity, personalization and the use of medical imaging to capture realistic anatomy. Our review showed that increased model complexity and personalization improved both mechanistic and translational studies. More specifically, the use of medical imaging enabled the development of patient-specific models that can help to transform clinical practice in spinal cord stimulation. Finally, we combined our results to provide clear guidelines for standardization and expansion of computational models for spinal cord stimulation.

Steering Toward Normative Wide-Dynamic-Range Neuron Activity in Nerve-Injured Rats With Closed-Loop Peripheral Nerve Stimulation

OBJECTIVES

Chronic pain is primarily treated with pharmaceuticals, but the effects remain unsatisfactory. A promising alternative therapy is peripheral nerve stimulation (PNS), but it has been associated with suboptimal efficacy because its modulation mechanisms are not clear and the current therapies are primarily open loop (ie, manually adjusting the stimulation parameters). In this study, we developed a proof-of-concept computational modeling as the first step toward implementing closed-loop PNS in future biological studies. When developing new pain therapies, a useful pain biomarker is the wide-dynamic-range (WDR) neuron activity in the dorsal horn. In healthy animals, the WDR neuron activity occurs in a stereotyped manner; however, this response profile can vary widely after nerve injury to create a chronic pain condition. We hypothesized that if injury-induced changes of neuronal response can be normalized to resemble those of a healthy condition, the pathological aspects of pain may be treated while maintaining protective physiological nociception.

MATERIALS AND METHODS

Using an in vivo electrophysiology data set of WDR neuron recordings obtained in nerve-injured rats and naïve rats, we constructed sets of linear phenomenologic models of WDR firing rate during windup stimulation for both conditions. Then, we applied robust control systems techniques to identify a closed-loop PNS controller, which can drive the dynamics of WDR neuron response in neuropathic pain model into ranges associated with normal physiological pain.

RESULTS

The sets of identified linear models can accurately predict, in silico, nonlinear neural responses to electrical stimulation of the peripheral nerve. In addition, we showed that continuous closed-loop control of PNS can be used to normalize WDR neuron firing responses in three injured cases.

CONCLUSIONS

In this proof-of-concept study, we show how tractable, linear mathematical models of pain-related neurotransmission can be used to inform the development of closed-loop PNS. This new application of robust control to neurotechnology may also be expanded and applied across other neuromodulation applications.

Methods and system for recording human physiological signals from implantable leads during spinal cord stimulation

Objectives

This article presents a method-including hardware configuration, sampling rate, filtering settings, and other data analysis techniques-to measure evoked compound action potentials (ECAPs) during spinal cord stimulation (SCS) in humans with externalized percutaneous electrodes. The goal is to provide a robust and standardized protocol for measuring ECAPs on the non-stimulation contacts and to demonstrate how measured signals depend on hardware and processing decisions.

Methods

Two participants were implanted with percutaneous leads for the treatment of chronic pain with externalized leads during a trial period for stimulation and recording. The leads were connected to a Neuralynx ATLAS system allowing us to simultaneously stimulate and record through selected electrodes. We examined different hardware settings, such as online filters and sampling rate, as well as processing techniques, such as stimulation artifact removal and offline filters, and measured the effects on the ECAPs metrics: the first negative peak (N1) time and peak-valley amplitude.

Results

For accurate measurements of ECAPs, the hardware sampling rate should be least at 8 kHz and should use a high pass filter with a low cutoff frequency, such as 0.1 Hz, to eliminate baseline drift and saturation (railing). Stimulation artifact removal can use a double exponential or a second-order polynomial. The polynomial fit is 6.4 times faster on average in computation time than the double exponential, while the resulting ECAPs' N1 time and peak-valley amplitude are similar between the two. If the baseline raw measurement drifts with stimulation, a median filter with a 100-ms window or a high pass filter with an 80-Hz cutoff frequency preserves the ECAPs.

Conclusions

This work is the first comprehensive analysis of hardware and processing variations on the observed ECAPs from SCS leads. It sets recommendations to properly record and process ECAPs from the non-stimulation contacts on the implantable leads.

Neurocapillary-Modulation

OBJECTIVES

We consider two consequences of brain capillary ultrastructure in neuromodulation. First, blood-brain barrier (BBB) polarization as a consequence of current crossing between interstitial space and the blood. Second, interstitial current flow distortion around capillaries impacting neuronal stimulation.

MATERIALS AND METHODS

We developed computational models of BBB ultrastructure morphologies to first assess electric field amplification at the BBB (principle 1) and neuron polarization amplification by the presence of capillaries (principle 2). We adapt neuron cable theory to develop an analytical solution for maximum BBB polarization sensitivity.

RESULTS

Electrical current crosses between the brain parenchyma (interstitial space) and capillaries, producing BBB electric fields (EBBB) that are >400x of the average parenchyma electric field (ĒBRAIN), which in turn modulates transport across the BBB. Specifically, for a BBB space constant (λBBB) and wall thickness (dth-BBB), the analytical solution for maximal BBB electric field (EABBB) is given as: (ĒBRAIN × λBBB)/dth-BBB. Electrical current in the brain parenchyma is distorted around brain capillaries, amplifying neuronal polarization. Specifically, capillary ultrastructure produces ∼50% modulation of the ĒBRAIN over the ∼40 μm inter-capillary distance. The divergence of EBRAIN (Activating function) is thus ∼100 kV/m2 per unit ĒBRAIN.

CONCLUSIONS

BBB stimulation by principle 1 suggests novel therapeutic strategies such as boosting metabolic capacity or interstitial fluid clearance. Whereas the spatial profile of EBRAIN is traditionally assumed to depend only on macroscopic anatomy, principle 2 suggests a central role for local capillary ultrastructure-which impact forms of neuromodulation including deep brain stimulation (DBS), spinal cord stimulation (SCS), transcranial magnetic stimulation (TMS), electroconvulsive therapy (ECT), and transcranial electrical stimulation (tES)/transcranial direct current stimulation (tDCS).

Non-invasive brain-spine interface: Continuous control of trans-spinal magnetic stimulation using EEG

Brain-controlled neuromodulation has emerged as a promising tool to promote functional recovery in patients with motor disorders. Brain-machine interfaces exploit this neuromodulatory strategy and could be used for restoring voluntary control of lower limbs. In this work, we propose a non-invasive brain-spine interface (BSI) that processes electroencephalographic (EEG) activity to volitionally control trans-spinal magnetic stimulation (ts-MS), as an approach for lower-limb neurorehabilitation. This novel platform allows to contingently connect motor cortical activation during leg motor imagery with the activation of leg muscles via ts-MS. We tested this closed-loop system in 10 healthy participants using different stimulation conditions. This BSI efficiently removed stimulation artifacts from EEG regardless of ts-MS intensity used, allowing continuous monitoring of cortical activity and real-time closed-loop control of ts-MS. Our BSI induced afferent and efferent evoked responses, being this activation ts-MS intensity-dependent. We demonstrated the feasibility, safety and usability of this non-invasive BSI. The presented system represents a novel non-invasive means of brain-controlled neuromodulation and opens the door towards its integration as a therapeutic tool for lower-limb rehabilitation.

Optimizing sensory fiber activation during cervical transcutaneous spinal stimulation using different electrode configurations: A computational analysis

BACKGROUND

Cervical transcutaneous spinal cord stimulation (tSCS) is a rehabilitation tool which has been used to promote upper-limb motor recovery after spinal cord injury. Importantly, optimizing sensory fiber activation at specific spinal segments could enable activity-dependent neuromodulation during rehabilitation.

METHODS

An anatomically realistic cervical tSCS computational model was used to analyze the activation of α-motor and Aα-sensory fibers at C7 and C8 spinal segments using nine cathode electrode configurations. Specifically, the cathode was simulated at three vertebral level positions: C6, C7, and T1; and in three sizes: 5.0 x 5.0, 3.5 x 3.5; and 2.5 x 2.5 cm² , while the anode was on the anterior neck. Finite element method was used to estimate the electric potential distribution along α-motor and Aα-sensory fibers, and computational models were applied to simulate the fiber membrane dynamics during tSCS. The minimum stimulation intensity necessary to activate the fibers (activation threshold) was estimated and compared across cathode configurations in an effort to optimize sensory fiber activation.

RESULTS

Our results showed that nerve fibers at both C7 and C8 spinal segments were recruited at lower stimulation intensities when the cathode was positioned over the C7 or T1 vertebra compared with the C6 position. Sensory fibers were activated at lower stimulation intensities using smaller electrodes, which could also affect the degree of nerve fiber activation across different positions. Importantly, Aα-sensory fibers were consistently recruited before α-motor fibers.

CONCLUSIONS

These results imply that cathode positioning could help optimize preferential activation of hand muscles during cervical tSCS.

Preferential activation of proprioceptive and cutaneous sensory fibers compared to motor fibers during cervical transcutaneous spinal cord stimulation: A computational study

OBJECTIVE

Cervical transcutaneous spinal cord stimulation (tSCS) is a promising technology that can support motor function recovery of upper-limbs after spinal cord injury. Its efficacy may depend on the ability to recruit sensory afferents, conveying excitatory inputs onto motoneurons. Therefore, understanding its physiological mechanisms is critical to accelerate its development towards clinical applications. In this study, we used an anatomically realistic cervical tSCS computational model to compare α-motor, Aα-sensory, and Aβ-sensory fiber activation thresholds and activation sites.

APPROACH

We developed a 3D geometry of the cervical body and tSCS electrodes with a cathode centred at the C7 spinous process and an anode placed over the anterior neck. The geometrical model was used to estimate the electric potential distributions along motor and sensory fiber trajectories at the C7 spinal level using a finite element method. We implemented dedicated motor and sensory fiber models to simulate the α-motor and Aα-sensory fibers using 12, 16, and 20 µm diameter fibers, and Aβ-sensory fibers using 6, 9, and 12 µm diameter fibers. We estimated nerve fiber activation thresholds and sites for a 2 ms monophasic stimulating pulse and compared them across the fiber groups.

MAIN RESULTS

Our results showed lower activation thresholds of Aα- and Aβ-sensory fibers compared with α-motor fibers, suggesting preferential sensory fiber activation. We also found no differences between activation thresholds of Aα-sensory and large Aβ-sensory fibers, implying their co-activation. The activation sites were located at the dorsal and ventral root levels.

SIGNIFICANCE

Using a realistic computational model, we demonstrated preferential activation of dorsal root Aα- and Aβ-sensory fibers compared with ventral root α-motor fibers during cervical tSCS. These findings suggest high proprioceptive and cutaneous contributions to neural activations during cervical tSCS, which inform the underlying mechanisms of upper-limb functional motor recovery.

Neural Recruitment During Conventional, Burst, and 10-kHz Spinal Cord Stimulation for Pain

Spinal cord stimulation (SCS) is a popular neurostimulation therapy for severe chronic pain. To improve stimulation efficacy, multiple modes are now used clinically, including conventional, burst, and 10-kHz SCS. Clinical observations have produced speculation that these modes target different neural elements and/or work via distinct mechanisms of action. However, in humans, these hypotheses cannot be conclusively answered via experimental methods. Therefore, we utilized computational modeling to assess the response of primary afferents, interneurons, and projection neurons to conventional, burst, and 10-kHz SCS. We found that local cell thresholds were always higher than afferent thresholds, arguing against direct recruitment of these local cells. Furthermore, although we observed relative threshold differences between conventional, burst, and 10-kHz SCS, the recruitment order was the same. Finally, contrary to previous reports, axon collateralization produced complex changes in activation thresholds of primary afferents. These results motivate future work to contextualize clinical observations across SCS paradigms. PERSPECTIVE: This article presents the first computational modeling study to investigate neural recruitment during conventional, burst, and 10-kilohertz spinal cord stimulation for chronic pain within a single modeling framework. The results provide insight into these treatments' unknown mechanisms of action and offer context to interpreting clinical observations.

Dataset of concurrent EEG, ECG, and behavior with multiple doses of transcranial electrical stimulation

We present a dataset combining human-participant high-density electroencephalography (EEG) with physiological and continuous behavioral metrics during transcranial electrical stimulation (tES). Data include within participant application of nine High-Definition tES (HD-tES) types, targeting three cortical regions (frontal, motor, parietal) with three stimulation waveforms (DC, 5 Hz, 30 Hz); more than 783 total stimulation trials over 62 sessions with EEG, physiological (ECG, EOG), and continuous behavioral vigilance/alertness metrics. Experiment 1 and 2 consisted of participants performing a continuous vigilance/alertness task over three 70-minute and two 70.5-minute sessions, respectively. Demographic data were collected, as well as self-reported wellness questionnaires before and after each session. Participants received all 9 stimulation types in Experiment 1, with each session including three stimulation types, with 4 trials per type. Participants received two stimulation types in Experiment 2, with 20 trials of a given stimulation type per session. Within-participant reliability was tested by repeating select sessions. This unique dataset supports a range of hypothesis testing including interactions of tDCS/tACS location and frequency, brain-state, physiology, fatigue, and cognitive performance.

A Call to Action Toward Optimizing the Electrical Dose Received by Neural Targets in Spinal Cord Stimulation Therapy for Neuropathic Pain

Spinal cord stimulation has seen unprecedented growth in new technology in the 50 years since the first subdural implant. As we continue to grow our understanding of spinal cord stimulation and relevant mechanisms of action, novel questions arise as to electrical dosing optimization. Programming adjustment — dose titration — is often a process of trial and error that can be time-consuming and frustrating for both patient and clinician. In this report, we review the current preclinical and clinical knowledge base in order to provide insights that may be helpful in developing more rational approaches to spinal cord stimulation dosing. We also provide key conclusions that may help in directing future research into electrical dosing, given the advent of newer waveforms outside traditional programming parameters.

3D patient-specific spinal cord computational model for SCS management: potential clinical applications

BACKGROUND AND OBJECTIVE

Although Spinal Cord Stimulation (SCS) is an established therapy for treating neuropathic chronic pain, in tonic stimulation, postural changes, electrode migration or badly-positioned electrodes can produce annoying stimulation (intercostal neuralgia) in about 35% of the patients. SCS models are used to study the effect of electrical stimulation to better manage the stimulation parameters and electrode position. The goal of this work was to develop a realistic 3D patient-specific spinal cord model from a real patient and develop a future clinical application that would help physicians to optimize paresthesia coverage in SCS therapy.

METHODS

We developed two 3D patient-specific models from a high-resolution MRI of two patients undergoing SCS treatment. The model consisted of a finite element model of the spinal cord and a sensory myelinated nerve fiber model. The same simulations were performed with a generalized spinal cord model and we compared the results with the clinical data to evaluate the advantages of a patient-specific model. To identify the geometrical parameters that most influence the stimulation predictions, a sensitivity analysis was conducted. We used the patient-specific model to perform a clinical application involving the pre-implantation selection of electrode polarity and study the effect of electrode offset.

RESULTS

The patient-specific model correlated better with clinical data than the generalized model. Electrode-dura mater distance, dorsal CSF thickness, and CSF diameter are the geometrical parameters that caused significant changes in the stimulation predictions. Electrode polarity could be planned and optimized to stimulate the patient's painful dermatomes. The addition of offset in parallel electrodes would not have been beneficial for one of the patients of this study because they reduce neural activation displacement.

CONCLUSIONS

This is the first study to relate the activation area model prediction in dorsal columns with the clinical effect on paresthesia coverage. The outcomes show that 3D patient-specific models would help physicians to choose the best stimulation parameters to optimize neural activation and SCS therapy in tonic stimulation.