Modeling parkinsonian circuitry and the DBS electrode. I. Biophysical background and software

Dynamic Computational Model of the Human Spinal Cord Connectome

Connectomes abound, but few for the human spinal cord. Using anatomical data in the literature, we constructed a draft connectivity map of the human spinal cord connectome, providing a template for the many calibrations of specialized behavior to be overlaid on it and the basis for an initial computational model. A thorough literature review gleaned cell types, connectivity, and connection strength indications. Where human data were not available, we selected species that have been studied. Cadaveric spinal cord measurements, cross-sectional histology images, and cytoarchitectural data regarding cell size and density served as the starting point for estimating numbers of neurons. Simulations were run using neural circuitry simulation software. The model contains the neural circuitry in all ten Rexed laminae with intralaminar, interlaminar, and intersegmental connections, as well as ascending and descending brain connections and estimated neuron counts for various cell types in every lamina of all 31 segments. We noted the presence of highly interconnected complex networks exhibiting several orders of recurrence. The model was used to perform a detailed study of spinal cord stimulation for analgesia. This model is a starting point for workers to develop and test hypotheses across an array of biomedical applications focused on the spinal cord. Each such model requires additional calibrations to constrain its output to verifiable predictions. Future work will include simulating additional segments and expanding the research uses of the model.

Electrode Position and Current Amplitude Modulate Impulsivity after Subthalamic Stimulation in Parkinsons Disease-A Computational Study

Background: Subthalamic Nucleus Deep Brain Stimulation (STN-DBS) is highly effective in alleviating motor symptoms of Parkinson's disease (PD) which are not optimally controlled by dopamine replacement therapy. Clinical studies and reports suggest that STN-DBS may result in increased impulsivity and de novo impulse control disorders (ICD).

Objective/Hypothesis: We aimed to compare performance on a decision making task, the Iowa Gambling Task (IGT), in healthy conditions (HC), untreated and medically-treated PD conditions with and without STN stimulation. We hypothesized that the position of electrode and stimulation current modulate impulsivity after STN-DBS.

Methods: We built a computational spiking network model of basal ganglia (BG) and compared the model's STN output with STN activity in PD. Reinforcement learning methodology was applied to simulate IGT performance under various conditions of dopaminergic and STN stimulation where IGT total and bin scores were compared among various conditions.

Results: The computational model reproduced neural activity observed in normal and PD conditions. Untreated and medically-treated PD conditions had lower total IGT scores (higher impulsivity) compared to HC (P < 0.0001). The electrode position that happens to selectively stimulate the part of the STN corresponding to an advantageous panel on IGT resulted in de-selection of that panel and worsening of performance (P < 0.0001). Supratherapeutic stimulation amplitudes also worsened IGT performance (P < 0.001).

Conclusion(s): In our computational model, STN stimulation led to impulsive decision making in IGT in PD condition. Electrode position and stimulation current influenced impulsivity which may explain the variable effects of STN-DBS reported in patients.

Computational modeling to improve treatments for essential tremor

Essential tremor (ET) is a neurological disorder of unknown etiology that is typically characterized by an involuntary periodic movement of the upper limbs. No longer considered monosymptomatic, ET patients often have additional motor and even cognitive impairments. Although there are several pharmacological treatments, no drugs have been developed specifically for ET [1], and 30-70% of patients are medication-refractory [2]. A subset of medication-refractory patients may benefit from electrical deep brain stimulation (DBS) of the ventral intermediate nucleus of the thalamus (VIM), which receives cerebellar inputs. Abnormal cerebellar input to VIM is presumed to be a major contributor to tremor symptoms, which is alleviated by DBS. Computational modeling of the effects of DBS in VIM has been a powerful tool to design DBS protocols to reduce tremor activity. However, far less is known about how these therapies affect non-tremor symptoms, and more experimental and computational modeling work is required to address these growing considerations. Models capable of addressing multiple facets of ET will lead to novel, more efficient treatment.

Deep brain stimulation for movement disorders

Deep brain stimulation (DBS) is an implanted electrical device that modulates specific targets in the brain resulting in symptomatic improvement in a particular neurologic disease, most commonly a movement disorder. It is preferred over previously used lesioning procedures due to its reversibility, adjustability, and ability to be used bilaterally with a good safety profile. Risks of DBS include intracranial bleeding, infection, malposition, and hardware issues, such migration, disconnection, or malfunction, but the risk of each of these complications is low--generally ≤ 5% at experienced, large-volume centers. It has been used widely in essential tremor, Parkinson's disease, and dystonia when medical treatment becomes ineffective, intolerable owing to side effects, or causes motor complications. Brain targets implanted include the thalamus (most commonly for essential tremor), subthalamic nucleus (most commonly for Parkinson's disease), and globus pallidus (Parkinson's disease and dystonia), although new targets are currently being explored. Future developments include brain electrodes that can steer current directionally and systems capable of "closed loop" stimulation, with systems that can record and interpret regional brain activity and modify stimulation parameters in a clinically meaningful way. New, image-guided implantation techniques may have advantages over traditional DBS surgery.

Mechanism of dorsal column stimulation to treat neuropathic but not nociceptive pain: analysis with a computational model

OBJECTIVE

Stimulation of axons within the dorsal columns of the human spinal cord has become a widely used therapy to treat refractory neuropathic pain. The mechanisms have yet to be fully elucidated and may even be contrary to standard "gate control theory." Our hypothesis is that a computational model provides a plausible description of the mechanism by which dorsal column stimulation (DCS) inhibits wide dynamic range (WDR) cell output in a neuropathic model but not in a nociceptive pain model.

MATERIALS AND METHODS

We created a computational model of the human spinal cord involving approximately 360,000 individual neurons and dendritic processing of some 60 million synapses--the most elaborate dynamic computational model of the human spinal cord to date. Neuropathic and nociceptive "pain" signals were created by activating topographically isolated regions of excitatory interneurons and high-threshold nociceptive fiber inputs, driving analogous regions of WDR neurons. Dorsal column fiber activity was then added at clinically relevant levels (e.g., Aβ firing rate between 0 and 110 Hz by using a 210-μsec pulse width, 50-150 Hz frequency, at 1-3 V amplitude).

RESULTS

Analysis of the nociceptive pain, neuropathic pain, and modulated circuits shows that, in contradiction to gate control theory, 1) nociceptive and neuropathic pain signaling must be distinct, and 2) DCS neuromodulation predominantly affects the neuropathic signal only, inhibiting centrally sensitized pathological neuron groups and ultimately the WDR pain transmission cells.

CONCLUSION

We offer a different set of necessary premises than gate control theory to explain neuropathic pain inhibition and the relative lack of nociceptive pain inhibition by using retrograde DCS. Hypotheses regarding not only the pain relief mechanisms of DCS were made but also regarding the circuitry of pain itself, both nociceptive and neuropathic. These hypotheses and further use of the model may lead to novel stimulation paradigms.

Short circuit in deep brain stimulation

OBJECT

The authors undertook this study to investigate the incidence, cause, and clinical influence of short circuits in patients treated with deep brain stimulation (DBS).

METHODS

After the incidental identification of a short circuit during routine follow-up, the authors initiated a policy at their institution of routinely evaluating both therapeutic impedance and system impendence at every outpatient DBS follow-up visit, irrespective of the presence of symptoms suggesting possible system malfunction. This study represents a report of their findings after 1 year of this policy.

RESULTS

Implanted DBS leads exhibiting short circuits were identified in 7 patients (8.9% of the patients seen for outpatient follow-up examinations during the 12-month study period). The mean duration from DBS lead implantation to the discovery of the short circuit was 64.7 months. The symptoms revealing short circuits included the wearing off of therapeutic effect, apraxia of eyelid opening, or dysarthria in 6 patients with Parkinson disease (PD), and dystonia deterioration in 1 patient with generalized dystonia. All DBS leads with short circuits had been anchored to the cranium using titanium miniplates. Altering electrode settings resulted in clinical improvement in the 2 PD cases in which patients had specific symptoms of short circuits (2.5%) but not in the other 4 cases. The patient with dystonia underwent repositioning and replacement of a lead because the previous lead was located too anteriorly, but did not experience symptom improvement.

CONCLUSIONS

In contrast to the sudden loss of clinical efficacy of DBS caused by an open circuit, short circuits may arise due to a gradual decrease in impedance, causing the insidious development of neurological symptoms via limited or extended potential fields as well as shortened battery longevity. The incidence of short circuits in DBS may be higher than previously thought, especially in cases in which DBS leads are anchored with miniplates. The circuit impedance of DBS should be routinely checked, even after a long history of DBS therapy, especially in cases of miniplate anchoring.

Patient-specific models of deep brain stimulation: influence of field model complexity on neural activation predictions

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become the surgical therapy of choice for medically intractable Parkinson's disease. However, quantitative understanding of the interaction between the electric field generated by DBS and the underlying neural tissue is limited. Recently, computational models of varying levels of complexity have been used to study the neural response to DBS. The goal of this study was to evaluate the quantitative impact of incrementally incorporating increasing levels of complexity into computer models of STN DBS. Our analysis focused on the direct activation of experimentally measureable fiber pathways within the internal capsule (IC). Our model system was customized to an STN DBS patient and stimulation thresholds for activation of IC axons were calculated with electric field models that ranged from an electrostatic, homogenous, isotropic model to one that explicitly incorporated the voltage-drop and capacitance of the electrode-electrolyte interface, tissue encapsulation of the electrode, and diffusion-tensor based 3D tissue anisotropy and inhomogeneity. The model predictions were compared to experimental IC activation defined from electromyographic (EMG) recordings from eight different muscle groups in the contralateral arm and leg of the STN DBS patient. Coupled evaluation of the model and experimental data showed that the most realistic predictions of axonal thresholds were achieved with the most detailed model. Furthermore, the more simplistic neurostimulation models substantially overestimated the spatial extent of neural activation.

Motor cortex stimulation for pain and movement disorders

Since initial reports in the early 1990s, stimulation of the M1 region of the cortex (MCS) has been used to treat chronic refractory pain conditions and a variety of movement disorders. A Medline search of literature between 1991 and 2007 revealed 512 cases using MCS. Although most of these relate to the treatment of pain (422), 84 of them involve movement disorders. More recently, several studies have specifically looked at treating Parkinson's disease (PD) with MCS. We report here several of our own cases using MCS to treat poststroke and non-poststroke pain syndromes and movement disorders (n = 8), PD (n = 4), ET (n = 2), and cortico-basal degeneration (n = 1). We also cover the essential history of this procedure and our current research using computational modeling to understand further the underlying mechanisms of MCS.

Modeling parkinsonian circuitry and the DBS electrode. II. Evaluation of a computer simulation model of the basal ganglia with and without subthalamic nucleus stimulation

Treatment with deep brain stimulation (DBS) for Parkinson's disease (PD) has become routine over the past decade, particularly using the subthalamic nucleus (STN) as a target and utilizing microelectrode recordings to ensure accurate placement of the stimulating electrodes. The clinical changes seen with DBS in the STN for PD are consistently beneficial, but there continues to be only marginal understanding of the mechanisms by which DBS achieves these results. Using an analytical model of the typical DBS 4-contact electrode and software developed to simulate individual neurons and neural circuitry of the basal ganglia we compare the results of the model to those of data obtained during DBS surgery of the STN. Firing rate, interspike intervals and regularity analyses were performed on the simulated data and compared to results in the literature.