Biomedical subjects

Cameron C McIntyre

Publications and source records attributed to Cameron C McIntyre.

14 recordsLinked to original sources

PubMed2006

Patient-specific analysis of the volume of tissue activated during deep brain stimulation.

Despite the clinical success of deep brain stimulation (DBS) for the treatment of movement disorders, many questions remain about its effects on the nervous system. This study presents a methodology to predict the volume of tissue activated (VTA) by DBS on a patient-specific basis. Our goals were to identify the intersection between the VTA and surrounding anatomical structures and to compare activation of these structures with clinical outcomes. The model system consisted of three fundamental components: (1) a 3D anatomical model of the subcortical nuclei and DBS electrode position in the brain, each derived from magnetic resonance imaging (MRI); (2) a finite element model of the DBS electrode and electric field transmitted to the brain, with tissue conductivity properties derived from diffusion tensor MRI; (3) VTA prediction derived from the response of myelinated axons to the applied electric field, which is a function of the stimulation parameters (contact, impedance, voltage, pulse width, frequency). We used this model system to analyze the effects of subthalamic nucleus (STN) DBS in a patient with Parkinson's disease. Quantitative measurements of bradykinesia, rigidity, and corticospinal tract (CST) motor thresholds were evaluated over a range of stimulation parameter settings. Our model predictions showed good agreement with CST thresholds. Additionally, stimulation through electrode contacts that improved bradykinesia and rigidity generated VTAs that overlapped the zona incerta/fields of Forel (ZI/H2). Application of DBS technology to various neurological disorders has preceded scientific characterization of the volume of tissue directly affected by the stimulation. Synergistic integration of clinical analysis, neuroimaging, neuroanatomy, and neurostimulation modeling provides an opportunity to address wide ranging questions on the factors linked with the therapeutic benefits and side effects of DBS.

Deep Brain Stimulation↗

PubMed2006

Computational analysis of subthalamic nucleus and lenticular fasciculus activation during therapeutic deep brain stimulation.

The subthalamic nucleus (STN) is the most common target for the treatment of Parkinson's disease (PD) with deep brain stimulation (DBS). DBS of the globus pallidus internus (GPi) is also effective in the treatment of PD. The output fibers of the GPi that form the lenticular fasciculus pass in close proximity to STN DBS electrodes. In turn, both STN projection neurons and GPi fibers of passage represent possible therapeutic targets of DBS in the STN region. We built a comprehensive computational model of STN DBS in parkinsonian macaques to study the effects of stimulation in a controlled environment. The model consisted of three fundamental components: 1) a three-dimensional (3D) anatomical model of the macaque basal ganglia, 2) a finite element model of the DBS electrode and electric field transmitted to the tissue medium, and 3) multicompartment biophysical models of STN projection neurons, GPi fibers of passage, and internal capsule fibers of passage. Populations of neurons were positioned within the 3D anatomical model. Neurons were stimulated with electrode positions and stimulation parameters defined as clinically effective in two parkinsonian monkeys. The model predicted axonal activation of STN neurons and GPi fibers during STN DBS. Model predictions regarding the degree of GPi fiber activation matched well with experimental recordings in both monkeys. Only axonal activation of the STN neurons showed a statistically significant increase in both monkeys when comparing clinically effective and ineffective stimulation. Nonetheless, both neural targets may play important roles in the therapeutic mechanisms of STN DBS.

Animals↗

PubMed2005

Sources and effects of electrode impedance during deep brain stimulation.

OBJECTIVE: Clinical impedance measurements for deep brain stimulation (DBS) electrodes in human patients are normally in the range 500-1500 Omega. DBS devices utilize voltage-controlled stimulation; therefore, the current delivered to the tissue is inversely proportional to the impedance. The goals of this study were to evaluate the effects of various electrical properties of the tissue medium and electrode-tissue interface on the impedance and to determine the impact of clinically relevant impedance variability on the volume of tissue activated (VTA) during DBS. METHODS: Axisymmetric finite-element models (FEM) of the DBS system were constructed with explicit representation of encapsulation layers around the electrode and implanted pulse generator. Impedance was calculated by dividing the stimulation voltage by the integrated current density along the active electrode contact. The models utilized a Fourier FEM solver that accounted for the capacitive components of the electrode-tissue interface during voltage-controlled stimulation. The resulting time- and space-dependent voltage waveforms generated in the tissue medium were superimposed onto cable model axons to calculate the VTA. RESULTS: The primary determinants of electrode impedance were the thickness and conductivity of the encapsulation layer around the electrode contact and the conductivity of the bulk tissue medium. The difference in the VTA between our low (790 Omega) and high (1244 Omega) impedance models with typical DBS settings (-3 V, 90 mus, 130 Hz pulse train) was 121 mm3, representing a 52% volume reduction. CONCLUSIONS: Electrode impedance has a substantial effect on the VTA and accurate representation of electrode impedance should be an explicit component of computational models of voltage-controlled DBS. SIGNIFICANCE: Impedance is often used to identify broken leads (for values > 2000 Omega) or short circuits in the hardware (for values < 50 Omega); however, clinical impedance values also represent an important parameter in defining the spread of stimulation during DBS.

Brain↗

PubMed2005

Role of electrode design on the volume of tissue activated during deep brain stimulation.

Deep brain stimulation (DBS) is an established clinical treatment for a range of neurological disorders. Depending on the disease state of the patient, different anatomical structures such as the ventral intermediate nucleus of the thalamus (VIM), the subthalamic nucleus or the globus pallidus are targeted for stimulation. However, the same electrode design is currently used in nearly all DBS applications, even though substantial morphological and anatomical differences exist between the various target nuclei. The fundamental goal of this study was to develop a theoretical understanding of the impact of changes in the DBS electrode contact geometry on the volume of tissue activated (VTA) during stimulation. Finite element models of the electrodes and surrounding medium were coupled to cable models of myelinated axons to predict the VTA as a function of stimulation parameter settings and electrode design. Clinical DBS electrodes have cylindrical contacts 1.27 mm in diameter (d) and 1.5 mm in height (h). Our results show that changes in contact height and diameter can substantially modulate the size and shape of the VTA, even when contact surface area is preserved. Electrode designs with a low aspect ratio (d/h) maximize the VTA by providing greater spread of the stimulation parallel to the electrode shaft without sacrificing lateral spread. The results of this study provide the foundation necessary to customize electrode design and VTA shape for specific anatomical targets, and an example is presented for the VIM. A range of opportunities exist to engineer DBS systems to maximize stimulation of the target area while minimizing stimulation of non-target areas. Therefore, it may be possible to improve therapeutic benefit and minimize side effects from DBS with the design of target-specific electrodes.

Animals↗

PubMed2005

Model-based analysis of cortical recording with silicon microelectrodes.

OBJECTIVE: The purpose of this study was to use computational modeling to better understand factors that impact neural recordings with silicon microelectrodes used in brain-machine interfaces. METHODS: A non-linear cable model of a layer V pyramidal cell was coupled with a finite-element electric field model with explicit representation of the microelectrode. The model system enabled analysis of extracellular neural recordings as a function of the electrode contact size, neuron position, edema, and chronic encapsulation. RESULTS: The model predicted spike waveforms and amplitudes that were consistent with experimental recordings. Small (< 1000 microm2) and large (10 k microm2) electrode contacts had similar volumes of recording sensitivity, but small contacts exhibited higher signal amplitudes (approximately 50%) when neurons were in close proximity (50 microm) to the electrode. The model results support the notion that acute edema causes a signal decrease ( approximately 24%), and certain encapsulation conditions can result in a signal increase (approximately 17%), a mechanism that may contribute to signal increases observed experimentally in chronic recordings. CONCLUSIONS: Optimal electrode design is application-dependent. Small and large contact sizes have contrasting recording properties that can be exploited in the design process. In addition, the presence of local electrical inhomogeneities (encapsulation, edema, coatings) around the electrode shank can substantially influence neural recordings and requires further theoretical and experimental investigation. SIGNIFICANCE: Thought-controlled devices using cortical command signals have exciting therapeutic potential for persons with neurological deficit. The results of this study provide the foundation for refining and optimizing microelectrode design for human brain-machine interfaces.

Algorithms↗

PubMed2005

Tissue and electrode capacitance reduce neural activation volumes during deep brain stimulation.

OBJECTIVE: The growing clinical acceptance of neurostimulation technology has highlighted the need to accurately predict neural activation as a function of stimulation parameters and electrode design. In this study we evaluate the effects of the tissue and electrode capacitance on the volume of tissue activated (VTA) during deep brain stimulation (DBS). METHODS: We use a Fourier finite element method (Fourier FEM) to calculate the potential distribution in the tissue medium as a function of time and space simultaneously for a range of stimulus waveforms. The extracellular voltages are then applied to detailed multi-compartment cable models of myelinated axons to determine neural activation. Neural activation volumes are calculated as a function of the stimulation parameters and magnitude of the capacitive components of the electrode-tissue interface. RESULTS: Inclusion of either electrode or tissue capacitance reduces the VTA compared to electrostatic simulations in a manner dependent on the capacitance magnitude and the stimulation parameters (amplitude and pulse width). Electrostatic simulations with typical DBS parameter settings (-3 V or -3 mA, 90 micros, 130 Hz) overestimate the VTA by approximately 20% for voltage- or current-controlled stimulation. In addition, strength-duration time constants decrease and more closely match clinical measurements when explicitly accounting for the effects of voltage-controlled stimulation. CONCLUSIONS: Attempts to quantify the VTA from clinical neurostimulation devices should account for the effects of electrode and tissue capacitance. SIGNIFICANCE: DBS has rapidly emerged as an effective treatment for movement disorders; however, little is known about the VTA during therapeutic stimulation. In addition, the influence of tissue and electrode capacitance has been largely ignored in previous models of neural stimulation. The results and methodology of this study provide the foundation for the quantitative analysis of the VTA during clinical neurostimulation.

Algorithms↗

PubMed2004

Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus.

OBJECTIVE: The goal of this project was to develop a quantitative understanding of the volume of axonal tissue directly activated by deep brain stimulation (DBS) of the subthalamic nucleus (STN). METHODS: The 3-dimensionally inhomogeneous and anisotropic tissue medium surrounding DBS electrodes complicates our understanding of the electric field and tissue response generated by the stimulation. We developed finite element computer models to address the effects of DBS in a homogeneous isotropic medium, and a medium with tissue conductivity properties derived from human diffusion tensor magnetic resonance data. The second difference of the potential distribution generated in the tissue medium was used as a predictor of the volume of tissue supra-threshold for axonal activation. RESULTS: The model predicts that clinically effective stimulation parameters (-3 V; 0.1 ms; 150 Hz) result in activation of large diameter (5.7 microm) myelinated axons over a volume that spreads outside the borders of the STN. The shape of the activation volume was dependent on the strong dorsal-ventral anisotropy of the internal capsule, and the moderate anterior-posterior anisotropy of the region around zona incerta. CONCLUSIONS: Small deviations ( approximately 1 mm) in the electrode position within STN can substantially alter the shape of the activation volume as well as its spread to neighboring structures. SIGNIFICANCE: STN DBS represents an effective treatment for medically refractory movement disorders such as Parkinson's disease. However, stimulation induced side effects such as tetanic muscle contraction, speech disturbance and ocular deviation are not uncommon. Quantitative characterization of the spread of stimulation will aid in the development of techniques to maximize the efficacy of DBS.

Artifacts↗

PubMed2004

Uncovering the mechanism(s) of action of deep brain stimulation: activation, inhibition, or both.

High-frequency deep brain stimulation (DBS) of the thalamus or basal ganglia represents an effective clinical technique for the treatment of several medically refractory movement disorders. However, understanding of the mechanisms responsible for the therapeutic action of DBS remains elusive. The goal of this review is to address our present knowledge of the effects of high-frequency stimulation within the central nervous system and comment on the functional implications of this knowledge for uncovering the mechanism(s) of DBS. Four general hypotheses have been developed to explain the mechanism(s) of DBS: depolarization blockade, synaptic inhibition, synaptic depression, and stimulation-induced modulation of pathological network activity. Using the results from functional imaging, neurochemistry, neural recording, and neural modeling experiments we address the general hypotheses and attempt to reconcile what have been considered conflicting results from these different research modalities. Our analysis suggests stimulation-induced modulation of pathological network activity represents the most likely mechanism of DBS; however, several open questions remain to explicitly link the effects of DBS with therapeutic outcomes.

Animals↗

PubMed2004

Prediction of myelinated nerve fiber stimulation thresholds: limitations of linear models.

Computer models of neurons are used to simulate neural behavior, and are important tools for designing neural prostheses. Computation time remains an issue when simulating large numbers of neurons or applying models to real time applications. Warman et al. developed a method to predict excitation thresholds for axons using linear models and a predetermined critical voltage. We calculated threshold prediction error as a function of the location of an extracellular electrode using two different axon models to examine further threshold prediction using linear models. Threshold prediction error was low (<3% error) under the conditions examined by Warman et al., but under more general conditions, threshold prediction error was as high as 23.6%. Linear models were limited as effective tools for single fiber threshold prediction because accuracy was dependent on the nonlinear and linear models used, and any parameter that affected the extracellular potential distribution. Threshold prediction could be improved by appropriately choosing the membrane conductance of the linear model, but determination of an optimal conductance was computationally expensive. Finally, although single fiber threshold prediction error was partially masked when considering the input-output (I/O) properties of populations of axons, relatively large errors still occurred in population I/O curves generated with linear models.

Axons↗

PubMed2003

Cellular effects of deep brain stimulation: model-based analysis of activation and inhibition.

Deep brain stimulation (DBS) is an effective therapy for medically refractory movement disorders. However, fundamental questions remain about the effects of DBS on neurons surrounding the electrode. Experimental studies have produced apparently contradictory results showing suppression of activity in the stimulated nucleus, but increased inputs to projection nuclei. We hypothesized that cell body firing does not accurately reflect the efferent output of neurons stimulated with high-frequency extracellular pulses, and that this decoupling of somatic and axonal activity explains the paradoxical experimental results. We studied stimulation using the combination of a finite-element model of the clinical DBS electrode and a multicompartment cable model of a thalamocortical (TC) relay neuron. Both the electric potentials generated by the electrode and a distribution of excitatory and inhibitory trans-synaptic inputs induced by stimulation of presynaptic terminals were applied to the TC relay neuron. The response of the neuron to DBS was primarily dependent on the position and orientation of the axon with respect to the electrode and the stimulation parameters. Stimulation subthreshold for direct activation of TC relay neurons caused suppression of intrinsic firing (tonic or burst) activity during the stimulus train mediated by activation of presynaptic terminals. Suprathreshold stimulation caused suppression of intrinsic firing in the soma, but generated efferent output at the stimulus frequency in the axon. This independence of firing in the cell body and axon resolves the apparently contradictory experimental results on the effects of DBS. In turn, the results of this study support the hypothesis of stimulation-induced modulation of pathological network activity as a therapeutic mechanism of DBS.

Action Potentials↗

PubMed2002

Modeling the excitability of mammalian nerve fibers: influence of afterpotentials on the recovery cycle.

Human nerve fibers exhibit a distinct pattern of threshold fluctuation following a single action potential known as the recovery cycle. We developed geometrically and electrically accurate models of mammalian motor nerve fibers to gain insight into the biophysical mechanisms that underlie the changes in axonal excitability and regulate the recovery cycle. The models developed in this study incorporated a double cable structure, with explicit representation of the nodes of Ranvier, paranodal, and internodal sections of the axon as well as a finite impedance myelin sheath. These models were able to reproduce a wide range of experimental data on the excitation properties of mammalian myelinated nerve fibers. The combination of an accurate representation of the ion channels at the node (based on experimental studies of human, cat, and rat) and matching the geometry of the paranode, internode, and myelin to measured morphology (necessitating the double cable representation) were needed to match the model behavior to the experimental data. Following an action potential, the models generated both depolarizing (DAP) and hyperpolarizing (AHP) afterpotentials. The model results support the hypothesis that both active (persistent Na(+) channel activation) and passive (discharging of the internodal axolemma through the paranodal seal) mechanisms contributed to the DAP, while the AHP was generated solely through active (slow K(+) channel activation) mechanisms. The recovery cycle of the fiber was dependent on the DAP and AHP, as well as the time constant of activation and inactivation of the fast Na(+) conductance. We propose that experimentally documented differences in the action potential shape, strength-duration relationship, and the recovery cycle of motor and sensory nerve fibers can be attributed to kinetic differences in their nodal Na(+) conductances.

Action Potentials↗

PubMed2002

Extracellular stimulation of central neurons: influence of stimulus waveform and frequency on neuronal output.

The objective of this project was to examine the influence of stimulus waveform and frequency on extracellular stimulation of neurons with their cell bodies near the electrode (local cells) and fibers of passage in the CNS. Detailed computer-based models of CNS cells and axons were developed that accurately reproduced the dynamic firing properties of mammalian motoneurons including afterpotential shape, spike-frequency adaptation, and firing frequency as a function of stimulus amplitude. The neuron models were coupled to a three-dimensional finite element model of the spinal cord that solved for the potentials generated in the tissue medium by an extracellular electrode. Extracellular stimulation of the CNS with symmetrical charge balanced biphasic stimuli resulted in activation of fibers of passage, axon terminals, and local cells around the electrode at similar thresholds. While high stimulus frequencies enhanced activation of fibers of passage, a much more robust technique to achieve selective activation of targeted neuronal populations was via alterations in the stimulus waveform. Asymmetrical charge-balanced biphasic stimuli, consisting of a long-duration low-amplitude cathodic prepulse phase followed by a short-duration high-amplitude anodic stimulus phase, enabled selective activation of local cells. Conversely, an anodic prepulse phase followed by a cathodic stimulus phase enabled selective activation of fibers of passage. The threshold for activation of axon terminals in the vicinity of the electrode was lower than the threshold for direct activation of local cells, independent of the stimulus waveform. As a result, stimulation induced trans-synaptic influences (indirect depolarization/hyperpolarization) on local cells altered their neural output, and this indirect effect was dependent on stimulus frequency. If the indirect activation of local cells was inhibitory, there was little effect on the stimulation induced neural output of the local cells. However, if the indirect activation of the local cells was excitatory, attempts to activate selectively fibers of passage over local cells was limited. These outcomes provide a biophysical basis for understanding frequency-dependent outputs during CNS stimulation and provide useful tools for selective stimulation of the CNS.

Animals↗

PubMed2002

Uncovering the mechanisms of deep brain stimulation for Parkinson's disease through functional imaging, neural recording, and neural modeling.

High-frequency deep brain stimulation (DBS) of the thalamus or basal ganglia represents an effective clinical technique for the treatment of several medically refractory movement disorders, including Parkinson's disease. However, understanding of the mechanisms of action of DBS remains elusive. The goal of this review is to address our understanding of the effects of high-frequency stimulation within the central nervous system based on results from functional imaging, neural recording, and neural modeling experiments. Using these results, we address the main hypotheses on the mechanisms of action of DBS and conclude that stimulation-induced desynchronization of network oscillations represents the hypothesis that best explains the presently available data.

Basal Ganglia↗

PubMedDate not supplied

How does deep brain stimulation work? Present understanding and future questions.

High-frequency deep brain stimulation (DBS) of the thalamus or basal ganglia represents an effective clinical technique for the treatment of several medically refractory movement disorders (e.g., Parkinson's disease, essential tremor, and dystonia). In addition, new clinical applications of DBS for other neurologic and psychiatric disorders (e.g., epilepsy and obsessive-compulsive disorder) have been vaulted forward. Although DBS has been effective in the treatment of movement disorders and is rapidly being explored for the treatment of other neurologic disorders, the scientific understanding of its mechanisms of action remains unclear and continues to be debated in the scientific community. Optimization of DBS technology for present and future therapeutic applications will depend on identification of the therapeutic mechanism(s) of action. The goal of this review is to address the present knowledge of the effects of high frequency stimulation within the central nervous system and comment on the functional implications of this knowledge for uncovering the mechanism(s) of DBS. Four general hypotheses have been developed to explain the mechanism(s) of DBS: depolarization blockade, synaptic inhibition, synaptic depression, and stimulation-induced modulation of pathologic network activity. Using the results from microdialysis, neural recording, functional imaging, and neural modeling experiments, the authors address the main hypotheses and attempt to reconcile what have been considered conflicting results from different research modalities.

Basal Ganglia↗