Scott E. Cooper

Accuracy of planar reaching movements

This study examined the variability in movement end points in a task in which human subjects reached to targets in different locations on a horizontal surface. The primary purpose was to determine whether patterns in the variable errors would reveal the nature and origin of the coordinate system in which the movements were planned. Six subjects moved a hand-held cursor on a digitizing tablet. Target and cursor positions were displayed on a computer screen, and vision of the hand and arm was blocked. The screen cursor was blanked during movement to prevent visual corrections. The paths of the movements were straight and thus directions were largely specified at the onset of movement. The velocity profiles were bell-shaped, and peak velocities and accelerations were scaled to target distance, implying that movement extent was also programmed in advance of the movement. The spatial distributions of movement end points were elliptical in shape. The major axes of these ellipses were systematically oriented in the direction of hand movement with respect to its initial position. This was true for both fast and slow movements, as well as for pointing movements involving rotations of the wrist joint. Using principal components analysis to compute the axes of these ellipses, we found that the eccentricity of the elliptical dispersions was uniformly greater for small than for large movements: variability along the axis of movement, representing extent variability, increased markedly but nonlinearly with distance. Variability perpendicular to the direction of movement, which results from directional errors, was generally smaller than extent variability, but it increased in proportion to the extent of the movement. Therefore, directional variability, in angular terms, was constant and independent of distance. Because the patterns of variability were similar for both slow and fast movements, as well as for movements involving different joints, we conclude that they result largely from errors in the planning process. We also argue that they cannot be simply explained as consequences of the inertial properties of the limb. Rather they provide evidence for an organizing mechanism that moves the limb along a straight path. We further conclude that reaching movements are planned in a hand-centered coordinate system, with direction and extent of hand movement as the planned parameters. Since the factors which influence directional variability are independent of those that influence extent errors, we propose that these two variables can be separately specified by the brain.

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 Parkinsons 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.

Accuracy of planar reaching movements - II. Systematic extent errors resulting from inertial anisotropy

This study examines the source of directiondependent errors in movement extent made by human subjects in a reaching task. As in the preceding study, subjects were to move a cursor on a digitizing tablet to targets displayed on a computer monitor. Movements were made without concurrent visual feedback of cursor position, but movement paths were displayed on the monitor after the completion of each movement. We first examined horizontal hand movements made at waist level with the upper arm in a vertical orientation. Targets were located at five distances and two directions (30° and 150°) from one of two initial positions. Trajectory shapes were stereotyped, and movements to more distant targets had larger accelerations and velocities. Comparison of movements in the two directions showed that in the 30° direction responses were hypermetric, accelerations and velocities were larger, and movement times were shorter. Since movements in the 30° direction required less motion of the upper arm than movements in the 150° direction, we hypothesized that the differences in accuracy and acceleration reflected a failure to take into account the difference in total limb inertia in the two directions. To test this hypothesis we simulated the initial accelerations of a two-segment limb moving in the horizontal plane with the hand at shoulder level when a constant force was applied at the hand in each of 24 directions. We compared these simulated accelerations to ones produced by our subjects with their arms in the same position when they aimed movements to targets in the 24 directions and at equal distances from an initial position. The magnitudes of both simulated and actual accelerations were greatest in the two directions perpendicular to the forearm, where inertial resistance is least, and lowest for movements directed along the axis of the forearm. In all subjects, the directional variation in peak acceleration was similar to that predicted by the model and shifted in the same way when the initial position of the hand was displaced. The pattern of direction-dependent variations in initial acceleration did not depend on the speed of movement. It was also unchanged when subjects aimed their movements toward targets presented within the workspace on the tablet instead of on the computer monitor. These findings indicate that, in programming the magnitude of the initial force that will accelerate the hand, subjects do not fully compensate for direction-dependent differences in inertial resistance. The direction-dependent differences in peak acceleration were associated with systematic variations in movement extent in all subjects, but the variations in extent were proportionately smaller than those in acceleration. This compensation for inertial anisotropy, which differed in degree among subjects, was associated with changes in movement duration. The possible contributions of elastic properties of the musculoskeletal system and proprioceptive feed-back to the compensatory variations in movement time are discussed. The finding that the magnitude of the initial force that accelerates the hand is planned without regard to movement direction adds support for the hypothesis that extent and direction of an intended movement are planned independently. Furthermore, the lack of compensation for inertia in the acceleration of the simple reaching movements studied here suggests that they are planned by the central nervous system without explicit inverse kinematic and dynamic computations.

Primary Dystonia Is More Responsive than Secondary Dystonia to Pallidal Interventions: Outcome after Pallidotomy or Pallidal Deep Brain Stimulation

OBJECTIVEThe response of patients with dystonia to pallidal procedures is not well understood. In this study, we assessed the postoperative outcome of patients with primary and secondary dystonia undergoing pallidotomy or pallidal deep brain stimulation. METHODSFifteen patients with dystonia had pallidal surgery (lesions or deep brain stimulation). These included nine patients with primary dystonia (generalized and cervical dystonias) and six with secondary dystonia (generalized, segmental, and hemidystonias). There were nine male patients and six female patients. The mean age at onset was 21 years for primary dystonia and 18 years for secondary dystonia. The primary outcome measure was a Global Outcome Scale score for dystonia at 6 months after surgery. Other outcome measures were the Burke-Fahn-Marsden Dystonia Rating Scale and Toronto Western Spasmodic Torticollis Rating Scale scores. RESULTSThe mean Global Outcome Scale score at 6 months for patients with primary dystonia was 3 (improvement in both movement disorder and function). In contrast, patients with secondary dystonia had a mean score of 0.83 (mild or no improvement in movement disorder with no functional improvement). All patients with primary dystonia had normal brains by magnetic resonance imaging, whereas five of six patients with secondary dystonia had basal ganglia abnormalities on their magnetic resonance imaging scans. CONCLUSIONThis study indicates that primary dystonia responds much better than secondary dystonia to pallidal procedures. We could not distinguish a difference in efficacy between pallidotomy and pallidal deep brain stimulation. The presence of basal ganglia abnormalities on the preoperative magnetic resonance imaging scan is an indicator of a lesser response to pallidal interventions for dystonia.

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 Parkinsons 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.

Clinical response to varying the stimulus parameters in deep brain stimulation for essential tremor

Deep brain stimulation (DBS) of the ventral intermediate nucleus of the thalamus for essential tremor is sometimes limited by side effects. The mechanisms by which DBS alleviates tremor or causes side effects are unclear; thus, it is difficult to select stimulus parameters that maximize the width of the therapeutic window. The goal of this study was to quantify the impact on side effect intensity (SE), tremor amplitude, and the therapeutic window of varying stimulus parameters. Tremor amplitude and SE were recorded at 40 to 90 combinations of pulse width, frequency, and voltage across 14 thalami. Posterior variable inclusion probabilities indicated that frequency and voltage were the most important predictors of both SE and tremor amplitude. The amount of tremor suppression achieved at frequencies of 90 to 100 Hz was not different from that at 160 to 170 Hz. However, the width of the therapeutic window decreased significantly and power consumption increased as frequency was increased above 90 to 100 Hz. Improved understanding of the relationships between stimulus parameters and clinical responses may lead to improved techniques of stimulus parameter adjustment.

Probabilistic analysis of activation volumes generated during deep brain stimulation

Deep brain stimulation (DBS) is an established therapy for the treatment of Parkinsons disease (PD) and shows great promise for the treatment of several other disorders. However, while the clinical analysis of DBS has received great attention, a relative paucity of quantitative techniques exists to define the optimal surgical target and most effective stimulation protocol for a given disorder. In this study we describe a methodology that represents an evolutionary addition to the concept of a probabilistic brain atlas, which we call a probabilistic stimulation atlas (PSA). We outline steps to combine quantitative clinical outcome measures with advanced computational models of DBS to identify regions where stimulation-induced activation could provide the best therapeutic improvement on a per-symptom basis. While this methodology is relevant to any form of DBS, we present example results from subthalamic nucleus (STN) DBS for PD. We constructed patient-specific computer models of the volume of tissue activated (VTA) for 163 different stimulation parameter settings which were tested in six patients. We then assigned clinical outcome scores to each VTA and compiled all of the VTAs into a PSA to identify stimulation-induced activation targets that maximized therapeutic response with minimal side effects. The results suggest that selection of both electrode placement and clinical stimulation parameter settings could be tailored to the patients primary symptoms using patient-specific models and PSAs.

Amplitude- and Frequency-Dependent Changes in Neuronal Regularity Parallel Changes in Tremor With Thalamic Deep Brain Stimulation

The mechanisms by which deep brain stimulation (DBS) alleviates tremor remain unclear, but successful treatment can be achieved with properly selected frequency and amplitude. The clinical tremor response to thalamic DBS for essential tremor is dependent on the stimulation frequency and amplitude, and for high frequencies (ges90 Hz), increasing amplitude suppressed tremor, whereas for low frequencies (<60 Hz), increasing amplitude aggravated tremor. We studied the effects of stimulation frequency and amplitude on the output of a population of intrinsically active model neurons to test the hypothesis that regularization of neuronal firing patterns is responsible for the clinical effectiveness of DBS. The firing patterns of model thalamocortical neurons were dependent on stimulation frequency and amplitude in a manner similar to the clinical tremor response. Above a critical frequency, increasing amplitude reduced the coefficient of variation (CV) of the neuronal firing pattern, whereas for low frequencies, increasing the amplitude increased the CV of neuronal activity. The correlation between the changes in tremor and the changes in the C V of neuronal firing supports the hypothesis that regularization of neuronal firing pattern during DBS is one of the mechanisms underlying the suppression of tremor.

Predicting the effects of deep brain stimulation with diffusion tensor based electric field models

Deep brain stimulation (DBS) is an established therapy for the treatment of movement disorders, and has shown promising results for the treatment of a wide range of other neurological disorders. However, little is known about the mechanism of action of DBS or the volume of brain tissue affected by stimulation. We have developed methods that use anatomical and diffusion tensor MRI (DTI) data to predict the volume of tissue activated (VTA) during DBS. We co-register the imaging data with detailed finite element models of the brain and stimulating electrode to enable anatomically and electrically accurate predictions of the spread of stimulation. One critical component of the model is the DTI tensor field that is used to represent the 3-dimensionally anisotropic and inhomogeneous tissue conductivity. With this system we are able to fuse structural and functional information to study a relevant clinical problem: DBS of the subthalamic nucleus for the treatment of Parkinsons disease (PD). Our results show that inclusion of the tensor field in our model caused significant differences in the size and shape of the VTA when compared to a homogeneous, isotropic tissue volume. The magnitude of these differences was proportional to the stimulation voltage. Our model predictions are validated by comparing spread of predicted activation to observed effects of oculomotor nerve stimulation in a PD patient. In turn, the 3D tissue electrical properties of the brain play an important role in regulating the spread of neural activation generated by DBS.

A method to estimate the spatial extent of activation in thalamic deep brain stimulation

OBJECTIVEnThe goal of this study was to develop, evaluate, and apply a method to quantify the unknown spatial extent of activation in deep brain stimulation (DBS) of the ventral intermedius nucleus (Vim) of the thalamus.nnnMETHODSnThe amplitude-distance relationship and the threshold amplitudes to elicit clinical responses were combined to estimate the unknown amplitude-distance constant and the distance between the electrode and the border between the Vim and the ventrocaudal nucleus (Vc) of the thalamus. We tested the sensitivity of the method to errors in the input parameters, and subsequently applied the method to estimate the amplitude-distance constant from clinically-measured threshold amplitudes.nnnRESULTSnThe method enabled estimation of the amplitude-distance constant with a median squared error of 0.07-0.23V/mm2 and provided an estimate of the distance between the electrode and the Vc/Vim border with a median squared error of 0.01-0.04mm. Application of the method to clinically-measured threshold amplitudes to elicit paresthesias estimated the amplitude-distance constant to be 0.22V/mm2.nnnCONCLUSIONSnThe method enabled robust quantification of the spatial extent of activation in thalamic DBS and predicted that stimulation amplitudes of 1-3.5V would produce a mean effective radius of activation of 2.0-3.9mm.nnnSIGNIFICANCEnKnowing the spatial extent of activation may improve methods of electrode placement and stimulation parameter selection in DBS.