Modeling eye-head gaze shifts in multiple contexts without motor planning.

During gaze shifts, the eyes and head collaborate to rapidly capture a target (saccade) and fixate it. Accordingly, models of gaze shift control should embed both saccadic and fixation modes and a mechanism for switching between them. We demonstrate a model in which the eye and head platforms are driven by a shared gaze error signal. To limit the number of free parameters, we implement a model reduction approach in which steady-state cerebellar effects at each of their projection sites are lumped with the parameter of that site. The model topology is consistent with anatomy and neurophysiology, and can replicate eye-head responses observed in multiple experimental contexts: 1) observed gaze characteristics across species and subjects can emerge from this structure with minor parametric changes; 2) gaze can move to a goal while in the fixation mode; 3) ocular compensation for head perturbations during saccades could rely on vestibular-only cells in the vestibular nuclei with postulated projections to burst neurons; 4) two nonlinearities suffice, i.e., the experimentally-determined mapping of tectoreticular cells onto brain stem targets and the increased recruitment of the head for larger target eccentricities; 5) the effects of initial conditions on eye/head trajectories are due to neural circuit dynamics, not planning; and 6) "compensatory" ocular slow phases exist even after semicircular canal plugging, because of interconnections linking eye-head circuits. Our model structure also simulates classical vestibulo-ocular reflex and pursuit nystagmus, and provides novel neural circuit and behavioral predictions, notably that both eye-head coordination and segmental limb coordination are possible without trajectory planning.

Vestibular Compensation in Unilateral Patients Often Causes Both Gain and Time Constant Asymmetries in the VOR.

The vestibulo-ocular reflex (VOR) is essential in our daily life to stabilize retinal images during head movements. Balanced vestibular functionality secures optimal reflex performance which otherwise can be distorted by peripheral vestibular lesions. Luckily, vestibular compensation in different neuronal sites restores VOR function to some extent over time. Studying vestibular compensation gives insight into the possible mechanisms for plasticity in the brain. In this work, novel experimental analysis tools are employed to reevaluate the VOR characteristics following unilateral vestibular lesions and compensation. Our results suggest that following vestibular lesions, asymmetric performance of the VOR is not only limited to its gain. Vestibular compensation also causes asymmetric dynamics, i.e., different time constants for the VOR during leftward or rightward passive head rotation. Potential mechanisms for these experimental observations are provided using simulation studies.

Automatic Classification of the Vestibulo-Ocular Reflex Nystagmus: Integration of Data Clustering and System Identification.

The vestibulo-ocular reflex (VOR) plays an important role in our daily activities by enabling us to fixate on objects during head movements. Modeling and identification of the VOR improves our insight into the system behavior and improves diagnosis of various disorders. However, the switching nature of eye movements (nystagmus), including the VOR, makes dynamic analysis challenging. The first step in such analysis is to segment data into its subsystem responses (here slow and fast segment intervals). Misclassification of segments results in biased analysis of the system of interest. Here, we develop a novel three-step algorithm to classify the VOR data into slow and fast intervals automatically. The proposed algorithm is initialized using a K-means clustering method. The initial classification is then refined using system identification approaches and prediction error statistics. The performance of the algorithm is evaluated on simulated and experimental data. It is shown that the new algorithm performance is much improved over the previous methods, in terms of higher specificity.

Efferent Feedback in a Spinal-Like Controller: Reaching With Perturbations.

We use simulations of a controller that adopts a spinal-like network topology for goal-oriented reaching and assess its sensitivity to the dynamics of internal elements that allow context-independent performance. Such internal elements are often referred to as inverse or forward models of the periphery dynamics, depending on the proposed controller theory. Here, the "models" are used in a forward implementation, and we evaluate how the controller's performance would be affected by the nature of the model. For each point-to-point reaching motion experiment, we use forms of internal "efference models" (e.g., full mathematical representations of peripheral dynamics, simple spindle feedback, etc.) driven by motor reafference, then compare hand trajectories and hand path speeds in the presence or absence of external perturbations. It is demonstrated that a simple velocity-based model reduced the effects of dynamic perturbations by as much as 66%. In addition, the 2D hand trajectories varied from a biological reference by only 0.05 cm. Thus, the controller facilitated biological like motions while providing response to dynamic events which are omitted in earlier biomimetic controllers. This research suggests that these spinal-like systems are robust and tunable via gain-fields without the need of context dependent pre-planning.

Hybrid model of the context dependent vestibulo-ocular reflex: implications for vergence-version interactions.

The vestibulo-ocular reflex (VOR) is an involuntary eye movement evoked by head movements. It is also influenced by viewing distance. This paper presents a hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) in the dark. The model is based on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during fast and slow phase intervals of nystagmus. We implemented a viable switching strategy for the timing of nystagmus events to allow emulation of real nystagmus data. The performance of the hybrid model is evaluated with simulations, and results are consistent with experimental observations. The hybrid model replicates realistic AVOR nystagmus patterns during sinusoidal or step head rotations in the dark and during interactions with vergence, e.g., fixation distance. By simply assigning proper nonlinear neural computations at the premotor level, the model replicates all reported experimental observations. This work sheds light on potential underlying neural mechanisms driving the context dependent AVOR and explains contradictory results in the literature. Moreover, context-dependent behaviors in more complex motor systems could also rely on local nonlinear neural computations.

An adaptive spinal-like controller: tunable biomimetic behavior for a robotic limb.

BACKGROUND: Spinal-like regulators have recently been shown to support complex behavioral patterns during volitional goal-oriented reaching paradigms. We use an interpretation of the adaptive spinal-like controller as inspiration for the development of a controller for a robotic limb. It will be demonstrated that a simulated robot arm with linear actuators can achieve biological-like limb movements. In addition, it will be shown that programmability in the regulator enables independent spatial and temporal changes to be defined for movement tasks, downstream of central commands using sensory stimuli. The adaptive spinal-like controller is the first to demonstrate such behavior for complex motor behaviors in multi-joint limb movements. METHODS: The controller is evaluated using a simulated robotic apparatus and three goal-oriented reaching paradigms: 1) shaping of trajectory profiles during reaching; 2) sensitivity of trajectories to sudden perturbations; 3) reaching to a moving target. The experiments were designed to highlight complex motor tasks that are omitted in earlier studies, and important for the development of improved artificial limb control. RESULTS: In all three cases the controller was able to reach the targets without a priori planning of end-point or segmental motor trajectories. Instead, trajectory spatio-temporal dynamics evolve from properties of the controller architecture using the spatial error (vector distance to goal). Results show that curvature amplitude in hand trajectory paths are reduced by as much as 98% using simple gain scaling techniques, while adaptive network behavior allows the regulator to successfully adapt to perturbations and track a moving target. An important observation for this study is that all motions resemble human-like movements with non-linear muscles and complex joint mechanics. CONCLUSIONS: The controller shows that it can adapt to various behavioral contexts which are not included in previous biomimetic studies. The research supplements an earlier study by examining the tunability of the spinal-like controller for complex reaching tasks. This work is a step toward building more robust controllers for powered artificial limbs.

A Simplified Spinal-Like Controller Facilitates Muscle Synergies and Robust Reaching Motions.

We develop an adaptive controller for multi-joint, multi-muscle arm movements based on simplified spinal-like circuits found in the periphery, muscle synergies, and interpretations of gain-field projections from reach related neurons in the Superior Colliculus. The resulting innovation provides a highly robust sensory based controller that can be adapted to systems which require multi-muscle co-ordination. It provides human-like responses during perturbations elicited either internally or by the environment and for simple point-to-point reaching. We simulate limb motion and EMGs in Simulink using Virtual Muscle models and a variety of paradigms, including motion with external perturbations, and varying levels of antagonist muscle co-contractions. The results show that the system can exhibit smooth coordinated motions, without explicit kinematic or dynamic planning even in the presence of perturbations. In addition, we show by varying the level of muscle co-contractions from 0% to 40%, that the effects of external perturbations on joint trajectories can be reduced by up to 42%. The improved controller design is novel providing robust behavior during dynamic events and an automatic adaptive response from sensory-integration.

Identification of the vestibulo-ocular reflex dynamics.

The vestibulo-ocular reflex (VOR) plays an important role in our daily activities by enabling us to fixate on objects during head movements. Modeling and identification of the VOR improves our insight into the system behavior and helps in diagnosing various disorders. However, the switching nature of eye movements, including the VOR, makes the dynamic analysis challenging. In this work we are using integration of subspace and prediction error methods to analyze VOR dynamics. The performance of the method is evaluated using simulation studies and experimental data.

Analysis and modeling of noise in biomedical systems.

Noise characteristics play an important role in evaluating tools developed to study biomedical systems. Despite usual assumptions, noise in biomedical systems is often nonwhite or non-Gaussian. In this paper, we present a method to analyze the noise component of a biomedical system. We demonstrate the effectiveness of the method in the analysis of noise in voluntary ankle torque measured by a torque transducer and eye movements measured by electro-oculography (EOG).

Hybrid nonlinear model of the angular vestibulo-ocular reflex.

A hybrid nonlinear bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) is presented in this paper. The model relies on known interconnections between saccadic burst circuits in the brainstem and ocular premotor areas in the vestibular nuclei during slow and fast phase intervals. A viable switching strategy for the timing of nystagmus events is proposed. Simulations show that this hybrid model replicates AVOR nystagmus patterns that are observed in experimentally recorded data.

The horizontal angular vestibulo-ocular reflex: a nonlinear mechanism for context-dependent responses.

Studies of the vestibulo-ocular reflex (VOR) have revealed that this type of involuntary eye movement is influenced by viewing distance. This paper presents a bilateral model for the horizontal angular VOR in the dark based on realistic physiological mechanisms. It is shown that by assigning proper nonlinear neural computations at the premotor level, the model is capable of replicating target-distance-dependent VOR responses that are in agreement with geometrical requirements. Central premotor responses in the model are also shown to be consistent with experimental observations. Moreover, the model performance after simulated unilateral canal plugging also reproduces experimental observations, an emerging property. Such local nonlinear computations could similarly generate context-dependent behaviors in other more complex motor systems.

Human eye-head gaze shifts preserve their accuracy and spatiotemporal trajectory profiles despite long-duration torque perturbations that assist or oppose head motion.

Humans routinely use coordinated eye-head gaze saccades to rapidly and accurately redirect the line of sight (Land MF. Vis Neurosci 26: 51-62, 2009). With a fixed body, the gaze control system combines visual, vestibular, and neck proprioceptive sensory information and coordinates two moving platforms, the eyes and head. Classic engineering tools have investigated the structure of motor systems by testing their ability to compensate for perturbations. When a reaching movement of the hand is subjected to an unexpected force field of random direction and strength, the trajectory is deviated and its final position is inaccurate. Here, we found that the gaze control system behaves differently. We perturbed horizontal gaze shifts with long-duration torques applied to the head that unpredictably either assisted or opposed head motion and very significantly altered the intended head trajectory. We found, as others have with brief head perturbations, that gaze accuracy was preserved. Unexpectedly, we found also that the eye compensated well--with saccadic and rollback movements--for long-duration head perturbations such that resulting gaze trajectories remained close to that when the head was not perturbed. However, the ocular compensation was best when torques assisted, compared with opposed, head motion. If the vestibuloocular reflex (VOR) is suppressed during gaze shifts, as currently thought, what caused invariant gaze trajectories and accuracy, early eye-direction reversals, and asymmetric compensations? We propose three mechanisms: a gaze feedback loop that generates a gaze-position error signal; a vestibular-to-oculomotor signal that dissociates self-generated from passively imposed head motion; and a saturation element that limits orbital eye excursion.

The horizontal angular vestibulo-ocular reflex: a non-linear mechanism for context-dependent responses.

A bilateral model for the horizontal angular vestibulo-ocular reflex (AVOR) is presented in this paper. It is shown that by assigning proper non-linear neural computations at the premotor level, the model is capable of replicating target-distance dependent VOR responses. Moreover, the model behavior in case of sensory plugging is also consistent with reported experimental observations.

Automated off-line respiratory event detection for the study of postoperative apnea in infants.

Previously, we presented automated methods for thoraco-abdominal asynchrony estimation and movement artifact detection in respiratory inductance plethysmography (RIP) signals. This paper combines and improves these methods to give a method for the automated, off-line detection of pause, movement artifact, and asynchrony. Simulation studies demonstrated that the new combined method is accurate and robust in the presence of noise. The new procedure was successfully applied to cardiorespiratory signals acquired postoperatively from infants in the recovery room. A comparison of the events detected with the automated method to those visually scored by an expert clinician demonstrated a higher agreement (κ = 0.52) than that amongst several human scorers (κ = 0.31) in a clinical study . The method provides the following advantages: first, it is fully automated; second, it is more efficient than visual scoring; third, the analysis is repeatable and standardized; fourth, it provides greater agreement with an expert scorer compared to the agreement between trained scorers; fifth, it is amenable to online detection; and lastly, it is applicable to uncalibrated RIP signals. Examples of applications include respiratory monitoring of postsurgical patients and sleep studies.

GNL-HybELS: an algorithm to classify and identify VOR responses simultaneously.

The Vestibulo-Ocular Reflex (VOR) stabilizes the images of the world on the retinae when the head is in motion. Basic daily activities such as walking or driving depend on the proper functioning of this reflex. For several decades, scientists have developed methods to model and identify this system mathematically. However, traditional methods cannot analyze VOR data comprehensively because they disregard pieces of data (fast phases) which biases estimated reflex dynamics. Here we propose, for the first time, an automated tool to analyze entire VOR responses (slow and fast phases), without apriori classification of nystagmus segments.

Simultaneous identification of oculomotor subsystems using a hybrid system approach: introducing hybrid extended least squares.

The oculomotor system plays an essential role in our daily activities. It keeps the images of the world steady on the retina and enables us to track visual targets, or switch between targets. The modeling and identification of this system is key in the diagnosis and treatment of various diseases and lesions. Today, clinical protocols incorporate mathematical techniques to test the functionality of patients' oculomotor modalities through the analysis of the patients' responses to various stimuli. We have developed a new tool for simultaneous identification of the two modes of oculomotor responses, using hybrid extended least squares (HybELS), a novel identification method tailored for hybrid autoregressive moving average with exogenous input models. Previously, modified extended least squares (MELS) was proposed for the identification of vestibular nystagmus dynamics, one mode at a time. It involved searching for segment initial conditions (ICs) to avoid biased results. HybELS identifies both modes simultaneously, and does not require estimation of ICs. Results on experimental vestibuloocular reflex (VOR) data show that HybELS proves to be more robust than MELS with respect to identification of complex models. Furthermore, it is notably less computationally expensive than MELS. In the multi-input case, HybELS outperforms other tested methods, including MELS, both in parameter estimation and prediction error.

A nonlinear model of the neural integrator improves detection of deficits in the human VOR.

A nonlinear model has been proposed to describe the set-point-dependent characteristics of the neural integrator (NI) in the oculomotor system. It was shown to yield improved prediction of slow-phase eye position in the vestibulo-ocular reflex (VOR) of normal subjects, when compared to the classical linear model of the NI. In this paper, we compare the parameters of this nonlinear NI model fitted to VOR data from: 1) compensated subjects diagnosed with vestibular deficiencies such as vestibular neuronitis and Meniere's disease and 2) normal (symptom-free) subjects. The identified models exhibit more severe nonlinearity in VOR patients than the normal controls. Several of the identified parameters in patients unmask asymmetries and more context dependence in the NI and in the VOR gain that are consistent with the lesioned side and could serve to support detection of lesions even after compensation.

A Hybrid Extended Least Squares method (HybELS) for Vestibulo-Ocular Reflex identification.

The Vestibulo-Ocular Reflex (VOR) plays an essential role in the majority of daily activities by keeping the images of the world steady on the retina when either the environment or the body is moving. The modeling and identification of this system plays a key role in the diagnosis and treatment of various diseases and lesions, and their associated syndromes. Today, clinical protocols incorporate mathematical techniques for testing the functionality of patients' VORs through the analysis of the patients' responses to various stimuli. We have developed a new tool for simultaneous identification of the two modes of the horizontal VOR, using a novel algorithm. This algorithm, HybELS (Hybrid Extended Least Squares), is a regression-based identification method tailored for hybrid ARMAX (AutoRegressive Moving Average with eXogenous inputs) models, which can also be used for the identification of other neural systems. In the context of the VOR, MELS (Modified Extended Least Squares) has been proposed previously for the identification of vestibular nystagmus dynamics, one mode at a time. It also involved searching for segment initial conditions to avoid biased results. Our hybrid approach identifies the two modes simultaneously, and does not require estimation of initial conditions, since it takes advantage of state continuity in the transitions between fast and slow phases. The results on experimental VOR in the dark show that HybELS outperforms MELS in several aspects: It proves to be more robust than MELS with respect to the system order used for identification, while resulting in more accurate estimates in almost all contexts as well. Furthermore, due to the hybrid nature of the method, its calculations are algebraically more compact, and HybELS turns out to be much less computationally expensive than MELS.

Primate disconjugate eye movements during the horizontal AVOR in darkness and a plausible mechanism.

Disconjugate eye movements during the horizontal angular vestibulo-ocular reflex (AVOR) evoked in response to steps or pulses of head velocity have been previously reported in lateral eyed animals. In this study, we measured binocular responses to sustained sinusoidal and pseudo-random vestibular stimuli in yaw, delivered in darkness, in both human and monkey. The vestibular stimuli used in our experiments had peak velocities in the range of 120-200 degrees /s, frequencies in the range of 0.17-0.5 Hz, and durations between 60 and 75 s. Our results show a large vergence component to the AVOR response that systematically modulated with head velocity. We also examined our results for temporal-nasal preponderance in slow eye velocity. Although each subject showed some degree of directional preference, we did not find a systematically greater eye velocity for temporal-nasal direction across all subjects. Here, we present these findings and discuss that at least two possible sources could result in disconjugate eye movements during the horizontal rotational VOR in darkness: peripheral and central mechanisms.

Implications of gain modulation in brainstem circuits: VOR control system.

Gain modulation is believed to be a common integration mechanism employed by neurons to combine information from various sources. Although gain fields have been shown to exist in some cortical and subcortical areas of the brain, their existence has not been explored in the brainstem. In the present modeling study, we develop a physiologically relevant simplified model for the angular vestibulo-ocular reflex (VOR) to show that gain modulation could also be the underlying mechanism that modifies VOR function with sensorimotor context (i.e. concurrent eye positions and stimulus intensity). The resulting nonlinear model is further extended to generate both slow and quick phases of the VOR. Through simulation of the hybrid nonlinear model we show that disconjugate eye movements during the VOR are an inevitable consequence of the existence of such gain fields in the bilateral VOR pathway. Finally, we will explore the properties of the predicted disconjugate component. We will demonstrate that the apparent phase characteristics of the disconjugate response vary with the concurrent conjugate component.