Alireza Ghahari

A NEURON-BASED TIME-OPTIMAL CONTROLLER OF HORIZONTAL SACCADIC EYE MOVEMENTS

A neural network model of biophysical neurons in the midbrain for controlling oculomotor muscles during horizontal human saccades is presented. Neural circuitry that includes omnipause neuron, premotor excitatory and inhibitory burst neurons, long lead burst neuron, tonic neuron, interneuron, abducens nucleus and oculomotor nucleus is developed to investigate saccade dynamics. The final motoneuronal signals drive a time-optimal controller that stimulates a linear homeomorphic model of the oculomotor plant. To our knowledge, this is the first report on modeling the neural circuits at both premotor and motor stages of neural activity in saccadic systems.

Integrated model-based and data-driven fault detection and diagnosis approach for an automotive electric power steering system

Integrity of electric power steering system is vital to vehicle handling and driving performance. Advances in electric power steering (EPS) system have increased complexity in detecting and isolating faults. In this paper, we propose a hybrid model-based and data-driven approach to fault detection and diagnosis (FDD) in an EPS system. We develop a physics-based model of an EPS system, conduct fault injection experiments to derive fault-sensor measurement dependencies, and investigate various FDD schemes to detect and isolate the faults. Finally, we use an SVM regression technique to estimate the severity of faults.

A Physiological Neural Controller of a Muscle Fiber Oculomotor Plant in Horizontal Monkey Saccades

A neural network model of biophysical neurons in the midbrain is presented to drive a muscle fiber oculomotor plant during horizontal monkey saccades. Neural circuitry, including omnipause neuron, premotor excitatory and inhibitory burst neurons, long lead burst neuron, tonic neuron, interneuron, abducens nucleus, and oculomotor nucleus, is developed to examine saccade dynamics. The time-optimal control strategy by realization of agonist and antagonist controller models is investigated. In consequence, each agonist muscle fiber is stimulated by an agonist neuron, while an antagonist muscle fiber is unstimulated by a pause and step from the antagonist neuron. It is concluded that the neural network is constrained by a minimum duration of the agonist pulse and that the most dominant factor in determining the saccade magnitude is the number of active neurons for the small saccades. For the large saccades, however, the duration of agonist burst firing significantly affects the control of saccades. The proposed saccadic circuitry establishes a complete model of saccade generation since it not only includes the neural circuits at both the premotor and motor stages of the saccade generator, but also uses a time-optimal controller to yield the desired saccade magnitude.

Models of Horizontal Eye Movements:Part 4, A Multiscale Neuron and Muscle Fiber-Based Linear Saccade Model

Abstract There are five different types of eye movements: saccades, smooth pursuit, vestibular ocular eye movements, optokinetic eye movements, and vergence eye movements. The purpose of this book series is focused primarily on mathematical models of the horizontal saccadic eye movement system and the smooth pursuit system, rather than on how visual information is processed. In Part 1, early models of saccades and smooth pursuit are presented. A number of oculomotor plant models are described here beginning with the Westheimer model published in 1954, and up through our 1995 model involving a 4th order oculomotor plant model. In Part 2, a 2009 version of a state-of-the-art model is presented for horizontal saccades that is 3rd-order and linear, and controlled by a physiologically based time-optimal neural network. Part 3 describes a model of the saccade system, focusing on the neural network. It presents a neural network model of biophysical neurons in the midbrain for controlling oculomotor muscles durin...

Characteristics of Auditory and Visual Elicited Saccades

Saccadic eye movements in response to visual stimuli (V-saccade), auditory stimuli (A-saccade) and auditory-visual stimuli (AV-saccade) were recorded and analyzed. Human saccade data was collected using a SMI Hi-Speed eye tracking system and analyzed with a FORTRAN program, which was used to compute parameter estimates for a 1D saccadic eye movement model. Saccade characteristics were investigated, and the results of saccadic eye movements induced by the three different stimuli types were compared. The auditory-visual stimuli provided the greatest saccade accuracy. Peak velocity increased with increasing saccade amplitude as an exponential shape, while A-saccade showed lower values than V-saccade and AV-saccade. Duration was linearly proportional to saccade amplitude and it was longer for A-saccade. Latent period was relatively independent of saccade amplitude, but there was a significant reduction in AV-saccade.

Parameter Estimation of Auditory Saccades and Visual Saccades

Saccadic eye movements induced by visual stimuli (V-saccade), auditory stimuli (A-saccade) and auditory-visual stimuli (AV-saccade) were recorded and analyzed. SMI Hi-Speed eye tracking system was used to collect human saccade data. A FORTRAN program designed to compute parameter estimates for a 1D saccadic eye movement model was used for data analysis. The controller for saccadic eye movements in response to the three different types of stimuli were compared. System parameters of agonist pulse and post-inhibitory rebound burst (PIRB) in the antagonist motoneurons that caused post-saccade phenomena were also estimated. A-saccade exhibited lower agonist pulse magnitude and longer agonist pulse duration in large saccade amplitude. Antagonist onset delay was longer in A-saccade for saccades of the same size. There was a higher incidence of dynamic overshoot in A-saccade, while more in the abducting than adducting direction.

Development of a Neural Network Model for Controlling Horizontal Saccadic Eye Movements

We present a neural network that mimics the timing, firing rate and synchrony of the neuronal populations involved in the execution of horizontal saccades. While each involved neuron encompasses dendritic, axonal and synaptic components, the control mechanism of the saccades is also investigated in our study. The proposed saccade generator captures in essence the neural dynamics of the Hodgkin-Huxley model and a time-varying FitzHugh-Nagumo model. It evolves so that a burst discharge (pulse) from the agonist motoneurons and a pause in firing from antagonist motoneurons serve as the neural inputs to the agonist and antagonist muscles. The importance of simulating horizontal saccades is that it provides a framework for early diagnosis and treatment of injuries sustained during the mild traumatic brain injury.

Dynamic Characteristics of a New Three-Dimensional Linear Homeomorphic Saccade Model

A linear homeomorphic eye movement model that produces 3D saccadic eye movements consistent with anatomical and physiological evidence is introduced in this second part of a two-paper sequence. Central to the model is the implementation of a time-optimal neural control strategy involving six linear muscle models that faithfully represent the dynamic characteristics of 3D saccades. The muscle is modeled as a parallel combination of viscosity [Formula: see text] and series elasticity [Formula: see text], connected to the parallel combination of active-state tension generator [Formula: see text], viscosity element [Formula: see text], and length tension elastic element [Formula: see text]. The neural input for each muscle is separately maintained while the effective pulling direction is modulated by its respective pulley. The results demonstrate that a time-optimal, 2D commutative neural controller, together with the pulley system, actively functions to implement Listings law during both static and dynamic simulations and provide an excellent match with the experimental data. The parameters and neural input to the muscles are estimated using a time domain system identification technique from saccade data, with an excellent match between the model estimates and the data. A total of 20 horizontal, 5 vertical and 62 oblique saccades are analyzed.

Identification of Double-Step Saccades Elicited by Auditory Double-StepStimuli

Voluntary Saccadic eye movements can have visual, auditory, and auditory-visual bisensory origins. An experiment may be defined to examine how changing the type of sensory inputs and the number of them in a sequence reveals the type of the saccade generated by the oculomotor system; herein deemed single-step or double-step. This work reports design of experiments of double-step auditory stimuli played for human subjects, recording triggered saccadic eye movements, detecting each saccade, as well as estimating the saccade response characteristics, namely duration and latency. Based on the latency, then, it determines the type of the generated saccade by the subject through a clustering technique. We found that when doubling the amplitude of the two separate steps in double-step inputs, while keeping their duration unchanged, the number of triggered double-step saccades rises. The hindsight from this finding is useful because it can guide future stimulus designs to trigger specific saccade types in humans. Such designs, in turn, demystify the nature of dominant saccadic response as we explore the changes of sounds in any controlled environment.

Linear programming relaxations of a network flow problem with applications in machinery industry

Globalization of design, manufacturing and logistics has made the production-transportation problem (PTP) an important aspect of the supply chain optimization. This problem is usually formulated with piecewise linear concave cost functions for both production and transportation costs, and then solved using a mixed-integer programming (MIP) algorithm. This paper studies the application of three different relaxations of the MIP formulation of the PTP and compares their computational efficiencies. A cutting-plane algorithm is adapted to improve the computational efficiency. Although the relaxations tend to provide similar optimal costs, they differ significantly with respect to computational complexity.