Firing rate relationship in the saccade system neural pathway.

This paper describes the relationship among the structures of the brain involved in the control of the saccadic system. The eye position information is pre-processed by the cerebral cortex and then projected to the cerebellum where this signal is propagated to several structures that are in charge of the control and correction of the eye movement signal. Once this processing is completed, the output is propagated to the final neural stage (the motor neurons), and then to the Rectus and Oblique group of muscles of the eye. In our simulated model, the interaction of the different areas in this neural pathway and its feedback loops is shown through the correlation of the different firing rates of each structure, including background or spontaneous activity components. In order to improve portability the model is implemented with the Matrix Laboratory Language (MATLAB) and the Simulink toolbox.

Porting GENESIS to SIMULINK.

This paper describes the porting of the general simulation system (GENESIS) to Matrix Language Laboratory language (MatLab) SIMULINK, based in the cable theory to simulate the behavior of neurons. A graphic programming approach serves as ideal platform for teaching physiological modeling and neuroengineering courses. The ultimate goal of this project is to integrate all of the chemical, electrical, material, mechanical and neural interactions into a single model that can be viewed seamlessly from a molecular model to the large scale model. Integration of all interactions is not possible with GENESIS, but can be accomplished with SIMULINK.

A cerebellar neural network model for adaptative control of saccades implemented with MATLAB.

This paper describes the implementation of a neural network for the adaptative control of the saccadic system. The model shows the cerebellum plays an important role in the adaptive control of the saccadic gain. Using only eye position input through the granule cells, the cerebellum projects this signal to the other cerebellar structures and then to motor neurons responsible for the saccade. The generation of an adjustment signal occurs in the inferior olive as a result of the error sensory signal created by the open loop saccade system from propioceptive position inputs from the last eye movement generated by the network until the movement towards the target is completed. In addition, a memory component has been defined in the error system to achieve the adaptation. This neural network involves only the horizontal saccade component modeled with Matrix Laboratory language (MATLAB), in conjunction with the Simulink tool.

The Eye Tracker System--a system to measure and record saccadic eye movements.

The Eye Tracker System, built at the University of Connecticut at Storrs in the Biomedical Instrumentation Lab, consists of three separate and distinct units brought together as a whole system to measure saccades. A seven row, eleven columned array of LEDs mounted on five degree centers along a concave surface provides targeting for the Eye Tracker System wherein the subject eye follows a pattern of illuminated LEDs as determined by the experimenter. The target system is digitally driven by serial inputs from the Main Command System. Subject positioning is aided by the concave surface of the Target System. The System Console employs a multiple regression Operating System to predict Eye Position. Twenty-four channels utilizing the theory of Infrared Light Reflective Differentiation make measurements of the location of the eye. These optoelectronics are mounted in a specialized head-mounted transducer. The optoelectronics are mounted on the interior of a parabolic surface automatically aiming them towards the limbus. The transducer is styled after an ophthalmologist's test frames and is comfortably worn and adjustable in size to fit any subject. The Main Command System authored under G programming language (LabView) provides a graphic user interface (GUI) that controls the generation of the target pattern. The Main Command System also coordinates the programs that acquire all data, the regression algorithm for the real-time prediction of the eye position and the initial calibration of the system. In addition the application is able to save a retrieve data for further analysis.