Document Type

Dissertation

Date of Award

Spring 5-31-2014

Degree Name

Doctor of Philosophy in Biomedical Engineering - (Ph.D.)

Department

Biomedical Engineering

First Advisor

Richard A. Foulds

Second Advisor

Mesut Sahin

Third Advisor

Sergei Adamovich

Fourth Advisor

Joshua R. Berlin

Fifth Advisor

Tara L. Alvarez

Sixth Advisor

Eugene Tunik

Abstract

The main goal of this project is to develop a rodent model to study the central command signals generated in the brain and spinal cord for the control of motor function in the forearms. The nature of the central command signal has been debated for many decades with only limited progress. This thesis presents a project that investigated this problem using novel techniques. Rats are instrumented to record the control signals in their spinal cord while they are performing lever press task they are trained in. A haptic interface and wireless neural data amplifier system simultaneously collects dynamic and neural data.

Isometric force is predicted from force signal using a combination of time-frequency analysis, Principle component analysis and linear filters. Neural-force mapping obtained at one location are subsequently applied to isometric data recorded at other locations.

Prediction errors exhibited negative relationship with the isometric position at upper half of movement range. This suggests the presence of restorative forces which are consistent with positional feedback at spinal level. The animal also appears to become unstable in the lower half of their movement ranges, likely caused by a transition from bipedal to quadruped posture.

The presence of local feedback and ability for animals to plan postures that are unstable in absence of external forces suggest that descending signal is a reference trajectory planned using internal models. This has important consequences in design of neuroprosthetic actuators: Inverse dynamic models of patient limbs and local positional feedbacks can improve their performance.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.