Jennie Si’s Neuroscience Lab

•   2003-04, participated in Darpa funded project on Bio:Info:Micro at ASU, and conducted preliminary studies of rat’s binary decision and control mechanism based on motor cortical neural recordings. Special thanks to Jiping He, Daryl Kipke, and others on the Darpa project team for the opportunity, and later for Jiping He who allowed me to piggy-back on his lab before I had my own facility.

•   May 2005, bought a TDT RX5 neural recording system, the first equipment ever, in preparation for my own lab.

•   April 2006, moved into my own lab and started operation upon the opening of the ISTB1 building!!

•   IACUC protocol #06-878R approval on May 24, 2006

•   The 1^st implant in the motor cortex on August 16, 2006 (successful but no behavioral training, no recording either); the second implant in November (rat died of complication); the third successful implant in mid-December, 2006, rat is still generating data.

 

 

 

 

 

 

 

Major Timeline

Neuroscientists have made tremendous effort and achieved significant milestones in understanding some of the fundamental causal relationships of specific areas of the brain and their induced behaviors. Clearly, on the great steps towards understanding these cognitive systems was the first recording of head direction (HD) cells from a rat’s postsubiculum by Ranck. Since then, extensive research on HD cells has revealed where the cells are located, the local causal circuits involving the cells, and the origin of the head direction signal. However, no effort has yet been made to study how the HD information influences directionally sensitive motor movement control tasks. Similarly, extensive research using lesions, stimulation, neural recordings, and modeling has revealed the rather detailed anatomical structures of certain key brain areas involved in sensory motor integration.  These studies have detailed components of the sensory and motor systems and the pathways through which sensory systems ultimately act on motor neurons and muscles to produce movements. Up to now, the important aspects of sensory motor integration have mostly been treated using specific, goal directed movements (i.e., arm reaching to specified targets, finger tracing of specified trajectories) in almost all neurophysiological studies. The proposed research aims at developing and studying a specific set of sensory motor integration tasks through which we might gain fundamental understanding of cognition based navigational control. Specifically we propose to chronically record from the anterior thalamic nucleus (ATN) and the motor areas simultaneously in behaving rats. The proposed behavioral apparatus consists of a directionally controlled robotic vehicle which the rat can steer left, right, or straight ahead by pressing one of three corresponding levers. At the start of each trial, the vehicle is preset to move in a biased direction that requires a sequence of corrections from the rat’s lever control to reach a cued location. The objectives of the proposed work are two folds: a systematic, experimental study of the neural representation of the proposed sensory-motor integration mechanism, and an attempt at modeling and interpreting how neural information from sensory and motor areas interact and impact on one another in relation to the cognitive direction based navigation control.

Research Motivation & Focus

Why a Neuroscience Lab

I have always had an interest in studying large, complex, and interconnected systems. In the mid 90’s I had an opportunity to work closely with Motorola engineers to study optimization and control issues of the etching process, one of the important steps in semiconductor manufacturing. I was excited and thought I could study this problem for a long time given the complexity and the scale of the problem, especially that I have access to real production data of a large manufacturing plant which is just 5 miles away from my office. Unfortunately the plant closed out shortly after. I continued my studies in dynamic system optimization and control by addressing problems formulated under the principle of optimality, especially using neural network approximations as a means of reducing complexity. The opportunity brought about by the Darpa funded project renewed my interest of examining the motor cortical control mechanism. A while ago, I had a brief encounter with the problem by analyzing primate’s motor cortical data from Andy Schwartz’s lab. Even though the Darpa project ended, my interest continued on. Plus that I have been studying system properties and algorithms inspired by artificial neural systems. I thought it was worthwhile to find a few fundamentally important questions and start from bottom up, pursuing some great insight. The only way of doing this is to have a neuroscience lab and design a few good studies.