Dr. Ranu Jung (jung@uky.edu)
Office: (859) 257-5931, Lab: (859) 323-5009, Fax: (859) 257-1856

Overview

The last decade of the twentieth century saw a tremendous growth in neurobiology, information technology, and microsystems engineering. These developments are merging to spawn new approaches to scientific study and engineering design. "Computational Neuroscience" and "Neural Engineering" are now complementing traditional neurophsyiological and engineering design approaches. Projects in our Experimental and Computational Neuroscience Laboratory (ECNL) are directed towards a) investigating the dynamics of normal and pathological neuromotor control and neuroplasticity through the combined use of experimental and computational neuroscience techniques and b) developing biomimetic and biohybrid living-hardware systems for motor control. We believe that an improved understanding of the nonlinear dynamics of the coordinating processes used by neurobiological systems will lead to better insight into the mechanisms that underlie sensorimotor deficits. Secondly, understanding features of biological control systems, some of which differ from the features of engineering control systems, will guide the development of new biologically-inspired methodologies for controlling processes in engineering systems (such as robot locomotion) and rehabilitation engineering systems (such as electrical stimulation systems for restoration of locomotor or respiratory function). Third, a better understanding of nervous system reorganization and function subsequent to neurotrauma (plasticity), will result in the design and development of improved neural interface devices for motor rehabilitation and therapy.

The primary challenges we face are:  real-time monitoring and control of spatially-distributed patterns of neural activity; designing and regulating the interface between implanted sensors/stimulators and neural tissue; analyzing and interpreting neurophysiological and biomechanical data that span multiple scales of organization; and designing practical adaptive control strategies that are based upon computational models of neural systems. Projects in ECNL provide an opportunity for examining the role of brain-spinal cord interactions in sensorimotor integration, for developing biomimetic and biohybrid living-hardware systems for motor control, and investigating spinal neural plasticity post neurotrauma. We are utilizing contemporary experimental techniques from neurophysiology and kinesiology and computational techniques from non-linear signal processing and dynamical systems theory to understand the dynamical nature of the brain-spinal cord interaction in mediating motor control. We study the swim motor behavior in lampreys and the walking motor behavior in rodents.  Quantitative analyses include kinematics of gait, analysis of EMGs, and time-frequency and wavelet analyses of extracellular and intracellular neural activity. We are merging the experimental and computational approaches in the design of hardware circuitry for the development of hybrid living-electronic hardware systems. We extensively use computational neuroscience models of the spinal motor pattern generator for understanding neuromotor control as well as in the development of biomimetic fixed-pattern and adaptive controllers. We are utilizing locomotor retraining therapies utilizing treadmill walking as well as functional neuromuscular stimulation to tap into spinal plasticity after neurotrauma, and we are developing in vivo magnetic resonance imaging techniques for non-invasive assessment of spinal neurotrauma, recovery and repair.