Computational neuroscience

Charles Higgins, PhD, is an Associate Professor in the Department of Neuroscience with a dual appointment in Electrical Engineering at the University of Arizona where he is also leader of the Higgins Lab. Though he started his career as an electrical engineer, his fascination with the natural world has led him to study insect vision and visual processing, while also trying to meld together the worlds of robotics and biology. His research ranges from software simulations of brain circuits to interfacing live insect brains with robots, but his driving interest continues to be building truly intelligent machines.Dr. Higgins’ lab conducts research in areas that vary from computational neuroscience to biologically-inspired engineering. The unifying goal of all these projects is to understand the representations and computational architectures used by biological systems. These projects are conducted in close collaboration with neurobiology laboratories that perform anatomical, electrophysiological, and histological studies, mostly in insects.More than three years ago he captured news headlines when he and his lab team demonstrated a robot they built which was guided by the brain and eyes of a moth. The moth, immobilized inside a plastic tube, was mounted on a 6-inch-tall wheeled robot. When the moth moved its eyes to the right, the robot turned in that direction, proving brain-machine interaction. While the demonstration was effective, Charles soon went to work to overcome the difficulty the methodology presented in keeping the electrodes attached to the brain of the moth while the robot was in motion. This has led him to focus his work on another insect species.

The broad goal of research in our laboratory is to understand how inhibitory inputs influence neuronal signaling and sensory signal processing in the healthy and diabetic retina. Neurons in the brain receive inputs that are both excitatory, increasing neural activity, and inhibitory, decreasing neural activity. Inhibitory and excitatory inputs to neurons must be properly balanced and timed for correct neural signaling to occur. To study sensory inhibition we use the retina, a unique preparation which can be removed intact and can be activated physiologically, with light, in vitro. Thus using the retina as a model system, we can study how inhibitory synaptic physiology influences inhibition in visual processing. This intact system also allows us to determine the mechanisms of retinal damage in early diabetes. Keywords: neuroscience, diabetes, vision, electrophysiology, light

Dr Chen's areas of expertise include:Security informatics, security big data; smart and connected health, health analytics; data, text, web mining.Digital library, intelligent information retrieval, automatic categorization and classification, machine learning for IR, large-scale information analysis and visualization.Internet resource discovery, digital libraries, IR for large-scale scientific and business databases, customized IR, multilingual IR.Knowledge-based systems design, knowledge discovery in databases, hypertext systems, machine learning, neural networks computing, genetic algorithms, simulated annealing.Cognitive modeling, human-computer interactions, IR behaviors, human problem-solving process.