Computational Neuro Engineering a Key Subject at University of Florida

by James Cavuoto, editor

The Computational NeuroEngineering Laboratory at the University of Florida in Gainesville, FL has quickly garnered a reputation as a leading research institution in neural engineering. In large part, this is because of the stature of the laboratory’s founder and director, Jose Principe. Principe is well know to many researchers in the field because he serves as editor-in-chief of the journal IEEE Transactions on Biomedical Engineering. He has also authored a number of publications and presented papers at several key conferences in the field and is president elect of the International Neural Network Society.

The laboratory is part of the electrical and computer engineering department at the university, and also collaborates with the Evelyn F. and William L. McKnight Brain Institute of the University of Florida. Another neurotechnology partner of the laboratory is the Brain Dynamics Bioengineering Research Partnership (BRP). BRP’s mission is to develop an on-line, real-time automated seizure warning and prevention system for use by epileptic patients and their caregivers. The Partnership is funded by the National Institutes of Health (NIH) and brings together a multi-disciplinary group of research scientists who are pioneers in the areas of signal processing, optimization, hybrid VLSI and DSP computation neurophysiology, neuroanatomy, epilepsy, and neurosurgery.

Another key faculty member at the laboratory is associate professor John Harris, who heads the hybrid computation group, which is looking into neural/analog inspired computation. The group is building analog VLSI circuit models in order to gain a better understanding of neurobiological computation. Since analog circuits operate under many of the same power and communication restrictions imposed upon their biological counterparts, the researchers hope that the silicon models will provide insights into these biological information processing systems.

Harris believes that we cannot easily model detailed biological systems with analog VLSI since the two media differ significantly at their lowest levels, however, these silicon systems can provide insights into neurophysiological organization—especially for higher level-brain functions where models cannot realistically model every biological detail.

Still another research aim of the laboratory is biologically inspired nanolattice computers. The laboratory is looking for a computing architecture that can capture the essence of neuroprocessing models in terms of primitives whose implementations are possible with nascent nanotechnologies.

Finally, the laboratory is seeking to construct a “silicon olfactory cortex” that would perform pattern recognition that operates in accordance with the neurodynamics of the cerebral cortex, and that has the sensitivity, selectivity, adaptiveness, speed, and tolerance of noise that characterizes human sensation. The team is looking at several DARPA-funded applications of pattern recognition, such as biomimetic mine sensing (either with artificial noses or by sonar), automatic target recognition, and sensor fusion.

Other sponsors of laboratory research are the Office of Naval Research and the Oak Ridge National Laboratory.