Neurophysiology Databases, Neural Networks, and Synaptic Plasticity

Neuroinformatics

One of the most exciting unsolved problems of biomedical science is how the cellular and network properties of individual neurons, and the information they convey, give rise to the complex behavior of the brain. This fundamental question is examined in the lab by synthesizing state-of-the-art neurobiology with informatics: the science of information underlying both brains and machines.

All our work is funded by the NIH, much of via the Human Brain Project, NIMH, and NINDS, with past support from these agencies and the NSF.

Our laboratory concentrates on a continuing multi-year initiative to develop networked databases of brain neurophysiology that will allow exploring two fundamental questions of neuroscience: neuronal identity and coding of neuronal signals. Our cortial neuron database includes somatosensory cortical neurons and characteristic neurophysiological data encapsulating these neurons' responses to specific stimuli.

The data--recordings from neurons in awake behaving brains--include metadata incorporating parameters used by neurophysiologists to describe recording methodology, stimulating paradigms, and electrophysiological responses. To make the database useful to brain neuroscientists, a suite of multiplatform tools supports acquisition, query, and visualization of single and multi-electrode spike train datasets. These tools allow integration of data characterizing responses of cortical neurons to complementary stimuli, synthesizing a unified understanding of brain information processing. With the resulting enhanced utilization of data, experiments can be coordinated among laboratories, conserving valuable and respected species. All data structures and methods defined in this project are designed to be generalizable to many electrophysiological studies in cortical and subcortical structures of the brain.

Our methodology includes development of object-oriented database schemas for neuronal data, as well as the use of Java, permitting databases to be accessible via the Web to any member of the international neuroscience community using any contemporary computer system, including Macintosh, linux or other flavors of UNIX, or MSWindows.

A new collaborative thrust will develop, implement, and apply parallelized computational algorithms to explore the information content of spike trains and other neuronal signals, towards an understanding of the neural coding underlying visual and somatosensory processing. This project brings to bear local and external collaborators, with local resources (our databases and 26-processor Beowulf array), to explore informational aspects of neural coding and processing. Via both user-specified and project-developed algorithms, we will enable analyses to be performed either on-the-fly during dataset submission, or on archived data, permitting post-hoc examination as well as searches for specific patterns of brain activity. A major goal is development of the new field of computational neuroinformatics.

The project coordinates the efforts of brain researchers, computer scientists, and mathematicians at Cornell and beyond. Our many collaborators aid development and testing of access and query methods and viewer tools and provide complementary physiological data from several techniques and preparations.

Neurophysiology

Believing strongly that informational, computational, or theoretical biology should never be divorced from experimental work, this thrust also continues my laboratory's long-standing interest in neural networks, their neuronal and synaptic components, and their emergent properties. Using techniques I developed and introduced for simultaneous voltage-clamping of multiple interconnected neurons, we will analyze the information carrying and processing capabilities of parallel channels formed by paired Aplysia neurons. These form a testbed, bridging the gap between the single neurons characteristic of invertebrates and the massively parallel columns and modules found in mammalian brains. Related experiments may test aspects of the fire-together, wire-together hypothesis. This work descends as well from studies of interneuronal organization begun 35 years ago in the laboratory of Eric R. Kandel.