Computational and Theoretical Neuroscience: From Synapse to Circuitry

[Publisher Link]  [Local Copy]
Boyden, E. S. (2000) Computational and Theoretical Neuroscience: From Synapse to Circuitry. National Institutes of Health/National Institute of Neurological Disorders and Stroke, Technical Report for Workshop of April 28, 2000.

The advent of ubiquitous computing brings us two universal and complementary scientific capabilities - data analysis and modeling. Taking full advantage of these capabilities requires new experimental methods and theoretical skill sets, but ultimately offers biologists the power to achieve deeper levels of understanding than otherwise imaginable. Genomic, biochemical, morphological, electrophysiological, and imaging data are accumulating at rates exceeding the capacity of manual analysis. Quantitative models of genetic, molecular, and neuronal networks are assuming increasing amounts of responsibility for clarifying how and why biological systems operate as they do. Ultimately the twin capabilities of analysis and modeling will provide a clearer picture of biology at a systems level, and coupled with inspired experimental design, they may resolve questions that are currently too complicated even to imagine. Perhaps even our most intricate neurological and psychiatric diseases, which are as yet unnamed, will one day be rendered trivial through our modeling efforts. In this workshop on April 28, 2000, many aspects of modeling were explored, and possible funding and policy initiatives of NIH and NINDS were suggested. In the following pages we interpret and summarize the principles and policies that came up during this workshop.