Nicholas Carnevale, MD/PhD

Some of my recent accomplishments and ongoing projects include:

* Developing a theoretical basis for predicting the outcome of a proposed cellular mechanism of learning. Tsai, K.Y., Carnevale, N.T., and Brown, T.H. Hebbian learning is jointly controlled by electrotonic and input structure. Network 5:1-19, 1994.

* Creating and applying new approaches to the analysis and understanding of electrical signaling in real neurons.

One example is the electrotonic transformation, an intuitive, empirically-based method for deriving insight to the functional consequences of neuronal anatomy and biophysical properties.

Most recently we have applied the transformation to the study of the principal neurons in the rat hippocampus, and extended its use to the interpretation of electrotonic architecture in the context of the circuitry in which neurons are embedded

Tsai, K.Y., Carnevale, N.T., Claiborne, B.J., and Brown, T.H. Efficient mapping from neuroanatomical to electrotonic space. Network 5:21-46, 1994.

Carnevale, N.T., Tsai, K.Y., Claiborne, B.J., and Brown, T.H. The electrotonic transformation: a tool for relating neuronal form to function. In: Advances in Neural Information Processing Systems, vol. 7, edited by Tesauro, G., Touretzky, D.S., and Leen, T.K. Cambridge, MA, MIT Press, 1995, p. 69-76. Preprint viewable and downloadable.

O'Boyle, M.P., Carnevale, N.T., Claiborne, B.J., and Brown, T.H. A new graphical approach for visualizing the relationship between anatomical and electrotonic structure. In: Computational Neuroscience: Trends in Research 1995, edited by J.M. Bower. San Diego: Academic Press, 1996, p. 423-428. Preprint available.

Carnevale, N.T., Tsai, K.Y., Claiborne, B.J., and Brown, T.H. Comparative electrotonic analysis of three classes of rat hippocampal neurons. J. Neurophysiol. 78:703-720, 1997.

Carnevale, N.T., O'Boyle, M.P., and Claiborne, B.J. Dendritic branching compensates for synaptic attenuation in granule cells of the rat dentate gyrus. Neuroscience Society Abstracts 24:1814, 1998.

* Collaborating with Michael Hines and John Moore in the support and enhancement of NEURON:

One practical outcome of this collaboration has been porting this sophisticated simulation environment from UNIX / Xwindows to MS-Windows and the Macintosh.

This put the leading software package for empirically-based modeling of individual neurons and networks of neurons within reach of everyone who is engaged in neuroscience research and teaching.

Hines, M. and Carnevale, N.T. Computer modeling methods for neurons. In: The Handbook of Brain Theory and Neural Networks, edited by M.A. Arbib. Cambridge, MA: MIT Press, 1995, p. 226-230. Preprint available as arbib.ps.Z, (a compressed PostScript file for ghostview) and arbib.zip (a pkzipped pdf file for Adobe Acrobat).

Carnevale, N.T., Tsai, K.Y., and Hines, M.L. The Electrotonic Workbench Neuroscience Society Abstracts 22:1741, 1996. Poster viewable in HTML format. Hines, M.L. and Carnevale, N.T. The NEURON simulation environment. Neural Computation 9:1179-1209, 1997. Preprint viewable and downloadable.

* Producing and directing short courses on NEURON that have been presented at Yale, annual meetings of the Society for Neuroscience, and the San Diego Supercomputer Center. Plans are now under way for future offerings of these courses plus new courses on related topics--see http://www.neuron.yale.edu/neuron/courses.html

* Developing new courses for undergraduate and graduate students that use simulation exercises implemented with NEURON to facilitate learning the physiology of excitable cells (see http://www.neuron.yale.edu/neuron/edu/nrnlab.htm and http://www.neuron.yale.edu/neuron/classes/445b/announce.htm ).

* A project to create a published set of laboratory simulation exercises, with an accompanying manual, that will advance neuroscience education by providing an intensive, interactive exploration of the processes that underlie neuronal function. More information about this NSF-supported collaboration with David Jaffe and Michael Hines is posted at http://www.neuron.yale.edu/neuron/edu/nrnlab.htm