John J. Hopfield

Professor Hopfield's research is chiefly concerned with the quantitative relation between structure and function in biology. The essential features of many aspects of biology can often be stated in terms of dynamical equations or chemical kinetics or equilibria, and thus reduced to physical terms. One then tries to understand how such a quantitative view produces the interesting and relevant biological properties of the system. For such an understanding to be useful and convincing, it must be quantitatively testable and should relate to a broad range of experiments of different types.

The major focus of this research at present is understanding the "computations" of neurobiology and the relation of such computations to those of physical electronic circuits. Mathematical models representing interactions of large number of model neurons or amplifiers are studied analytically and by simulations. These models emphasize the large connectivity, analog response, re-entrant connections, time dynamics, and adaptation (learning) characteristics of biological neural networks. Aspects of associative memory and collective computation emerge from such networks. The relations between the networks and biological tasks such as olfaction or recognition of time-dependent sequences are currently under study. The connection between such neural network ideas, difficult real-world problems such as character or speech recognition and vector quantization, and possible implementations of physical networks in electronics or optics, is also explored.

Electron transfers between biological molecules are central to oxidative phosphorylation and to the charge separation process in photosynthesis. These transfers must be specific; must, by some sequence of events, transfer electrons across a membrane; and must be coupled to useful chemical processes. Work on this process has included a theory that relates the site separation, transfer rate, and new superweak near-IR optical absorption bands; novel optical experiments discovering these bands; and a joint research effort with Professor Dervan's group to synthesize and study model systems which are analogs to the charge separation system used in photosynthesis.

Excerpt from 1987 Division faculty profiles.