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Bruce W. Knight, B.A.

Laboratory of Biophysics

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Faculty Bio

Bruce Knight

Everything we see is the result of light-induced patterns of electrical activity in the nerve networks of the retina and brain. What we see, however, is processed into an intelligible form by complex transformations within these networks. Mr. Knight works to develop a description of these networks in mathematical equations that will allow scientists to predict how the system will respond to specific visual patterns.

Mr. Knight and his colleagues study the visual part of the central nervous system, where they apply technology and theoretical means refined in their own laboratory in an effort to understand how the nervous system processes input information. Mr. Knight is specifically interested in the broad multicellular interactions among biophysical processes, which individually lie at the subcellular level. His laboratory’s efforts demand the conjoined development of experimental procedures that induce and record detailed neural responses and theoretical tools, including dynamical equations and computer simulation, that may then describe those neural responses quantitatively. Because the visual sense provides unique opportunities for highly structured input, their efforts focus on the visual part of the central nervous system, particularly that of humans and those of other vertebrates whose visual systems share key features of evolutionary kinship with humans.

Vision occurs when a stimulus — moving patterns of colored light, for example — arrives from the external visual world and induces dynamical patterns of electrical activity in a sequence of neural processing networks that start with the retina, which is specialized brain tissue, and continue into the brain. At each step, profound signal transformations occur that ultimately reduce the input to a form useful for action. Mr. Knight and his colleagues study that process with computer-generated stimuli, including modified natural-scene movies, designed by theoretical considerations that facilitate the interpretation of response features in terms of the responding system’s predictive dynamical laws. Their data include single-cell recordings from identified nerve cells of anesthetized animals, overall stimulus-evoked potentials in experimental animals and in humans and direct quantitative reports by human observers.

The lab’s emphasis has been on the retina, the primary visual cortex and the lateral geniculate nucleus, which is a processing network between the retina and the cortex. Members of Mr. Knight’s laboratory have been some of the principal contributors to our emerging understanding of the dynamics of the cat retina, which shows numerous dynamical features that prove typical of many vertebrates. Recent results with primate retinas from both monkeys and humans reveal not only cat-like cells, but a major additional interacting population with novel dynamical properties.

Researchers in Mr. Knight’s lab are currently investigating the dynamics of so-called relay neurons in the cat lateral geniculate nucleus via a technique they have developed that allows simultaneous electrical recording of both input and output nerve impulses in response to detailed computer-generated stimuli. They have shown that these cells can sculpt their throughput information in a manner much richer than their name would imply, and that response characteristics can be strongly modulated by nonretinal inputs from other brain regions.

Recent detailed analysis of responses of retinal ganglion cells to time-dependent naturalistic stimuli reveals that they may be classified within a special subset of neuron designs that might be descriptively called “faithful copy neurons.” A population of such neurons produces an aggregate firing rate that far better mimics its neural input than would different choices of neuron design. The way a network of such neurons behaves depends critically on the nature of interconnections and only insensitively on variations in the dynamics of the individual neurons. The generality of this feature and its implications for network design are currently under study.

Recently, Mr. Knight’s associates have been able to record simultaneously from numerous cells in the lateral geniculate nucleus. The responses of these cells naturally classify them into several response categories. By the creation of a new data analysis technique, it has proven possible to quantitatively measure the rate of information transfer through a group of such cells and also to measure the degree to which information transmitted by different cell groups is independent or redundant. 


Mr. Knight received his B.A. in physics and mathematics from Dartmouth College in 1952. He joined Rockefeller in 1961 as an affiliate, after academic appointments at Cornell University and Los Alamos National Laboratory. In 1973 he became a tenured associate professor. He was named head of the Laboratory of Biophysics in 1986 and was promoted to full professor in 1988.

Mr. Knight is a faculty member in the David Rockefeller Graduate Program and the Tri-Institutional M.D.-Ph.D. Program.

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