Franklin R. Amthor, Ph.D.
Primary Department Affiliation: Psychology
Primary Research Area: Sensory coding in retinal ganglion cells
Retinal synaptic mechanisms and central projections
Systems Neuroscience ,Vision, and Artificial Intelligence
Visual Prostheses for the blind
Department of Psychology, UAB (primary appointment)
Dept. of Biomedical Engineering, UAB (secondary appointment)
Dept. of Vision Sciences, School of Optometry, UAB (secondary appointment)
Dept. of Neurobiology, UAB (secondary appointment)
Vision Science Research Center (secondary appointment)
EDUCATION and TRAINING:
1979-1981 NIH Postdoctoral Research Fellow, School of Optometry, UAB
1979 Ph.D. Biomedical Engineering; Duke University, Durham, N.C.
Dissertation: Some Quantitative Characteristics of the Responses
of Frog Retinal Ganglion Cells
Advisor: Myron L. Wolbarsht, Ph.D.
Committee: Drs. Irving Diamond, James McElhaney, Lorne Mendell
Olaf vonRamm, Howard Wachtel
Support: FDA Research Assistantship and NIGMS-NIH
1971 B.S. Bioelectronic Engineering; Cornell University, Ithaca, N.Y.
Electrical engineering major with emphasis on applications to neurophysiology and artificial intelligence.
James Vick Scholar (full tuition scholarship)
1967 Graduated Trinity High School; Louisville, Kentucky
National Merit Semifinalist
Kentucky State Debate Champion (National Forensic League)
Biological and Artificial Intelligence (graduate level neuroscience, computer science, psychology, biomedical engineering; advanced undergraduate psychology and computer science). Courses on sensory coding and biological information processing in natural and artificial neural networks (such as Perceptrons, Kohonen nets, Grossberg Adaptive Resonant nets, Neocognitron, Edelman's Darwin nets), with particular emphasis on models of visual processing.
Sensation & Perception (upper level undergraduates). Coursemaster for Psychology Dept. course on sensation and perception which is taught at least once a year.
Behavioral Neuroscience (graduate students). Coursemaster and organizer for mandatory entry level course for all entering Behavioral Neuroscience (Psychology) graduate students.
Vision Sciences, School (Optometry students). Teaching involved basic optic principles, including function of various types of lenses, lens aberrations, physiological optics of the eye, and how patients are refracted and optically corrected with glasses and contact lenses.
Cognitive Neuroscience (Graduate Neuroscience). Originated and taught basic course on cognitive neuroscience as part of Cognitive Science and Behavioral Neuroscience Programs at UAB.
Electronics for neuroscientists and basic electronic circuits. (Graduate Neuroscience). Responsible for teaching basic electronic principles necessary for understanding activity in neural dendrites and axons. Taught basic electronic device and circuit principles as needed to understand operation of equipment used by electrophysiologists and other neuroscientists.
RESEARCH INTERESTS AND GOALS:
My early training in electrical engineering at Cornell University evolved into an interest in artificial neural nets like the Perceptron, which were developed to solve visual perception problems. I am particularly interested in how complex behavior emerges in the CNS via neural computations such as those that can be investigated in the retina. To date, little is known about how biological neural systems actually compute anything interesting. One place in the central nervous system that is computationally very interesting is the retina, because retinal ganglion cells are the first locus in the visual system of highly specific and nonlinear analyses such as motion and directional selectivity.
Complex response properties of retinal ganglion cells clearly involve interactions between bipolar and amacrine cell inputs to the ganglion cell dendritic arborization, and integrative properties of the ganglion cell dendritic tree itself. However, despite the importance of the ganglion cell dendritic morphology in their function, the morphologies of most mammalian retinal ganglion cells having complex response properties were unknown as little as ten years ago. My first major research effort during the last ten years has been to identify, by intracellular recording and staining, all the major ganglion cell classes in a mammalian retina (rabbit), including directionally selective, orientation-selective and edge-detecting ganglion cells. My colleagues and I have shown that the morphologies of different physiological classes of rabbit retinal ganglion cells are distinct, and typically associated with important physiological properties of each class. More recently I have shown that the dendritic trees of some retinal ganglion cells can be described as having a fractal dimension, corresponding to its need to fill two dimensional space.
My current research, supported by the National Eye Institute, seeks to determine how the entire ensemble of mammalian retinal ganglion cells apportions and codes information about the visual environment for transmission to the brain. I am particularly interested in how the temporal coherence of firing among nearby ganglion cells may help "bind" or code aspects of the visual input beyond the firing rate of any one cell by itself. I am also investigating the retinal circuitry and mechanisms underlying complex receptive field properties, and determining where in the brain each type of retinal ganglion cell projects, and what, therefore, is its role is in various aspects of visual acuity and perception. Most recently, I have developed the ability to optically image the responses of many neurons simultaneously in an isolated retina preparation, and will be using this technique to simultaneously study the responses of a large portion of the retinal network to visual stimulation.
I have previously been supported by the Sloan Foundation, and the Office of Naval Research to investigate the computational aspects of the mechanism of directional selectivity in retina. Directional selectivity is particularly robust in the On-Off directionally selective ganglion cells of the rabbit retina, being independent of object contrast, shape and velocity. I am using linear and nonlinear analyses of the responses to complex stimuli, in conjunction with electrotonic models of ganglion cell dendritic trees, to test biophysical hypotheses about the synaptic mechanisms and integrative properties underlying the nonlinear selectivity for direction of motion. A goal is to relate these biophysical properties to a computational algorithm for direction of motion in sufficient detail to synthesize the function.
My long term interests include research on several kinds of artificial neural nets that function in a more biophysically realistic manner than those currently in vogue. I also am interested in biomedical instrumentation relevant to visual and other neural prostheses, particularly sensory protheses for the blind, and for diagnosis of eye and visual function disease.