Faculty Research Page

Frank Werblin

Frank Werblin

Professor of the Graduate School Division of Neurobiology

Lab Homepage: http://mcb.berkeley.edu/labs/werblin/

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Research Interests

Our lab studies the neural circuitry in the retina that generates the representations of the visual world. The retina extracts about a dozen different abstractions, formed at different strata within the retina, and transmitted separately along the optic nerve. We are determining the structural and functional circuit components of these abstractions. One dominant component of this circuitry is "crossover inhibition" found at every stage of visual processing At early stages of visual processing the world is divided into neurons that signal increases, and others that signal decreases in contrast at each point in visual space. Subsequent to that division in activity, these two signal paths begin to interact, and they inhibit each other at every single stage of visual processing from retina to visual cortex. This fascinating "crossover inhibition" takes many forms....feedback, feed forward, feed across. It also serves many important signal processing functions including common mode rejection, non-linearity correction, drift compensation, and noise reduction. Our lab is studying the neural circuitry that mediates this crossover interaction in an attempt to learn the secrets embodied in this treasure trove of highly sophisticated biological technology.

Current Projects

Integrating the patterns of excitation and inhibition. The spiking retinal output is formed through the integration of excitation and inhibition at the ganglion cells. For natural scenes the spiking generated by ganglion cells is very sparse in both space and time. We are trying to understand the integrative rules that generate these very sparse representations, and we would like to understand how we manage to reconstruct the richness of the visual world at higher centers from these relatively meager visual cues.

Optical Recording of Retinal Activity. It is no easy matter to acquire the activity from large populations of neurons. One promising method is the use of optical recording techniques where large populations of cells are stained with a dye that changes its optical properties when neurons are active. These patterns can be read out with appropriate video cameras. The idea is to directly see each of the many "neural images" created in the retina through complex neuronal interactions.

Networks of Interacting interneurons. The patterns at the retinal output represent the cumulative effects of many simpler retinal networks at earlier stages of visual processing. We can study these networks directly using patch recording from a variety of cell types, still connected to their networks, in thin retinal slices, a technique pioneered in this laboratory. From these studies we are learning that many of the "movies" talk to one another to refine the set of abstractions.

Modeling retinal interactions. The dynamic interactions between thousands of individual cells, belonging to several different populations are difficult to think about without someinfrastructure upon which to place all the findings. We use the paradigm of the Cellular Neural Network, a supercomputer on a chip with architecture very similar to that of the retina: a massively parallel analog array processor. We can make the chip behave like each of the different elementary retinal networks, then allow these hypothetical networks to interact o generate each of the movies at the retinal output. Comparing the overall network response to measured activity serves as a test for our "hypothesis" about retinal connectivity. The feature detectors generated by implementation of our hypotheses form algorithms based upon retinal behavior that can be "exported" for use in practical systems such as the "camera" for a prosthetic vision device, or a detector of a variety of specific visual targets.

Introducing genetically-derived light-sensitivity to neurons in the blind retina. In many forms of blindness, the retinal photoreceptors are destroyed, but the inner retina remains intact. We are using virus vectors to introduce genes that generate photosensitive proteins into the membranes of the surviving retinal neurons in an effort to re-establish visual function in the retina.


Selected Publications

Werblin, F.S. (2010) Retinal Circuitry: Then and Now Handbook of Brain Microcircuits. Oxford University Press Gordon Shepherd, Ed.

Werblin, F.S. (2010) Introduction to Retinal Processing in Encyclopedia of the Eye. Elsevier

Werblin, F.S. (2010) Retinal Circuitry in Cellular Nanoscale Sensory Wave Computing. Chagaan Baatar, Wolfgang Porod, and Tamas Roska (Editors). Springer.

Differential Targeting of Optical Neuromodulators to Ganglion Cell Soma and Dendrites Allows Dynamic Control of Center-Surround Antagonism (in press)

Chen, X. & Werblin, F.S. (2010) Three forms of Spatial Temporal Feedforward Inhibition are Common to Different Ganglion Cell Types in Rabbit Retina. J Neurophysiol. 2010 Mar 10.

Russell, T. and Werblin, F.S. (2010) Retinal Synaptic Pathways Underlying the Response of the Rabbit Local Edge Detector (in press)

Molnar A, Hsueh HA, Roska B, Werblin FS. (2009) Crossover inhibition in the retina: circuitry that compensates for nonlinear rectifying synaptic transmission. J Comput Neurosci. 27: 569-90

Hsueh, H.A., Molnar, A. & Werblin, F.S. (2008) Amacrine-to-amacrine cell inhibition in the rabbit retina. J. Neurophysiol. 100(4): 2077-88.

Molnar A. & Werblin, F.S. (2007) Inhibitory feedback shapes bipolar cell responses in the rabbit retina. J. Neurophysiol. 98: 3423-3435.

Fried, S.I., Hsueh H.A., & Werblin F.S. (2006) A method for generating precise temporal patterns of retinal spiking using prosthetic stimulation. J Neurophysiol 95: 970-8.

Munch, T. A. and F. S. Werblin (2006). "Symmetric interactions within a homogeneous starburst cell network can lead to robust asymmetries in dendrites of starburst amacrine cells." J Neurophysiol 96(1): 471-7.

Roska, B., A. Molnar, et al. (2006). "Parallel processing in retinal ganglion cells: how integration of space-time patterns of excitation and inhibition form the spiking output." J Neurophysiol 95(6): 3810-22.

Fried, S.I., Munch, T.A. & Werblin, F.S. (2005) Directional selectivity is formed at multiple levels by laterally offset inhibition in the rabbit retina. Neuron 48: 117-127.

Werblin, F.S. & Roska, B. (2004) Parallel Visual Processing: A Tutorial of Retinal Function. Int. J. Bifurcation and Chaos 14: 83-852.

Last Updated 2010-03-11