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Tatyana Sharpee

Tatyana Sharpee, PhD

Assistant Professor

Contact Information

The Salk Institute for Biological Studies
10010 North Torrey Pines Road
La Jolla, CA 92037
Office Tel: 858-453-4100 x1857
Lab Website:

Research Title
Computational Principles of Natural Sensory Processing

Research Description
Our group works on computational principles of how the brain processes information. We are interested in how sensory processing in the brain is shaped by the animal's need to create parsimonious representations of events in the outside world. Our approaches are often derived from methods in statistical physics, mathematics, and information theory.

We also work on methods for analyzing neural data, including methods for analyzing neural responses to natural stimuli, such as a short video clip or sound recording during a stroll on a forest trail. In the past, scientists had to rely on simplified objects on a computer screen or random stimuli to garner information on how the brain processes visual information. Natural stimuli are often much better for probing neural responses than noise stimuli. Using approaches designed to work with natural stimuli, we hope to achieve a more complete picture of how the brain processes information.

Sharpee, T. O. Optimizing neural information capacity through discretization, Neuron, 94(5) 954-960, 2017

Rowekamp, R. J. Sharpee, T. O. Cross-orientation suppression in visual area V2, Nat Commun, 8:15739, 2017

Sharpee, T. O. Plasticity to the rescue, Neuron, 92(5): 935-936, 2016

Kuczala, A. Sharpee, T. O. Eigenvalue spectra of large correlated random matrices, Physical Review E, 2016

Sharpee, T. O. How invariant feature selectivity is achieved in cortex, Front Synaptic Neurosci., 23:8:26, 2016

Sharpee, T. O. Taking a close look at electrosensing, eLife, 29:5, 2016

Zhang, Y. Sharpee, T. O. A robust feedforward model of the olfactory system, PLoS Computational Biology, 12(4):e1004850, 2016

Calhoun, A. J. Tong, A. Pokala, N. Fitzpatrick, J. A. Sharpee, T .O. Chalasani, S. H. Neural mechanisms for evaluating environmental variability in Carnorhabditis elegans, Neuron, 86(2), 428-441, 2015

Kastner, D. B. Baccus, S. A. Sharpee, T .O. Critical and maximally informative encoding between neural populations in the retina, PNAS, 112, 8 2533-2538, 2015

Aljadeff, J. Stern, M. Sharpee, T. Transition to Chaos in Random Networks with Cell-Type-Specific Connectivity, Physical Review Letters, 114, 088101, 2015

Calhoun, A. Chalasani, S. Sharpee, T. O. Maximally informative foraging by Caenorhabditis elegans, eLife, e04220, 2014

Sharpee, T. O. Toward Functional Classification of Neuronal Types, Neuron, 83(6) 1329-1334, 2014

Sharpee, T. O. Function determines structure in complex neural networks, PNAS, 111 (23) 8327-8328, 2014

Sharpee, T. O. Calhoun, A. Chalasani, S. Information Theory of Adaption in Neurons, Behavior, and Mood, Current Opinion in Neurobiology, 25, 47-53, 2014

Morris, R. Sancho-Martinez , I. Sharpee, T. O. Izpisua Belmonte, J. C. Mathematical approaches to modeling development and reprogramming, PNAS, 111(14), 5076-5082, 2014

Aljadeff, J. Segev, R. Berry, M. J. Sharpee, T. O. Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli, PLoS Computational Biology, 9 (9): e1003206, 2013

Sharpee, T. O. Computational Identification of Receptive Fields, Annual Review of Neuroscience, 36, 103-20, 2013

Sharpee, T. O. Kouh, M. Reynolds, J. H. Trade-off between curvature tuning and position invariance in visual area V4, PNAS, 110(28), 11618-23, 2013

Nandy, A. Sharpee, T. O. Reynolds, J. H. Mitchel, J. The fine structure of shape tuning in area V4, Neuron, 78(6), 1102-1115, 2013

Saremi, S. Sejnowski, T. J. Sharpee, T. O. Double-Gabor Filters are Independent Components of Small "Translation-Invariant" Image Patches, Neural Computation, 25(4), 922-39, 2013

Jeanne, J. Sharpee, T. O. Gentner, T. Q. Associative learning enhances population coding by inverting inter-neuronal correlation patterns, Neuron, 78 (2), 352-363, 2013

Kaardal, J. Fitzgerald, J. D. Berry, M. J. Sharpee, T. O. Identifying functional bases for multidimensional neural computations, Neural Computation, 25 (7) 1870-1890, 2013

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