The broad goals of this project are to extend and deepen our understanding of the properties of neural circuits. The vertebrate retina is chosen as a model system, because of its ease of experimental access and its complex anatomy. When neurons are hooked together into a circuit, two properties become important: first, the activity of the neurons means something in the context of the animal; second, neurons perform a computation on their inputs. We thus will study how the retina encodes and processes visual information.
The specific aims are: 1) perform a functional classification of retinal ganglion cells using information theoretic techniques, 2) acquire a database of natural movie clips and categorize their statistics, 3) build a spike word dictionary to efficiently capture nonlinear processing in the retina, and 4) investigate the generality of retinal adaptation and characterize its effects on the neural code. A detailed knowledge of what image processing occurs in the retina is of fundamental interest to neuroscience and is also important for a retinal prosthesis to be able to restore vision successfully.
| Tka?ik, Gašper; Mora, Thierry; Marre, Olivier et al. (2015) Thermodynamics and signatures of criticality in a network of neurons. Proc Natl Acad Sci U S A 112:11508-13 |
| Marre, Olivier; Botella-Soler, Vicente; Simmons, Kristina D et al. (2015) High Accuracy Decoding of Dynamical Motion from a Large Retinal Population. PLoS Comput Biol 11:e1004304 |
| Palmer, Stephanie E; Marre, Olivier; Berry 2nd, Michael J et al. (2015) Predictive information in a sensory population. Proc Natl Acad Sci U S A 112:6908-13 |
| da Silveira, Rava Azeredo; Berry 2nd, Michael J (2014) High-fidelity coding with correlated neurons. PLoS Comput Biol 10:e1003970 |
| Tka?ik, Gašper; Marre, Olivier; Amodei, Dario et al. (2014) Searching for collective behavior in a large network of sensory neurons. PLoS Comput Biol 10:e1003408 |
| Aljadeff, Johnatan; Segev, Ronen; Berry 2nd, Michael J et al. (2013) Spike triggered covariance in strongly correlated gaussian stimuli. PLoS Comput Biol 9:e1003206 |
| Kaardal, Joel; Fitzgerald, Jeffrey D; Berry 2nd, Michael J et al. (2013) Identifying functional bases for multidimensional neural computations. Neural Comput 25:1870-90 |
| Schwartz, Greg; Macke, Jakob; Amodei, Dario et al. (2012) Low error discrimination using a correlated population code. J Neurophysiol 108:1069-88 |
| Marre, Olivier; Amodei, Dario; Deshmukh, Nikhil et al. (2012) Mapping a complete neural population in the retina. J Neurosci 32:14859-73 |
| Vasquez, J C; Marre, O; Palacios, A G et al. (2012) Gibbs distribution analysis of temporal correlations structure in retina ganglion cells. J Physiol Paris 106:120-7 |
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