Understanding the early visual system in health and disease is a key issue for neuroscience and neuroengineering applications such as visual prostheses.
Although the processing of visual information in the healthy retina and early visual cortex (EVC) has been studied in detail, no comprehensive computational model exists that captures the many cell-level and network-level biophysical changes common to retinal degenerative diseases and other sources of visual impairment.
To address this challenge, we are developing computational models of the retina and EVC to elucidate the neural code of vision.
Brains face the fundamental challenge of extracting relevant information from high-dimensional external stimuli in order to form the neural basis that can guide an organism’s behavior and its interaction with the world. One potential approach to addressing this challenge is to reduce the number of variables required to represent a particular …
Michael Beyeler, Emily L. Rounds, Kristofor D. Carlson, Nikil Dutt, Jeffrey L. Krichmar
PLOS Computational Biology 15(6):e1006908
To investigate the effect of axonal stimulation on the retinal response, we developed a computational model of a small population of morphologically and biophysically detailed retinal ganglion cells, and simulated their response to epiretinal electrical stimulation. We found that activation thresholds of ganglion cell somas and axons varied …
Using a dimensionality reduction technique known as non-negative matrix factorization, we found that a variety of medial superior temporal (MSTd) neural response properties could be derived from MT-like input features. The responses that emerge from this technique, such as 3D translation and rotation selectivity, spiral tuning, and heading …
Michael Beyeler, Nikil Dutt, Jeffrey L. Krichmar
Journal of Neuroscience 36(32): 8399-8415