Sparse Functional Identification of Complex Cells from Spike Times and the Decoding of Visual Stimuli

Aurel A. Lazar, Nikul H. Ukani and Yiyin Zhou. The Journal of Mathematical Neuroscience. DOI: 10.1186/s13408-017-0057-1

Abstract

We investigate the sparse functional identification of complex cells and the decoding of spatio-temporal visual stimuli encoded by an ensemble of complex cells. The reconstruction algorithm is formulated as a rank minimization problem that significantly reduces the number of sampling measurements (spikes) required for decoding. We also establish the duality between sparse decoding and functional identification, and provide algorithms for identification of low-rank dendritic stimulus processors. The duality enables us to efficiently evaluate our functional identification algorithms by reconstructing novel stimuli in the input space. Finally, we demonstrate that our identification algorithms substantially outperform the generalized quadratic model, the non-linear input model and the widely used spike-triggered covariance algorithm.


500 W. 120th St., Mudd Room 524, New York, NY 10027    212-854-5660               
©2014-2019 Columbia University