331 citations · 658 across the 10 of their papers we have counts for
10 papers
Eigenvalue spectra of large correlated random matrices
Alexander Kuczala, Tatyana O. Sharpee
Using the diagrammatic method, we derive a set of self-consistent equations that describe eigenvalue distributions of large correlated asymmetric random matrices. The matrix elemen…
On the low dimensional dynamics of structured random networks
Johnatan Aljadeff, David Renfrew, Marina Vegué +1
Using a generalized random recurrent neural network model, and by extending our recently developed mean-field approach [J. Aljadeff, M. Stern, T. Sharpee, Phys. Rev. Lett. 114, 088…
Critical and maximally informative encoding between neural populations in the retina
David B. Kastner, Stephen A. Baccus, Tatyana O. Sharpee
Computation in the brain involves multiple types of neurons, yet the organizing principles for how these neurons work together remain unclear. Information theory has offered explan…
Transition to chaos in random networks with cell-type-specific connectivity
Johnatan Aljadeff, Merav Stern, Tatyana O. Sharpee
In neural circuits, statistical connectivity rules strongly depend on neuronal type. Here we study dynamics of neural networks with cell-type specific connectivity by extending the…
Maximally informative pairwise interactions in networks
Jeffrey D. Fitzgerald, Tatyana O. Sharpee
Several types of biological networks have recently been shown to be accurately described by a maximum entropy model with pairwise interactions, also known as the Ising model. Here…
Comparison of objective functions for estimating linear-nonlinear models
Tatyana O. Sharpee
This paper compares a family of methods for characterizing neural feature selectivity with natural stimuli in the framework of the linear-nonlinear model. In this model, the neural…