34 citations · 62 across the 10 of their papers we have counts for
10 papers
Bayesian optimization of distributed neurodynamical controller models for spatial navigation
Armin Hadzic, Grace M. Hwang, Kechen Zhang +2
Dynamical systems models for controlling multi-agent swarms have demonstrated advances toward resilient, decentralized navigation algorithms. We previously introduced the NeuroSwar…
An interdisciplinary approach to high school curriculum development: Swarming Powered by Neuroscience
Elise Buckley, Joseph D. Monaco, Kevin M. Schultz +5
This article discusses how to create an interactive virtual training program at the intersection of neuroscience, robotics, and computer science for high school students. A four-da…
Cognitive swarming in complex environments with attractor dynamics and oscillatory computing
Joseph D. Monaco, Grace M. Hwang, Kevin M. Schultz +1
Neurobiological theories of spatial cognition developed with respect to recording data from relatively small and/or simplistic environments compared to animals' natural habitats. I…
Approximations of Shannon Mutual Information for Discrete Variables with Applications to Neural Population Coding
Wentao Huang, Kechen Zhang
Although Shannon mutual information has been widely used, its effective calculation is often difficult for many practical problems, including those in neural population coding. Asy…
Building a Dynamical Network Model from Neural Spiking Data: Application of Poisson Likelihood
Ozgur Doruk, Kechen Zhang
Research showed that, the information transmitted in biological neurons is encoded in the instants of successive action potentials or their firing rate. In addition to that, in-viv…
Fitting of dynamic recurrent neural network models to sensory stimulus-response data
R. Ozgur Doruk, Kechen Zhang
We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of contin…
Information-theoretic interpretation of tuning curves for multiple motion directions
Wentao Huang, Xin Huang, Kechen Zhang
We have developed an efficient information-maximization method for computing the optimal shapes of tuning curves of sensory neurons by optimizing the parameters of the underlying f…
An Information-Theoretic Framework for Fast and Robust Unsupervised Learning via Neural Population Infomax
Wentao Huang, Kechen Zhang
A framework is presented for unsupervised learning of representations based on infomax principle for large-scale neural populations. We use an asymptotic approximation to the Shann…
Information-Theoretic Bounds and Approximations in Neural Population Coding
Wentao Huang, Kechen Zhang
While Shannon's mutual information has widespread applications in many disciplines, for practical applications it is often difficult to calculate its value accurately for high-dime…
Adaptive stimulus design for dynamic recurrent neural network models
R. Ozgur Doruk, Kechen Zhang
We present a theoretical application of an optimal experiment design (OED) methodology to the development of mathematical models to describe the stimulus-response relationship of s…