Internal models engaged by brain-computer interface control. - Matthew D. Golub; Byron M. Yu; Steven M. Chase (EMBC, 2012)

Learning an Internal Dynamics Model from Control Demonstration. - Matthew D. Golub; Steven M. Chase; Byron M. Yu (ICML (1), 2013)

Neural constraints on learning. - Patrick T. Sadtler; Kristin M. Quick; Matthew D. Golub; Steven M. Chase; Stephen I. Ryu; Elizabeth C. Tyler-Kabara; Byron M. Yu; Aaron P. Batista (Nat., 2014)

FixedPointFinder: A Tensorflow toolbox for identifying and characterizing fixed points in recurrent neural networks. - Matthew D. Golub; David Sussillo (J. Open Source Softw., 2018)

Universality and individuality in neural dynamics across large populations of recurrent networks. - Niru Maheswaranathan; Alex H. Williams; Matthew D. Golub; Surya Ganguli; David Sussillo (NeurIPS, 2019)

Reverse engineering recurrent networks for sentiment classification reveals line attractor dynamics. - Niru Maheswaranathan; Alex H. Williams; Matthew D. Golub; Surya Ganguli; David Sussillo (NeurIPS, 2019)

Active learning of neural population dynamics using two-photon holographic optogenetics. - Andrew Wagenmaker; Lu Mi; Marton Rozsa; Matthew S. Bull; Karel Svoboda; Kayvon Daie; Matthew D. Golub; Kevin G. Jamieson (NeurIPS, 2024)

Accurate identification of communication between multiple interacting neural populations. - Belle Liu; Jacob Sacks; Matthew D. Golub (CoRR, 2025)