1 code implementation • NeurIPS 2023 • Shirui Chen, Linxing Preston Jiang, Rajesh P. N. Rao, Eric Shea-Brown
We show that the firing rate dynamics of a recurrent neural circuit with a separate set of output units can sample from an arbitrary probability distribution.
1 code implementation • 19 Oct 2022 • Matthew J. Bryan, Linxing Preston Jiang, Rajesh P N Rao
Approach: To achieve goal-directed closed-loop neurostimulation, we propose "neural co-processors" which use artificial neural networks and deep learning to learn optimal closed-loop stimulation policies, shaping neural activity and bridging injured neural circuits for targeted repair and rehabilitation.
no code implementations • 19 Dec 2021 • Linxing Preston Jiang, Rajesh P. N. Rao
Specifically, the Rao-Ballard hierarchical predictive coding model assumes that the top-down feedback connections from higher to lower order cortical areas convey predictions of lower-level activities.
no code implementations • 23 Jan 2021 • Linxing Preston Jiang, Luciano de la Iglesia
We propose a few heuristics to improve the training of SVAE and show that a unit $L_2$ norm constraint on the decoder is critical to produce sparse coding filters.