David Sussillo

Postdoctoral Research Scientist,

Stanford University


W1.3 James Clark Building




I am currently a post-doc in the lab of Krishna Shenoy.  We work on basic motor cortex neurophysiology as well as neural prosthetics applied to arm movements.  I am interested in studying how recurrently connected neural circuits lead to computation.  For example, how does a neural circuit hold memory, or compute a specific function?  How do two circuits communicate with each other?  What is the right level at which to think about these problems while still considering the mechanism?





A recurrent neural network for closed-loop intracortical brain-machine interface decoders, David Sussillo, Paul Nuyujukian, Joline Fan, Jonathan Kao, Sergey Stavisky, Stephen Ryu, Krishna Shenoy, (2012), J Neural Eng. 9(2):026027


Generating Coherent Patterns of Activity from Chaotic Neural Networks, David Sussillo,  L.F. Abbott, (2009). Neuron 63:544-557.


Self-Tuning of Neural Circuits Through Short-Term Synaptic Plasticity, David Sussillo, Taro Toyoizumi and Wolfgang Maass (2007). JN Physiol vol. 97 no. 6 4079-4095


Feedforward Inhibition Contributes to the Control of Epileptiform Propagation Speed, Andrew J. Trevelyan, David Sussillo, Rafael Yuste (2007). The Journal of Neuroscience, 27(13): 3383-3387


Modular Propagation of Epileptiform Activity: Evidence for an Inhibitory Veto in Neocortex Andrew J. Trevelyan, David Sussillo, Brendon O. Watson and Rafael Yuste (2006). The Journal of Neuroscience, 26(48): 12447-12455


Spectrogram Analysis of Genomes, David Sussillo, Anshul Kundaje, and Dimitris Anastassiou, (2004). EURASIP Journal on Applied Signal Processing Volume 2004  Issue 1, Pages 29-42






FORCE learning – simple MATLAB scripts to explore training RNNs.