DePasquale, Brian, Sussillo, David, Abbott, L.F., and Churchland, Mark M. The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks. Retrieved from https://par.nsf.gov/biblio/10432433. Neuron 111.5 Web. doi:10.1016/j.neuron.2022.12.007.

DePasquale, Brian, Sussillo, David, Abbott, L.F., & Churchland, Mark M. The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks. Neuron, 111 (5). Retrieved from https://par.nsf.gov/biblio/10432433. https://doi.org/10.1016/j.neuron.2022.12.007

DePasquale, Brian, Sussillo, David, Abbott, L.F., and Churchland, Mark M. "The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks". Neuron 111 (5). Country unknown/Code not available. https://doi.org/10.1016/j.neuron.2022.12.007. https://par.nsf.gov/biblio/10432433.

@article{osti_10432433,
place = {Country unknown/Code not available}, title = {The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks}, url = {https://par.nsf.gov/biblio/10432433}, DOI = {10.1016/j.neuron.2022.12.007}, abstractNote = {}, journal = {Neuron}, volume = {111}, number = {5}, author = {DePasquale, Brian and Sussillo, David and Abbott, L.F. and Churchland, Mark M.}, }