Cone I, Shouval HZ. (2021). Learning precise spatiotemporal sequences via biophysically realistic learning rules in a modular, spiking network. eLife. 10 [PubMed]

• Sequence learning via biophysically realistic learning rules (Cone and Shouval 2021) [Model]

Dura-Bernal S et al. (2023). Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics. Cell reports. 42 [PubMed]

• Data-driven multiscale model of macaque auditory thalamocortical circuits reproduces in vivo dynamics (Dura-Bernal et al., 2023) [Model]

Maes A, Barahona M, Clopath C. (2020). Learning spatiotemporal signals using a recurrent spiking network that discretizes time. PLoS computational biology. 16 [PubMed]

• Learning spatiotemporal sequences using recurrent spiking NN that discretizes time (Maes et al 2020) [Model]

Muscinelli SP, Gerstner W, Schwalger T. (2019). How single neuron properties shape chaotic dynamics and signal transmission in random neural networks. PLoS computational biology. 15 [PubMed]

• Single neuron properties shape chaos and signal transmission in random NNs (Muscinelli et al 2019) [Model]