1: Pellegrino*, A., Stein*, H., & Cayco-Gajic, N. A. (2023). Disentangling Mixed Classes of Covariability in Large-Scale Neural Data. bioRxiv, 2023-03.
2: Lanore*, F., Cayco-Gajic*, N. A., Gurnani, H., Coyle, D., & Silver, R. A. (2021). Cerebellar granule cell axons support high-dimensional representations. Nature neuroscience, 24(8), 1142-1150.
3: Cayco-Gajic, N. A., & Silver, R. A. (2019). Re-evaluating circuit mechanisms underlying pattern separation. Neuron, 101(4), 584-602.
4: Cayco-Gajic, N. A., Clopath, C., & Silver, R. A. (2017). Sparse synaptic connectivity is required for decorrelation and pattern separation in feedforward networks. Nature communications, 8(1), 1116.
5: Cayco-Gajic, N. A., Zylberberg, J., & Shea-Brown, E. (2015). Triplet correlations among similarly tuned cells impact population coding. Frontiers in computational neuroscience, 9, 57.
6: Cayco-Gajic, N. A., & Shea-Brown, E. (2013). Neutral stability, rate propagation, and critical branching in feedforward networks. Neural Computation, 25(7), 1768-1806.
