Refereed Publications

  1. Culp, J. M., Ashby, D. M., George, A. G., Teskey, G. C., Nicola, W., & McGirr, A. (2024). A Markovian neural barcode representing mesoscale cortical spatiotemporal dynamics. bioRxiv, 2024-06. (In Press, Cell Reports Methods)

  2. Masoliver M, Davidsen J, Nicola W. Hippocampal phase precession may be generated by chimera dynamics. Frontiers in Neural Circuits. 2025 Oct 6;19:1634298.

  3. Boyce, A. K., Fouad, Y., Gom, R. C., Ashby, D. M., Martins-Silva, C., Molina, L., ... & Thompson, R. J. (2025). Contralesional hippocampal spreading depolarization promotes functional recovery after stroke. Nature Communications, 16(1), 3428.

  4. Vandal, M., Institoris, A., Reveret, L., Korin, B., Gunn, C., Hirai, S., ... & Nguyen, M. D. (2025). Loss of endothelial CD2AP causes sex-dependent cerebrovascular dysfunction. Neuron, 113(6), 876-895.

  5. Newton, T. R., & Nicola, W. (2025). Comparison of FORCE trained spiking and rate neural networks shows spiking networks learn slowly with noisy, cross-trial firing rates. PLOS Computational Biology, 21(7), e1013224.

  6. Culp, J. M., & Nicola, W. (2025). Input driven synchronization of chaotic neural networks with analyticaly determined conditional Lyapunov exponents. Nonlinear Dynamics, 113(10), 12131-12141.

  7. Nicola, W., Newton, T. R., & Clopath, C. (2024). The impact of spike timing precision and spike emission reliability on decoding accuracy. Scientific Reports, 14(1), 10536.

  8. Nicola, W. (2024). Rapid changes in synchronizability in conductance-based neuronal networks with conductance-based coupling. Chaos: An Interdisciplinary Journal of Nonlinear Science, 34(2).

  9. Rabus, A., Masoliver, M., Gruber, A. J., Nicola, W., & Davidsen, J. (2024). Non-trivial relationship between behavioral avalanches and internal neuronal dynamics in a recurrent neural network. Chaos: An Interdisciplinary Journal of Nonlinear Science, 34(5).

  10. Shamsi, J., & Nicola, W. (2024). Implementation of Linear Differential Equations Using Pulse-Coupled Oscillators With an Ultra-Low Power Neuromorphic Realization. IEEE Transactions on Circuits and Systems I: Regular Papers.

  11. Füzesi, T., Rasiah, N. P., Rosenegger, D. G., Rojas-Carvajal, M., Chomiak, T., Daviu, N., ... & Bains, J. S. (2023). Hypothalamic CRH neurons represent physiological memory of positive and negative experience. Nature communications, 14(1), 8522.

  12. Lameu, E. L., Rasiah, N. P., Baimoukhametova, D. V., Loewen, S. P., Bains, J. S., & Nicola, W. (2023). Particle‐swarm based modelling reveals two distinct classes of CRHPVN neurons. The Journal of Physiology, 601(15), 3151-3171.

  13. Masoliver, M., Davidsen, J., & Nicola, W. (2022). Embedded chimera states in recurrent neural networks. Communications Physics, 5(1), 205.

  14. Zarkeshian, P., Kergan, T., Ghobadi, R., Nicola, W., & Simon, C. (2022). Photons guided by axons may enable backpropagation-based learning in the brain. Scientific Reports, 12(1), 20720.

  15. Haidey, J. N., Peringod, G., Institoris, A., Gorzo, K. A., Nicola, W., Vandal, M., ... & Gordon, G. R. (2021). Astrocytes regulate ultra-slow arteriole oscillations via stretch-mediated TRPV4-COX-1 feedback. Cell reports, 36(5).

  16. Al-Darabsah, I., Chen, L., Nicola, W., & Campbell, S. A. (2021). The impact of small time delays on the onset of oscillations and synchrony in brain networks. Frontiers in Systems Neuroscience, 15, 688517.

  17. Nicola, W., & Campbell, S. A. (2021). Normalized connectomes show increased synchronizability with age through their second largest eigenvalue. SIAM Journal on Applied Dynamical Systems, 20(2), 1158-1176.

  18. Nicola, W., & Clopath, C. (2019). A diversity of interneurons and Hebbian plasticity facilitate rapid compressible learning in the hippocampus. Nature neuroscience, 22(7), 1168-1181.

  19. Pernelle, G., Nicola, W., & Clopath, C. (2018). Gap junction plasticity as a mechanism to regulate network-wide oscillations. PLoS computational biology, 14(3), e1006025.

  20. Nicola, W., Hellyer, P. J., Campbell, S. A., & Clopath, C. (2018). Chaos in homeostatically regulated neural systems. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(8).

  21. Nicola, W., & Clopath, C. (2017). Supervised learning in spiking neural networks with FORCE training. Nature communications, 8(1), 2208.

  22. Nicola, W., & Campbell, S. A. (2017). Nonsmooth Dynamical Systems in Neuroscience. Collections, 50(05).

  23. Nicola, W., Tripp, B., & Scott, M. (2016). Obtaining Arbitrary Prescribed Mean Field Dynamics for Recurrently Coupled Networks of Type-I Spiking Neurons with Analytically Determined Weights. Frontiers in Computational Neuroscience, 10, 15.

  24. Nicola, W., & Campbell, S. A. (2016). Nonsmooth bifurcations of mean field systems of two-dimensional integrate and fire neurons. SIAM Journal on Applied Dynamical Systems, 15(1), 391-439.

  25. Nicola, W., Ly, C., & Campbell, S. A. (2015). One-dimensional population density approaches to recurrently coupled networks of neurons with noise. SIAM Journal on Applied Mathematics, 75(5), 2333-2360.

  26. Ferguson, K. A., Njap, F., Nicola, W., Skinner, F. K., & Campbell, S. A. (2015). Examining the limits of cellular adaptation bursting mechanisms in biologically-based excitatory networks of the hippocampus. Journal of Computational Neuroscience, 39(3), 289-309.

  27. Nicola, W., & Campbell, S. A. (2013). Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons. Frontiers in computational neuroscience, 7, 184.

  28. Nicola, W., & Campbell, S. A. (2013). Bifurcations of large networks of two-dimensional integrate and fire neurons. Journal of computational neuroscience, 35(1), 87-108.

  29. Dur-e-Ahmad, M., Nicola, W., Campbell, S. A., & Skinner, F. K. (2012). Network bursting using experimentally constrained single compartment CA3 hippocampal neuron models with adaptation. Journal of computational neuroscience, 33(1), 21-40.

Preprints

  1. Ichiyama, A., Mestern, S., Fuzesi, T., Allman, B. L., Nicola, W., Bains, J., ... & Inoue, W. (2025). Hypothalamic recurrent inhibition regulates functional states of stress effector neurons. bioRxiv, 2025-09.

  2. Mason, K., Sennik, S., Clopath, C., Gruber, A., & Nicola, W. (2025). Rapidly Reconfigurable Dynamic Computing in Neural Networks with Fixed Synaptic Connectivity. bioRxiv, 2025-10.

  3. Sahu, G., Greening, D., Nicola, W., & Turner, R. W. (2024). Ion channels that mediate calcium-dependent control of spike patterns are spatially organized across the soma in relation to a cytoskeletal assembly. bioRxiv, 2024-08.

  4. Nicola, W., Dupret, D., & Clopath, C. (2022). Disk-Drive-Like Operations in the Hippocampus. bioRxiv, 2022-10.

Published Patents

  1. https://patents.google.com/patent/US20240306976A1/en

  2. https://patents.google.com/patent/US20240303352A1/en

Conference Proceedings

  1. Garasto, S., Nicola, W., Bharath, A. A., & Schultz, S. R. (2019, March). Neural sampling strategies for visual stimulus reconstruction from two-photon imaging of mouse primary visual cortex. In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER) (pp. 566-570). IEEE.

  2. Nicola, W., Njap, F., Ferguson, K., Skinner, F., & Campbell, S. A. (2014). Mean field analysis gives accurate predictions of the behaviour of large networks of sparsely coupled and heterogeneous neurons. BMC Neuroscience, 15(Suppl 1), O3.

  3. Ibarra Molinas, J., Sollini, J., Chadderton, P., & Nicola, W. (2025). Data-driven modelling of rodent auditory processing of pure tones as low-order polynomial encodings of spectral features. Bulletin of the American Physical Society.