Ulises Pereira Obilinovic

Understanding how the dynamics of neural activity patterns across multiple brain regions give rise to behavior is one of the fundamental questions in systems neuroscience. The understanding the field seeks goes beyond merely simulating and predicting behavior and neural activity; it involves comprehending how the activity of neurons, interacting through synaptic connections, can be reduced into causal models with a few key variables that produce neural activity and behavior. As a scientist at the Allen Institute for Neural Dynamics, my research focuses on building such models.

Education

Google scholar and GitHub

Contact: ulises.pereira.o[at]alleninstitute.org

Publications & Preprints

* Denotes co-first authors
  1. L. Kuśmierz, U. Pereira-Obilinovic, Z. Lu, D. Mastrovito, S. Mihalas. Hierarchy of chaotic dynamics in random modular networks. arXiv. [preprint]
  2. K. Mohan, U. Pereira-Obilinovic, S. Srednyak, Y. Amit, N. Brunel, D. Freedman. Visual image familiarity learning at multiple timescales in the primate inferotemporal cortex. bioRxiv. [preprint]
  3. X.-J. Wang, J. Jiang, U. Pereira-Obilinovic. Bifurcation in space: How does functional modularity arise in the cortex made with repeats of a canonical local circuit?. bioRxiv. [preprint]
  4. U. Pereira-Obilinovic, H. Hou, K. Svoboda, X.-J. Wang. Brain mechanism of foraging: Reward-dependent synaptic plasticity versus neural integration of values. PNAS, 121 (14) e2318521121, 2024. [paper][code]
  5. U. Pereira-Obilinovic, J. Aljadeff, and N. Brunel. Forgetting leads to chaos in attractor networks. Physical Review X, 13(1), p.011009, 2023. [paper][code][featured]
  6. S. Recanatesi*, U. Pereira-Obilinovic*, M. Murakami, Z. Mainen✝, L. Mazzucato✝. Metastable attractors explain the variable timing of stable behavioral action sequences. Neuron, 110(1):139–153, 2022. [paper][code][featured]
  7. J. Aljadeff, M. Gillett, U. Pereira-Obilinovic, and N. Brunel. From synapse to network: models of informationstorage and retrieval in neural circuits. Current Opinion in Neurobiology, 2021. [paper]
  8. X.-J. Wang, U. Pereira, M.G.P. Rosa, and H. Kennedy. Brain connectomes come of age. Current Opinion in Neurobiology, 2020 [paper]
  9. M. Gillett, U. Pereira and N. Brunel. Characteristics of sequential activity in networks with temporally asymmetric Hebbian learning. PNAS, 2020 [paper][code]
  10. U. Pereira and N. Brunel. Unsupervised learning of persistent and sequential activity. Frontiers in computational neuroscience, 13:97, 2020 [paper][code]
  11. J. Vera, U. Pereira, B. Reynaert, J. Bacigalupo, and M. Sanhueza. Modulation of frequency preference in heterogeneous populations of theta-resonant neurons. Neuroscience, 426:13–32, 2020 [paper]
  12. U. Pereira and N. Brunel. Attractor dynamics in networks with learning rules inferred from in vivo data. Neuron, 99(1):227–238, 2018 [paper][code]
  13. U. Pereira, P. Coullet, and E. Tirapegui. The bogdanov–takens normal form: A minimal model for single neuron dynamics. Entropy, 17(12):7859–7874, 2015 [paper]
  14. J. Vera, M. Pezzoli, U. Pereira, J. Bacigalupo, and M. Sanhueza. Electricalresonance in the θ frequency range in olfactory amygdala neurons. PLoS One, 9(1):e85826, 2014 [paper]