Recent Publications & Preprints

• The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks
  DePasquale, B, Sussillo, D., Abbott, L.F., Churchland, M.M. (2023)
  in press at Neuron
• Neural population dynamics underlying evidence accumulation in multiple rat brain regions
  DePasquale, B., Brody, C.D., Pillow, J. (2022)
  in revision at eLife
• Recurrent dynamics of prefrontal cortex during context-dependent decision-making
  Cohen Z, DePasquale, B., Aoi, M., Pillow, J. (2020)
  bioRxiv
• Task-dependent changes in the large-scale dynamics and necessity of cortical regions
  Pinto, L., Rajan, K., DePasquale, B., Thiberge, S.Y., Tank, D.W., Brody, C.D. (2019)
  Neuron, 104(4), 810-824. e9
• full-FORCE: A target-based method for training recurrent networks code
  DePasquale, B., Cueva, C.J., Rajan, K., Escola, G.S. & Abbott, L.F. (2018)
  PLoS One 13(2): e0191527
• Error-correcting dynamics in visual working memory
  Panichello, M.F., DePasquale, B., Pillow, J.W. & Buschman, T.J. (2018)
  Nature Communications 10, Article number: 3366
• Building functional networks of spiking model neurons
  Abbott, L.F., DePasquale, B., Memmesheimer, R.-M. (2016)
  Nature Neuroscience 19:350-355

For a full list of publications, see Brian’s Google Scholar.