Feel free to email paper suggestions to Stephen Keeley (skeeley[at] princeton).

Paper Suggestions

  1. Learning arbitrary dynamics in efficient, balanced spiking networks using local plasticity rules.
    Alemi, Machens, Deneve & Slotine arxiv (2017).
  2. A unifying motif for spatial and directional surround suppression.
    Liu, Miller & Pack biorxiv (2017).
  3. Neuron’s eye view: Inferring features of complex stimuli from neural responses.
    Chen, Beck & Pearson PLOS Computational Biology (2017).
  4. Nonlinear hebbian learning as a unifying principle in receptive field formation.
    Brito & Gerstner PLOS Computational Biology (2016).
  5. Adaptation without plasticity.
    del Mar Quiroga, Morris & Krekelberg Cell (2016).
  6. A Global Geometric Framework for Nonlinear Dimensionality Reduction.
    Tenenbaum, de Silva & Langford. Science (2000).
  7. Distinct recurrent versus afferent dynamics in cortical visual processing.
    Reinhold, Lien, & Scanziani, Nat Neurosci (2015).
  8. Modular deconstruction reveals the dynamical and physical building blocks of a locomotion motor program.
    Bruno, Frost & Humphries,Neuron (2015).
  9. Spatial segregation of adaptation and predictive sensitization in retinal ganglion cells.
    Kastner & Baccus, Neuron, (2013).
  10. Marginalization in neural circuits with divisive normalization.
    Beck, Latham & Pouget J. Neuroscience, (2011).
  11. Computational account of spontaneous activity as a signature of predictive coding.
    Koran & Deneve, PLOS Comp. Bio., (2017).
  12. Visual motion computation in recurrent neural networks.
    Pachitariu & Sahani NIPS, (2017).
  13. Computing by robust transience: How the fronto-parietal network performs sequential, category-based decisions.
    Chaisangmongkon, Swaminathan, Freedman & Wang, Neuron, (2017).
  14. A modeling framework for deriving the structural and functional architecture of a short-term memory microcircuit.
    Fisher et al., Neuron, (1997).