Publikationen:
Neuronale Informationsverarbeitung und Verhalten

Zeitschriftenartikel (4)

  1. 1.
    Zeitschriftenartikel
    Nonnenmacher, M.; Behrens, C.; Berens, P.; Bethge, M.; Macke, J.: Signatures of criticality arise from random subsampling in simple population models. PLoS Computational Biology 13 (10), S. 1 - 23 (2017)
  2. 2.
    Zeitschriftenartikel
    Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.: Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research 122, S. 105 - 123 (2016)
  3. 3.
    Zeitschriftenartikel
    Archer, E. W.; Park, I.; Pillow, J.: Bayesian Entropy Estimation for Countable Discrete Distributions. Journal of Machine Learning Research 15, S. 2833 - 2868 (2014)
  4. 4.
    Zeitschriftenartikel
    Haefner, R.; Gerwinn, S.; Macke, J.; Bethge, M.: Inferring decoding strategies from choice probabilities in the presence of correlated variability. Nature Neuroscience 16 (2), S. 235 - 242 (2013)

Konferenzbeitrag (1)

  1. 5.
    Konferenzbeitrag
    Park, M.; Bohner, G.; Macke, J.: Unlocking neural population non-stationarity using a hierarchical dynamics model. In: Advances in Neural Information Processing Systems 28, S. 145 - 153 (Hg. Cortes, C.; Lawrence, N.D.; Lee, D.D.; Sugiyama, M.; Garnett, R. et al.). Twenty-Ninth Annual Conference on Neural Information Processing Systems (NIPS 2015), Montréal, Canada. Curran, Red Hook, NY, USA (2016)

Meeting Abstract (1)

  1. 6.
    Meeting Abstract
    Goncalves, P.; Luckmann, J.-M.; Bassetto, G.; Nonnenmacher, M.; Macke, J.: Flexible Bayesian inference for complex models of single neurons. In: BMC Neuroscience, Bd. 18, S. 58 - 58. Twenty-Sixth Annual Computational Neuroscience Meeting (CNS*2017), Antwerpen, Belgium. (2017)

Vortrag (5)

  1. 7.
    Vortrag
    Macke, J. H.: Correlations and signatures of criticality in neural population models. Institut d'Etudes de la Cognition (IEC) at the Ecole Normale Supérieure: Group for Neural Theory, Paris, France (2015)
  2. 8.
    Vortrag
    Macke, J. H.: Correlations, criticality and common input. University of Zurich: Swiss Computational Neuroscience Seminars, Zürich, Switzerland (2015)
  3. 9.
    Vortrag
    Macke, J.: Statistical methods for characterizing cortical population activity. Osnabrück Computational Cognition Alliance Meeting on "The Brain as a Probabilistic Inference Engine" (OCCAM 2014), Osnabrück, Germany (2014)
  4. 10.
    Vortrag
    Macke, J.: Inferring neural population dynamics from multiple partial measurements of the same circuit. Group Seminar C. Gros "Complex and Cognitive Systems": Max-Planck-Institute for Brain Research, Frankfurt a.M., Germany (2013)
  5. 11.
    Vortrag
    Macke, J.: Characterizing the dynamics of large neural populations. ICB Institute of Computational Biology: Helmholtz Zentrum, München, Germany (2013)

Poster (11)

  1. 12.
    Poster
    Bassetto, G.; Macke, J.: Full Bayesian inference for model-based receptive field estimation, with application to primary visual cortex. Bernstein Conference 2016, Berlin, Germany (2016)
  2. 13.
    Poster
    Nienborg, H.; Macke, J.: Using sequential dependencies in neural activity and behavior to dissect choice related activity in V2. 44th Annual Meeting of the Society for Neuroscience (Neuroscience 2014), Washington, DC, USA (2014)
  3. 14.
    Poster
    Archer, E. W.; Pillow, J.; Macke, J.: Low Dimensional Dynamical Models of Neural Populations with Common Input. 15th Conference of Junior Neuroscientists of Tübingen (NeNa 2014): The Changing Face of Publishing and Scientific Evaluation, Schramberg, Germany (2014)
  4. 15.
    Poster
    Archer, E. W.; Pillow, J.; Macke, J.: Low-dimensional dynamical neural population models with shared stimulus drive. Bernstein Conference 2014, Göttingen, Germany (2014)
  5. 16.
    Poster
    Nienborg, H.; Macke, J.: Using sequential dependencies in neural activity and behavior to dissect choice related activity in V2. Bernstein Conference 2014, Göttingen, Germany (2014)
  6. 17.
    Poster
    Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F. A.: Pain-free bayesian inference for psychometric functions. 37th European Conference on Visual Perception (ECVP 2014), Beograd, Serbia (2014)
  7. 18.
    Poster
    Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.; Wichmann, F. A.: Pain-free Bayesian inference for psychometric functions. 2014 European Mathematical Psychology Group Meeting (EMPG), Tübingen, Germany (2014)
  8. 19.
    Poster
    Archer, E. W.; Pillow, J.; Macke, J. H.: Low-dimensional models of neural population recordings with complex stimulus selectivity. Computational and Systems Neuroscience Meeting (COSYNE 2014), Salt Lake City, UT, USA (2014)
  9. 20.
    Poster
    Park, I.; Archer, E. W.; Latimer, K.; Pillow, J.: Scalable nonparametric models for binary spike patterns. Computational and Systems Neuroscience Meeting (COSYNE 2014), Salt Lake City, UT, USA (2014)
  10. 21.
    Poster
    Turaga, S.; Buesing, L.; Packer, A.; Dalgleish, A.; Pettit, N.; Hauser, M.; Macke, J. H.: Predicting noise correlations for non-simultaneously measured neuron pairs. Computational and Systems Neuroscience Meeting (COSYNE 2014), Salt Lake City, UT, USA (2014)
  11. 22.
    Poster
    Turaga, S.; Buesing, L.; Packer, M.; Hausser, M.; Macke, J.: Inferring interactions between cell types from multiple calcium imaging snapshots of the same neural circuit. 43rd Annual Meeting of the Society for Neuroscience (Neuroscience 2013), San Diego, CA, USA (2013)
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