_{Publications:
Neural Computation and Behavior}

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), pp. 1 - 23 (2017)

Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.: Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data. Vision Research 122, pp. 105 - 123 (2016)

Panzeri, S.; Macke, J.; Gross, J.; Kayser, C.: Neural population coding: combining insights from microscopic and mass signals. Trends in Cognitive Sciences 19 (3), pp. 162 - 172 (2015)

Archer, E. W.; Park, I.; Pillow, J.: Bayesian Entropy Estimation for Countable Discrete Distributions. Journal of Machine Learning Research 15, pp. 2833 - 2868 (2014)

Haefner, R.; Gerwinn, S.; Macke, J.; Bethge, M.: Inferring decoding strategies from choice probabilities in the presence of correlated variability. Nature Neuroscience 16 (2), pp. 235 - 242 (2013)

Bassetto, G.; Macke, J.: Electrophysiology Analysis, Bayesian. In: Encyclopedia of Computational Neuroscience, pp. 1280 - 1284 (Eds. Jaeger, D.; Jung, R.). Springer, New York, NY, USA (2022)

Park, M.; Bohner, G.; Macke, J.: Unlocking neural population non-stationarity using a hierarchical dynamics model. In: Advances in Neural Information Processing Systems 28, pp. 145 - 153 (Eds. Cortes, C.; Lawrence, N.; Lee, D.; Sugiyama, M.; Garnett, R.). Twenty-Ninth Annual Conference on Neural Information Processing Systems (NIPS 2015), Montréal, Canada, December 07, 2015 - December 12, 2015. Curran, Red Hook, NY, USA (2016)

Goncalves, P.; Luckmann, J.-M.; Bassetto, G.; Nonnenmacher, M.; Macke, J.: Flexible Bayesian inference for complex models of single neurons. In BMC Neuroscience, 18 (Supplement 1), O4, p. 58. Twenty-Sixth Annual Computational Neuroscience Meeting (CNS*2017), Antwerpen, Belgium, July 15, 2017 - July 20, 2017. BioMed Central (2017)

Macke, J.: 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)

Macke, J. H.: Correlations, criticality and common input. University of Zurich: Swiss Computational Neuroscience Seminars, Zürich, Switzerland (2015)

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)

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)

Macke, J.: Characterizing the dynamics of large neural populations. ICB Institute of Computational Biology: Helmholtz Zentrum, München, Germany (2013)

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)

Czubayko, U.; Bassetto, G.; Narayanan, R.; Oberlaender, M.; Macke, J.; Kerr, J.: Anatomical basis of spiking correlation in upper layers of somatosensory cortex. 45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), Chicago, IL, USA (2015)

Rulla, S.; Ng, B.; Macke, J.; Wallace, D.; Sawinski, J.; Kerr, J.: Two-photon imaging of neuronal populations in the primary visual cortex representation of the overhead visual field. 45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), Chicago, IL, USA (2015)

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)

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)

Archer, E. W.; Pillow, J.; Macke, J.: Low-dimensional dynamical neural population models with shared stimulus drive. Bernstein Conference 2014, Göttingen, Germany (2014)

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)

Schütt, H.; Harmeling, S.; Macke, J.; Wichmann, F.: Pain-free bayesian inference for psychometric functions. 37th European Conference on Visual Perception (ECVP 2014), Beograd, Serbia (2014)

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)

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)

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)

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)

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)