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Spatio-temporal correlations and visual signalling in a complete neuronal population

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Cited by:

  1. Bo Zhou & David E. Moorman & Sam Behseta & Hernando Ombao & Babak Shahbaba, 2016. "A Dynamic Bayesian Model for Characterizing Cross-Neuronal Interactions During Decision-Making," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(514), pages 459-471, April.
  2. Franklin Leong & Babak Rahmani & Demetri Psaltis & Christophe Moser & Diego Ghezzi, 2024. "An actor-model framework for visual sensory encoding," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  3. Skander Mensi & Olivier Hagens & Wulfram Gerstner & Christian Pozzorini, 2016. "Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-38, February.
  4. Urs Köster & Jascha Sohl-Dickstein & Charles M Gray & Bruno A Olshausen, 2014. "Modeling Higher-Order Correlations within Cortical Microcolumns," PLOS Computational Biology, Public Library of Science, vol. 10(7), pages 1-12, July.
  5. Dimitri Yatsenko & Krešimir Josić & Alexander S Ecker & Emmanouil Froudarakis & R James Cotton & Andreas S Tolias, 2015. "Improved Estimation and Interpretation of Correlations in Neural Circuits," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-28, March.
  6. Guillaume Viejo & Thomas Cortier & Adrien Peyrache, 2018. "Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-25, March.
  7. Arno Onken & Valentin Dragoi & Klaus Obermayer, 2012. "A Maximum Entropy Test for Evaluating Higher-Order Correlations in Spike Counts," PLOS Computational Biology, Public Library of Science, vol. 8(6), pages 1-12, June.
  8. Lucas Rudelt & Daniel González Marx & Michael Wibral & Viola Priesemann, 2021. "Embedding optimization reveals long-lasting history dependence in neural spiking activity," PLOS Computational Biology, Public Library of Science, vol. 17(6), pages 1-51, June.
  9. Eric G. Wu & Nora Brackbill & Colleen Rhoades & Alexandra Kling & Alex R. Gogliettino & Nishal P. Shah & Alexander Sher & Alan M. Litke & Eero P. Simoncelli & E. J. Chichilnisky, 2024. "Fixational eye movements enhance the precision of visual information transmitted by the primate retina," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  10. Lars Buesing & Johannes Bill & Bernhard Nessler & Wolfgang Maass, 2011. "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons," PLOS Computational Biology, Public Library of Science, vol. 7(11), pages 1-22, November.
  11. Christian Donner & Klaus Obermayer & Hideaki Shimazaki, 2017. "Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-27, January.
  12. Niru Maheswaranathan & David B Kastner & Stephen A Baccus & Surya Ganguli, 2018. "Inferring hidden structure in multilayered neural circuits," PLOS Computational Biology, Public Library of Science, vol. 14(8), pages 1-30, August.
  13. Michelle F Craft & Andrea K Barreiro & Shree Hari Gautam & Woodrow L Shew & Cheng Ly, 2021. "Differences in olfactory bulb mitral cell spiking with ortho- and retronasal stimulation revealed by data-driven models," PLOS Computational Biology, Public Library of Science, vol. 17(9), pages 1-28, September.
  14. Philip A. White & Alan E. Gelfand, 2021. "Generalized Evolutionary Point Processes: Model Specifications and Model Comparison," Methodology and Computing in Applied Probability, Springer, vol. 23(3), pages 1001-1021, September.
  15. Michael E Rule & David Schnoerr & Matthias H Hennig & Guido Sanguinetti, 2019. "Neural field models for latent state inference: Application to large-scale neuronal recordings," PLOS Computational Biology, Public Library of Science, vol. 15(11), pages 1-23, November.
  16. Pengcheng Zhou & Shawn D Burton & Adam C Snyder & Matthew A Smith & Nathaniel N Urban & Robert E Kass, 2015. "Establishing a Statistical Link between Network Oscillations and Neural Synchrony," PLOS Computational Biology, Public Library of Science, vol. 11(10), pages 1-25, October.
  17. Chevallier, Julien, 2017. "Mean-field limit of generalized Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 127(12), pages 3870-3912.
  18. Stefano Recanatesi & Gabriel Koch Ocker & Michael A Buice & Eric Shea-Brown, 2019. "Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity," PLOS Computational Biology, Public Library of Science, vol. 15(7), pages 1-29, July.
  19. Liangyu Tao & Samuel P. Wechsler & Vikas Bhandawat, 2023. "Sensorimotor transformation underlying odor-modulated locomotion in walking Drosophila," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
  20. Srdjan Ostojic & Nicolas Brunel, 2011. "From Spiking Neuron Models to Linear-Nonlinear Models," PLOS Computational Biology, Public Library of Science, vol. 7(1), pages 1-16, January.
  21. Arne F Meyer & Jan-Philipp Diepenbrock & Max F K Happel & Frank W Ohl & Jörn Anemüller, 2014. "Discriminative Learning of Receptive Fields from Responses to Non-Gaussian Stimulus Ensembles," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-15, April.
  22. Seif Eldawlatly & Karim G Oweiss, 2011. "Millisecond-Timescale Local Network Coding in the Rat Primary Somatosensory Cortex," PLOS ONE, Public Library of Science, vol. 6(6), pages 1-14, June.
  23. Felipe Gerhard & Moritz Deger & Wilson Truccolo, 2017. "On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-31, February.
  24. Richard Naud & Wulfram Gerstner, 2012. "Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-14, October.
  25. Fanfan Li & Dingwei Li & Chuanqing Wang & Guolei Liu & Rui Wang & Huihui Ren & Yingjie Tang & Yan Wang & Yitong Chen & Kun Liang & Qi Huang & Mohamad Sawan & Min Qiu & Hong Wang & Bowen Zhu, 2024. "An artificial visual neuron with multiplexed rate and time-to-first-spike coding," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
  26. Braden A W Brinkman & Alison I Weber & Fred Rieke & Eric Shea-Brown, 2016. "How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?," PLOS Computational Biology, Public Library of Science, vol. 12(10), pages 1-34, October.
  27. Geyu Weng & Amir Akbarian & Kelsey Clark & Behrad Noudoost & Neda Nategh, 2024. "Neural correlates of perisaccadic visual mislocalization in extrastriate cortex," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  28. Schmutz, Valentin, 2022. "Mean-field limit of age and leaky memory dependent Hawkes processes," Stochastic Processes and their Applications, Elsevier, vol. 149(C), pages 39-59.
  29. Jan Humplik & Gašper Tkačik, 2017. "Probabilistic models for neural populations that naturally capture global coupling and criticality," PLOS Computational Biology, Public Library of Science, vol. 13(9), pages 1-26, September.
  30. Martin J M Lankheet & P Christiaan Klink & Bart G Borghuis & André J Noest, 2012. "Spike-Interval Triggered Averaging Reveals a Quasi-Periodic Spiking Alternative for Stochastic Resonance in Catfish Electroreceptors," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-11, March.
  31. Rong J. B. Zhu & Xue-Xin Wei, 2023. "Unsupervised approach to decomposing neural tuning variability," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  32. Xin Chen & Jeffrey M Beck & John M Pearson, 2017. "Neuron’s eye view: Inferring features of complex stimuli from neural responses," PLOS Computational Biology, Public Library of Science, vol. 13(8), pages 1-18, August.
  33. Thomas Bury, 2013. "Predicting trend reversals using market instantaneous state," Papers 1310.8169, arXiv.org, revised Mar 2014.
  34. Volker Pernice & Rava Azeredo da Silveira, 2018. "Interpretation of correlated neural variability from models of feed-forward and recurrent circuits," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-26, February.
  35. Anirban Das & Alec G. Sheffield & Anirvan S. Nandy & Monika P. Jadi, 2024. "Brain-state mediated modulation of inter-laminar dependencies in visual cortex," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  36. Maxim Volgushev & Vladimir Ilin & Ian H Stevenson, 2015. "Identifying and Tracking Simulated Synaptic Inputs from Neuronal Firing: Insights from In Vitro Experiments," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-31, March.
  37. Jason S Prentice & Olivier Marre & Mark L Ioffe & Adrianna R Loback & Gašper Tkačik & Michael J Berry II, 2016. "Error-Robust Modes of the Retinal Population Code," PLOS Computational Biology, Public Library of Science, vol. 12(11), pages 1-32, November.
  38. Yanyun Ren & Xiaobo Bu & Ming Wang & Yue Gong & Junjie Wang & Yuyang Yang & Guijun Li & Meng Zhang & Ye Zhou & Su-Ting Han, 2022. "Synaptic plasticity in self-powered artificial striate cortex for binocular orientation selectivity," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
  39. Amir Akbarian & Kelsey Clark & Behrad Noudoost & Neda Nategh, 2021. "A sensory memory to preserve visual representations across eye movements," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
  40. Benjamin Dunn & Maria Mørreaunet & Yasser Roudi, 2015. "Correlations and Functional Connections in a Population of Grid Cells," PLOS Computational Biology, Public Library of Science, vol. 11(2), pages 1-21, February.
  41. Julian Rossbroich & Daniel Trotter & John Beninger & Katalin Tóth & Richard Naud, 2021. "Linear-nonlinear cascades capture synaptic dynamics," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-27, March.
  42. Gašper Tkačik & Olivier Marre & Dario Amodei & Elad Schneidman & William Bialek & Michael J Berry II, 2014. "Searching for Collective Behavior in a Large Network of Sensory Neurons," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-23, January.
  43. Stojan Jovanović & Stefan Rotter, 2016. "Interplay between Graph Topology and Correlations of Third Order in Spiking Neuronal Networks," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-28, June.
  44. Cristiano Capone & Carla Filosa & Guido Gigante & Federico Ricci-Tersenghi & Paolo Del Giudice, 2015. "Inferring Synaptic Structure in Presence of Neural Interaction Time Scales," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-21, March.
  45. Noel Federman & Sebastián A. Romano & Macarena Amigo-Duran & Lucca Salomon & Antonia Marin-Burgin, 2024. "Acquisition of non-olfactory encoding improves odour discrimination in olfactory cortex," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
  46. Jonathan Rubin & Nachum Ulanovsky & Israel Nelken & Naftali Tishby, 2016. "The Representation of Prediction Error in Auditory Cortex," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-28, August.
  47. Daniel Durstewitz, 2017. "A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-33, June.
  48. Shinichiro Kira & Houman Safaai & Ari S. Morcos & Stefano Panzeri & Christopher D. Harvey, 2023. "A distributed and efficient population code of mixed selectivity neurons for flexible navigation decisions," Nature Communications, Nature, vol. 14(1), pages 1-28, December.
  49. Kenneth W. Latimer & David J. Freedman, 2023. "Low-dimensional encoding of decisions in parietal cortex reflects long-term training history," Nature Communications, Nature, vol. 14(1), pages 1-24, December.
  50. Bury, Thomas, 2014. "Predicting trend reversals using market instantaneous state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 79-91.
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