IDEAS home Printed from https://ideas.repec.org/r/nat/nature/v440y2006i7087d10.1038_nature04701.html
   My bibliography  Save this item

Weak pairwise correlations imply strongly correlated network states in a neural population

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Fred Glover & Gary Kochenberger & Rick Hennig & Yu Du, 2022. "Quantum bridge analytics I: a tutorial on formulating and using QUBO models," Annals of Operations Research, Springer, vol. 314(1), pages 141-183, July.
  2. Emili Balaguer-Ballester & Christopher C Lapish & Jeremy K Seamans & Daniel Durstewitz, 2011. "Attracting Dynamics of Frontal Cortex Ensembles during Memory-Guided Decision-Making," PLOS Computational Biology, Public Library of Science, vol. 7(5), pages 1-19, May.
  3. Duy Duong-Tran & Ralph Kaufmann & Jiong Chen & Xuan Wang & Sumita Garai & Frederick H. Xu & Jingxuan Bao & Enrico Amico & Alan D. Kaplan & Giovanni Petri & Joaquin Goni & Yize Zhao & Li Shen, 2024. "Homological Landscape of Human Brain Functional Sub-Circuits," Mathematics, MDPI, vol. 12(3), pages 1-25, January.
  4. Hongli Zeng & R'emi Lemoy & Mikko Alava, 2013. "Financial interaction networks inferred from traded volumes," Papers 1311.3871, arXiv.org.
  5. Eddie Nijholt & Jorge Luis Ocampo-Espindola & Deniz Eroglu & István Z. Kiss & Tiago Pereira, 2022. "Emergent hypernetworks in weakly coupled oscillators," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
  6. Cofré, Rodrigo & Cessac, Bruno, 2013. "Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses," Chaos, Solitons & Fractals, Elsevier, vol. 50(C), pages 13-31.
  7. Fred Glover & Gary Kochenberger & Yu Du, 2019. "Quantum Bridge Analytics I: a tutorial on formulating and using QUBO models," 4OR, Springer, vol. 17(4), pages 335-371, December.
  8. Simona Cocco & Remi Monasson & Martin Weigt, 2013. "From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction," PLOS Computational Biology, Public Library of Science, vol. 9(8), pages 1-17, August.
  9. Polanski, Arnold & Stoja, Evarist, 2016. "Extreme risk interdependence," ESRB Working Paper Series 12, European Systemic Risk Board.
  10. 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.
  11. Montani, Fernando & Phoka, Elena & Portesi, Mariela & Schultz, Simon R., 2013. "Statistical modelling of higher-order correlations in pools of neural activity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(14), pages 3066-3086.
  12. Alves, Luiz G.A. & Andrade, José S. & Hanley, Quentin S. & Ribeiro, Haroldo V., 2019. "The hidden traits of endemic illiteracy in cities," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 566-574.
  13. 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.
  14. 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.
  15. Rava Azeredo da Silveira & Michael J Berry II, 2014. "High-Fidelity Coding with Correlated Neurons," PLOS Computational Biology, Public Library of Science, vol. 10(11), pages 1-25, November.
  16. Thomas Bury, 2012. "Statistical pairwise interaction model of stock market," Papers 1206.4420, arXiv.org, revised Jan 2014.
  17. Lipovetsky, Stan, 2018. "Quantum paradigm of probability amplitude and complex utility in entangled discrete choice modeling," Journal of choice modelling, Elsevier, vol. 27(C), pages 62-73.
  18. Xiaochuan Zhao & Germán Plata & Purushottam D Dixit, 2021. "SiGMoiD: A super-statistical generative model for binary data," PLOS Computational Biology, Public Library of Science, vol. 17(8), pages 1-13, August.
  19. Takafumi Arakaki & G Barello & Yashar Ahmadian, 2019. "Inferring neural circuit structure from datasets of heterogeneous tuning curves," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-38, April.
  20. Rodrigo P. Rocha & Loren Koçillari & Samir Suweis & Michele Filippo De Grazia & Michel Thiebaut Schotten & Marco Zorzi & Maurizio Corbetta, 2022. "Recovery of neural dynamics criticality in personalized whole-brain models of stroke," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
  21. Richard R Stein & Debora S Marks & Chris Sander, 2015. "Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models," PLOS Computational Biology, Public Library of Science, vol. 11(7), pages 1-22, July.
  22. 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.
  23. Miguel Aguilera, 2018. "Rhythms of the Collective Brain: Metastable Synchronization and Cross-Scale Interactions in Connected Multitudes," Complexity, Hindawi, vol. 2018, pages 1-9, March.
  24. Montangie, Lisandro & Montani, Fernando, 2015. "Quantifying higher-order correlations in a neuronal pool," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 388-400.
  25. Xiaokan Guo & James Q Boedicker, 2016. "The Contribution of High-Order Metabolic Interactions to the Global Activity of a Four-Species Microbial Community," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-13, September.
  26. Valle, Mauricio A. & Ruz, Gonzalo A. & Rica, Sergio, 2019. "Market basket analysis by solving the inverse Ising problem: Discovering pairwise interaction strengths among products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 36-44.
  27. Jian Zhou & Olga G Troyanskaya, 2014. "Global Quantitative Modeling of Chromatin Factor Interactions," PLOS Computational Biology, Public Library of Science, vol. 10(3), pages 1-13, March.
  28. 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.
  29. Mark L Ioffe & Michael J Berry II, 2017. "The structured ‘low temperature’ phase of the retinal population code," PLOS Computational Biology, Public Library of Science, vol. 13(10), pages 1-31, October.
  30. Hideaki Shimazaki & Shun-ichi Amari & Emery N Brown & Sonja Grün, 2012. "State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data," PLOS Computational Biology, Public Library of Science, vol. 8(3), pages 1-27, March.
  31. Ovidiu F Jurjuţ & Danko Nikolić & Wolf Singer & Shan Yu & Martha N Havenith & Raul C Mureşan, 2011. "Timescales of Multineuronal Activity Patterns Reflect Temporal Structure of Visual Stimuli," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-15, February.
  32. Ross S Williamson & Maneesh Sahani & Jonathan W Pillow, 2015. "The Equivalence of Information-Theoretic and Likelihood-Based Methods for Neural Dimensionality Reduction," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-31, April.
  33. Rajita Menon & Vivek Ramanan & Kirill S Korolev, 2018. "Interactions between species introduce spurious associations in microbiome studies," PLOS Computational Biology, Public Library of Science, vol. 14(1), pages 1-20, January.
  34. Bury, Thomas, 2014. "Predicting trend reversals using market instantaneous state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 79-91.
  35. Bozhokin, S.V. & Suslova, I.B., 2015. "Wavelet-based analysis of spectral rearrangements of EEG patterns and of non-stationary correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 151-160.
  36. Katarína Bod’ová & Enikő Szép & Nicholas H Barton, 2021. "Dynamic maximum entropy provides accurate approximation of structured population dynamics," PLOS Computational Biology, Public Library of Science, vol. 17(12), pages 1-22, December.
  37. 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.
  38. MohammadReza Zahedian & Mahsa Bagherikalhor & Andrey Trufanov & G. Reza Jafari, 2022. "Financial Crisis in the Framework of Non-zero Temperature Balance Theory," Papers 2202.03198, arXiv.org.
  39. 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.
  40. 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.
  41. 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.
  42. Polanski, Arnold & Stoja, Evarist, 2015. "Extreme risk interdependence," Bank of England working papers 563, Bank of England.
  43. N Blasco & P Corredor & S Ferreruela, 2011. "Detecting intentional herding: what lies beneath intraday data in the Spanish stock market," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1056-1066, June.
  44. Sinisa Pajevic & Dietmar Plenz, 2009. "Efficient Network Reconstruction from Dynamical Cascades Identifies Small-World Topology of Neuronal Avalanches," PLOS Computational Biology, Public Library of Science, vol. 5(1), pages 1-20, January.
  45. Porta Mana, PierGianLuca & Rostami, Vahid & Torre, Emiliano & Roudi, Yasser, 2018. "Maximum-entropy and representative samples of neuronal activity: a dilemma," OSF Preprints uz29n, Center for Open Science.
  46. Barbara Casillas-Pérez & Katarína Boďová & Anna V. Grasse & Gašper Tkačik & Sylvia Cremer, 2023. "Dynamic pathogen detection and social feedback shape collective hygiene in ants," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  47. 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.
  48. Marco Mancastroppa & Iacopo Iacopini & Giovanni Petri & Alain Barrat, 2023. "Hyper-cores promote localization and efficient seeding in higher-order processes," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  49. Rachata Muneepeerakul & José Lobo & Shade T Shutters & Andrés Goméz-Liévano & Murad R Qubbaj, 2013. "Urban Economies and Occupation Space: Can They Get “There” from “Here”?," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-8, September.
  50. Timothy R Lezon & Ivet Bahar, 2010. "Using Entropy Maximization to Understand the Determinants of Structural Dynamics beyond Native Contact Topology," PLOS Computational Biology, Public Library of Science, vol. 6(6), pages 1-12, June.
  51. Xiaoyuan Liu & Hayato Ushijima-Mwesigwa & Avradip Mandal & Sarvagya Upadhyay & Ilya Safro & Arnab Roy, 2022. "Leveraging special-purpose hardware for local search heuristics," Computational Optimization and Applications, Springer, vol. 82(1), pages 1-29, May.
  52. Gaëlle Desbordes & Jianzhong Jin & Chong Weng & Nicholas A Lesica & Garrett B Stanley & Jose-Manuel Alonso, 2008. "Timing Precision in Population Coding of Natural Scenes in the Early Visual System," PLOS Biology, Public Library of Science, vol. 6(12), pages 1-11, December.
  53. Lisewski, Andreas Martin & Lichtarge, Olivier, 2010. "Untangling complex networks: Risk minimization in financial markets through accessible spin glass ground states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3250-3253.
  54. Sacha Jennifer van Albada & Moritz Helias & Markus Diesmann, 2015. "Scalability of Asynchronous Networks Is Limited by One-to-One Mapping between Effective Connectivity and Correlations," PLOS Computational Biology, Public Library of Science, vol. 11(9), pages 1-37, September.
  55. Yasser Roudi & Sheila Nirenberg & Peter E Latham, 2009. "Pairwise Maximum Entropy Models for Studying Large Biological Systems: When They Can Work and When They Can't," PLOS Computational Biology, Public Library of Science, vol. 5(5), pages 1-18, May.
  56. Jasleen Gundh & Awaneesh Singh & R K Brojen Singh, 2015. "Ordering Dynamics in Neuron Activity Pattern Model: An Insight to Brain Functionality," PLOS ONE, Public Library of Science, vol. 10(10), pages 1-16, October.
  57. Bury, Thomas, 2013. "Market structure explained by pairwise interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(6), pages 1375-1385.
  58. Sahar Gelfman & Quanli Wang & Yi-Fan Lu & Diana Hall & Christopher D Bostick & Ryan Dhindsa & Matt Halvorsen & K Melodi McSweeney & Ellese Cotterill & Tom Edinburgh & Michael A Beaumont & Wayne N Fran, 2018. "meaRtools: An R package for the analysis of neuronal networks recorded on microelectrode arrays," PLOS Computational Biology, Public Library of Science, vol. 14(10), pages 1-20, October.
  59. Shohei Hidaka & Masafumi Oizumi, 2018. "Fast and exact search for the partition with minimal information loss," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-14, September.
  60. Korosh Mahmoodi & Bruce J. West & Paolo Grigolini, 2018. "Self-Organized Temporal Criticality: Bottom-Up Resilience versus Top-Down Vulnerability," Complexity, Hindawi, vol. 2018, pages 1-10, March.
  61. P. Fraundorf, 2019. "Task-Layer Multiplicity as a Measure of Community Level Health," Complexity, Hindawi, vol. 2019, pages 1-8, July.
  62. Thomas Bury, 2013. "Predicting trend reversals using market instantaneous state," Papers 1310.8169, arXiv.org, revised Mar 2014.
  63. Thomas Bury, 2013. "A statistical physics perspective on criticality in financial markets," Papers 1310.2446, arXiv.org, revised Jan 2014.
  64. Xi, Ning & Muneepeerakul, Rachata & Azaele, Sandro & Wang, Yougui, 2014. "Maximum entropy model for business cycle synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 189-194.
  65. 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.
  66. Zhang, Qi & Li, Meizhu, 2022. "A betweenness structural entropy of complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
  67. Maulana, Ardian & Situngkir, Hokky, 2015. "Korelasi Bebas-skala dalam Studi Geo-politik Pemilihan [Scale-free correlation within Geopolitics of Election Studies]," MPRA Paper 66351, University Library of Munich, Germany.
  68. 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.
  69. 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.
  70. Gabriel Baglietto & Guido Gigante & Paolo Del Giudice, 2017. "Density-based clustering: A ‘landscape view’ of multi-channel neural data for inference and dynamic complexity analysis," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-25, April.
  71. Einat Granot-Atedgi & Gašper Tkačik & Ronen Segev & Elad Schneidman, 2013. "Stimulus-dependent Maximum Entropy Models of Neural Population Codes," PLOS Computational Biology, Public Library of Science, vol. 9(3), pages 1-14, March.
  72. Zhong, Li-Xin & Xu, Wen-Juan & Chen, Rong-Da & Zhong, Chen-Yang & Qiu, Tian & Shi, Yong-Dong & Wang, Li-Liang, 2016. "A generalized voter model with time-decaying memory on a multilayer network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 458(C), pages 95-105.
  73. Arno Onken & Steffen Grünewälder & Matthias H J Munk & Klaus Obermayer, 2009. "Analyzing Short-Term Noise Dependencies of Spike-Counts in Macaque Prefrontal Cortex Using Copulas and the Flashlight Transformation," PLOS Computational Biology, Public Library of Science, vol. 5(11), pages 1-13, November.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.