John M. Beggs

Cognitive Neuroscience · 2003–2012

A researcher in the Science corpus: 5 papers; trusts 37 researchers and is trusted by 60 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 42 citations into it; #376 of 10,852 by trust here, #1,393 by citations
• Cellular and Molecular Neuroscience — 20 citations into it; #159 of 2,998 by trust here, #757 by citations
• Artificial Intelligence — 14 citations into it
• Statistical and Nonlinear Physics — 11 citations into it; #348 of 10,127 by trust here, #793 by citations
• Electrical and Electronic Engineering — 10 citations into it; #1,543 of 16,539 by trust here, #7,175 by citations
• Computer Networks and Communications — 7 citations into it
• Economics and Econometrics — 7 citations into it

Whom John M. Beggs trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. C. Haldeman
2. Wolfgang Maass
3. Thomas Natschläger
4. Dietmar Plenz
5. Tim P. Vogels
6. Aaron Clauset
7. Mark Newman
8. Shan Yu
9. Osame Kinouchi
10. Gasper Tkacik

Who trusts John M. Beggs overall

1. Paolo Moretti
2. Miguel Angel Muñoz
3. Woodrow L. Shew
4. Manfred G. Kitzbichler
5. Marcus Kaiser
6. Luca Cocchi
7. Dimitrije Marković
8. Andrew Zalesky
9. Alexander A. Fingelkurts
10. Janina Hesse

Papers from John M. Beggs's perspective

Ordered by how strongly the researchers John M. Beggs trusts endorse each paper. Same corpus, a different order for every researcher.

1. Neuronal Avalanches in Neocortical Circuits (Journal of Neuroscience)
2. Real-Time Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
3. Information Theory and Statistical Mechanics
4. Weak pairwise correlations imply strongly correlated network states in a neural population
5. Real-Time Computation at the Edge of Chaos in Recurrent Neural Networks (Neural Computation)
6. Modeling brain function: the world of attractor neural networks, 1st Edition
7. Dynamics of Ongoing Activity: Explanation of the Large Variability in Evoked Cortical Responses
8. Information Theory: 1948-1998 - Guest Editorial
9. Neuronal Avalanches Imply Maximum Dynamic Range in Cortical Networks at Criticality (Journal of Neuroscience)
10. Optimal dynamical range of excitable networks at criticality

Their papers

• Critical branching captures activity in living neural networks and maximizes the number of metastable States. (2005) — 435 citations
• The criticality hypothesis: how local cortical networks might optimize information processing (2008) — 509 citations
• Being Critical of Criticality in the Brain (2012) — 512 citations
• A Maximum Entropy Model Applied to Spatial and Temporal Correlations from Cortical Networks In Vitro (2008) — 302 citations
• Neuronal Avalanches in Neocortical Circuits (2003) — 2,196 citations