Publications

For a full list of publications, see our Google Scholar.

Preprints:

  • Christopher W. Lynn, Qiwei Yu, Rich Pang, William Bialek, and Stephanie E. Palmer. Exactly solvable statistical physics models for large neuronal populations. | arXiv

  • Christopher W. Lynn, Qiwei Yu, Rich Pang, Stephanie E. Palmer, and William Bialek. Exact minimax entropy models of large-scale neuronal activity. | arXiv

  • Sebastian M. Geli, Christopher W. Lynn, Morten L. Kringelbach, Gustavo Deco, Yonatan Sanz Per. Non-equilibrium whole-brain dynamics arise from pairwise interactions.

2024:

  • David H. Wolpert, Jan Korbel, Christopher W. Lynn, et al. Is stochastic thermodynamics the key to understanding the energy costs of computation? PNAS (2024). | arXiv
  • Kenneth Shinozuka, Prejaas Twearie, Andrea Luppi, Christopher W. Lynn, et al. LSD flattens the hierarchy of directed information flow in fast whole-brain dynamics. Imaging Neuroscience (2024). | bioRxiv

  • Richard E. Rosch, Dominic R. W. Burrows, Christopher W. Lynn, and Arian Ashourvan. Spontaneous brain activity emerges from pairwise interactions in the larval zebrafish brain. Physical Review X (2024). | PRX

  • Christopher W. Lynn, Caroline M. Holmes, and Stephanie E. Palmer. Emergent scale-free networks. PNAS Nexus (2024). | PNAS Nexus

  • Xiaohuan Xia, Andrei A. Klishin, Jennifer Stiso, Christopher W. Lynn, Ari E. Kahn, Lorenzo Caciagli, and Dani S. Bassett. Human learning of hierarchical graphs. Physical Review E (2024).| PRE

  • Suman Kulkarni, Sophia U. David, Christopher W. Lynn, and Dani S. Bassett. Information content of note transitions in the music of J. S. Bach. Physical Review Research (2024). | PRR

  • Christopher W. Lynn, Caroline M. Holmes, and Stephanie E. Palmer. Heavy-tailed neuronal connectivity arises from Hebbian self-organization. Nature Physics (2024). | Nat Phys

2023:

  • Gustavo Deco, Christopher W. Lynn, Yonatan Sanz Perl, and Morten L. Kringelbach. Violations of the fluctuation-dissipation theorem reveal distinct non-equilibrium dynamics of brain states. Physical Review E (2023). | Phys Rev E

  • Shubhankar P. Patankar, Dale Zhou, Christopher W. Lynn, Jason Z. Kim, Mathieu Ouellet, Harang Ju, Perry Zurn, David M. Lydon-Staley, and Dani S. Bassett. Curiosity as filling, compressing, and reconfiguring knowledge networks. Collective Intelligence (2023). | Coll Intell

2022:

  • Erin G. Teich, Jason Z. Kim,  Christopher W. Lynn, Samantha C. Simon, Andrei A. Klishin, Karol P. Szymula, Pragya Srivastava, Lee C. Bassett, Perry Zurn, Jordan D. Dworkin, Dani S. Bassett. Citation inequity and gendered citation practices in contemporary physics. Nature Physics (2022). | Nat Phys

  • Christopher W. Lynn, Caroline M. Holmes, William Bialek, and David J. Schwab. Decomposing the local arrow of time in interacting systems. Physical Review Letters (2022). | PRL

  • Christopher W. Lynn, Caroline M. Holmes, William Bialek, and David J. Schwab. Emergence of local irreversibility in complex interacting systems. Physical Review E (2022). | PRE

  • William Qian, Christopher W. Lynn, Andrei A. Klishin, Jennifer Stiso, Nicolas H. Christianson, and Dani S. Bassett. Optimizing the human learnability of abstract network representations. Proceedings of the National Academy of Sciences (2022). | PNAS

  • Sophia U. David, Sophie E. Loman, Christopher W. Lynn, Ann S. Blevins, Mathieu Ouellet, and Dani S. Bassett. How we learn about our networked world. Frontiers for Young Minds (2022). | Front Young Minds

  • Dale Zhou, Christopher W. Lynn, Zaixu Cui, Rastko Ciric, Graham L. Baum, Tyler M. More, David R. Roalf, John A. Detre, Ruben C. Gur, Raquel E. Gur, Theodore D. Satterthwaite, and Dani S. Bassett. Efficient coding in the economics of human brain connectomics. Network Neuroscience (2022). | Netw Neurosci

  • Jennifer Stiso, Christopher W. Lynn, Ari E. Kahn, Vinitha Rangarajan, Karol P. Szymula, Ryan Archer, Andrew Revell, Joel M. Stein, Brian Litt, Kathryn A. Davis, Timothy H. Lucas, and Dani S. Bassett. Neurophysiological evidence for cognitive map formation during sequence learning. eNeuro (2022). | eNeuro

2021:

  • Christopher W. Lynn, Eli J. Cornblath, Lia Papadopoulos, Maxwell A. Bertolero, and Dani S. Bassett. Broken detailed balance and entropy production in the human brain. Proceedings of the National Academy of Sciences (2021). | PNAS

  • Christopher W. Lynn and Dani S. Bassett. Quantifying the compressibility of complex networks. Proceedings of the National Academy of Sciences (2021). | PNAS

  • Arian Ashourvan, Preya Shah, Adam Pines, Shi Gu, Christopher W. Lynn, Dani S. Bassett, Katheryn A. Davis, and Brian Litt. Pairwise maximum entropy model explains the role of white matter structure in shaping emergent co-activation states. Communications Biology (2021). | Commun Biol

2020:

  • Christopher W. Lynn and Dani S. Bassett. How humans learn and represent networks. Proceedings of the National Academy of Sciences (2020). | PNAS

  • Lia Papadopoulos, Christopher W. Lynn, Demian Battaglia, and Dani S. Bassett. Relations between large-scale brain connectivity and effects of regional stimulation depend on collective dynamical state. PLOS Computational Biology (2020). | PLOS Comput Biol

  • Christopher W. Lynn, Lia Papadopoulos, Ari E. Kahn, and Dani S. Bassett. Human information processing in complex networks. Nature Physics (2020). | Nat Phys

  • Christopher W. Lynn, Ari E. Kahn, Nathaniel Nyema, and Dani S. Bassett. Abstract representations of events arise from mental errors in learning and memory. Nature Communications (2020). | Nat Commun

2019:

  • Christopher W. Lynn and Dani S. Bassett. The physics of brain network structure, function, and control. Nature Reviews Physics (2019). | Nat Rev Phys

  • Christopher W. Lynn, Lia Papadopoulos, Daniel D. Lee, and Dani S. Bassett. Surges of collective human activity emerge from simple pairwise correlations. Physical Review X (2019). | Phys Rev X

≤2018:

  • Christopher W. Lynn and Daniel D. Lee. Maximizing Activity in Ising Networks via the TAP Approximation. In Association for the Advancement of Artificial Intelligence (2018). | AAAI

  • Christopher W. Lynn and Daniel D. Lee. Statistical Mechanics of Influence Maximization with Thermal Noise. Europhysics Letters (2017). | EPL

  • Christopher W. Lynn and Daniel D. Lee. Maximizing Influence in an Ising Network: A Mean-Field Optimal Solution. In Advances in Neural Information Processing Systems (2016). | NeurIPS

  • Tanaji Sen and Christopher Lynn. Spectral Brilliance of Channeling Radiation at the ASTA Photoinjector. International Journal of Modern Physics A (2014). | Int J Mod Phys A