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Computational Brain & Behavior|July 16, 2026
Continuous Attractor Networks for Laplace Neural ManifoldsBryan C Daniels, Marc W HowardNature Communications|August 22, 2015
Automated adaptive inference of phenomenological dynamical modelsBryan C Daniels, Ilya NemenmanNature Communications|September 2, 2021
The basis of easy controllability in Boolean networksEnrico Borriello, Bryan C DanielsTheory in Biosciences = Theorie in Den Biowissenschaften|February 26, 2021
Quantifying the impact of network structure on speed and accuracy in collective decision-makingBryan C Daniels, Pawel RomanczukPlos One|March 26, 2015
Efficient inference of parsimonious phenomenological models of cellular dynamics using S-systems and alternating regressionBryan C Daniels, Ilya NemenmanPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 24, 2011
Nucleation at the DNA supercoiling transitionBryan C Daniels, James P SethnaJournal of the Royal Society, Interface|February 10, 2026
Tuning regimes in ant foraging dynamics depend on the existence of bistabilityColin M Lynch, Bryan C DanielsCurrent Opinion in Behavioral Sciences|August 29, 2017
Temporal and spatial context in the mind and brainMarc W HowardTrends in Cognitive Sciences|February 2, 2018
Memory as Perception of the Past: Compressed Time inMind and BrainMarc W HowardProceedings of the National Academy of Sciences of the United States of America|March 24, 2019
Automated, predictive, and interpretable inference of Caenorhabditis elegans escape dynamicsBryan C Daniels, William S Ryu, Ilya NemenmanPageof 9