no code implementations • 28 Feb 2024 • Bryan C. Daniels, Enrico Borriello
Previous work in Boolean dynamical networks has suggested that the number of components that must be controlled to select an existing attractor is typically set by the number of attractors admitted by the dynamics, with no dependence on the size of the network.
1 code implementation • 2 Aug 2021 • Edward D. Lee, Xiaowen Chen, Bryan C. Daniels
Applying the protocol to a minimal model of C. elegans neural activity, we find that collective neural statistics are most sensitive to a few principal perturbative modes.
no code implementations • 22 Oct 2020 • Enrico Borriello, Bryan C. Daniels
Effective control of biological systems can often be achieved through the control of a surprisingly small number of distinct variables.
1 code implementation • 31 Jul 2020 • Sebastiano Stramaglia, Tomas Scagliarini, Bryan C. Daniels, Daniele Marinazzo
We address the problem of efficiently and informatively quantifying how multiplets of variables carry information about the future of the dynamical system they belong to.
no code implementations • 25 Sep 2018 • Bryan C. Daniels, William S. Ryu, Ilya Nemenman
The roundworm C. elegans exhibits robust escape behavior in response to rapidly rising temperature.
2 code implementations • 24 Jan 2018 • Edward D. Lee, Bryan C. Daniels
ConIII (pronounced CON-ee) is an open-source Python project providing a simple interface to solving maximum entropy models, with a focus on the Ising model.
Quantitative Methods Statistical Mechanics Computational Physics
no code implementations • 24 Apr 2014 • Bryan C. Daniels, Ilya Nemenman
Such adaptive models lead to accurate predictions even when microscopic details of the studied systems are unknown due to insufficient data.
