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pro vyhledávání: '"Beer, Randall D."'
Autor:
Beer, Randall D.
Garden of Eden (GOE) states in cellular automata are grid configurations which have no precursors, that is, they can only occur as initial conditions. Finding individual configurations that minimize or maximize some criterion of interest (e.g., grid
Externí odkaz:
http://arxiv.org/abs/2210.07837
Autor:
Beer, Randall D.
Publikováno v:
Biological Cybernetics (2022) 116:501-515
If we are ever to move beyond the study of isolated special cases in theoretical neuroscience, we need to develop more general theories of neural circuits over a given neural model. The present paper considers this challenge in the context of continu
Externí odkaz:
http://arxiv.org/abs/2111.04547
Akademický článek
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Publikováno v:
In BioSystems January 2023 223
Akademický článek
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Autor:
Beer, Randall D.
Publikováno v:
Chaos 27:111104 (2017)
Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This pa
Externí odkaz:
http://arxiv.org/abs/1711.04563
Despite the relative simplicity of C. elegans, its locomotion machinery is not yet well understood. We focus on the generation of dorsoventral body bends. While central pattern generators are commonly involved in animal locomotion, their presence in
Externí odkaz:
http://arxiv.org/abs/1705.02301
Publikováno v:
PLoS ONE 10(10): e0140397. (2015)
Understanding how information about external stimuli is transformed into behavior is one of the central goals of neuroscience. Here we characterize the information flow through a complete sensorimotor circuit: from stimulus, to sensory neurons, to in
Externí odkaz:
http://arxiv.org/abs/1502.04262
Autor:
Williams, Paul L., Beer, Randall D.
Transfer entropy provides a general tool for analyzing the magnitudes and directions---but not the \emph{kinds}---of information transfer in a system. We extend transfer entropy in two complementary ways. First, we distinguish state-dependent from st
Externí odkaz:
http://arxiv.org/abs/1102.1507
Autor:
Beer, Randall D., Daniels, Bryan
From genetic regulatory networks to nervous systems, the interactions between elements in biological networks often take a sigmoidal or S-shaped form. This paper develops a probabilistic characterization of the parameter space of continuous-time sigm
Externí odkaz:
http://arxiv.org/abs/1010.1714