Multistability and Long-Timescale Transients Encoded by Network Structure in a Model of C. elegans Connectome Dynamics
The neural dynamics of the nematode Caenorhabditis elegans are experimentally low-dimensional and may be understood as long-timescale transitions between multiple low-dimensional attractors. Previous modeling work has found that dynamic models of the worm's full neuronal network are capable of...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2017-06-01
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Series: | Frontiers in Computational Neuroscience |
Subjects: | |
Online Access: | http://journal.frontiersin.org/article/10.3389/fncom.2017.00053/full |