Integrating variational approaches to pattern formation into a deeper physics: Reply to comments on "Morphogenesis as Bayesian inference: A variational approach to pattern formation and manipulation in complex biological systems"
Phys Life Rev
.
2020 Jul:33:125-128.
doi: 10.1016/j.plrev.2020.07.001.
Epub 2020 Jul 10.
Authors
Franz Kuchling
1
,
Karl Friston
2
,
Georgi Georgiev
3
,
Michael Levin
4
Affiliations
1
Biology Department, Allen Discovery Center at Tufts University, Medford, MA, USA.
2
The Wellcome Trust Centre for Neuroimaging, Institute of Neurology, Queen Square, London, UK.
3
Assumption College, Department of Physics, 500 Salisbury St., Worcester, MA, USA.
4
Biology Department, Allen Discovery Center at Tufts University, Medford, MA, USA. Electronic address: Michael.Levin@tufts.edu.
PMID:
32682906
DOI:
10.1016/j.plrev.2020.07.001
No abstract available
Keywords:
Basal cognition; Development; Free energy; Pattern homeostasis.
Publication types
Research Support, Non-U.S. Gov't
Comment
MeSH terms
Bayes Theorem
Morphogenesis
Physics*