Title
Signatures of criticality in a maximum entropy model of the C. elegans brain during free behaviour.
Abstract
A popular hypothesis suggests that the nervous system of different organisms, from neural tissue to whole brains, may operate at or near a critical point. During the last decade, maximum entropy techniques have allowed to go beyond merely finding statistical signatures of criticality, to models directly inferred from data recorded in neural cultures, providing stronger evidence of criticality in neural activity. Nevertheless, these modeling techniques are restricted to neural cultures and have not been extended to neural tissue in living organisms. In this paper, we extend this line of research by analyzing signatures of criticality in a pairwise maximum entropy model inferred from neural recordings of C. elegans during freely-moving locomotion. From the analysis of the inferred models we find some signatures of criticality, as a divergence of the heat capacity of the system. Other indicators, such as Zipf's distributions, were not found. However, inspecting a similar analysis based in a 2D lattice Ising model we suggest that this could be due to the restricted number of samples in our data set. The availability of larger recordings of the C. elegans neural system during free locomotion could provide more conclusive results.
Year
Venue
Field
2017
FOURTEENTH EUROPEAN CONFERENCE ON ARTIFICIAL LIFE (ECAL 2017)
Statistical physics,Pairwise comparison,Zipf's law,Divergence,Lattice (order),Computer science,Critical point (thermodynamics),Ising model,Artificial intelligence,Criticality,Principle of maximum entropy
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Miguel Aguilera134.11
Carlos Alquézar200.34
Eduardo Izquierdo3467.91