TY - JOUR
AU - 
AB - UC Berkeley UC Berkeley Previously Published Works Title Permalink https://escholarship.org/uc/item/1hj0g59z Authors Freeman, Walter J, III Kozma, Robert Bollobás, Béla et al. Publication Date License https://creativecommons.org/licenses/by/3.0/ 4.0 Peer reviewed eScholarship.org Powered by the California Digital Library University of California 1 1 2 2,3 Walter J. Freeman , Robert Kozma , with an appendix by Bela ´ Bollobas ´ , and Oliver Riordan University of California at Berkeley, Berkeley, CA 94720, USA University of Memphis, Memphis TN 38152, USA Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, Cambridge CB3 0WB, UK. Research supported in part by NSF grants DMS-0505550, CNS-0721983 and CCF-0728928, and ARO grant W911NF-06-1-0076. Mathematical Institute, University of Oxford, 24–29 St Giles’, Oxford OX1 3LB, United Kingdom Summary. Modeling brain dynamics requires us to define the behavioral context in which brains interact with the world; to choose appropriate mathematics, here ordinary differential equations (ODE) and random graph theory (RGT); to choose the levels of description and scales in the hierarchy of neurodynamics; to define an appropriate module for each level; and to address questions of boundary conditions, linearity, time-variance, autonomy, and critical- ity. ODE applied to the olfactory system serves to model perception by a phase transition 
TI - Scale-Free Cortical Planar Networks
JF - Handbook of Large-Scale Random Networks
DO - 10.1007/978-3-540-69395-6_7
DA - 2008-01-01
UR - https://www.deepdyve.com/lp/unpaywall/scale-free-cortical-planar-networks-8K3HArcVlr
DP - DeepDyve
ER -