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Critical branching captures activity in living neural networks and maximizes the number of metastable states

Citation:
Haldeman C and Beggs JM (2005). Critical branching captures activity in living neural networks and maximizes the number of metastable states. Physical Review Letters 94(058101).


Abstract:
Recent experimental work has shown that activity in living neural networks can propagate as a critical branching process that revisits many metastable states. Neural network theory suggests that attracting states could store information, but little is known about how a branching process could form such states. Here we use a branching process to model actual data and to explore metastable states in the network. When we tune the branching parameter to the critical point, we find that metastable states are most numerous and that network dynamics are not attracting, but neutral.

PACS numbers: 05.70.Jk, 87.18.Sn, 87.19.La, 89.75.Fb


Additional Notes:

Funded by the National Science Foundation [nsf.gov]


Other Information:
Added by: jbeggs 10 Feb 2005 9:14 PM
Last modified by: jbeggs 16 Feb 2005 9:14 PM
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Paper ID: 13

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