Abstract

We quantify observability in small (3 node) neuronal networks as a function of 1) the connection topology and symmetry, 2) the measured nodes, and 3) the nodal dynamics (linear and nonlinear). We find that typical observability metrics for 3 neuron motifs range over several orders of magnitude, depending upon topology, and for motifs containing symmetry the network observability decreases when observing from particularly confounded nodes. Nonlinearities in the nodal equations generally decrease the average network observability and full network information becomes available only in limited regions of the system phase space. Our findings demonstrate that such networks are partially observable, and suggest their potential efficacy in reconstructing network dynamics from limited measurement data. How well such strategies can be used to reconstruct and control network dynamics in experimental settings is a subject for future experimental work.

Original languageEnglish (US)
Title of host publication2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
DOIs
StatePublished - Nov 12 2012
Event2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 - Princeton, NJ, United States
Duration: Mar 21 2012Mar 23 2012

Publication series

Name2012 46th Annual Conference on Information Sciences and Systems, CISS 2012

Other

Other2012 46th Annual Conference on Information Sciences and Systems, CISS 2012
CountryUnited States
CityPrinceton, NJ
Period3/21/123/23/12

Fingerprint

Observability
Topology
Neurons

All Science Journal Classification (ASJC) codes

  • Information Systems

Cite this

Whalen, A. J., Brennan, S. N., Sauer, T. D., & Schiff, S. J. (2012). Observability of neuronal network motifs. In 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012 [6310923] (2012 46th Annual Conference on Information Sciences and Systems, CISS 2012). https://doi.org/10.1109/CISS.2012.6310923
Whalen, Andrew J. ; Brennan, Sean N. ; Sauer, Timothy D. ; Schiff, Steven J. / Observability of neuronal network motifs. 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012. 2012. (2012 46th Annual Conference on Information Sciences and Systems, CISS 2012).
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abstract = "We quantify observability in small (3 node) neuronal networks as a function of 1) the connection topology and symmetry, 2) the measured nodes, and 3) the nodal dynamics (linear and nonlinear). We find that typical observability metrics for 3 neuron motifs range over several orders of magnitude, depending upon topology, and for motifs containing symmetry the network observability decreases when observing from particularly confounded nodes. Nonlinearities in the nodal equations generally decrease the average network observability and full network information becomes available only in limited regions of the system phase space. Our findings demonstrate that such networks are partially observable, and suggest their potential efficacy in reconstructing network dynamics from limited measurement data. How well such strategies can be used to reconstruct and control network dynamics in experimental settings is a subject for future experimental work.",
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Whalen, AJ, Brennan, SN, Sauer, TD & Schiff, SJ 2012, Observability of neuronal network motifs. in 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012., 6310923, 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012, 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012, Princeton, NJ, United States, 3/21/12. https://doi.org/10.1109/CISS.2012.6310923

Observability of neuronal network motifs. / Whalen, Andrew J.; Brennan, Sean N.; Sauer, Timothy D.; Schiff, Steven J.

2012 46th Annual Conference on Information Sciences and Systems, CISS 2012. 2012. 6310923 (2012 46th Annual Conference on Information Sciences and Systems, CISS 2012).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AU - Whalen, Andrew J.

AU - Brennan, Sean N.

AU - Sauer, Timothy D.

AU - Schiff, Steven J.

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N2 - We quantify observability in small (3 node) neuronal networks as a function of 1) the connection topology and symmetry, 2) the measured nodes, and 3) the nodal dynamics (linear and nonlinear). We find that typical observability metrics for 3 neuron motifs range over several orders of magnitude, depending upon topology, and for motifs containing symmetry the network observability decreases when observing from particularly confounded nodes. Nonlinearities in the nodal equations generally decrease the average network observability and full network information becomes available only in limited regions of the system phase space. Our findings demonstrate that such networks are partially observable, and suggest their potential efficacy in reconstructing network dynamics from limited measurement data. How well such strategies can be used to reconstruct and control network dynamics in experimental settings is a subject for future experimental work.

AB - We quantify observability in small (3 node) neuronal networks as a function of 1) the connection topology and symmetry, 2) the measured nodes, and 3) the nodal dynamics (linear and nonlinear). We find that typical observability metrics for 3 neuron motifs range over several orders of magnitude, depending upon topology, and for motifs containing symmetry the network observability decreases when observing from particularly confounded nodes. Nonlinearities in the nodal equations generally decrease the average network observability and full network information becomes available only in limited regions of the system phase space. Our findings demonstrate that such networks are partially observable, and suggest their potential efficacy in reconstructing network dynamics from limited measurement data. How well such strategies can be used to reconstruct and control network dynamics in experimental settings is a subject for future experimental work.

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Whalen AJ, Brennan SN, Sauer TD, Schiff SJ. Observability of neuronal network motifs. In 2012 46th Annual Conference on Information Sciences and Systems, CISS 2012. 2012. 6310923. (2012 46th Annual Conference on Information Sciences and Systems, CISS 2012). https://doi.org/10.1109/CISS.2012.6310923