Michael Buice, Ph.D.
Affiliations: | Allen Institute for Brain Science, Seattle, WA, United States |
Area:
visual system, computation & theoryGoogle:
"Michael Buice"Mean distance: 15.59 (cluster 17)
Cross-listing: Computer Science Tree
Parents
Sign in to add mentor| Jack D. Cowan | grad student | 2005 | Chicago | |
| (Neural networks, field theory, directed percolation, and critical branching.) | ||||
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Publications
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| Ocker GK, Buice MA. (2020) Flexible neural connectivity under constraints on total connection strength. Plos Computational Biology. 16: e1008080 |
| Recanatesi S, Ocker GK, Buice MA, et al. (2019) Dimensionality in recurrent spiking networks: Global trends in activity and local origins in connectivity. Plos Computational Biology. 15: e1006446 |
| Ocker GK, Hu Y, Buice MA, et al. (2017) From the statistics of connectivity to the statistics of spike times in neuronal networks. Current Opinion in Neurobiology. 46: 109-119 |
| Ocker GK, Josić K, Shea-Brown E, et al. (2017) Linking structure and activity in nonlinear spiking networks. Plos Computational Biology. 13: e1005583 |
| Sharpee TO, Destexhe A, Kawato M, et al. (2016) 25th Annual Computational Neuroscience Meeting: CNS-2016 Bmc Neuroscience. 17: 54 |
| Chow CC, Buice MA. (2015) Path integral methods for stochastic differential equations. Journal of Mathematical Neuroscience. 5: 8 |
| Buice MA, Chow CC. (2013) Beyond mean field theory: statistical field theory for neural networks. Journal of Statistical Mechanics (Online). 2013: P03003 |
| Buice MA, Chow CC. (2013) Generalized activity equations for spiking neural network dynamics. Frontiers in Computational Neuroscience. 7: 162 |
| Buice MA, Chow CC. (2013) Dynamic finite size effects in spiking neural networks. Plos Computational Biology. 9: e1002872 |
| Campbell P, Nykamp DQ, Buice M. (2013) The influence of network structure on neuronal dynamics Bmc Neuroscience. 14 |