George L. Gerstein

Affiliations: 
University of Pennsylvania, Philadelphia, PA, United States 
Website:
http://mulab.physiol.upenn.edu/index.html
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"George Gerstein"
Mean distance: 12.89 (cluster 17)
 
SNBCP

Children

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Judith E Dayhoff grad student 1976- Penn
Purvis H. Bedenbaugh grad student 1985- Penn
Russell Fernald grad student 1963-1968 Penn
William B. Kristan grad student 1969 Penn
Ismael Espinosa Espinosa grad student 1984-1987 Penn
Michael A. Kisley grad student 2000 Penn
Pedro E. Maldonado grad student 1988-2003 Penn
Stuart N. Baker post-doc Penn
Andrzej Wróbel post-doc
Bruce H. Lindsey post-doc 1975- Penn (MathTree)
Ad Aertsen post-doc 1983-1984 Penn

Collaborators

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Markus Diesmann collaborator
Benoît B. Mandelbrot collaborator (Physics Tree)
 (Mandelbrot and Gerstein colloborated on the 1964 paper "random walk models for the spike activity of a single neuron")
Donald H. Perkel collaborator
Eberhard E. Fetz collaborator 1962- MIT
Moshe Abeles collaborator 1969-
 ((Abeles and Gerstein collaborated on the 1988 paper "Detecting Spatiotemporal Firing Patterns Among Simultaneously Recorded Single Neurons"))
Guenther Palm collaborator 1988- MPI Tuebingen
 ((Palm, Aertsen and Gerstein collaborated on the 1988 paper "On the significance of correlations among neuronal spike trains"))
Sonja Grün collaborator 1996- Penn
Charles Gross collaborator 1961-1979 MIT
BETA: Related publications

Publications

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Torre E, Canova C, Denker M, et al. (2016) ASSET: Analysis of Sequences of Synchronous Events in Massively Parallel Spike Trains. Plos Computational Biology. 12: e1004939
Picado-Muiño D, Borgelt C, Berger D, et al. (2013) Finding neural assemblies with frequent item set mining. Frontiers in Neuroinformatics. 7: 9
Gerstein GL, Williams ER, Diesmann M, et al. (2012) Detecting synfire chains in parallel spike data. Journal of Neuroscience Methods. 206: 54-64
Borgelt C, Picado D, Berger D, et al. (2012) Cell assembly detection with frequent item set mining Bmc Neuroscience. 13
Louis S, Gerstein GL, Grün S, et al. (2010) Surrogate spike train generation through dithering in operational time. Frontiers in Computational Neuroscience. 4: 127
Grün S, Borgelt C, Gerstein G, et al. (2010) Selecting appropriate surrogate methods for spike correlation analysis Bmc Neuroscience. 11
Gruen S, Louis S, Gerstein G, et al. (2010) Surrogates for spike correlation analysis through dithering in operational time Neuroscience Research. 68: e51
Berger D, Borgelt C, Diesmann M, et al. (2009) An accretion based data mining algorithm for identification of sets of correlated neurons Bmc Neuroscience. 10
Schrader S, Grün S, Diesmann M, et al. (2008) Detecting synfire chain activity using massively parallel spike train recording. Journal of Neurophysiology. 100: 2165-76
Davies RM, Gerstein GL, Baker SN. (2006) Measurement of time-dependent changes in the irregularity of neural spiking. Journal of Neurophysiology. 96: 906-18
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