Statistics of neural spike trains

 

A. Date, E. Bienenstock, and S. Geman. On the Temporal Resolution of Neural Activity, Technical Report, Division of Applied Mathematics, Brown University (1998). (pdf)

 

N. Hatsopoulos, S. Geman, A. Amarasingham, and E. Bienenstock. At what time scale does the nervous system operate? Neurocomputing, Volumes 52-54, June 2003, 25-29. (pdf)

 

A. Amarasingham, T.-L. Chen, S. Geman, M. Harrison, and D. Sheinberg. Spike count reliability and the Poisson Hypothesis. Journal of Neuroscience, 26(3), 2006, 801-809. (pdf)

 

M.T. Harrison and S. Geman. A Rate and History-Preserving Resampling Algorithm for Neural Spike Trains, Neural Computation, 21, 2009, 1244-1258. (pdf)

 

A. Amarasingham, M.T. Harrison, N.G. Hatsopoulos, and S. Geman. Conditional modeling and the jitter method of spike resampling, Journal of Neurophysiology, 107(2), 2012, 517-531. (pdf)

 

A. Amarasingham, S. Geman, and M. Harrison. Ambiguity and non-identifiability in the statistical analysis of neural codes. PNAS, vol. 112(20), 2015, 6455–6460. (pdf)

 

M.A. Paradiso, S. Akers-Campbell, O. Ruiz, J. Niemeyer, S. Geman, and J. Loper. Transsacadic information and corollary discharge in local field potentials of macaque V1. Frontiers in Integrative Neuroscience, vol. 12, article 63, 2019. (pdf)