Improved characterization of neural and behavioral response properties using point-process state-space framework. Anna Alexandra Dreyer. Harvard-MIT Division of Health Sciences and Technology Speech and Hearing Bioscience and Technology Program Neurostatistics Research Laboratory, MIT
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Improved characterization of neural and behavioral response properties using point-process state-space framework
Anna Alexandra Dreyer
Harvard-MIT Division of Health Sciences and Technology
Speech and Hearing Bioscience and Technology Program
Neurostatistics Research Laboratory, MIT
PI: Emery Brown, M.D., Ph.D.
September 27, 2007
Figure from laboratory of Mark Ungless
Point Process Framework: Definition of Conditional Intensity Function
Brown et al., 2003; Daley and Vere-Jones, 2003; Brown, 2005
where o(J) represents the probability of seeing two or more events on the interval (tb-1,tb].
Truccolo et al., 2005
Data from Lim and Anderson (2006)
Typical autoregressive components
Conditional firing intensity
Past spiking history effect
where εl+1,r is a Gaussian random vector
Computational methods developed with G Czanner, U Eden, E Brown
Dempster et al., 1977; McLachlan and Krishnan, 1997; Pawitan, 2001
Stimulus Effect (spikes/s)
Time since stimulus onset (ms)
Dreyer et al., 2007; Czanner et al., 2007
Johnson & Kotz, 1970; Brown et al, 2002; Box et al., 1994
The area under ROC curve specifies the probability that, when two responses are drawn, one from a lower level and one from a higher level, the algorithm assigns a larger value to the draw from a higher level.
In collaboration with B. Pfingst, A. Smith, A. Graybiel, E. Brown
Gilks et al., 1996; Congdon, 2003