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SS-L11: Signal Processing for Neural Spike Trains

Session Type: Lecture
Time: Friday, April 24, 13:30 - 15:30
Location: Room 102, TICC
Session Chairs: Zhe (Sage) Chen, Massachusetts Institute of Technology, Karim Oweiss, Michigan State University and Andrzej Cichocki, RIKEN Brain Science Institute
 
  SS-L11.1: INFERRING FUNCTIONAL CORTICAL NETWORKS FROM SPIKE TRAIN ENSEMBLES USING DYNAMIC BAYESIAN NETWORKS
         Seif Eldawlatly; Michigan State University
         Yang Zhou; Michigan State University
         Rong Jin; Michigan State University
         Karim Oweiss; Michigan State University
 
  SS-L11.2: IDENTIFICATION OF NEURONS PARTICIPATING IN CELL ASSEMBLIES
         Sonja Gruen; RIKEN Brain Science Institute
         Denise Berger; Freie Universitaet Berlin
         Christian Borgelt; European Centre for Soft Computing
 
  SS-L11.3: CONSISTENT RECOVERY OF STIMULI ENCODED WITH A NEURAL ENSEMBLE
         Aurel A. Lazar; Columbia University
         Eftychios A. Pnevmatikakis; Columbia University
 
  SS-L11.4: STATE-SPACE ANALYSIS ON TIME-VARYING CORRELATIONS IN PARALLEL SPIKE SEQUENCES
         Hideaki Shimazaki; RIKEN Brain Science Institute
         Shun-ichi Amari; RIKEN Brain Science Institute
         Emery N. Brown; Harvard-MIT Division of Health Science and Technology, Massachusetts Institute of Technology
         Sonja Gruen; RIKEN Brain Science Institute
 
  SS-L11.5: HIERARCHICAL CLUSTERING OF NEURAL DATA USING LINKED-MIXTURES OF HIDDEN MARKOV MODELS FOR BRAIN MACHINE INTERFACES
         Shalom Darmanjian; University of Florida
         Jose Principe; University of Florida
 
  SS-L11.6: SOME STATISTICAL ISSUES IN ESTIMATING INFORMATION IN NEURAL SPIKE TRAINS
         Vincent Q. Vu; University of California, Berkeley
         Bin Yu; University of California, Berkeley
         Robert E. Kass; Carnegie Mellon University
 

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