Reisensburg 1996: Abstract K. Utikal
Statistical Computing '96 - Schloß Reisensburg

A New Method for Detecting Neural Interconnectivity

Klaus J. Utikal

Fakultät für Wirtschaftswissenschaften, Universität Bonn

The statistical analysis of firing activities of an observed group of neurons is an important problem in neurology.

Among existing methods we will briefly mention those based on cross correlation analysis [1], [2], the Gravity Method [3], and counting process regression models [4], [5].

In this last approach we assume that the intensity of firings of a (target) neuron is some unknown function of the times since the last firing of the target and of the other neurons (triggers) in the ensemble. The nature of neural interactions can be inferred from geometric features of the representation of the intensity estimate as a surface in three dimensional space.

This method is applied to empirically obtained data [6], [7]. Comparisons with the other two methods mentioned are drawn [8].

Some open, computationally intensive problems regarding information transmission in neural networks will be discussed.


  1. Perkel, D.H., Gerstein, G.L., and Moore, G.P. (1967). Neuronal spike trains and stochastic point process. II. Simultaneous spike trains. Biophys. J., 7, 419-440.
  2. Aertsen, A.M.H.J. and Gerstein, G.L. (1985). Evaluation of neuronal connectivity: sensivity of cross-correlation. Brain Res. 340 341-345.
  3. Gerstein, G.L., Perkel, D.H., and Dayhoffs, J.E. (1985). Cooperative Firing Activity in Simultaneously Recorded Populations of Neurons: Detection and Measurement. The Journal of Neuroscience. Vol. 5, 4, 881-889.
  4. Utikal, K.J. (1995a). Markovian interval processes I: nonparametic inference, submitted to JSPA.
  5. Utikal, K.J. (1995b). Markovian interval processes II: analysis of neural spike train data. submitted to JSPA
  6. Lindsey, B.G., Hernandez, Y.M., Morris, K.F., and Shannon, R. (1992). Functional connectivity between brain stem midline neurons with respiratory-modulated firing rates. Journal Neurophysiology. 67, 890-904.
  7. Lindsey, B.G., Segers, L.S., Morris, K.F., Hernandez, Y.M., Saporta, S., and Shannon, R. (1994). Distributed Actions and Dynamic Associations in Respiratory-Related Neuronal Assemblies of the Ventrolateral Medulla and Brain Stem Midline: Evidence From Spike Train Analysis. Journal Neurophysiology. 72, 1830-1851.
  8. Utikal, K.J. (1995c). A nonparametric method for detecting neural connectivity. Proceedings of the 10 th Intl. Workshop on Statist. Modeling. Springer.

Statistical Computing '96 auf Schloß Reisensburg