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Detection and estimation of neural connectivity based on crosscorrelation analysis

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Abstract

Crosscorrelation analysis of simultaneously recorded activity of pairs of neurons is a common tool to infer functional neural connectivity. The adequacy of crosscorrelation procedures to detect and estimate neural connectivity has been investigated by means of computer simulations of small networks composed of fairly realistic modelneurons. If the mean interval of neural firings is much larger than the duration of postsynaptic potentials, which will be the case in many central brain areas excitatory connections are easier to detect than inhibitory ones. On the other hand, inhibitory connections are revealed better if the mean firing interval is much smaller than post-synaptic potential duration. In general the effects of external stimuli and the effects of neural connectivity do not add linearly. Furthermore, neurons may exhibit a certain degree of timelock to the stimulus. For these reasons the commonly applied “shift predictor” procedure to separate stimulus and neural effects appears to be of limited value. In case of parallel direct and indirect neural pathways between two neurons crosscorrelation analysis does not estimate the direct connection but instead an effective connectivity, which reflects the combined influences of the parallel pathways.

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Abbreviations

ACH:

autocoincidence histogram

CCH:

crosscoincidence histogram

CPDF:

crossproduct density function

DCH:

difference crosscoincidence histogram

NACH:

nonsimultaneous autocoincidence histogram

NCCH:

nonsimultaneous crosscoincidence histogram

SCCH:

scaled crosscoincidence histogram

SDCH:

scaled difference crosscoincidence histogram

References

  • Abeles M, Ribaupierre F de, Ribaupierre Y de (1983) Detection of single unit responses which are loosely time-locked to a stimulus. IEEE Trans SMC 13:683–691

    Google Scholar 

  • Abramowitz M, Stegun IA (eds) (1972) Handbook of mathematical functions. Dover, New York

    Google Scholar 

  • Aertsen AMHJ, Gerstein GL (1985) Evaluation of neuronal connectivity: sensitivity of crosscorrelation. Brain Res 340:341–354

    Google Scholar 

  • Aertsen AMHJ, Johannesma PIM (1981) A comparison of the spectro-temporal sensitivity of auditory neurons to tonal and natural stimuli. Biol Cybern 42:145–156

    Google Scholar 

  • Aertsen AMHJ, Smolders JWT, Johannesma PIM (1979) Neural representation of the acoustic biotope: on the existence of stimulus-event relations for sensory neurons. Biol Cybern 32:175–185

    Google Scholar 

  • Boogaard HFP van den, Hesselmans GHFM, Johannesma PIM (1986) Transformation of point processes, correlation functions and system identification. Math Biosci 80:143–177

    Google Scholar 

  • Brillinger DR (1975) The identification of point process systems. The Ann Probab 3:909–929

    Google Scholar 

  • Cox DR, Isham V (1980) Point processes Chapman and Hall, London

    Google Scholar 

  • Creutzfeldt OD, Kuhnt U, Benevento LA (1974) An intracellular analysis of visual cortical neurons to moving stimuli: responses in a co-operative neuronal network. Exp Brain Res 21:251–274

    Google Scholar 

  • Dickson JW, Gerstein GL (1974) Interactions between neurons in auditory cortex of the cat. J Neurophysiol 37:1239–1261

    Google Scholar 

  • Eggermont JJ, Epping WJM, Aertsen AMHJ (1983) Stimulus dependent neural correlations in the auditory midbrain of the grassfrog (Rana Temporaria L.). Biol Cybern 47:103–117

    Google Scholar 

  • Epping WJM, Eggermont JJ (1986) Sensitivity of neurons in the auditory midbrain of the grassfrog to temporal characteristics of sound. I. Stimulation with acoustic clicks. Hear Res 24:37–54

    Google Scholar 

  • Epping WJM, Eggermont JJ (1987) Coherent neural activity in the auditory midbrain of the grassfrog. J Neurophysiol 57:1464–1483

    Google Scholar 

  • Frostig RD, Gottlieb Y, Vaadia E, Abeles M (1983) The effects of stimuli on the activity and functional connectivity of local neural groups in the cat auditory cortex. Brain Res 272:211–221

    Google Scholar 

  • Fuzessery ZM, Feng AS (1982) Frequency selectivity in the anuran auditory midbrain: single unit responses to single and multiple tone stimulation. J Comp Physiol A 146:471–484

    Google Scholar 

  • Gerstein GL, Aertsen, AMHJ (1985) Representation of cooperative firing activity among simultaneously recorded neurons. J Neurophysiol 54:1513–1527

    Google Scholar 

  • Gerstein GL, Perkel DH (1972) Mutual temporal relationships among neuronal spike trains: Statistical techniques for display and analysis. Biophys J 12:453–473

    Google Scholar 

  • Gerstein GL, Bloom MJ, Espinosa IE, Evanczuk S, Turner MR (1983) Design of a laboratory for multi-unit studies. IEEE Trans SMC 13:668–676

    Google Scholar 

  • Gerstein GL, Perkel DH, Dayhoff JE (1985) Cooperative firing activity in simultaneously recorded populations of neurons: detection and measurement. J Neurosci 5:881–889

    Google Scholar 

  • Johannesma PIM, Boogaard HFP van den (1985) Stochastic formulation of neural interaction. Acta Applic Math 4:201–224

    Google Scholar 

  • Knox CK (1974) Cross-correlation functions for a neuronal model. Biophys J 14:567–582

    Google Scholar 

  • Krausz HI (1975) Identification of nonlinear systems using random impulse train inputs. Biol Cybern 19:217–230

    Google Scholar 

  • Kuznetsov PI, Stratonovitch RL (1954) A note on the mathematical theory of correlated random points. In: Kuznetsov PI, Stratonovitch, RL, Tikhonov VI (eds) Non-linear transformations of random processes (1965) Pergamon Press, New York, pp 101–115

    Google Scholar 

  • Michalski A, Gerstein GL, Czarkowska J, Tarnecki R (1983) Interactions between cat striate cortex neurons. Exp Brain Res 51:97–107

    Google Scholar 

  • Moore GP, Segundo JP, Perkel DH, Levitan H (1970) Statistical signs of synaptic interaction in neurons. Biophys J 10:876–900

    Google Scholar 

  • Perkel DH, Gerstein GL, Moore GP (1967a) Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains. Biophys J 7:391–418

    Google Scholar 

  • Perkel DH, Gerstein GL, Moore GP (1967b) Neuronal spike trains and stochastic point processes. II. Simultaneous spike trains. Biophys J 7:419–440

    Google Scholar 

  • Ribaupierre F de, Goldstein MH Jr, Yeni-Komshian G (1972) Intracellular study of the cat's primary auditory cortex. Brain Res 48:185–204

    Google Scholar 

  • Snyder DL (1975) Random point processes. Wiley, New York

    Google Scholar 

  • Surmeier DJ, Weinberg RJ (1985) The relationship between cross-correlation measures and underlying synaptic events. Brain Res 331:180–184

    Google Scholar 

  • Toyama K, Kimura M, Tanaka K (1981) Cross-correlation analysis of interneuronal connectivity in cat visual cortex. J Neurophysiol 46:191–201

    Google Scholar 

  • Voigt HF, Young ED (1985) Stimulus dependent neural correlation: an example from the cochlear nucleus. Exp Brain Res 60:594–598

    Google Scholar 

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Authors and Affiliations

  1. Department of Medical Physics and Biophysics, University of Nijmegen, Geert Grooteplein Noord 21, NL-6525 EZ, Nijmegen, The Netherlands

    W. J. Melssen & W. J. M. Epping

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  1. W. J. Melssen
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  2. W. J. M. Epping
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Melssen, W.J., Epping, W.J.M. Detection and estimation of neural connectivity based on crosscorrelation analysis. Biol. Cybern. 57, 403–414 (1987). https://doi.org/10.1007/BF00354985

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  • DOI: https://doi.org/10.1007/BF00354985

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