Overview of numerical models of cell types in the cochlear nucleus

Authors

  • Stephan Werner Institute for Media Technology, Faculty of Electrical Engineering and Information Technology, Ilmenau University of Technology, Helmholtzplatz 2, 98693 Ilmenau, Germany
  • Tamás Harczos Institute for Media Technology, Faculty of Electrical Engineering and Information Technology, Ilmenau University of Technology, Helmholtzplatz 2, 98693 Ilmenau, Germany; Fraunhofer Institute for Digital Media Technology IDMT, Ehrenbergstr. 31, 98693 Ilmenau, Germany
  • Karlheinz Brandenburg Institute for Media Technology, Faculty of Electrical Engineering and Information Technology, Ilmenau University of Technology, Helmholtzplatz 2, 98693 Ilmenau, Germany; Fraunhofer Institute for Digital Media Technology IDMT, Ehrenbergstr. 31, 98693 Ilmenau, Germany

Abstract

The cochlear nucleus (CN) plays an important role in auditory scene analysis. It is the rst center in the auditory pathway and the rst stage for cue encoding. Examples for modeled cue extractions are the onset detection, periodicity analysis, monaural reverberation removal, and preprocessing for binaural cue analysis. The studies on the CN have been done incorporating different disciplines, in particular neurobiology and computational neurophysiology. As a result, several types of cells with different response behaviors, interconnections, and connections to other parts of the brain are determined and modeled. One aim of these investigations is to model the auditory processing, which can be used to simulate acoustical phenomena. The number of published contributions about the structure and components of the CN, and their computational models is numerous. Especially the modeling of various cell types, their different cue encoding methods, and their diverse interconnections can increase perplexity. The intention of the authors is to give an insight in numerical models of the cochlea nucleus. For this, a simpli ed map of the cochlear nucleus with its connections is built up from the literature of the different disciplines. The authors are aware of that this paper cannot give an all-embracing overview of all models and intricacies.

References

Borst, M., Langner, G., and Palm, G. (2004). “A biologically motivated neural network for phase extraction from complex sounds,” Biological Cybernetics, 90, 98-104.

Bürck, M., and van Hemmen, J. L. (2007). “Modeling the Cochlear Nucleus: A site for monaural echo suppression?,” J. Acoust. Soc. Am. 122, 2226-2235.

Carney, L. H. (1990). “Sensitivities of cells in anteroventral cochlear nucleus of cat to spatiotemporal discharge patterns across primary afferents,” J. Neurophysiol. 64, 437-456.

Ehret, G., and Romand, R. (1997). The Central Auditory System (Oxford University Press).

Faller, C., and Merimaa, J. (2004). “Source localization in complex listening situations: Selection of binaural cues based on interaural coherence,” J. Acoust. Soc. Am. 116, 3075-3089.

Friedel, P., Bürck, M., and van Hemmen, J. L. (2007). “Neuronal identi cation of acoustic signal periodicity,” Biological Cybernetics, 97, 247–260.

Frisina, R. D., Smith, R. L., and Chamberlain, S. C. (1990). “Encoding of amplitude modulation in the gerbil cochlear nucleus: I. A hierarchy of enhancement,” Hear Res. 44, 99-122.

Gai, Y., and Carney, L. H. (2008). “In uence of Inhibitory Inputs on Rate and Timing of Responses in the Anteroventral Cochlear Nucleus,” J. Neurophysiol. 99, 1077- 1095.

Hemmert, W., Holmberg, M., and Ramacher, U. (2005). “Temporal Sound Processing by Cochlear Nucleus Octopus Neurons,“ in Arti cial Neural Networks: Biological Inspirations-ICANN 2005 edited by W. Duch, J. Kacprzyk, E. Oja, and S. Zadrozny (Springer), pp. 583-588.

Hu, G., and Wang, D. (2004). “Monaural Speech Segregation Based on Pitch Tracking and Amplitude Modulation,” IEEE Transactions on Neural Networks 15, 1135- 1150.

Hu, G., and Wang, D. (2007). “Auditory Segmentation Based on Onset and Offset Analysis,” IEEE Transactions on Audio, Speech, and Language Processing 15, 396-405.

Kalluri, S., and Delgutte, B. (2003). “Mathematical Models of Cochlear Nucleus Onset Neurons: I. Point Neuron with ManyWeak Synaptic Inputs,” J Comput Neurosci. 14, 71–90.

Louage, D. H. G., van der Hejiden, M., and Joris, P. X. (2005). “Enhanced Temporal Response Properties of Anteroventral Cochlear Nucleus Neurons to Broadband Noise,” J Neurosci. 25, 1560–1570.

Oertel, D., and Golding, N. L. (1997). “Circuits of the Dorsal Cochlear Nucleus,” in Acoustical Signal Processing in the Central Auditory System edited by J. Syka (Plenum Press).

Oertel, D., and Young, E. D. (2004). “What ́s a cerebellar circuit doing in the auditory system?,” TRENDS in Neuroscience, 27, 104-110.

Pecka, M., Zahn T. P., and Grothe, B. (2007). “Inhibiting the Inhibition: A Neuronal Network for Sound Localization in Reverberant Environments,“ J Neurosci. 27, 1782-1790.

Schauer, C., Zahn T.P., Paschke, P., and Gross, H.-M. (2007). “More than Left or Right: An Advanced Approach to Binaural Sound Localization in the Horizontal Plane.”

Tzounopoulos, T., Kim, Y., Oertel, D., and Trussell, L. O. (2004). “Cell-speci c, spike timing-dependent plasticities in the dorsal cochlear nucleus,” Nature neuroscience 7, 719-725.

Voutsas, K., and Adamy, J. (2007). “A Biologically Inspired Spiking Neural Network for Sound Source Localization,” IEEE Transactions on Neural Networks, 18, 1785-1799.

Voutsas, K., Langner, G., Adamy, J., and Ochse, M. (2005). “A Brain-Like Neural Network for Periodicity Analysis,” IEEE Transactions on Systems, Man, and Cybernetics 35, 12-22.

Wang, D., and Brown, G. J. (1999). “Separation of speech from interfering sounds based on oscillatory correlation,” IEEE Trans. on Neural Networks 10, 684–697.

Wiegrebe, L., and Meddis, R. (2004). “The representation of periodic sounds in simulated sustained chopper units of the ventral cochlear nucleus,” J. Acoust. Soc. Am. 115, 1207-1218.

Wittig jr., J. H. (2004). Encoding and Enhancing Acoustic Information at the First Stages of the Auditory System, PhD thesis (University of Pennsylvania, USA).

Additional Files

Published

2009-12-15

How to Cite

Werner, S., Harczos, T., & Brandenburg, K. (2009). Overview of numerical models of cell types in the cochlear nucleus. Proceedings of the International Symposium on Auditory and Audiological Research, 2, 61–70. Retrieved from https://proceedings.isaar.eu/index.php/isaarproc/article/view/2009-07

Issue

Vol. 2 (2009): Binaural Processing and Spatial Hearing

Section

2009/1. Physiological measures and models of binaural hearing

License

Authors who publish with this journal agree to the following terms:

a. Authors retain copyright* and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

b. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

c. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

*From the 2017 issue onward. The Danavox Jubilee Foundation owns the copyright of all articles published in the 1969-2015 issues. However, authors are still allowed to share the work with an acknowledgement of the work's authorship and initial publication in this journal.