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a Model of the Avian Superior Olivary Nucleus

a Model of the Avian Superior Olivary Nucleus. C omputational S ensorimotor S ystems L ab. Raúl Rodríguez Esteban Master Thesis Defense August 1, 2002. Comparing the sound cues of its ears. How does the owl hunt in total darkness ?. Raúl Rodríguez Esteban Master Thesis Defense

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a Model of the Avian Superior Olivary Nucleus

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  1. a Model of the Avian Superior Olivary Nucleus Computational Sensorimotor Systems Lab Raúl Rodríguez Esteban Master Thesis Defense August 1, 2002

  2. Comparing the sound cues of its ears How does the owl hunt in total darkness ? Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002

  3. Objectives of the model • In particular, its influence in the coincidence detection process • Study the role of the Superior Olivary Nucleus (SON) in the auditory system of the avians

  4. Auditory circuitry NA NM NL SON Section of a chicken brainstem

  5. ILD: Elevation (latitude) ITD: Azimuth (longitude) Interaural Level Difference (ILD) Interaural Time Difference (ITD) Sound localization in avians

  6. ILD pathway NA NA NM NM ITD pathway Two pathways for two coordinates Sullivan and Konishi (1984)

  7. Nucleus Angularis (NA) NA NA NM NM • Features: • Tonotopic organization • Anatomically, 4 kinds of cells Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002 Soares et al. (2001)

  8. Nucleus Angularis (NA) NA NA NM NM damped tonic I tonic III tonic II one-spike • Features: • Physiologically, 5 kinds of cells Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002 Soares et al. (2002)

  9. Phase locking • Features: • Tonotopic organization • Spherical soma with few dendrites Nucleus Magnocellularis (NM) NA NA NM NM Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002

  10. The ITD pathway NM NM NL Parks and Rubel (1975)

  11. Coincidence Detection ‘AND gate’ Nucleus Laminaris (NL) NM NM NM NM NL • Features: • Tonotopic organization • Bilateral dendrites with a length that depends on the frequency • Inputs that follow the Jeffress model Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002

  12. Nucleus Laminaris (NL) Problems NM NM NM NM NL Bilateral summation Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002

  13. Nucleus Laminaris (NL) Problems NM NM NM NM NL Timing errors Raúl Rodríguez Esteban Master Thesis Defense August 1st, 2002

  14. Excitatory Inhibitory The Superior Olivary Nucleus (SON) NA NM NL SON Yang et al. (1999)

  15. Banks and Sachs (1991) Model proposal Yang et al. (1999)

  16. Passive (Rall) Active (Hodgkin & Huxley) • Every part of the cell can be approximated as a piece of cable (compartment) • Branched areas can be simplified as much as we need • The soma and the axon have gates that are opened at certain voltages • These gates can be described mathematically Electrical behavior of neurons

  17. Passive behavior Ball-and-stick model (Rall 1959, 1960) Data recorded by Katrina Macleod

  18. Active behavior Hodgkin and Huxley (1952) Data recorded by Katrina Macleod

  19. Model proposal lden=120m dden=4.8m dsoma=18m laxon=40m daxon=4.8m

  20. Components modeled and unknown NA NM Connections not modeled Sound Connections already studied NL Funabiki et al. (1998) Yang et al. (1999) Model by Jonathan Z. Simon Simon et al. (2001) The SON model connected SON

  21. Increasing the discrimination ratio by reducing ‘good’ and mistaken spikes evenly • These improvements occur only in certain cases Results: improvement of the coincidence detection in NL • Reducing high frequency mistakes due to bilateral summation

  22. Results: hypothesis about the heterogeneity of the SON • Three studies talk about the anatomical and • physiological heterogeneity of the SON cells • (Takahashi and Konishi, 1988; Carr et al., 1989; Lachica et al., 1994) • However, the most recent study declares homogeneity, although using a small sample (n=23) • (Yang et al., 1999) • Our model suggests that there is some kind of physiological or anatomical adaptation for different types of inputs

  23. Future work • Assess the relationship between the NA and the SON • Simulate heterogeneity in the SON cells • Link the NM to the SON

  24. Jonathan Simon Katrina Macleod Catherine Carr Daphne Soares Sridhar Kalluri Michael Burger Nichola O’Hara Hisham Abdalla Matt Cheely Timothy Horiuchi Rock Shi Jonathan Fritz Mounya El Hilali Nikolaos Kanlis And the rest of the NS Lab Acknowledgements

  25. Results: the parameters of the model

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