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  • Poster presentation
  • Open Access

Parallel pathways at the auditory periphery

BMC Neuroscience201415 (Suppl 1) :P193

  • Published:


  • Hair Cell
  • Tuning Curve
  • Parallel Pathway
  • Auditory Nerve Fiber
  • Spontaneous Rate
We should consider the possibility that Low- and High- spontaneous rate (SR) auditory nerve fibers (ANFs) [1] constitute two different parallel pathways at the auditory periphery. The present study used a computational model of the auditory periphery [2] to demonstrate that Low- and High- SR ANFs have contrasting response properties. Anatomical studies suggest that Low- and High- SR ANF types have separate innervation sites (Figure 1A) on the same inner hair cell; lower-SR fibers synapse on the modiolar side and high-SR fibers synapse on the pillar side [3]. My hypothesis, prior to modeling the tuning curves (Figure 1B), was that Low Spontaneous Rate (Low-SR) fibers have a higher threshold for simulation and thus will have demonstrably sharper frequency selectivity than High-SR fibers. The results of the simulation support this framework; Low-SR ANFs were shown to have sharper frequency tuning (Figure 1B) than High-SR ANFs throughout a range of characteristic frequencies (CFs). While Low-SR ANFs have sharper frequency selectivity (Figure 1B), High-SR ANFs have finer temporal resolution, as the rate of change of the mean firing rate in High-SR ANFs was well above that of Low-SR fibers in the simulation (Figure 1C). It would seem that Low-SR and Medium-SR fibers (i.e. Lower-SR fibers) are optimized for “place theory” frequency coding and High-SR fibers are optimized for “volley-theory” synchronous phase locking. Future modeling efforts might maintain the integrity of these two parallel pathways, optimized for fine spectral (Lower-SR) and fine temporal (High-SR) resolution, by separating rather than summing their respective outputs.
Figure 1
Figure 1

Innervation sites (A), tuning curves (B) and temporal response properties for Low- and High- SR ANFs

Authors’ Affiliations

Center for Computational Neuroscience and Neural Technology (CompNet), Boston University, Boston, MA, USA
Graduate Program for Neuroscience (GPN), Boston University, Boston, MA, USA


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