Stochastic model shows how cochlear implants process azimuth in real auditory space.

Interaural time difference (ITD) is a major cue for sound azimuth localization at lower sound frequencies. We review two theories of how the sound localization neural circuit works. One of them proposes labeling of sound direction in the array of delay lines by maximal response of the tuning curve (Jeffress model). The other proposes detection of the direction by calculating the maximum slope of tuning curves. We formulate a simple hypothesis from this that stochastic neural response infers sound direction from this maximum slope, which supports the second theory. We calculate the output spike time density used in the readout of sound direction analytically. We show that the numerical implementation of the model yields results similar to those observed in experiments in mammals. We then go one step further and show that our model also gives similar results when a detailed implementation of the cochlear implant processor and simulation of implant to auditory nerve transduction are used, instead of the simplified model of auditory nerve input. Our results are useful in explaining some recent puzzling observations on the binaural cochlear implantees.

[1]  M. White,et al.  A stochastic model of the electrically stimulated auditory nerve: pulse-train response , 1999, IEEE Transactions on Biomedical Engineering.

[2]  B. Grothe,et al.  Precise inhibition is essential for microsecond interaural time difference coding , 2002, Nature.

[3]  Johannes M. Zanker,et al.  Speed tuning in elementary motion detectors of the correlation type , 1999, Biological Cybernetics.

[4]  P. Loizou Introduction to cochlear implants. , 1999, IEEE engineering in medicine and biology magazine : the quarterly magazine of the Engineering in Medicine & Biology Society.

[5]  Philip H Smith,et al.  Coincidence Detection in the Auditory System 50 Years after Jeffress , 1998, Neuron.

[6]  M. White,et al.  A stochastic model of the electrically stimulated auditory nerve: single-pulse response , 1999, IEEE Transactions on Biomedical Engineering.

[7]  L. Carney,et al.  A Model for Interaural Time Difference Sensitivity in the Medial Superior Olive: Interaction of Excitatory and Inhibitory Synaptic Inputs, Channel Dynamics, and Cellular Morphology , 2005, The Journal of Neuroscience.

[8]  P. Poon,et al.  Similarities of FM and AM receptive space of single units at the auditory midbrain. , 2000, Bio Systems.

[9]  L A JEFFRESS,et al.  A place theory of sound localization. , 1948, Journal of comparative and physiological psychology.

[10]  I.C. Bruce,et al.  The effects of stochastic neural activity in a model predicting intensity perception with cochlear implants: low-rate stimulation , 1999, IEEE Transactions on Biomedical Engineering.

[11]  B. Grothe,et al.  New roles for synaptic inhibition in sound localization , 2003, Nature Reviews Neuroscience.

[12]  Graeme M Clark,et al.  Personal reflections on the multichannel cochlear implant and a view of the future. , 2008, Journal of rehabilitation research and development.

[13]  P. Marsalek Coincidence detection in the Hodgkin-Huxley equations. , 2000, Bio Systems.

[14]  Anil K. Bera,et al.  Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo Evidence , 1981 .

[15]  J B Millar,et al.  Speech processing for cochlear implant prostheses. , 1984, Journal of speech and hearing research.

[16]  C E Schreiner,et al.  Neural processing of amplitude-modulated sounds. , 2004, Physiological reviews.

[17]  Piotr Majdak,et al.  Binaural jitter improves interaural time-difference sensitivity of cochlear implantees at high pulse rates , 2008, Proceedings of the National Academy of Sciences.

[18]  J. Brugge,et al.  Progress in neurophysiology of sound localization. , 1985, Annual review of psychology.

[19]  Michael C. Reed,et al.  Precision of Neural Timing: Effects of Convergence and Time-Windowing , 2002, Journal of Computational Neuroscience.

[20]  David McAlpine,et al.  Optimal neural population coding of an auditory spatial cue , 2004, Nature.

[21]  Alessandro E. P. Villa,et al.  Evidence for spatiotemporal firing patterns within the auditory thalamus of the cat , 1990, Brain Research.

[22]  Wulfram Gerstner,et al.  A neuronal learning rule for sub-millisecond temporal coding , 1996, Nature.

[23]  B. Suresh Krishna,et al.  A Unified Mechanism for Spontaneous-Rate and First-Spike Timing in the Auditory Nerve , 2002, Journal of Computational Neuroscience.

[24]  W REICHARDT,et al.  Nervous integration in the facet eye. , 1962, Biophysical journal.

[25]  D. McAlpine,et al.  A neural code for low-frequency sound localization in mammals , 2001, Nature Neuroscience.