[ANresp,fc] = zilany2014(lvl,stim,fsstim); [ANresp,fc,psth,ihc,t_var] = zilany2014(lvl,stim,fsstim); [ANresp,fc,psth,ihc,t_var] = zilany2014(lvl,stim,fsstim);
stim | Pressure waveform of stimulus (timeseries) |
fsstim | Sampling frequency of stimulus |
fc | Frequency vector containing the CFs. Use fc=audspace(lo,hi,numCF,'erb'); to space equally on the ERB frequency scale. |
r_mean | Instantaneous mean spiking rate (incl. refractoriness) of different AN fibers at corresponding CFs. Size: [time CFs] |
psth | Spike histogram |
ihc | Output from inner hair cells (IHCs) in Volts |
c1 | Output from the chirping filter C1 |
c2 | Output from the chirping filter C2 |
r_var | Instananeous variance in the discharge rate of the ANs |
This function takes the following optional key/value pairs:
'fsmod',fsmod | Model sampling rate. It is possible to run the model at a range of fsmod between 100 kHz and 500 kHz. Default value is 200kHz for cats and 100kHz for humans. |
'fiberType',fT | Type of the fiber based on spontaneous rate (SR) 1: Low SR, SR fixed to 0.1 spikes/s 2: Medium SR, SR fixed to 4 spikes/s 3: High SR, SR fixed to 100 spikes/s 4: Custom, defined by the fibre numbers in numH, numM and numL |
'numH' | Number of high SR fibres. Only if fiberType is 4. |
'numM' | Number of medium SR fibres. Only if fiberType is 4. |
'numL' | Number of low SR fibres. Only if fiberType is 4. |
'cohc',cohc | OHC scaling factor: 1 denotes normal OHC function (default); 0 denotes complete OHC dysfunction. |
'cihc',cihc | IHC scaling factor: 1 denotes normal IHC function (default); 0 denotes complete IHC dysfunction. |
'nrep',nrep | Number of repetitions for the mean rate, rate variance & psth calculation. |
zilany2014 accepts the following flag:
'human' | Use model parameters for humans. This is the default. |
'cat' | Use model parameters for cats. |
'fixedFGn' | Fractional Gaussian noise will be the same in every simulation. This is the default. |
'varFGn' | Fractional Gaussian noise will be different in every simulation. |
'approxPL' | Use approxiate implementation of the power-law functions. This is the default. |
'actualPL' | Use actual implementation of the power-law functions. |
'shera2002' | Selects the BM tuning from Shera et al. (2002) (default). |
'glasberg1990' | Selects the BM tuning from Glasberg & Moore (1990) |
zilany2014(...) returns modeled responses of multiple AN fibers tuned to various characteristic frequencies (CFs). Middle-ear filtering is included and corresponds to middleearfilter(...,'zilany2009'); Please cite the references below if you use this model.
C. A. Shera, J. J. J. Guinan, and O. A. J. Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements. Proceedings of the National Academy of Sciences of the United States of America, 99(5):3318--3323, 2002. [ http ]
B. R. Glasberg and B. Moore. Derivation of auditory filter shapes from notched-noise data. Hearing Research, 47(1-2):103--138, 1990.
M. S. A. Zilany, I. C. Bruce, and L. H. Carney. Updated parameters and expanded simulation options for a model of the auditory periphery. The Journal of the Acoustical Society of America, 135(1):283--286, Jan. 2014. [ DOI ]
M. Zilany, I. Bruce, P. Nelson, and L. Carney. A phenomenological model of the synapse between the inner hair cell and auditory nerve: Long-term adaptation with power-law dynamics. J. Acoust. Soc. Am., 126(5):2390 -- 2412, 2009.