THE AUDITORY MODELING TOOLBOX

Applies to version: 1.5.0

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CARNEY2015 - Brainstem processing

Usage:

[ic_sout_BE,ic_sout_BS,cn_sout] = carney2015(an_sout, BMF, fs)
[ic_sout_BE,ic_sout_BS,cn_sout, keyvals] = carney2015(an_sout, BMF, fs)
[..] = carney2015(an_sout, BMF, fs, varargin)

Input parameters:

an_sout auditory nerve output [time CF]
BMF best masking frequency (Hz)
fs sampling frequency (Hz)

Output parameters:

ic_sout_BE output of the band-enhanced cell [time CF]
ic_sout_BS output of the band-suppressed cell [time CF]
cn_sout cochlear nucleus output [time CF]
keyvals parameters used in calculations, as key-value pairs: keyvals.t_cn : time vector for plotting CN responses, see arg_carney2015 for the list of other parameters

Description:

This function implements the LPBR model from Carney et al. (2015), which is an extension of the SFIE model from Nelson and Carney (2004). As in the Nelson and Carney (2004) model, it calculates the output ic_sout_BE of the BP IC cell. Further, it also calculates the output ic_sout_BS which is the output of the band-supressive IC cell. Further, the output cn_sout of the CN cell is provided.

Additional input parameters:

'tau_ex_cn',texc CN excitation time constant (in s), see Eq. 2 in Nelson et al. (2004)
'tau_inh_cn',tic CN inhibition time constant (in s)
'cn_delay',D CN disynaptic inhibition delay (in s)
'Sinh_cn',Sc CN excitatory strength
'afamp_cn',ac CN alpha function area --> changes RATE of output cell
'tau_ex_ic',texc IC excitation time constant (in s), see Eq. 2 in Nelson et al. (2004)
'tau_inh_ic',tic IC inhibition time constant (in s)
'ic_delay_inh',D IC inhibition delay (in s)
'afamp_ic',ai IC alpha function area --> changes RATE of output IC BE cell
'Sinh_ic',Si IC inhibitory strength
'inh_str_bs',isb IC inhibitory strength, BS cell, see Carney et al. (2015)
'tau_inh_bs',tib IC inhibition, from BE to BS cell
'ic_delay_bs',idb IC local delay from BE to BS cell (in s)
'Aex',ae rate Scalar for BS cell

References:

L. Carney, T. Li, and J. McDonough. Speech coding in the brain: Representation of vowel formants by midbrain neurons tuned to sound fluctuations. eNeuro, 20(2), 2015.

P. C. Nelson and L. Carney. A phenomenological model of peripheral and central neural responses to amplitude-modulated tones. J. Acoust. Soc. Am., 116(4), 2004.