# THE AUDITORY MODELING TOOLBOX

Applies to version: 1.1.0

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# KELVASA2015_LOCALIZE - uses calibration data to map bilateral spike rate differences to an azimuthal angle

## Usage

[ANbinPredictions, weightedPredictions, mappingData] = ...
kelvasa2015_localize(mappingData, SpkDiffPerBin, SpkSumPerBin, varargin)


## Input parameters

 mappingData Structure containing the necessary data to map bilateral spike rate differences to a predicted azimuthal angle. SpkDiffPerBin N x M matrix of chan2 - chan1 spike rate differences in spikes/sec where N are user defined AN frequency bands and M are time bins over the entire signal. SpkSumPerBin N x M matrix of chan2 + chan1 spike rate sums in spikes/sec where N are user defined AN frequency bands and M are time bins over the entire signal.

## Output parameters

 ANbinPredictions N x M matrix of bin azimuthal angle predictions in degrees with N being the number of user defined AN frequency bands and M being the number of time windows. weightedPredictions 1 x M vector of bin weighted azimuthal angle predictions in degrees with M being the number of time windows.

## Description

RateLevelPerBin :
N x M matrix of monaural spike rates in spikes/sec with N being the number of user defined AN frequency bands and M being the range of signal levels in dB SPL over which the calibration signal was processed.
ILDcentFreq :
1 x N vector of center frequencies in Hz used in CI processing that correspond to the N user defined AN frequency bands.
ILD :
N x M matrix of interaural level differences in dB SPL for each of the the N user defined AN frequency bands over the M azimuthal angles for which the signal was processed.
IldAngSlope :
1 x N vector of linear regression slopes in dB/degree for each of the the N user defined AN frequency bands.
RateLevelSlope :
1 x N vector of linear regression slopes in spike Rate/dB for each of the the N user defined AN frequency bands.
spkDiffAziSlopes :
1 x N vector of linear regression slopes in bilateral spike rate differences /dB for each of the the N user defined AN frequency bands.
Avg :
M x N vector of spike rate difference averages over all time bins where N are user defined AN frequency bands and M are the range of azimuthal angles over which the signal was processed.
covariance :
M x N vector of spike rate difference covariances over all time bins where N are user defined AN frequency bands and M are the range of azimuthal angles over which the signal was processed.

KELVASA2015_localize(APvec,sigLengthSec,varargin)implements a user defined localization model as detailed in (Kelvasa & Dietz (2015)) to map bilateral spike rate differences to a predicted azimuithal source angle.

## References:

D. Kelvasa and M. Dietz. Auditory model-based sound direction estimation with bilateral cochlear implants. Trends in Hearing, 19:2331216515616378, 2015. [ DOI ]