Usage

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

Input parameters

Output parameters

Fields added to "mappingData":

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.