function [waveVamp, waveVlat] = roenne2012chirp(levels,chirps,varargin)
%ROENNE2012CHIRP Simulate chirp evoked ABRs
% Usage: [waveVamp, waveVlat] = ronne2012_chirp(flag)
%
% Output parameters:
% waveVamp : Amplitude of simulated ABR wave V.
% waveVlat : Latency of simulated ABR wave V peak.
%
% ronne2012_chirp(levels,chirps) returns simulations from Rønne et
% al. (2012) for a range of input levels levels. The values of
% chirps selects which stimuli from Elberling et al. (2010) stimuli to
% simulate, 1 = click, 2 to 6 = chirp 1 to 5.
%
% Simulates ABR responses to five chirps and one click using the ABR model
% of Rønne et al. (2012). Fig. 6 or 7 of Rønne et al. (2012) can be
% reproduced based on these data - use plot_ROENNE2012CHIRP. Simulations
% can be compared to data from Elberling et al. (2010). Stimuli are
% defined similar to Elberling et al. (2010).
%
% This function takes the following optional parameters:
%
% 'plot2' Plot extra figures for all individual simulations (3
% figures x stimulus levels x number of chirps).
%
% 'noplot' Do not plot main figure (fig 6 or 7).
%
% 'plot' Plot main figure (fig 6 or 7). See PLOT_ROENNE2012CHIRP.
%
% ---------
%
% Please cite Rønne et al. (2012) and Zilany and Bruce (2007) if you use
% this model.
%
% See also: roenne2012, plot_roenne2012chirp, exp_roenne2012
%
% References:
% C. Elberling, J. Calloe, and M. Don. Evaluating auditory brainstem
% responses to different chirp stimuli at three levels of stimulation. J.
% Acoust. Soc. Am., 128(1):215-223, 2010.
%
% F. Roenne, J. Harte, C. Elberling, and T. Dau. Modeling auditory evoked
% brainstem responses to transient stimuli. J. Acoust. Soc. Am., accepted
% for publication, 2012.
%
% M. S. A. Zilany and I. C. Bruce. Representation of the vowel (epsilon)
% in normal and impaired auditory nerve fibers: Model predictions of
% responses in cats. J. Acoust. Soc. Am., 122(1):402-417, jul 2007.
%
%
% Url: http://amtoolbox.sourceforge.net/amt-0.9.7/doc/monaural/roenne2012chirp.php
% Copyright (C) 2009-2014 Peter L. Søndergaard and Piotr Majdak.
% This file is part of AMToolbox version 0.9.7
%
% This program is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
% Define input flags
definput.flags.plot = {'noplot','plot','plot2'};
[flags,kv] = ltfatarghelper({},definput,varargin);
%% Init
fsmod = 200000; % AN model fs
% load Unitary Response and its samlping frequency
[ur,fs]=data_roenne2012;
% load Elberling et al (2010) click and chirp stimuli
[Elberlingstim,fsstim] = data_elberling2010('stim');
% length of modelling [ms]
modellength = 40;
% Output filter corresponding to recording settings (see Elberling et al
% 2010 section 3)
b=fir1(200,[100/(fs/2),3000/(fs/2)]);
a=1;
%% ABR model
% Loop over stimulus levels
for L = 1:length(levels)
lvl = levels(L);
% Loop over chosen Elberling et al. (2010) stimuli
for CE = chirps
% Define length of stimulus, uses variable modellength
stim = zeros(modellength/1000*fsstim,1);
% Use one of Elberling et al. (2010) stimuli
stimCE = Elberlingstim.(['c' num2str(CE-1)]);
% Create stimulus with chirp stimulus and concatenated zeros => combined
% length = "modellength"
stim(1:length(stimCE)) = stimCE;
% call AN model, note that lots of extra outputs are possible
[ANout,vFreq] = zilany2007humanized(lvl, stim', fsstim, fsmod);
% Subtract 50 due to spontaneous rate
ANout = ANout'-50;
% Sum in time across fibers = summed activity pattern
ANsum = sum(ANout,2);
% Downsample ANsum to get fs = fs_UR = 30kHz
ANsum = resample(ANsum ,fs,fsmod);
% Simulated potential = UR * ANsum (* = convolved)
simpot = filter(ur,1,ANsum);
% apply output filter similar to the recording conditions in
% Elberling et al. (2010)
simpot = filtfilt(b,a,simpot);
% Find max peak value (wave V)
maxpeak(CE,L) = max(simpot);
% Find corresponding time of max peak value (latency of wave V)
waveVlat(CE,L) = find(simpot == maxpeak(CE,L));
% find minimum in the interval from "max peak" to 6.7 ms later
minpeak(CE,L) = min(simpot(find(simpot == maxpeak(CE,L)):find(simpot == maxpeak(CE,L))+200));
%% PLOTS, extra plots created for all conditions used, i.e. three
% plots for each stimulus level x each chirp sweeping rate. If this
% is switched on and all other variables are set to default,
% 3 (levels) x 6 (chirps / clicks) x 3 (different figures) = 48
% figures will be created.
if flags.do_plot2
% Plot simulated ABR
figure, t = 1e3.*[0:length(simpot)-1]./fs-15;
plot(t,simpot,'k','linewidth',2),xlabel('time [ms]'),
title(['Simulated ABR (Elberling et al stimulus c' ...
num2str(CE-1) ' at ' num2str(lvl) 'dB)']),
set(gca, 'fontsize',12), axis([0 10 -.2 .3])
% Plot "AN-gram" - spectrogram-like representation of the
% discharge rate after the IHC-AN synapse
figure, set(gca, 'fontsize',12),imagesc(ANout'),
title(['ANgram - (Elberling et al stimulus c' num2str(CE-1) ...
' at ' num2str(lvl) 'dB)'])
set(gca,'YTick',[1 100 200 300 400 500]),
set(gca,'YTicklabel',round(vFreq([1 100 200 300 400 500]))),
ylabel('model CF'), xlabel('time [ms]'),set(gca,'XTick',(0:500:8000)),
set(gca,'XTicklabel',(0:500:8000)/fsmod*1000-15), xlabel('time [ms]'),
xlim([12/1000*fsmod 26/1000*fsmod]),colorbar
% Plot "AN-UR-gram" - spectrogram-like representation of the
% discharge rate convolved line by line with the UR.
figure, ANUR = resample(ANout,fs,fsmod);
ANUR = filter(ur,1,ANUR); imagesc(ANUR'),
set(gca,'YTick',[1 100 200 300 400 500]),
set(gca,'YTicklabel',round(vFreq([1 100 200 300 400 500]))),
ylabel('model CF'), xlabel('time [ms]'),
set(gca,'XTick',(0:150:1500)), xlabel('time [ms]'),
set(gca,'XTicklabel',(0:150:1500)/fs*1000-15)
colorbar, xlim([450 1000]),
title(['AN-URgram (Elberling et al stimulus c' num2str(CE-1) ' stimulus at ' num2str(lvl) 'dB)'])
end
end
end
% Calculate wave V amplitude, as the difference between the peak and
% the dip.
waveVamp = (maxpeak-minpeak);
% Subtract 15 ms as click stimulus peaks 15 ms into the time series
waveVlat = waveVlat*1000/fs-15;
if flags.do_plot
figure;
plot_roenne2012chirp(waveVamp, waveVlat);
end