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CompareDetectedEvents.m
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%% Parameters
% I/O
params
cd(fileparts(mfilename('fullpath')));
dataFolder = fullfile(dataRepo, recFolder);
dataFolderReal = fullfile(dataRepo, recFolder);
recs = {'p103a','p106b','p108a','p108b','p108c','p120b','p122a','p124b','p125a', ...
'p127c','p128c','p129a','p131a','p131c'};
simDetectionType1Files = 'algorithm_performance_data__amp0p3_sAmp0p05';
simDetectionType2Files = 'algorithm_performance_data__amp0p3_sAmp1e_09';
dataSubfolder1.minis = 'txt_minis1';
dataSubfolder1.MiniAnalysis = 'csv_MA';
dataSubfolder1.pClamp = 'csv_pC_raw';
dataSubfolder2.minis = 'txt_minis2';
dataSubfolder2.MiniAnalysis = 'csv_MA';
dataSubfolder2.pClamp = 'csv_pC_raw';
dataSubfolderReal.minis = 'txt_minis_real';
dataSubfolderReal.MiniAnalysis = 'csv_MA_real';
dataSubfolderReal.pClamp = 'csv_pC_real';
% Half-width to exponential decay conversion factor
half2expConversionFactor = 1/0.69315;
% Frequency conditions
highFreqMinis = {'4000', '8000', '16000', '32000', '64000', '128000'};
lowFreqMinis = '500';
realFreqMinis = {'500', '1000', '2000'};
% Detection conditions
detectionConditions = {'Type 1 All'; 'Type 1 High Freq'; 'Type 1 Low Freq'; ...
'Type 1 Real Freq'; 'Type 2 Real Freq'; 'Real'};
% Excluded times and excluded time durations per sweep
excludedSweepTimes = {[0.05 1.10; 1.65 2.20]; % p103a
[0.25 0.90; 1.60 2.20]; % p106b
[0.50 1.15; 1.85 2.40]; % p108a
[0.50 1.25; 1.85 2.40]; % p108b
[0.50 1.20; 1.85 2.40]; % p108c
[0.50 1.20; 1.85 2.40]; % p120b
[0.50 1.25; 1.85 2.40]; % p122a
[0.50 1.15; 1.85 2.40]; % p124b
[0.50 1.20; 1.85 2.40]; % p125a
[0.50 1.20; 1.85 2.40]; % p127c
[0.50 1.20; 1.85 2.40]; % p128c
[0.50 1.20; 1.85 2.40]; % p129a
[0.50 2.25; 2.85 3.40]; % p131a
[0.50 1.00; 2.90 3.40]}; % p131c
excludedTimeDurations = zeros(1, numel(excludedSweepTimes));
for iRec = 1:numel(excludedSweepTimes)
excludedTimeDurations(iRec) = (excludedSweepTimes{iRec}(1,2) - excludedSweepTimes{iRec}(1,1)) + (excludedSweepTimes{iRec}(2,2) - excludedSweepTimes{iRec}(2,1));
end
% End times of simulated files for each recording
endTimes = [200 40 repmat(100, 1, 12)];
% Number of sweeps per simulated file for each recording
nSweeps = [50 10 repmat(5, 1, 12)];
% Simulated file durations after accounting for excluded times
durations = [endTimes(1)-nSweeps(1)*excludedTimeDurations(1) % p103a
endTimes(2)-nSweeps(2)*excludedTimeDurations(2) % p106b
endTimes(3)-nSweeps(3)*excludedTimeDurations(3) % p108a
endTimes(4)-nSweeps(4)*excludedTimeDurations(4) % p108b
endTimes(5)-nSweeps(5)*excludedTimeDurations(5) % p108c
endTimes(6)-nSweeps(6)*excludedTimeDurations(6) % p120b
endTimes(7)-nSweeps(7)*excludedTimeDurations(7) % p122a
endTimes(8)-nSweeps(8)*excludedTimeDurations(8) % p124b
endTimes(9)-nSweeps(9)*excludedTimeDurations(9) % p125a
endTimes(10)-nSweeps(10)*excludedTimeDurations(10) % p127c
endTimes(11)-nSweeps(11)*excludedTimeDurations(11) % p128c
endTimes(12)-nSweeps(12)*excludedTimeDurations(12) % p129a
endTimes(13)-nSweeps(13)*excludedTimeDurations(13) % p131a
endTimes(14)-nSweeps(14)*excludedTimeDurations(14)]'; % p131c
% Number of simulated files per condition
nFiles = 4;
% Number of simulation conditions for the two experiments
nConditions = [14 3];
% Simulated sweep durations for each recording
sweepDurations = [4 % p103a
4 % p106b
20 % p108a
20 % p108b
20 % p108c
20 % p120b
20 % p122a
20 % p124b
20 % p125a
20 % p127c
20 % p128c
20 % p129a
20 % p131a
20]'; % p131c
% Excluded times for simulated files for each recording
excludedTimes = {};
for iRec = 1:numel(excludedSweepTimes)
excludedTimes{iRec} = excludedSweepTimes{iRec};
for iSweep = 2:nSweeps(iRec)
excludedTimes{iRec} = [excludedTimes{iRec}; ...
excludedSweepTimes{iRec} + sweepDurations(iRec)*(iSweep-1)];
end
end
% Number of sweeps per real files for each recording
nSweepsReal = {[repmat(10, 1, 17) 9 10 10 10 4 5 10 10 9 repmat(10, 1, 14) 9 repmat(10, 1, 6) 50 50 50]; % p103a
[repmat(10, 1, 11) 9 repmat(10, 1, 5)]; % p106b
[2 4 4 5]; % p108a
[6 9 4 5 7]; % p108b
[repmat(5, 1, 6) 6]; % p108c
[5 5 7 6 4 5 6]; % p120b
[10 8 9 5 5 6]; % p122a
repmat(5, 1, 7); % p124b
[7 6 7 2 5 3]; % p125a
[10 5 5 5 8]; % p127c
[2 7 5 4 5 4]; % p128c
[10 5 5 6]; % p129a
[10 9 5 1 1]; % p131a
repmat(5, 1, 8)}; % p131c
nFilesRealpClamp = nSweepsReal;
% Sum duration of all real files for each recording
durationsReal = zeros(1, numel(excludedSweepTimes));
for iRec = 1:numel(excludedSweepTimes)
durationsReal(iRec) = sum(nSweepsReal{iRec}.*(sweepDurations(iRec) - excludedTimeDurations(iRec)));
end
durationsRealpClamp = durationsReal;
% Excluded times for all real files for each recording
excludedTimesReal = {};
for iRec = 1:numel(excludedSweepTimes)
for iFile = 1:numel(nSweepsReal{iRec})
excludedTimesReal{iRec}{iFile} = excludedSweepTimes{iRec}; %#ok<*SAGROW>
for iSweep = 2:nSweepsReal{iRec}(iFile)
excludedTimesReal{iRec}{iFile} = [excludedTimesReal{iRec}{iFile}; ...
excludedSweepTimes{iRec} + sweepDurations(iRec)*(iSweep-1)];
end
end
end
% End times for all real files for each recording
endTimesReal = {};
for iRec = 1:numel(excludedSweepTimes)
endTimesReal{iRec} = nSweepsReal{iRec}.*sweepDurations(iRec);
end
%% Containers
% Extract info about detected events by the three algorithms
% Data aggregate containers
simulatedDetectionType1All.minis.data = [];
simulatedDetectionType1All.MiniAnalysis.data = [];
simulatedDetectionType1All.pClamp.data = [];
simulatedDetectionType1HighFreq.minis.data = [];
simulatedDetectionType1HighFreq.MiniAnalysis.data = [];
simulatedDetectionType1HighFreq.pClamp.data = [];
simulatedDetectionType1LowFreq.minis.data = [];
simulatedDetectionType1LowFreq.MiniAnalysis.data = [];
simulatedDetectionType1LowFreq.pClamp.data = [];
simulatedDetectionType1RealFreq.minis.data = [];
simulatedDetectionType1RealFreq.MiniAnalysis.data = [];
simulatedDetectionType1RealFreq.pClamp.data = [];
simulatedDetectionType2.minis.data = [];
simulatedDetectionType2.MiniAnalysis.data = [];
simulatedDetectionType2.pClamp.data = [];
realDetection.minis.data = [];
realDetection.MiniAnalysis.data = [];
realDetection.pClamp.data = [];
%% simulatedDetectionType1All
% Type 1 simulation: minis across all conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.minis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.txt')
T = readtable(detectionFile);
simulatedDetectionType1All.minis.data = [simulatedDetectionType1All.minis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90_RT T.decayTime T.tau]];
end
end
end
% Type 1 simulation: MiniAnalysis across all conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.MiniAnalysis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv')
T = readtable(detectionFile);
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
try
times = cellfun(@str2double, T.Time_ms_)./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
simulatedDetectionType1All.MiniAnalysis.data = [simulatedDetectionType1All.MiniAnalysis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90Rise T.Decay_ms_]];
catch
times = cellfun(@str2double, T.Var2(2:end))./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
inds2include = inds2include + 1;
T = T(inds2include,:);
simulatedDetectionType1All.MiniAnalysis.data = [simulatedDetectionType1All.MiniAnalysis.data; ...
[ones(size(T,1)-1,1)*iRec T.Var3(2:end) T.Var11(2:end) T.Var5(2:end)]];
end
end
end
end
% Type 1 simulation: pClamp across all conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.pClamp);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv')
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
T = readtable(detectionFile);
times = T.Var5./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
RTs = NaN(size(T,1),1);
for rt = 1:numel(RTs)
if iscell(T.Var25)
if ~strcmpi(T.Var25{rt}, 'Not found')
RTs(rt) = str2double(T.Var25{rt})*half2expConversionFactor;
end
else
RTs = T.Var25.*half2expConversionFactor;
end
end
simulatedDetectionType1All.pClamp.data = [simulatedDetectionType1All.pClamp.data; ...
[ones(size(T,1),1)*iRec T.Var8 RTs T.Var17]];
end
end
end
%% simulatedDetectionType1HighFreq
% Type 1 simulation: minis across high frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.minis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.txt') && ...
contains(detectionFile, highFreqMinis) && contains(detectionFile, 'noiseScaleFactor1')
T = readtable(detectionFile);
simulatedDetectionType1HighFreq.minis.data = [simulatedDetectionType1HighFreq.minis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90_RT T.decayTime T.tau]];
end
end
end
% Type 1 simulation: MiniAnalysis across high frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.MiniAnalysis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv') && ...
contains(detectionFile, highFreqMinis) && contains(detectionFile, 'noiseScaleFactor1')
T = readtable(detectionFile);
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
try
times = cellfun(@str2double, T.Time_ms_)./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
simulatedDetectionType1HighFreq.MiniAnalysis.data = [simulatedDetectionType1HighFreq.MiniAnalysis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90Rise T.Decay_ms_]];
catch
times = cellfun(@str2double, T.Var2(2:end))./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
inds2include = inds2include + 1;
T = T(inds2include,:);
simulatedDetectionType1HighFreq.MiniAnalysis.data = [simulatedDetectionType1HighFreq.MiniAnalysis.data; ...
[ones(size(T,1)-1,1)*iRec T.Var3(2:end) T.Var11(2:end) T.Var5(2:end)]];
end
end
end
end
% Type 1 simulation: pClamp across high frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.pClamp);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv') && ...
contains(detectionFile, highFreqMinis) && contains(detectionFile, 'noiseScaleFactor1')
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
T = readtable(detectionFile);
times = T.Var5./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
RTs = NaN(size(T,1),1);
for rt = 1:numel(RTs)
if iscell(T.Var25)
if ~strcmpi(T.Var25{rt}, 'Not found')
RTs(rt) = str2double(T.Var25{rt})*half2expConversionFactor;
end
else
RTs = T.Var25.*half2expConversionFactor;
end
end
simulatedDetectionType1HighFreq.pClamp.data = [simulatedDetectionType1HighFreq.pClamp.data; ...
[ones(size(T,1),1)*iRec T.Var8 RTs T.Var17]];
end
end
end
%% simulatedDetectionType1LowFreq
% Type 1 simulation: minis across low frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.minis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.txt') && contains(detectionFile, lowFreqMinis)
T = readtable(detectionFile);
simulatedDetectionType1LowFreq.minis.data = [simulatedDetectionType1LowFreq.minis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90_RT T.decayTime T.tau]];
end
end
end
% Type 1 simulation: MiniAnalysis across low frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.MiniAnalysis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv') && ...
contains(detectionFile, lowFreqMinis)
T = readtable(detectionFile);
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
try
times = cellfun(@str2double, T.Time_ms_)./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
simulatedDetectionType1LowFreq.MiniAnalysis.data = [simulatedDetectionType1LowFreq.MiniAnalysis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90Rise T.Decay_ms_]];
catch
times = cellfun(@str2double, T.Var2(2:end))./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
inds2include = inds2include + 1;
T = T(inds2include,:);
simulatedDetectionType1LowFreq.MiniAnalysis.data = [simulatedDetectionType1LowFreq.MiniAnalysis.data; ...
[ones(size(T,1)-1,1)*iRec T.Var3(2:end) T.Var11(2:end) T.Var5(2:end)]];
end
end
end
end
% Type 1 simulation: pClamp across low frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.pClamp);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv') && ...
contains(detectionFile, lowFreqMinis)
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
T = readtable(detectionFile);
times = T.Var5./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
RTs = NaN(size(T,1),1);
for rt = 1:numel(RTs)
if iscell(T.Var25)
if ~strcmpi(T.Var25{rt}, 'Not found')
RTs(rt) = str2double(T.Var25{rt})*half2expConversionFactor;
end
else
RTs = T.Var25.*half2expConversionFactor;
end
end
simulatedDetectionType1LowFreq.pClamp.data = [simulatedDetectionType1LowFreq.pClamp.data; ...
[ones(size(T,1),1)*iRec T.Var8 RTs T.Var17]];
end
end
end
%% simulatedDetectionType1RealFreq
% Type 1 simulation: minis across realistic frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.minis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.txt') && ...
contains(detectionFile, realFreqMinis) && contains(detectionFile, 'noiseScaleFactor1')
T = readtable(detectionFile);
simulatedDetectionType1RealFreq.minis.data = [simulatedDetectionType1RealFreq.minis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90_RT T.decayTime T.tau]];
end
end
end
% Type 1 simulation: MiniAnalysis across realistic frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.MiniAnalysis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv') && ...
contains(detectionFile, realFreqMinis) && contains(detectionFile, 'noiseScaleFactor1')
T = readtable(detectionFile);
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
try
times = cellfun(@str2double, T.Time_ms_)./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
simulatedDetectionType1RealFreq.MiniAnalysis.data = [simulatedDetectionType1RealFreq.MiniAnalysis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90Rise T.Decay_ms_]];
catch
times = cellfun(@str2double, T.Var2(2:end))./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
inds2include = inds2include + 1;
T = T(inds2include,:);
simulatedDetectionType1RealFreq.MiniAnalysis.data = [simulatedDetectionType1RealFreq.MiniAnalysis.data; ...
[ones(size(T,1)-1,1)*iRec T.Var3(2:end) T.Var11(2:end) T.Var5(2:end)]];
end
end
end
end
% Type 1 simulation: pClamp across realistic frequency conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder1.pClamp);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType1Files) && endsWith(detectionFile, '.csv') && ...
contains(detectionFile, realFreqMinis) && contains(detectionFile, 'noiseScaleFactor1')
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
T = readtable(detectionFile);
times = T.Var5./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
RTs = NaN(size(T,1),1);
for rt = 1:numel(RTs)
if iscell(T.Var25)
if ~strcmpi(T.Var25{rt}, 'Not found')
RTs(rt) = str2double(T.Var25{rt})*half2expConversionFactor;
end
else
RTs = T.Var25.*half2expConversionFactor;
end
end
simulatedDetectionType1RealFreq.pClamp.data = [simulatedDetectionType1RealFreq.pClamp.data; ...
[ones(size(T,1),1)*iRec T.Var8 RTs T.Var17]];
end
end
end
%% simulatedDetectionType2
% Type 2 simulation: minis across realistic frequency and amplitude conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder2.minis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.txt')
T = readtable(detectionFile);
simulatedDetectionType2.minis.data = [simulatedDetectionType2.minis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90_RT T.decayTime T.tau]];
end
end
end
% Type 2 simulation: MiniAnalysis across realistic frequency and amplitude conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder2.MiniAnalysis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType2Files) && endsWith(detectionFile, '.csv')
T = readtable(detectionFile);
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
try
times = cellfun(@str2double, T.Time_ms_)./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
simulatedDetectionType2.MiniAnalysis.data = [simulatedDetectionType2.MiniAnalysis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90Rise T.Decay_ms_]];
catch
times = cellfun(@str2double, T.Var2(2:end))./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
inds2include = inds2include + 1;
T = T(inds2include,:);
simulatedDetectionType2.MiniAnalysis.data = [simulatedDetectionType2.MiniAnalysis.data; ...
[ones(size(T,1)-1,1)*iRec T.Var3(2:end) T.Var11(2:end) T.Var5(2:end)]];
end
end
end
end
% Type 2 simulation: pClamp across realistic frequency and amplitude conditions
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolder, recs{iRec}, dataSubfolder2.pClamp);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if startsWith(files(iFile).name, simDetectionType2Files) && endsWith(detectionFile, '.csv')
includedTimesRec = invertIntervals(excludedTimes{iRec}, endTimes(iRec));
T = readtable(detectionFile);
times = T.Var5./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
RTs = NaN(size(T,1),1);
for rt = 1:numel(RTs)
if iscell(T.Var25)
if ~strcmpi(T.Var25{rt}, 'Not found')
RTs(rt) = str2double(T.Var25{rt})*half2expConversionFactor;
end
else
RTs = T.Var25.*half2expConversionFactor;
end
end
simulatedDetectionType2.pClamp.data = [simulatedDetectionType2.pClamp.data; ...
[ones(size(T,1),1)*iRec T.Var8 RTs T.Var17]];
end
end
end
%% Real data detection
% minis
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolderReal, recs{iRec}, dataSubfolderReal.minis);
files = dir(detectionFolder);
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.txt')
T = readtable(detectionFile);
realDetection.minis.data = [realDetection.minis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90_RT T.decayTime T.tau]];
end
end
end
% MiniAnalysis
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolderReal, recs{iRec}, dataSubfolderReal.MiniAnalysis);
files = dir(detectionFolder);
fileCounter = 0;
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.csv')
fileCounter = fileCounter + 1;
includedTimesRec = invertIntervals(excludedTimesReal{iRec}{fileCounter}, endTimesReal{iRec}(fileCounter));
T = readtable(detectionFile);
try
times = cellfun(@str2double, T.Time_ms_)./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
realDetection.MiniAnalysis.data = [realDetection.MiniAnalysis.data; ...
[ones(size(T,1),1)*iRec T.Amplitude T.x10_90Rise T.Decay_ms_]];
catch
times = cellfun(@str2double, T.Var2(2:end))./1000;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
inds2include = inds2include + 1;
T = T(inds2include,:);
realDetection.MiniAnalysis.data = [realDetection.MiniAnalysis.data; ...
[ones(size(T,1)-1,1)*iRec T.Var3(2:end) T.Var11(2:end) T.Var5(2:end)]];
end
end
end
end
% pClamp
for iRec = 1:numel(recs)
detectionFolder = fullfile(dataFolderReal, recs{iRec}, dataSubfolderReal.pClamp);
files = dir(detectionFolder);
fileCounter = 0;
for iFile = 1:numel(files)
detectionFile = fullfile(detectionFolder, files(iFile).name);
if endsWith(detectionFile, '.csv')
fileCounter = fileCounter + 1;
includedTimesRec = invertIntervals(excludedTimesReal{iRec}{fileCounter}, endTimesReal{iRec}(fileCounter));
T = readtable(detectionFile);
times = T.Var5./1000;
ISIs = diff(times);
missingPeriodSum = sum(floor(ISIs(ISIs>1)));
durationsRealpClamp(iRec) = durationsRealpClamp(iRec) - missingPeriodSum;
[~, inds2include] = selectArrayValues(times, includedTimesRec);
T = T(inds2include,:);
RTs = NaN(size(T,1),1);
for rt = 1:numel(RTs)
if iscell(T.Var25)
if ~strcmpi(T.Var25{rt}, 'Not found')
RTs(rt) = str2double(T.Var25{rt})*half2expConversionFactor;
end
else
RTs = T.Var25.*half2expConversionFactor;
end
end
realDetection.pClamp.data = [realDetection.pClamp.data; ...
[ones(size(T,1),1)*iRec T.Var8 RTs T.Var17]];
end
end
end
%% Calculate detected event means and incidence rates
% Means and ranges
simulatedDetectionType1All.minis.means = zeros(numel(recs), size(simulatedDetectionType1All.minis.data,2)-1);
simulatedDetectionType1All.MiniAnalysis.means = zeros(numel(recs), size(simulatedDetectionType1All.MiniAnalysis.data,2)-1);
simulatedDetectionType1All.pClamp.means = zeros(numel(recs), size(simulatedDetectionType1All.pClamp.data,2)-1);
simulatedDetectionType1HighFreq.minis.means = zeros(numel(recs), size(simulatedDetectionType1HighFreq.minis.data,2)-1);
simulatedDetectionType1HighFreq.MiniAnalysis.means = zeros(numel(recs), size(simulatedDetectionType1HighFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1HighFreq.pClamp.means = zeros(numel(recs), size(simulatedDetectionType1HighFreq.pClamp.data,2)-1);
simulatedDetectionType1LowFreq.minis.means = zeros(numel(recs), size(simulatedDetectionType1LowFreq.minis.data,2)-1);
simulatedDetectionType1LowFreq.MiniAnalysis.means = zeros(numel(recs), size(simulatedDetectionType1LowFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1LowFreq.pClamp.means = zeros(numel(recs), size(simulatedDetectionType1LowFreq.pClamp.data,2)-1);
simulatedDetectionType1RealFreq.minis.means = zeros(numel(recs), size(simulatedDetectionType1RealFreq.minis.data,2)-1);
simulatedDetectionType1RealFreq.MiniAnalysis.means = zeros(numel(recs), size(simulatedDetectionType1RealFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1RealFreq.pClamp.means = zeros(numel(recs), size(simulatedDetectionType1RealFreq.pClamp.data,2)-1);
simulatedDetectionType2.minis.means = zeros(numel(recs), size(simulatedDetectionType2.minis.data,2)-1);
simulatedDetectionType2.MiniAnalysis.means = zeros(numel(recs), size(simulatedDetectionType2.MiniAnalysis.data,2)-1);
simulatedDetectionType2.pClamp.means = zeros(numel(recs), size(simulatedDetectionType2.pClamp.data,2)-1);
realDetection.minis.means = zeros(numel(recs), size(realDetection.minis.data,2)-1);
realDetection.MiniAnalysis.means = zeros(numel(recs), size(realDetection.MiniAnalysis.data,2)-1);
realDetection.pClamp.means = zeros(numel(recs), size(realDetection.pClamp.data,2)-1);
simulatedDetectionType1All.minis.min = zeros(numel(recs), size(simulatedDetectionType1All.minis.data,2)-1);
simulatedDetectionType1All.MiniAnalysis.min = zeros(numel(recs), size(simulatedDetectionType1All.MiniAnalysis.data,2)-1);
simulatedDetectionType1All.pClamp.min = zeros(numel(recs), size(simulatedDetectionType1All.pClamp.data,2)-1);
simulatedDetectionType1HighFreq.minis.min = zeros(numel(recs), size(simulatedDetectionType1HighFreq.minis.data,2)-1);
simulatedDetectionType1HighFreq.MiniAnalysis.min = zeros(numel(recs), size(simulatedDetectionType1HighFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1HighFreq.pClamp.min = zeros(numel(recs), size(simulatedDetectionType1HighFreq.pClamp.data,2)-1);
simulatedDetectionType1LowFreq.minis.min = zeros(numel(recs), size(simulatedDetectionType1LowFreq.minis.data,2)-1);
simulatedDetectionType1LowFreq.MiniAnalysis.min = zeros(numel(recs), size(simulatedDetectionType1LowFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1LowFreq.pClamp.min = zeros(numel(recs), size(simulatedDetectionType1LowFreq.pClamp.data,2)-1);
simulatedDetectionType1RealFreq.minis.min = zeros(numel(recs), size(simulatedDetectionType1RealFreq.minis.data,2)-1);
simulatedDetectionType1RealFreq.MiniAnalysis.min = zeros(numel(recs), size(simulatedDetectionType1RealFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1RealFreq.pClamp.min = zeros(numel(recs), size(simulatedDetectionType1RealFreq.pClamp.data,2)-1);
simulatedDetectionType2.minis.min = zeros(numel(recs), size(simulatedDetectionType2.minis.data,2)-1);
simulatedDetectionType2.MiniAnalysis.min = zeros(numel(recs), size(simulatedDetectionType2.MiniAnalysis.data,2)-1);
simulatedDetectionType2.pClamp.min = zeros(numel(recs), size(simulatedDetectionType2.pClamp.data,2)-1);
realDetection.minis.min = zeros(numel(recs), size(realDetection.minis.data,2)-1);
realDetection.MiniAnalysis.min = zeros(numel(recs), size(realDetection.MiniAnalysis.data,2)-1);
realDetection.pClamp.min = zeros(numel(recs), size(realDetection.pClamp.data,2)-1);
simulatedDetectionType1All.minis.max = zeros(numel(recs), size(simulatedDetectionType1All.minis.data,2)-1);
simulatedDetectionType1All.MiniAnalysis.max = zeros(numel(recs), size(simulatedDetectionType1All.MiniAnalysis.data,2)-1);
simulatedDetectionType1All.pClamp.max = zeros(numel(recs), size(simulatedDetectionType1All.pClamp.data,2)-1);
simulatedDetectionType1HighFreq.minis.max = zeros(numel(recs), size(simulatedDetectionType1HighFreq.minis.data,2)-1);
simulatedDetectionType1HighFreq.MiniAnalysis.max = zeros(numel(recs), size(simulatedDetectionType1HighFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1HighFreq.pClamp.max = zeros(numel(recs), size(simulatedDetectionType1HighFreq.pClamp.data,2)-1);
simulatedDetectionType1LowFreq.minis.max = zeros(numel(recs), size(simulatedDetectionType1LowFreq.minis.data,2)-1);
simulatedDetectionType1LowFreq.MiniAnalysis.max = zeros(numel(recs), size(simulatedDetectionType1LowFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1LowFreq.pClamp.max = zeros(numel(recs), size(simulatedDetectionType1LowFreq.pClamp.data,2)-1);
simulatedDetectionType1RealFreq.minis.max = zeros(numel(recs), size(simulatedDetectionType1RealFreq.minis.data,2)-1);
simulatedDetectionType1RealFreq.MiniAnalysis.max = zeros(numel(recs), size(simulatedDetectionType1RealFreq.MiniAnalysis.data,2)-1);
simulatedDetectionType1RealFreq.pClamp.max = zeros(numel(recs), size(simulatedDetectionType1RealFreq.pClamp.data,2)-1);
simulatedDetectionType2.minis.max = zeros(numel(recs), size(simulatedDetectionType2.minis.data,2)-1);
simulatedDetectionType2.MiniAnalysis.max = zeros(numel(recs), size(simulatedDetectionType2.MiniAnalysis.data,2)-1);
simulatedDetectionType2.pClamp.max = zeros(numel(recs), size(simulatedDetectionType2.pClamp.data,2)-1);
realDetection.minis.max = zeros(numel(recs), size(realDetection.minis.data,2)-1);
realDetection.MiniAnalysis.max = zeros(numel(recs), size(realDetection.MiniAnalysis.data,2)-1);
realDetection.pClamp.max = zeros(numel(recs), size(realDetection.pClamp.data,2)-1);
for iRec = 1:numel(recs)
inds = simulatedDetectionType1All.minis.data(:,1) == iRec & simulatedDetectionType1All.minis.data(:,2) > 0 & ...
simulatedDetectionType1All.minis.data(:,3) > 0;
simulatedDetectionType1All.minis.means(iRec,:) = mean(simulatedDetectionType1All.minis.data(inds,2:end), 'omitnan');
simulatedDetectionType1All.minis.min(iRec,:) = min(simulatedDetectionType1All.minis.data(inds,2:end));
simulatedDetectionType1All.minis.max(iRec,:) = max(simulatedDetectionType1All.minis.data(inds,2:end));
inds = simulatedDetectionType1All.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1All.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1All.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1All.MiniAnalysis.means(iRec,:) = mean(simulatedDetectionType1All.MiniAnalysis.data(inds,2:end), 'omitnan');
simulatedDetectionType1All.MiniAnalysis.min(iRec,:) = min(simulatedDetectionType1All.MiniAnalysis.data(inds,2:end));
simulatedDetectionType1All.MiniAnalysis.max(iRec,:) = max(simulatedDetectionType1All.MiniAnalysis.data(inds,2:end));
inds = simulatedDetectionType1All.pClamp.data(:,1) == iRec & simulatedDetectionType1All.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1All.pClamp.data(:,3) > 0;
simulatedDetectionType1All.pClamp.means(iRec,:) = mean(simulatedDetectionType1All.pClamp.data(inds,2:end), 'omitnan');
simulatedDetectionType1All.pClamp.min(iRec,:) = min(simulatedDetectionType1All.pClamp.data(inds,2:end));
simulatedDetectionType1All.pClamp.max(iRec,:) = max(simulatedDetectionType1All.pClamp.data(inds,2:end));
inds = simulatedDetectionType1HighFreq.minis.data(:,1) == iRec & simulatedDetectionType1HighFreq.minis.data(:,2) > 0 & ...
simulatedDetectionType1HighFreq.minis.data(:,3) > 0;
simulatedDetectionType1HighFreq.minis.means(iRec,:) = mean(simulatedDetectionType1HighFreq.minis.data(inds,2:end), 'omitnan');
simulatedDetectionType1HighFreq.minis.min(iRec,:) = min(simulatedDetectionType1HighFreq.minis.data(inds,2:end));
simulatedDetectionType1HighFreq.minis.max(iRec,:) = max(simulatedDetectionType1HighFreq.minis.data(inds,2:end));
inds = simulatedDetectionType1HighFreq.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1HighFreq.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1HighFreq.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1HighFreq.MiniAnalysis.means(iRec,:) = mean(simulatedDetectionType1HighFreq.MiniAnalysis.data(inds,2:end), 'omitnan');
simulatedDetectionType1HighFreq.MiniAnalysis.min(iRec,:) = min(simulatedDetectionType1HighFreq.MiniAnalysis.data(inds,2:end));
simulatedDetectionType1HighFreq.MiniAnalysis.max(iRec,:) = max(simulatedDetectionType1HighFreq.MiniAnalysis.data(inds,2:end));
inds = simulatedDetectionType1HighFreq.pClamp.data(:,1) == iRec & simulatedDetectionType1HighFreq.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1HighFreq.pClamp.data(:,3) > 0;
simulatedDetectionType1HighFreq.pClamp.means(iRec,:) = mean(simulatedDetectionType1HighFreq.pClamp.data(inds,2:end), 'omitnan');
simulatedDetectionType1HighFreq.pClamp.min(iRec,:) = min(simulatedDetectionType1HighFreq.pClamp.data(inds,2:end));
simulatedDetectionType1HighFreq.pClamp.max(iRec,:) = max(simulatedDetectionType1HighFreq.pClamp.data(inds,2:end));
inds = simulatedDetectionType1LowFreq.minis.data(:,1) == iRec & simulatedDetectionType1LowFreq.minis.data(:,2) > 0 & ...
simulatedDetectionType1LowFreq.minis.data(:,3) > 0;
simulatedDetectionType1LowFreq.minis.means(iRec,:) = mean(simulatedDetectionType1LowFreq.minis.data(inds,2:end), 'omitnan');
simulatedDetectionType1LowFreq.minis.min(iRec,:) = min(simulatedDetectionType1LowFreq.minis.data(inds,2:end));
simulatedDetectionType1LowFreq.minis.max(iRec,:) = max(simulatedDetectionType1LowFreq.minis.data(inds,2:end));
inds = simulatedDetectionType1LowFreq.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1LowFreq.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1LowFreq.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1LowFreq.MiniAnalysis.means(iRec,:) = mean(simulatedDetectionType1LowFreq.MiniAnalysis.data(inds,2:end), 'omitnan');
simulatedDetectionType1LowFreq.MiniAnalysis.min(iRec,:) = min(simulatedDetectionType1LowFreq.MiniAnalysis.data(inds,2:end));
simulatedDetectionType1LowFreq.MiniAnalysis.max(iRec,:) = max(simulatedDetectionType1LowFreq.MiniAnalysis.data(inds,2:end));
inds = simulatedDetectionType1LowFreq.pClamp.data(:,1) == iRec & simulatedDetectionType1LowFreq.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1LowFreq.pClamp.data(:,3) > 0;
simulatedDetectionType1LowFreq.pClamp.means(iRec,:) = mean(simulatedDetectionType1LowFreq.pClamp.data(inds,2:end), 'omitnan');
simulatedDetectionType1LowFreq.pClamp.min(iRec,:) = min(simulatedDetectionType1LowFreq.pClamp.data(inds,2:end));
simulatedDetectionType1LowFreq.pClamp.max(iRec,:) = max(simulatedDetectionType1LowFreq.pClamp.data(inds,2:end));
inds = simulatedDetectionType1RealFreq.minis.data(:,1) == iRec & simulatedDetectionType1RealFreq.minis.data(:,2) > 0 & ...
simulatedDetectionType1RealFreq.minis.data(:,3) > 0;
simulatedDetectionType1RealFreq.minis.means(iRec,:) = mean(simulatedDetectionType1RealFreq.minis.data(inds,2:end), 'omitnan');
simulatedDetectionType1RealFreq.minis.min(iRec,:) = min(simulatedDetectionType1RealFreq.minis.data(inds,2:end));
simulatedDetectionType1RealFreq.minis.max(iRec,:) = max(simulatedDetectionType1RealFreq.minis.data(inds,2:end));
inds = simulatedDetectionType1RealFreq.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1RealFreq.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1RealFreq.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1RealFreq.MiniAnalysis.means(iRec,:) = mean(simulatedDetectionType1RealFreq.MiniAnalysis.data(inds,2:end), 'omitnan');
simulatedDetectionType1RealFreq.MiniAnalysis.min(iRec,:) = min(simulatedDetectionType1RealFreq.MiniAnalysis.data(inds,2:end));
simulatedDetectionType1RealFreq.MiniAnalysis.max(iRec,:) = max(simulatedDetectionType1RealFreq.MiniAnalysis.data(inds,2:end));
inds = simulatedDetectionType1RealFreq.pClamp.data(:,1) == iRec & simulatedDetectionType1RealFreq.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1RealFreq.pClamp.data(:,3) > 0;
simulatedDetectionType1RealFreq.pClamp.means(iRec,:) = mean(simulatedDetectionType1RealFreq.pClamp.data(inds,2:end), 'omitnan');
simulatedDetectionType1RealFreq.pClamp.min(iRec,:) = min(simulatedDetectionType1RealFreq.pClamp.data(inds,2:end));
simulatedDetectionType1RealFreq.pClamp.max(iRec,:) = max(simulatedDetectionType1RealFreq.pClamp.data(inds,2:end));
inds = simulatedDetectionType2.minis.data(:,1) == iRec & simulatedDetectionType2.minis.data(:,2) > 0 & ...
simulatedDetectionType2.minis.data(:,3) > 0;
simulatedDetectionType2.minis.means(iRec,:) = mean(simulatedDetectionType2.minis.data(inds,2:end), 'omitnan');
simulatedDetectionType2.minis.min(iRec,:) = min(simulatedDetectionType2.minis.data(inds,2:end));
simulatedDetectionType2.minis.max(iRec,:) = max(simulatedDetectionType2.minis.data(inds,2:end));
inds = simulatedDetectionType2.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType2.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType2.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType2.MiniAnalysis.means(iRec,:) = mean(simulatedDetectionType2.MiniAnalysis.data(inds,2:end), 'omitnan');
simulatedDetectionType2.MiniAnalysis.min(iRec,:) = min(simulatedDetectionType2.MiniAnalysis.data(inds,2:end));
simulatedDetectionType2.MiniAnalysis.max(iRec,:) = max(simulatedDetectionType2.MiniAnalysis.data(inds,2:end));
inds = simulatedDetectionType2.pClamp.data(:,1) == iRec & simulatedDetectionType2.pClamp.data(:,2) > 0 & ...
simulatedDetectionType2.pClamp.data(:,3) > 0;
simulatedDetectionType2.pClamp.means(iRec,:) = mean(simulatedDetectionType2.pClamp.data(inds,2:end), 'omitnan');
simulatedDetectionType2.pClamp.min(iRec,:) = min(simulatedDetectionType2.pClamp.data(inds,2:end));
simulatedDetectionType2.pClamp.max(iRec,:) = max(simulatedDetectionType2.pClamp.data(inds,2:end));
inds = realDetection.minis.data(:,1) == iRec & realDetection.minis.data(:,2) > 0 & ...
realDetection.minis.data(:,3) > 0;
realDetection.minis.means(iRec,:) = mean(realDetection.minis.data(inds,2:end), 'omitnan');
realDetection.minis.min(iRec,:) = min(realDetection.minis.data(inds,2:end));
realDetection.minis.max(iRec,:) = max(realDetection.minis.data(inds,2:end));
inds = realDetection.MiniAnalysis.data(:,1) == iRec & realDetection.MiniAnalysis.data(:,2) > 0 & ...
realDetection.MiniAnalysis.data(:,3) > 0;
realDetection.MiniAnalysis.means(iRec,:) = mean(realDetection.MiniAnalysis.data(inds,2:end), 'omitnan');
realDetection.MiniAnalysis.min(iRec,:) = min(realDetection.MiniAnalysis.data(inds,2:end));
realDetection.MiniAnalysis.max(iRec,:) = max(realDetection.MiniAnalysis.data(inds,2:end));
realDetection.MiniAnalysis.max(iRec,1) = max(realDetection.MiniAnalysis.data(inds ...
& realDetection.MiniAnalysis.data(:,2) < 50, 2));
inds = realDetection.pClamp.data(:,1) == iRec & realDetection.pClamp.data(:,2) > 0 & ...
realDetection.pClamp.data(:,3) > 0;
realDetection.pClamp.means(iRec,:) = mean(realDetection.pClamp.data(inds,2:end), 'omitnan');
realDetection.pClamp.min(iRec,:) = min(realDetection.pClamp.data(inds,2:end));
realDetection.pClamp.max(iRec,:) = max(realDetection.pClamp.data(inds,2:end));
end
[simulatedDetectionType1All.minis.overallMean, simulatedDetectionType1All.minis.overallMeanCI] = datamean(simulatedDetectionType1All.minis.means);
[simulatedDetectionType1All.MiniAnalysis.overallMean, simulatedDetectionType1All.MiniAnalysis.overallMeanCI] = datamean(simulatedDetectionType1All.MiniAnalysis.means);
[simulatedDetectionType1All.pClamp.overallMean, simulatedDetectionType1All.pClamp.overallMeanCI] = datamean(simulatedDetectionType1All.pClamp.means);
[simulatedDetectionType1HighFreq.minis.overallMean, simulatedDetectionType1HighFreq.minis.overallMeanCI] = datamean(simulatedDetectionType1HighFreq.minis.means);
[simulatedDetectionType1HighFreq.MiniAnalysis.overallMean, simulatedDetectionType1HighFreq.MiniAnalysis.overallMeanCI] = datamean(simulatedDetectionType1HighFreq.MiniAnalysis.means);
[simulatedDetectionType1HighFreq.pClamp.overallMean, simulatedDetectionType1HighFreq.pClamp.overallMeanCI] = datamean(simulatedDetectionType1HighFreq.pClamp.means);
[simulatedDetectionType1LowFreq.minis.overallMean, simulatedDetectionType1LowFreq.minis.overallMeanCI] = datamean(simulatedDetectionType1LowFreq.minis.means);
[simulatedDetectionType1LowFreq.MiniAnalysis.overallMean, simulatedDetectionType1LowFreq.MiniAnalysis.overallMeanCI] = datamean(simulatedDetectionType1LowFreq.MiniAnalysis.means);
[simulatedDetectionType1LowFreq.pClamp.overallMean, simulatedDetectionType1LowFreq.pClamp.overallMeanCI] = datamean(simulatedDetectionType1LowFreq.pClamp.means);
[simulatedDetectionType1RealFreq.minis.overallMean, simulatedDetectionType1RealFreq.minis.overallMeanCI] = datamean(simulatedDetectionType1RealFreq.minis.means);
[simulatedDetectionType1RealFreq.MiniAnalysis.overallMean, simulatedDetectionType1RealFreq.MiniAnalysis.overallMeanCI] = datamean(simulatedDetectionType1RealFreq.MiniAnalysis.means);
[simulatedDetectionType1RealFreq.pClamp.overallMean, simulatedDetectionType1RealFreq.pClamp.overallMeanCI] = datamean(simulatedDetectionType1RealFreq.pClamp.means);
[simulatedDetectionType2.minis.overallMean, simulatedDetectionType2.minis.overallMeanCI] = datamean(simulatedDetectionType2.minis.means);
[simulatedDetectionType2.MiniAnalysis.overallMean, simulatedDetectionType2.MiniAnalysis.overallMeanCI] = datamean(simulatedDetectionType2.MiniAnalysis.means);
[simulatedDetectionType2.pClamp.overallMean, simulatedDetectionType2.pClamp.overallMeanCI] = datamean(simulatedDetectionType2.pClamp.means);
[realDetection.minis.overallMean, realDetection.minis.overallMeanCI] = datamean(realDetection.minis.means);
[realDetection.MiniAnalysis.overallMean, realDetection.MiniAnalysis.overallMeanCI] = datamean(realDetection.MiniAnalysis.means);
[realDetection.pClamp.overallMean, realDetection.pClamp.overallMeanCI] = datamean(realDetection.pClamp.means);
simulatedDetectionType1All.minis.range = [min(simulatedDetectionType1All.minis.min); max(simulatedDetectionType1All.minis.max)];
simulatedDetectionType1All.MiniAnalysis.range = [min(simulatedDetectionType1All.MiniAnalysis.min); max(simulatedDetectionType1All.MiniAnalysis.max)];
simulatedDetectionType1All.pClamp.range = [min(simulatedDetectionType1All.pClamp.min); max(simulatedDetectionType1All.pClamp.max)];
simulatedDetectionType1HighFreq.minis.range = [min(simulatedDetectionType1HighFreq.minis.min); max(simulatedDetectionType1HighFreq.minis.max)];
simulatedDetectionType1HighFreq.MiniAnalysis.range = [min(simulatedDetectionType1HighFreq.MiniAnalysis.min); max(simulatedDetectionType1HighFreq.MiniAnalysis.max)];
simulatedDetectionType1HighFreq.pClamp.range = [min(simulatedDetectionType1HighFreq.pClamp.min); max(simulatedDetectionType1HighFreq.pClamp.max)];
simulatedDetectionType1LowFreq.minis.range = [min(simulatedDetectionType1LowFreq.minis.min); max(simulatedDetectionType1LowFreq.minis.max)];
simulatedDetectionType1LowFreq.MiniAnalysis.range = [min(simulatedDetectionType1LowFreq.MiniAnalysis.min); max(simulatedDetectionType1LowFreq.MiniAnalysis.max)];
simulatedDetectionType1LowFreq.pClamp.range = [min(simulatedDetectionType1LowFreq.pClamp.min); max(simulatedDetectionType1LowFreq.pClamp.max)];
simulatedDetectionType1RealFreq.minis.range = [min(simulatedDetectionType1RealFreq.minis.min); max(simulatedDetectionType1RealFreq.minis.max)];
simulatedDetectionType1RealFreq.MiniAnalysis.range = [min(simulatedDetectionType1RealFreq.MiniAnalysis.min); max(simulatedDetectionType1RealFreq.MiniAnalysis.max)];
simulatedDetectionType1RealFreq.pClamp.range = [min(simulatedDetectionType1RealFreq.pClamp.min); max(simulatedDetectionType1RealFreq.pClamp.max)];
simulatedDetectionType2.minis.range = [min(simulatedDetectionType2.minis.min); max(simulatedDetectionType2.minis.max)];
simulatedDetectionType2.MiniAnalysis.range = [min(simulatedDetectionType2.MiniAnalysis.min); max(simulatedDetectionType2.MiniAnalysis.max)];
simulatedDetectionType2.pClamp.range = [min(simulatedDetectionType2.pClamp.min); max(simulatedDetectionType2.pClamp.max)];
realDetection.minis.range = [min(realDetection.minis.min); max(realDetection.minis.max)];
realDetection.MiniAnalysis.range = [min(realDetection.MiniAnalysis.min); max(realDetection.MiniAnalysis.max)];
realDetection.pClamp.range = [min(realDetection.pClamp.min); max(realDetection.pClamp.max)];
% Incidence rates
simulatedDetectionType1All.minis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1All.MiniAnalysis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1All.pClamp.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1HighFreq.minis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1HighFreq.MiniAnalysis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1HighFreq.pClamp.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1LowFreq.minis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1LowFreq.MiniAnalysis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1LowFreq.pClamp.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1RealFreq.minis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1RealFreq.MiniAnalysis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType1RealFreq.pClamp.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType2.minis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType2.MiniAnalysis.incidenceRates = zeros(numel(recs),1);
simulatedDetectionType2.pClamp.incidenceRates = zeros(numel(recs),1);
realDetection.minis.incidenceRates = zeros(numel(recs),1);
realDetection.MiniAnalysis.incidenceRates = zeros(numel(recs),1);
realDetection.pClamp.incidenceRates = zeros(numel(recs),1);
for iRec = 1:numel(recs)
inds = simulatedDetectionType1All.minis.data(:,1) == iRec & simulatedDetectionType1All.minis.data(:,2) > 0 & ...
simulatedDetectionType1All.minis.data(:,3) > 0;
simulatedDetectionType1All.minis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*nConditions(1));
simulatedDetectionType1All.minis.max(iRec,:) = max(simulatedDetectionType1All.minis.data(inds,2:end));
inds = simulatedDetectionType1All.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1All.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1All.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1All.MiniAnalysis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*nConditions(1));
inds = simulatedDetectionType1All.pClamp.data(:,1) == iRec & simulatedDetectionType1All.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1All.pClamp.data(:,3) > 0;
simulatedDetectionType1All.pClamp.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*nConditions(1));
inds = simulatedDetectionType1HighFreq.minis.data(:,1) == iRec & simulatedDetectionType1HighFreq.minis.data(:,2) > 0 & ...
simulatedDetectionType1HighFreq.minis.data(:,3) > 0;
simulatedDetectionType1HighFreq.minis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*numel(highFreqMinis));
inds = simulatedDetectionType1HighFreq.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1HighFreq.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1HighFreq.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1HighFreq.MiniAnalysis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*numel(highFreqMinis));
inds = simulatedDetectionType1HighFreq.pClamp.data(:,1) == iRec & simulatedDetectionType1HighFreq.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1HighFreq.pClamp.data(:,3) > 0;
simulatedDetectionType1HighFreq.pClamp.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*numel(highFreqMinis));
inds = simulatedDetectionType1LowFreq.minis.data(:,1) == iRec & simulatedDetectionType1LowFreq.minis.data(:,2) > 0 & ...
simulatedDetectionType1LowFreq.minis.data(:,3) > 0;
simulatedDetectionType1LowFreq.minis.incidenceRates(iRec) = ...
sum(inds)/(durations(iRec)*4*(nConditions(1)-numel(highFreqMinis)-numel(realFreqMinis)));
inds = simulatedDetectionType1LowFreq.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1LowFreq.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1LowFreq.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1LowFreq.MiniAnalysis.incidenceRates(iRec) = ...
sum(inds)/(durations(iRec)*4*(nConditions(1)-numel(highFreqMinis)-numel(realFreqMinis)));
inds = simulatedDetectionType1LowFreq.pClamp.data(:,1) == iRec & simulatedDetectionType1LowFreq.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1LowFreq.pClamp.data(:,3) > 0;
simulatedDetectionType1LowFreq.pClamp.incidenceRates(iRec) = ...
sum(inds)/(durations(iRec)*4*(nConditions(1)-numel(highFreqMinis)-numel(realFreqMinis)));
inds = simulatedDetectionType1RealFreq.minis.data(:,1) == iRec & simulatedDetectionType1RealFreq.minis.data(:,2) > 0 & ...
simulatedDetectionType1RealFreq.minis.data(:,3) > 0;
simulatedDetectionType1RealFreq.minis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*numel(realFreqMinis));
inds = simulatedDetectionType1RealFreq.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType1RealFreq.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType1RealFreq.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType1RealFreq.MiniAnalysis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*numel(realFreqMinis));
inds = simulatedDetectionType1RealFreq.pClamp.data(:,1) == iRec & simulatedDetectionType1RealFreq.pClamp.data(:,2) > 0 & ...
simulatedDetectionType1RealFreq.pClamp.data(:,3) > 0;
simulatedDetectionType1RealFreq.pClamp.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*numel(realFreqMinis));
inds = simulatedDetectionType2.minis.data(:,1) == iRec & simulatedDetectionType2.minis.data(:,2) > 0 & ...
simulatedDetectionType2.minis.data(:,3) > 0;
simulatedDetectionType2.minis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*nConditions(2));
inds = simulatedDetectionType2.MiniAnalysis.data(:,1) == iRec & simulatedDetectionType2.MiniAnalysis.data(:,2) > 0 & ...
simulatedDetectionType2.MiniAnalysis.data(:,3) > 0;
simulatedDetectionType2.MiniAnalysis.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*nConditions(2));
inds = simulatedDetectionType2.pClamp.data(:,1) == iRec & simulatedDetectionType2.pClamp.data(:,2) > 0 & ...
simulatedDetectionType2.pClamp.data(:,3) > 0;
simulatedDetectionType2.pClamp.incidenceRates(iRec) = sum(inds)/(durations(iRec)*4*nConditions(2));
inds = realDetection.minis.data(:,1) == iRec & realDetection.minis.data(:,2) > 0 & ...
realDetection.minis.data(:,3) > 0;
realDetection.minis.incidenceRates(iRec) = sum(inds)/(durationsReal(iRec));
inds = realDetection.MiniAnalysis.data(:,1) == iRec & realDetection.MiniAnalysis.data(:,2) > 0 & ...
realDetection.MiniAnalysis.data(:,3) > 0;
realDetection.MiniAnalysis.incidenceRates(iRec) = sum(inds)/(durationsReal(iRec));
inds = realDetection.pClamp.data(:,1) == iRec & realDetection.pClamp.data(:,2) > 0 & ...
realDetection.pClamp.data(:,3) > 0;
realDetection.pClamp.incidenceRates(iRec) = sum(inds)/(durationsRealpClamp(iRec));
end
[simulatedDetectionType1All.minis.meanIncidenceRate, simulatedDetectionType1All.minis.meanIncidenceRateCI] = datamean(simulatedDetectionType1All.minis.incidenceRates);
[simulatedDetectionType1All.MiniAnalysis.meanIncidenceRate, simulatedDetectionType1All.MiniAnalysis.meanIncidenceRateCI] = datamean(simulatedDetectionType1All.MiniAnalysis.incidenceRates);
[simulatedDetectionType1All.pClamp.meanIncidenceRate, simulatedDetectionType1All.pClamp.meanIncidenceRateCI] = datamean(simulatedDetectionType1All.pClamp.incidenceRates);
[simulatedDetectionType1HighFreq.minis.meanIncidenceRate, simulatedDetectionType1HighFreq.minis.meanIncidenceRateCI] = datamean(simulatedDetectionType1HighFreq.minis.incidenceRates);
[simulatedDetectionType1HighFreq.MiniAnalysis.meanIncidenceRate, simulatedDetectionType1HighFreq.MiniAnalysis.meanIncidenceRateCI] = datamean(simulatedDetectionType1HighFreq.MiniAnalysis.incidenceRates);
[simulatedDetectionType1HighFreq.pClamp.meanIncidenceRate, simulatedDetectionType1HighFreq.pClamp.meanIncidenceRateCI] = datamean(simulatedDetectionType1HighFreq.pClamp.incidenceRates);
[simulatedDetectionType1LowFreq.minis.meanIncidenceRate, simulatedDetectionType1LowFreq.minis.meanIncidenceRateCI] = datamean(simulatedDetectionType1LowFreq.minis.incidenceRates);
[simulatedDetectionType1LowFreq.MiniAnalysis.meanIncidenceRate, simulatedDetectionType1LowFreq.MiniAnalysis.meanIncidenceRateCI] = datamean(simulatedDetectionType1LowFreq.MiniAnalysis.incidenceRates);
[simulatedDetectionType1LowFreq.pClamp.meanIncidenceRate, simulatedDetectionType1LowFreq.pClamp.meanIncidenceRateCI] = datamean(simulatedDetectionType1LowFreq.pClamp.incidenceRates);
[simulatedDetectionType1RealFreq.minis.meanIncidenceRate, simulatedDetectionType1RealFreq.minis.meanIncidenceRateCI] = datamean(simulatedDetectionType1RealFreq.minis.incidenceRates);
[simulatedDetectionType1RealFreq.MiniAnalysis.meanIncidenceRate, simulatedDetectionType1RealFreq.MiniAnalysis.meanIncidenceRateCI] = datamean(simulatedDetectionType1RealFreq.MiniAnalysis.incidenceRates);
[simulatedDetectionType1RealFreq.pClamp.meanIncidenceRate, simulatedDetectionType1RealFreq.pClamp.meanIncidenceRateCI] = datamean(simulatedDetectionType1RealFreq.pClamp.incidenceRates);
[simulatedDetectionType2.minis.meanIncidenceRate, simulatedDetectionType2.minis.meanIncidenceRateCI] = datamean(simulatedDetectionType2.minis.incidenceRates);
[simulatedDetectionType2.MiniAnalysis.meanIncidenceRate, simulatedDetectionType2.MiniAnalysis.meanIncidenceRateCI] = datamean(simulatedDetectionType2.MiniAnalysis.incidenceRates);
[simulatedDetectionType2.pClamp.meanIncidenceRate, simulatedDetectionType2.pClamp.meanIncidenceRateCI] = datamean(simulatedDetectionType2.pClamp.incidenceRates);
[realDetection.minis.meanIncidenceRate, realDetection.minis.meanIncidenceRateCI] = datamean(realDetection.minis.incidenceRates);
[realDetection.MiniAnalysis.meanIncidenceRate, realDetection.MiniAnalysis.meanIncidenceRateCI] = datamean(realDetection.MiniAnalysis.incidenceRates);
[realDetection.pClamp.meanIncidenceRate, realDetection.pClamp.meanIncidenceRateCI] = datamean(realDetection.pClamp.incidenceRates);
%% Stats on means
true_amplitudes = [0.3 0.3 0.3 0.3 mean(0.05:0.05:0.5) NaN]';
true_RTs = [repmat(2.6, 1, 5) NaN]';
simTau_m = [13.5288 12.4926 8.95132 10.9887 9.99453 9.06286 10.3236 9.3484 ...
7.54192 8.32906 10.0965 13.8749 13.395 14.3358]';
[trueDecay, trueDecay95CI] = datamean(simTau_m);
true_decays = [repmat(trueDecay, 1, 6)]';
true_decay_95CI = [repmat(trueDecay95CI(2), 1, 6)]';
refIR = 700;
adjustedIncidenceRates = [refIR refIR/2 refIR/4 refIR/8 refIR/16 refIR/32 ...
refIR/64 refIR/128 refIR/256 refIR/256 refIR/256 refIR/256 refIR/256 refIR/256];
true_incidenceRates = ([mean(adjustedIncidenceRates) ...
mean(adjustedIncidenceRates(1:3)) mean(adjustedIncidenceRates(7:end)) ...
mean(adjustedIncidenceRates(4:6)) mean([61 38 27]) NaN]').*(1 - 1/14);
meanInd = 1;
trueMeans = repmat([true_amplitudes(meanInd) true_RTs(meanInd) true_decays(meanInd)], numel(recs), 1);
minisMeans = [simulatedDetectionType1All.minis.means(:,1:end-2) (simulatedDetectionType1All.minis.means(:,3)+simulatedDetectionType1All.minis.means(:,4))/2];
[~, simulatedDetectionType1All.stats.minisVMiniAnalysis.p, ~, stats] = ttest(minisMeans, simulatedDetectionType1All.MiniAnalysis.means);
simulatedDetectionType1All.stats.minisVMiniAnalysis.t = stats.tstat;
[~, simulatedDetectionType1All.stats.minisVpClamp.p, ~, stats] = ttest(minisMeans, simulatedDetectionType1All.pClamp.means);
simulatedDetectionType1All.stats.minisVpClamp.t = stats.tstat;
[~, simulatedDetectionType1All.stats.minisVtrue.p, ~, stats] = ttest(minisMeans - trueMeans);
simulatedDetectionType1All.stats.minisVtrue.t = stats.tstat;
[~, simulatedDetectionType1All.stats.minisVtrue.p(3), ~, stats] = ttest(minisMeans(:,3), simTau_m);
simulatedDetectionType1All.stats.minisVtrue.t(3) = stats.tstat;
[~, simulatedDetectionType1All.stats.MiniAnalysisVpClamp.p, ~, stats] = ttest(simulatedDetectionType1All.MiniAnalysis.means, simulatedDetectionType1All.pClamp.means);
simulatedDetectionType1All.stats.MiniAnalysisVpClamp.t = stats.tstat;
[~, simulatedDetectionType1All.stats.MiniAnalysisVtrue.p, ~, stats] = ttest(simulatedDetectionType1All.MiniAnalysis.means - trueMeans);
simulatedDetectionType1All.stats.MiniAnalysisVtrue.t = stats.tstat;
[~, simulatedDetectionType1All.stats.MiniAnalysisVtrue.p(3), ~, stats] = ttest(simulatedDetectionType1All.MiniAnalysis.means(:,3), simTau_m);
simulatedDetectionType1All.stats.MiniAnalysisVtrue.t(3) = stats.tstat;
[~, simulatedDetectionType1All.stats.pClampVtrue.p, ~, stats] = ttest(simulatedDetectionType1All.pClamp.means - trueMeans);
simulatedDetectionType1All.stats.pClampVtrue.t = stats.tstat;
[~, simulatedDetectionType1All.stats.pClampVtrue.p(3), ~, stats] = ttest(simulatedDetectionType1All.pClamp.means(:,3), simTau_m);
simulatedDetectionType1All.stats.pClampVtrue.t(3) = stats.tstat;
[~, simulatedDetectionType1All.statsIncidenceRates.minisVMiniAnalysis.p, ~, stats] = ttest( ...
simulatedDetectionType1All.minis.incidenceRates, simulatedDetectionType1All.MiniAnalysis.incidenceRates);
simulatedDetectionType1All.statsIncidenceRates.minisVMiniAnalysis.t = stats.tstat;
[~, simulatedDetectionType1All.statsIncidenceRates.minisVpClamp.p, ~, stats] = ttest( ...
simulatedDetectionType1All.minis.incidenceRates, simulatedDetectionType1All.pClamp.incidenceRates);
simulatedDetectionType1All.statsIncidenceRates.minisVpClamp.t = stats.tstat;
[~, simulatedDetectionType1All.statsIncidenceRates.minisVtrue.p, ~, stats] = ttest( ...
simulatedDetectionType1All.minis.incidenceRates - repmat(true_incidenceRates(meanInd), numel(recs), 1));
simulatedDetectionType1All.statsIncidenceRates.minisVtrue.t = stats.tstat;
[~, simulatedDetectionType1All.statsIncidenceRates.MiniAnalysisVpClamp.p, ~, stats] = ttest( ...
simulatedDetectionType1All.MiniAnalysis.incidenceRates, simulatedDetectionType1All.pClamp.incidenceRates);
simulatedDetectionType1All.statsIncidenceRates.MiniAnalysisVpClamp.t = stats.tstat;
[~, simulatedDetectionType1All.statsIncidenceRates.MiniAnalysisVtrue.p, ~, stats] = ttest( ...
simulatedDetectionType1All.MiniAnalysis.incidenceRates - repmat(true_incidenceRates(meanInd), numel(recs), 1));
simulatedDetectionType1All.statsIncidenceRates.MiniAnalysisVtrue.t = stats.tstat;
[~, simulatedDetectionType1All.statsIncidenceRates.pClampVtrue.p, ~, stats] = ttest( ...
simulatedDetectionType1All.pClamp.incidenceRates - repmat(true_incidenceRates(meanInd), numel(recs), 1));
simulatedDetectionType1All.statsIncidenceRates.pClampVtrue.t = stats.tstat;
meanInd = 2;
trueMeans = repmat([true_amplitudes(meanInd) true_RTs(meanInd) true_decays(meanInd)], numel(recs), 1);
minisMeans = [simulatedDetectionType1HighFreq.minis.means(:,1:end-2) (simulatedDetectionType1HighFreq.minis.means(:,3)+simulatedDetectionType1HighFreq.minis.means(:,4))/2];
[~, simulatedDetectionType1HighFreq.stats.minisVMiniAnalysis.p, ~, stats] = ttest(minisMeans, simulatedDetectionType1HighFreq.MiniAnalysis.means);
simulatedDetectionType1HighFreq.stats.minisVMiniAnalysis.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.minisVpClamp.p, ~, stats] = ttest(minisMeans, simulatedDetectionType1HighFreq.pClamp.means);
simulatedDetectionType1HighFreq.stats.minisVpClamp.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.minisVtrue.p, ~, stats] = ttest(minisMeans - trueMeans);
simulatedDetectionType1HighFreq.stats.minisVtrue.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.minisVtrue.p(3), ~, stats] = ttest(minisMeans(:,3), simTau_m);
simulatedDetectionType1HighFreq.stats.minisVtrue.t(3) = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.MiniAnalysisVpClamp.p, ~, stats] = ttest(simulatedDetectionType1HighFreq.MiniAnalysis.means, simulatedDetectionType1HighFreq.pClamp.means);
simulatedDetectionType1HighFreq.stats.MiniAnalysisVpClamp.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.MiniAnalysisVtrue.p, ~, stats] = ttest(simulatedDetectionType1HighFreq.MiniAnalysis.means - trueMeans);
simulatedDetectionType1HighFreq.stats.MiniAnalysisVtrue.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.MiniAnalysisVtrue.p(3), ~, stats] = ttest(simulatedDetectionType1HighFreq.MiniAnalysis.means(:,3), simTau_m);
simulatedDetectionType1HighFreq.stats.MiniAnalysisVtrue.t(3) = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.pClampVtrue.p, ~, stats] = ttest(simulatedDetectionType1HighFreq.pClamp.means - trueMeans);
simulatedDetectionType1HighFreq.stats.pClampVtrue.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.stats.pClampVtrue.p(3), ~, stats] = ttest(simulatedDetectionType1HighFreq.pClamp.means(:,3), simTau_m);
simulatedDetectionType1HighFreq.stats.pClampVtrue.t(3) = stats.tstat;
[~, simulatedDetectionType1HighFreq.statsIncidenceRates.minisVMiniAnalysis.p, ~, stats] = ttest( ...
simulatedDetectionType1HighFreq.minis.incidenceRates, simulatedDetectionType1HighFreq.MiniAnalysis.incidenceRates);
simulatedDetectionType1HighFreq.statsIncidenceRates.minisVMiniAnalysis.t = stats.tstat;
[~, simulatedDetectionType1HighFreq.statsIncidenceRates.minisVpClamp.p, ~, stats] = ttest( ...
simulatedDetectionType1HighFreq.minis.incidenceRates, simulatedDetectionType1HighFreq.pClamp.incidenceRates);
simulatedDetectionType1HighFreq.statsIncidenceRates.minisVpClamp.t = stats.tstat;