-
Notifications
You must be signed in to change notification settings - Fork 0
/
intensity_population_ana.m
246 lines (199 loc) · 9.44 KB
/
intensity_population_ana.m
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
function intensity_population_ana
% %SCNN-CHR2 Population
% animalids = {'150323', '150325','150326'};
% blocks = [7, 7, 5];
% animal = [1 2, 3];
% popfile = 'C:\Users\Julia\work\data\populations\scnn_chr2\intensity_population.mat';
% SOM later population
animalids = {'150331', '150401','150527','150529','150602','150603','150825','150831','150902', '151023', '151109', '151110'};
blocks = [5, 9, 13, 9, 9, 8, 16, 10, 15, 17, 11, 16];
animal = [1, 2, 3, 4, 5, 6, 7, 8, 9, 11, 12, 13];
electrodes =[[1,32]; [1,32]; [1,32]; [1,32]; [1,32]; [1,16]; [17,32]; [1,16]; [1,16]; [17,32]; [17,32]; [1,16]];
penangle = [25, 25, 25, 25, 25, 10, 25, 25, 25, 25, 25, 25];
% age [P6, P6, P2?(P0), P2?(P0), P2?(P0), P1
popfile = 'C:\Users\Julia\work\data\populations\SOM_Halo_later\intensity\intensity_population.mat';
recalculate = 0;
prestim = 300;
% poststim = 300;
poststim = 300;
respwin = 501:1500; % after stimulus onset
% respwin = 501:4500; % after stimulus onset
respwin = respwin+prestim;
if ~exist(popfile) || recalculate
cll = 1;
for blck = 1: length(blocks)
supath = ['C:\Users\Julia\work\data\' animalids{blck} '\singleunits\'];
basename = [animalids{blck} '_block' int2str(blocks(blck)) '_tet'];
files = dir([supath, basename, '*.mat']);
prestim = 300;
poststim = 700;
respwin = 501:1500; % after stimulus onset
respwin = respwin+prestim;
for fi = 1:length(files)
if strfind(files(fi).name, 'MU')
continue;
end
load([supath, files(fi).name]);
% calc spiking to see if includable
msStimes = round(result.spikes);
if ~isempty(msStimes) & msStimes(1) == 0, msStimes(1) = 1; end
chan = zeros(1,length(result.lfp));
chan(msStimes) = 1;
wvchan = find(var(result.waveforms) == max(var(result.waveforms)));
trialdur = result.stimduration*1000;
msstamps = result.msstamps;
if length(msstamps)~=length(result.light)
% msstamps(385) = []; % for 140703 block 5
% result.msstamps = msstamps;
% save([supath, files(fi).name],'result');
pause;
end
for i = 1:length(msstamps)
resp(i,:) = chan(msstamps(i) - prestim+1:msstamps(i) + trialdur + poststim);
lfpresp(i,:) = result.lfp(msstamps(i) - prestim+1:msstamps(i) + trialdur + poststim);
speed(i,:) = result.runspeed(msstamps(i) - prestim+1:msstamps(i) + trialdur + poststim);
end
% figure out sufficiently high and nonvariable runspeed trials
meanspeed = mean(speed(:,respwin),2);
stdspeed = std(speed(:,respwin),1,2);
notstill = find(meanspeed>1);
okspeed = find(meanspeed>( mean(meanspeed(notstill))-(1.5*std(meanspeed(notstill))) ) );
okvar = find(stdspeed<( mean(stdspeed(notstill))+(1.5*std(stdspeed(notstill)))) & stdspeed>.5);
oktrials = intersect(okspeed,okvar);
nonoktrials = 1:size(resp,1); nonoktrials(oktrials) = [];
stilltrials = 1:size(resp,1); stilltrials(notstill) = [];
frs = sum(resp(:,respwin),2)./(length(respwin)/1000);
bl = sum(resp(:,1:prestim),2)./(prestim/1000);
%determine if cell is visually modulated
blfr = sum(resp(:,1:prestim),2);
cellname{cll} = files(fi).name;
i = strfind(files(fi).name, 'tet');
if strcmp(files(fi).name(i+4),'_')
tetno = strread(files(fi).name(i+3)); % single character number
else
tetno = strread(files(fi).name(i+3:i+4)); % number >10
end
tetnos(cll) = tetno;
if tetno>8
v1(cll) = logical(0); v2(cll) = logical(1); cellstr = 'V2';
else
v1(cll) = logical(1); v2(cll) = logical(0); cellstr = 'V1';
end
spike = result.waveforms(:,wvchan);
interpspike = spline(1:32,spike,1:.1:32);
[adiff(cll),swidth(cll),ptr(cll),eslope(cll)] = spikequant(interpspike);
depth(cll) = result.depth;
cellresp(cll,:,:) = resp;
celllfpresp(cll,:,:) = lfpresp;
msta = linspace(-prestim,trialdur+poststim,size(resp,2));
printname = files(fi).name;
printname(find(printname=='_')) = ' ';
binwidth = 50;
oris = unique(result.gratingInfo.Orientation); oris(find(oris == 180)) = [];
lightlevels = unique(result.light);
for l = 1:length(lightlevels)
for ori = 1:length(oris)
thisinds = find((result.gratingInfo.Orientation == oris(ori) | result.gratingInfo.Orientation ==oris(ori)+180) &...
result.light == lightlevels(l));
condn(l,ori) = length(thisinds);
condresp(l,ori,:) = nanmean(resp(thisinds,:),1);
condresperr(l,ori,:) = nanstd(resp(thisinds,:),1,1)./sqrt(length(thisinds));
if ~isnan(condresp(l,ori,:))
[bincondresp(l,ori,:),bta] = binit(condresp(l,ori,:),binwidth);
else
bincondresp(l,ori,:) = binit(condresp(l,ori,:),binwidth);
end
binconderr(l,ori,:) = binit(condresperr(l,ori,:),binwidth);
cfr(l,ori) = nanmean(frs(thisinds));
cerr(l,ori) =nanstd(frs(thisinds))./sqrt(length(thisinds));
end
end
bincondresp = bincondresp.*(1000/binwidth);
binconderr = binconderr.*(1000/binwidth);
bta = bta-prestim;
% anovavec = [cfr(:,1);cfr(:,2)];
% g1 = ones(numel(cfr),1); g1(1:6) = 0;
% g2 = [lightlevels';lightlevels'];
% [p(cll,:),table,stats] = anovan(anovavec,{g1 g2},'display','off');
% figure('name' ,['cll: ' int2str(cll), ' p vis: ' num2str(p(cll,1)) ' p light: ' num2str(p(cll,2))])
% for i = 1:6
% subplot(2,6,i)
% boundedline(bta, squeeze(bincondresp(i,1,:)),squeeze(binconderr(i,1,:)));
% hold on
% line([500,500],[0,max(max(max(bincondresp)))+max(max(max(binconderr)))],'color','r')
% % line([5500,5500],[0,max(max(max(bincondresp)))+max(max(max(binconderr)))],'color','r')
% line([1500,1500],[0,max(max(max(bincondresp)))+max(max(max(binconderr)))],'color','r')
% % axis([-300,8300,0,max(max(max(bincondresp)))+max(max(max(binconderr)))+1])
% axis([-300,2300,0,max(max(max(bincondresp)))+max(max(max(binconderr)))+1])
% title(['level: ' num2str(lightlevels(i))]);
%
% subplot(2,6,6+i)
% boundedline(bta, squeeze(bincondresp(i,2,:)),squeeze(binconderr(i,2,:)));
% hold on
% line([500,500],[0,max(max(max(bincondresp)))+max(max(max(binconderr)))],'color','r')
% % line([5500,5500],[0,max(max(max(bincondresp)))+max(max(max(binconderr)))],'color','r')
% line([1500,1500],[0,max(max(max(bincondresp)))+max(max(max(binconderr)))],'color','r')
% % axis([-300,8300,0,max(max(max(bincondresp)))+max(max(max(binconderr)))+1])
% axis([-300,2300,0,max(max(max(bincondresp)))+max(max(max(binconderr)))+1])
% end
%
% figure
% errorbar(lightlevels,cfr(:,1),cerr(:,1),'.')
% hold on
% errorbar(lightlevels,cfr(:,2),cerr(:,2),'r.')
% xlabel('lightintensity % max')
% ylabel('firing rate [Hz]')
% legend([{'no stimulus'},{'drifting grating'}])
% title(['cell: ' cellname{cll}, ' spikewidth: ' num2str(swidth(cll)) ' depth: ' num2str(depth(cll))])
condfr(cll,:,:) = cfr; conderr(cll,:,:) = cerr;
cll = cll+1;
disp('');
end
end
save(popfile, '-v7.3');
else
load(popfile);
end
%spike classification
kmeansind = kmeans([eslope',ptr',swidth',adiff'],2);
if mean(swidth(find(kmeansind==1)))<mean(swidth(find(kmeansind==2))) %1 is FS
pfs = find(kmeansind==1); prs = find(kmeansind==2); pfsv = kmeansind==1; prsv = kmeansind==2;
else
pfs = find(kmeansind==2); prs = find(kmeansind==1); pfsv = kmeansind==2; prsv = kmeansind==1;
end
secpersamp = 1/30000;
interpf = secpersamp/10;
swidthms = swidth*interpf*1000;
figure
plot(swidthms(prs),adiff(prs),'b.')
xlabel('spike width')
ylabel('amplitude diff')
hold on
plot(swidthms(pfs),adiff(pfs),'r.')
% axis([5.5,20.5,-.9,.7])
l23 = depth<375;
l4 = depth>=375&depth<=500;
l5 = depth>500&depth<=800;
l23rs = l23&prsv';
l23fs = l23&pfsv';
l4rs = l4&prsv';
l4fs = l4&pfsv';
l5rs = l5&prsv';
l5fs = l5&pfsv';
for i = 1:5
condomi(:,i,:) = (condfr(:,i+1,:)-condfr(:,1,:))./(condfr(:,i+1,:)+condfr(:,1,:));
end
cond = l5rs;
figure
hold on
for i = find(cond)
for j = 1:5
plot(j,condomi(i,j,1),'o')
end
end
for i = find(cond)
plot(condomi(i,:,1))
end
axis([.5,5.5,-1.1,1.1])
line([.5,5.5],[0,0],'color','r')
disp('')