神经生理学记录MATLAB

Question

我将我的数据存储在与神经元记录相关的结构中。神经元尖峰电位存储在逻辑数组中，其中尖峰电位为1，没有尖峰电位为0。

spike = <1x50 logical> 
spike = [1 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1 1 0 1 0 1 0 0 0 1 1 0 0 ...]

我要做的是用高斯滤波器将这些尖峰信号转换成平滑的曲线信号。

我有以下平滑函数：

function z = spikes(x, winWidth)
% places a Gaussian centered on every spike
% if x is matrix, then perform on the columns

winWidth = round(winWidth);

if winWidth == 0
    y = [0 1 0];
    w = 1;
else
    w = winWidth * 5;
    t = -w : w;
    y = normpdf(t,0,winWidth);
end

if isvector(x)
    z = conv(x,y);
    z = z(w+1 : end);
    z = z(1 : length(x));
else
    z = zeros(size(x));
    for i = 1 : size(x,2)
        z1 = conv(x(:,i),y);
        z1 = z1(w+1 : end);
        z1 = z1(1 : length(x));
        z(:,i) = z1;
    end
end

end

我只是想知道如何从像上面的逻辑数组这样的尖峰信号中产生神经信号？

附言:我很迷茫，我的答案不能理解的贴在这里。

Answer 1

如果我理解正确的话，你只需要增加采样频率和卷积。由于原始数组对应于采样频率为一个尖峰的信号，如果您想要提高尖峰的分辨率，则需要在尖峰之间人为地引入更多数据点。

spike = [1 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1 1 0 1 0 1 0 0 0 1 1 0 0];

![n_samples = numel(spike);
resampling_f = 50;
new_signal = zeros(n_samples*resampling_f,1);

spikes_ind = find(spike);
new_signal((spikes_ind-1)*50+round(resampling_f/2)) = 1;

%here you can use the spikes function you defined
winWidth = 10;
w = winWidth * 5;
t = -w : w;
kernel = normpdf(t,0,winWidth);
spikes_sample = conv(x,kernel);

figure, hold on
subplot(1,2,1), hold on
plot(new_signal)

subplot(1,2,2), hold on
plot(spikes_sample)][1]

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