how to do neuron spike sorting in matlab

main.m
% Neuron spike sorting in Matlab can be achieved by using clustering algorithms
% such as k-means or Gaussian mixture models (GMM).

% Load the spike data
spike_data = load('spike_data.mat');

% Preprocess the spike data (filtering, feature extraction, normalization, etc.)

% Apply dimensionality reduction techniques if necessary
% For example, using Principal Component Analysis (PCA)
[coeff, score, latent] = pca(spike_data);

% Choose the number of clusters using Elbow method or other validation techniques

% Perform clustering using k-means
num_clusters = 3; % specify the number of clusters
[idx, C] = kmeans(score, num_clusters);

% Visualize the clustered data
scatter3(score(:,1), score(:,2), score(:,3), 10, idx, 'filled');
xlabel('PC1');
ylabel('PC2');
zlabel('PC3');
title('Clustered Neuron Spikes');

% Alternatively, you can use Gaussian Mixture Models (GMM) for clustering
% using the fitgmdist() function

% Reference: https://www.mathworks.com/help/stats/cluster-ensemble.html

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