A method for unsupervised sorting, in real time, of action potentials of biological neurons by a network of artificial neurons including input, intermediate and output layers, the method according to which: the input layer receives an electrical signal measuring an electrical activity of biological neurons, the electrical signal having a variable amplitude as a function of action potentials emitted by the plurality of biological neurons over time; the input layer converts the amplitude of the electrical signal into a train of first spikes; the input layer transmits the train of first spikes to the intermediate layer; the intermediate layer converts the train of first spikes into a train of second spikes; the intermediate layer transmits the train of second spikes to the output layer; as a function of the train of second spikes, the output layer sorts each occurrence of each type of action potential present in the electrical signal.
Method for unsupervised sorting in real time of action potentials of a plurality of biological neurons