Neuron discharge spike signal picking method and device and computer equipment

Abstract

The invention relates to a neuron discharge spike signal picking method and device, computer equipment and a storage medium. The method comprises the following steps: preprocessing a to-be-picked neuron discharge signal to obtain a continuous filtering discharge signal; performing energy calculation on the continuous filtering discharge signal to obtain a continuous energy signal; performing peakvalue statistics on the continuous energy signal to determine an energy peak value; establishing a cumulative distribution function of chi-square distribution according to the continuous energy signals for analysis, and determining a picking threshold; screening the energy peak values through a preliminary peak value extraction model constructed by the picking threshold value to obtain a preliminary peak value; extracting a signal segment in the continuous filtering discharge signal according to the preliminary peak value to obtain a discharge signal segment; and analyzing the discharge signalsegment according to the picking threshold, and determining a neuron discharge peak signal. Through the method, the robustness of picking the neuron discharge spike signals is stronger, and the accuracy of the picking result is also improved.

Description

technical field [0001] The present application relates to the technical field of digital signal processing, in particular to a method, device, computer equipment and storage medium for picking out neuron discharge spike signals. Background technique [0002] When collecting neural signals, a high sampling rate method is used to record the continuous signals around the neurons, and the neuron spike signal (Spike) is a short discharge process, lasting about 1ms. In order to extract this short-term signal, the commonly used method is to observe the signal, set a threshold, and select the signal that exceeds the threshold as a firing process of a neuron. [0003] This method requires people to observe the signal threshold, which increases the workload, and because the threshold is artificially specified, it increases the instability of signal extraction; and this method can only pick out the neural discharge spikes with large amplitudes. However, some spikes with smaller amplit...

AI Technical Summary

Problems solved by technology

[0003] This method requires people to observe the signal threshold, which increases the workload, and because the threshold is artificially specified, it increases the instability of signal extraction; and this method can only pick out the neural discharge spikes with large amplitudes. However, some spikes with smaller amplitudes will be ignored in this method, resulting in statistical errors in neural signals.

[0004] Therefore, the accuracy of neuron firing spikes picked by the current neural firing spike picking method is low

Images