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Journal of Integrative Neuroscience  2018, Vol. 17 Issue (2): 97-104    DOI: 10.31083/JIN-170046
Research article Previous articles | Next articles
The effect of an exogenous alternating magnetic field on neural coding in deep spiking neural networks
Lei Guo1, 2, *(), Wei Zhang1, 2, Jialei Zhang1, 2
1 State Key Laboratory for Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, P.R. China
2 Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, P.R. China
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Abstract  

A ten-layer feed forward network was constructed in the presence of an exogenous alternating magnetic field. Results indicate that for rate coding, the firing rate is increased in the presence of an exogenous alternating magnetic field and particularly with increasing enhancement of the alternating magnetic field amplitude. For temporal coding, in the presence of alternating magnetic field, the interspike intervals of the spiking sequence are decreased and the distribution of interspike intervals tends to be uniform.

Key words:  Spiking neural network      neural coding      reduced neuron model     
Submitted:  19 June 2017      Accepted:  07 August 2017      Published:  15 May 2018     
*Corresponding Author(s):  Lei Guo     E-mail:  2004008@hebut.edu.cn

Cite this article: 

Lei Guo, Wei Zhang, Jialei Zhang. The effect of an exogenous alternating magnetic field on neural coding in deep spiking neural networks. Journal of Integrative Neuroscience, 2018, 17(2): 97-104.

URL: 

https://jin.imrpress.com/EN/10.31083/JIN-170046     OR     https://jin.imrpress.com/EN/Y2018/V17/I2/97

Fig. 1.  Schematic illustration of the deep spiking feed forward neural network.Input to the deep spiking neural network is Poissonian. $Gi$ is the synaptic conductance matrix of neurons in the $i$th layer in the deep spiking neural network, $N$ is the number of neurons in each layer (except Layer 10), $k$ and $j$ give the pre- and post-synaptic neuron, respectively.

Table 1  Mean firing rate under alternating magnetic field
Fig. 2.  Dynamic change of mean firing rate of the neuron under alternating magnetic field stimulation. Horizontal axis indicates simulation time and the vertical axis gives neuron index. Vertical color scale to the right ranges from red (high firing rate) to blue (low firing rate). a, the mean firing rate of the neurons in layer 1 is lower than the neurons in other layers, mean firing rate of neurons during the initial period is higher than other periods. b-f, under the alternating magnetic field, mean firing rate of neurons in layer 1 is also lower than the neurons in other layers; the mean firing rate of the neurons during the initial period is higher than other periods.

Fig. 3.  ISI time domain diagram for a deep spiking neural network stimulated by an alternating magnetic field. Horizontal axis gives discrete time points of spike firing, vertical axis gives ISI value at spike firing time. For the 0-200 ms period the ISI distributionI was unstable and the distribution range of ISIs was 250 ms under the different amplitudes of the alternating magnetic field. During the period 200-1000 ms ISIs were divided into two populations in response to the different amplitudes of the alternating magnetic field. The top layer gives the ISIs between bursts of action potentials and ranges over 150-200 ms. The bottom layer gives ISIs inside the bursts of action potentials and ISIs range over 100-150 ms. Increased amplitude of the alternating magnetic field during the period 0-200 ms, decreases the ISI range, during the period from 200-1000 ms, the distribution range of the bottom layer ISIs is decreased.

Fig. 4.  ISI histogram obtained from a deep spiking neural network under alternating magnetic field stimulation. The horizontal axis gives different values of ISIs, vertical axis gives the repeated number of ISIs as a proportion of the total number of ISIs. a, the distribution of the ISIs is concentrated in a 100 ms period and the distribution of ISIs in the other period is less without stimulation. b-f, in the presence of an alternating magnetic field, the distribution of the ISIs is also concentrated within 100 ms. With increased amplitude of the alternating magnetic field, the distribution of ISIs in 100 ms is decreased and the distribution of ISIs in the other period is increased.

Fig. 5.  Joint ISI distributions obtained from a spiking neural network under an alternating magnetic field stimulus. The horizontal axis gives each ISI($n$) in the spike firing sequence; vertical axis gives adjacent ISI($n$ 1). a, in the absence of stimulation, most joint ISIs of neurons in the spiking neural network are distributed in the center and other joint ISIs are distributed along the horizontal and vertical axes. b-f, under an alternating magnetic field, the central coverage area of joint ISI distribution becomes dispersed and the distribution of the joint ISIs along the horizontal axis and vertical axes is increased. With increased amplitude of the alternating magnetic field, the distribution of the central coverage area of joint ISI becomes more dispersed.

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