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<p>Spiking neural P (SNP) systems are a category of parallel and distributed computational models that draw inspiration from the functioning of discrete neurons. In this paper, we introduce transcription factors into neurons to guide the transmission of generated spikes and propose a new variant called weighted spiking neural P systems with transcription factors (TFWSNP system). In the TFWSNP system, transcription factors not only indicate the direction of spikes transmission, but also the activation conditions of transcription rules are determined by the number of spikes in the postsynaptic neuron. The quantity of spikes in postsynaptic neurons can be modulated as required by employing transcriptional rules and by assigning varying weights to synapses, thereby regulating the transmission of spikes between neurons. These characteristics not only make the spike transmission of TFWSNP system more flexible, but also make the TFWSNP system have strong control ability and prove the Turing universality of the TFWSNP system. Finally, a small general function computing device composed of 63 neurons was constructed.</p>

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Weighted spiking neural P systems with transcription factors

  • 期刊论文

  • 发表日期：

    2026年2月20日

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  • Yajun Zhu,
  • Xiyu Liu

摘要

Spiking neural P (SNP) systems are a category of parallel and distributed computational models that draw inspiration from the functioning of discrete neurons. In this paper, we introduce transcription factors into neurons to guide the transmission of generated spikes and propose a new variant called weighted spiking neural P systems with transcription factors (TFWSNP system). In the TFWSNP system, transcription factors not only indicate the direction of spikes transmission, but also the activation conditions of transcription rules are determined by the number of spikes in the postsynaptic neuron. The quantity of spikes in postsynaptic neurons can be modulated as required by employing transcriptional rules and by assigning varying weights to synapses, thereby regulating the transmission of spikes between neurons. These characteristics not only make the spike transmission of TFWSNP system more flexible, but also make the TFWSNP system have strong control ability and prove the Turing universality of the TFWSNP system. Finally, a small general function computing device composed of 63 neurons was constructed.