On the Excitability of Ultra-Low-Power CMOS Analog Spiking Neurons
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914160331194368 |
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| author | Van Brandt, Léopold Brandsteert, Grégoire Flandre, Denis |
| author_facet | Van Brandt, Léopold Brandsteert, Grégoire Flandre, Denis |
| contents | The excitability property of spiking neurons describes their capability to output an action potential as a real-time response to an input synaptic excitation current and is central to the event-based neuromorphic computing paradigm. The spiking mechanism is analysed in a representative ultra-low-power analog neuron from the circuit literature. Relying on conventional SPICE simulations compatible with industrial transistor compact models, we establish a excitation criterion, quantified either in terms of critical supplied charge or membrane potential threshold. Only the latter is found intrinsic to the neuron, i.e. independent of the input stimulus. Rigorous analysis of the nonlinear neuron dynamics provides insight but still needs to be explored further, as well as the effect of the intrinsic noise. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_12753 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | On the Excitability of Ultra-Low-Power CMOS Analog Spiking Neurons Van Brandt, Léopold Brandsteert, Grégoire Flandre, Denis Statistical Mechanics Hardware Architecture The excitability property of spiking neurons describes their capability to output an action potential as a real-time response to an input synaptic excitation current and is central to the event-based neuromorphic computing paradigm. The spiking mechanism is analysed in a representative ultra-low-power analog neuron from the circuit literature. Relying on conventional SPICE simulations compatible with industrial transistor compact models, we establish a excitation criterion, quantified either in terms of critical supplied charge or membrane potential threshold. Only the latter is found intrinsic to the neuron, i.e. independent of the input stimulus. Rigorous analysis of the nonlinear neuron dynamics provides insight but still needs to be explored further, as well as the effect of the intrinsic noise. |
| title | On the Excitability of Ultra-Low-Power CMOS Analog Spiking Neurons |
| topic | Statistical Mechanics Hardware Architecture |
| url | https://arxiv.org/abs/2511.12753 |