Neuromorphic Control
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Abstract (arXiv)
Neuromorphic engineering is a rapidly developing field that aims to take inspiration from the biological organization of neural systems to develop novel technology for computing, sensing, and actuating. The unique properties of such systems call for new signal processing and control paradigms. The article introduces the mixed feedback organization of excitable neuronal systems, consisting of interlocked positive and negative feedback loops acting in distinct timescales. The principles of biological neuromodulation suggest a methodology for designing and controlling mixed-feedback systems neuromorphically. The proposed design consists of a parallel interconnection of elementary circuit elements that mirrors the organization of biological neurons and utilizes the hardware components of neuromorphic electronic circuits. The interconnection structure endows the neuromorphic systems with a simple control methodology that reframes the neuronal control as an input-output shaping problem. The potential of neuronal control is illustrated on elementary network examples that suggest the scalability of the mixed-feedback principles.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 9 Nov 2020.
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Citing papers per year: 2024: 1; 2025: 3.
4 papers.
- 2024Augmenting learning in neuro-embodied systems through neurobiological first principlescited by 2
- 2025Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamicscited by 2
- 2025A Winner-Takes-All Mechanism for Event Generationcited by 1
- 2025A Neuromorphic Architecture for Scalable Event-Based Controlcited by 0
- 2025A Neuromorphic Architecture for Scalable Event-Based Control14 Nov 2025
- 2025A Winner-Takes-All Mechanism for Event Generation15 Apr 2025
- 2025Improving the adaptive and continuous learning capabilities of artificial neural networks: Lessons from multi-neuromodulatory dynamics12 Jan 2025
- 2024Augmenting learning in neuro-embodied systems through neurobiological first principles5 Jul 2024