Autapse-inspired neuromorphic hardware with synapse–neuron integration for bidirectional feedback control
Abstract Establishing autonomous and energy-efficient feedback control at the hardware level remains challenging because conventional systems rely on centralized processing and continuous external computation, increasing energy consumption and system complexity. Here we show a neuromorphic autapse-inspired system that enables localized and bidirectional feedback control, using thermoregulation as a representative application. An autapse is a self-synaptic connection in which a neuron feeds its output back to its own synaptic input, enabling intrinsic feedback modulation. The system integrates a solid electrolyte-based synaptic transistor capable of multiplexing multiple inputs and a bidirectional leaky integrate-and-fire artificial neuron. By feeding the neuronal output back to an additional synaptic gate, excitatory and inhibitory feedback loops are realized within a compact architecture. Using an artificial thermoregulation platform, temperature-dependent inputs bidirectionally modulate neuronal firing frequency, demonstrating biologically inspired feedback control with a compact set of neuromorphic devices for autonomous and energy-efficient systems.
Authors
- Jeong Hwan Song (ORCID: https://orcid.org/0000-0001-9284-2632)
- Yoon Seok Jung (ORCID: https://orcid.org/0000-0003-0357-9508)
- Seonkwon Kim (ORCID: https://orcid.org/0000-0001-6382-2018)
- Jeong Ho Cho (ORCID: https://orcid.org/0000-0002-1030-9920)
- Hyunsu Ju (ORCID: https://orcid.org/0000-0002-2453-5021)
- Chan Kim (ORCID: https://orcid.org/0009-0008-9664-8608)
- Leejae Kim (ORCID: https://orcid.org/0009-0001-7804-0120)
- Seongil Im (ORCID: https://orcid.org/0000-0002-7993-0715)
- Gun Hwan Kim (ORCID: https://orcid.org/0000-0002-2911-4525)
- Jongyoung Lee
Publication Details
- Journal
- Nature Communications
- Published
- 2026-11-12
- DOI
- https://doi.org/10.1038/s41467-026-79401-z
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00