Electrically reconfigurable skyrmion lattice based self-adaptive oscillating neurons

Neuromorphic computing promises to realize the transformative potential of Artificial Intelligence (AI) by enabling ultra-low power, advanced AI. Spintronic materials are particularly attractive for neuromorphic computing as they have a small footprint, use low power and can mimic the complex properties of the brain. Here, we utilize an electrically reconfigurable skyrmion lattice to design and simulate a novel artificial neuron that incorporates two advanced neural behaviors: oscillatory dynamics and neuromodulation. Neuromodulation is the self-adaptive ability of a neuron to regulate its dynamics in response to its environment. Here, neuromodulation arises from the reconfigurability of the skyrmion lattice, i.e, skyrmions in a lattice are rearranged via electrical currents, shifting the resonant frequencies and altering the amplitudes of oscillation of the neuron. The neuron is implemented with a lattice of five magnetic skyrmions in a thulium iron garnet and platinum bilayer. We utilize the neuron to demonstrate 2 high-level cognitive processes: context-aware decision making and feature binding. These results can be used for advanced AI applications including biomedicine, neuro-prosthesis and human-machine interaction.