Antiferromagnetic artificial neuron modeling of biological neural networks

Replicating neural responses observed in biological systems using artificial neural networks has applications in both medicine and engineering. Here, we use an artificial neuron model based on antiferromagnetic (AFM) spin Hall oscillators [1] to model the biological withdrawal reflex responsible for the preservation of self from a harmful stimulus. The withdrawal reflex responds to sensory stimuli by flexing agonist muscles and relaxing the opposing antagonist muscles in the same limb [2]. We build an artificial neural network from AFM neurons that simulates the biological neural network responsible for this reflex. The unique features of AFM neurons, such as inhibition that stems from an effective AFM inertia, allow for the creation of biologically realistic neural network components, like the interneurons in the spinal cord. The effectiveness of AFM neuron modeling is proven by simulating various scenarios that define the withdrawal reflex, such as the reaction to a weak or strong stimulus and voluntary suppression of the reflex.



[1] R. Khymyn et al. Sci. Rep. 8, 15727 (2018).

[2] S. Schmidt, Human Anatomy & Physiology, p. 470.