Biological neurons are electro-mechanical systems, where the generation and propagation of an action potential are coupled to the generation and transmission of an acoustic wave. Neuristors, such as VO2, characterized by insulator-metal transition (IMT) and negative differential resistance, can be engineered as self-oscillators, which are good approximations of biological neurons in the domain of electrical signals. In this study, we show that these self-oscillators are coupled electro-opto-mechanical systems, with better energy conversion coefficients than the conventional electro-mechanical or electro-optical materials. This is due to the significant contrast in the material's resistance, optical refractive index, and density across the induced temperature range in a Joule heating driven IMT. We carried out laser interferometry to measure the opto-mechanical response while simultaneously driving the devices electrically into self-oscillations of different kinds. We analyzed films of various thicknesses, engineered device geometry, and performed analytical modeling to decouple the effects of refractive index change vis-à-vis mechanical strain in the interferometry signal. We show that the effective piezoelectric coefficient (d13*) for our neuristor devices is 660 ± 20 pm/V, with a 31% internal energy conversion efficiency, making them viable alternatives to Pb-based piezoelectrics for MEMS applications. Furthermore, we show that the effective electro-optic coefficient (r13*) is ∼22 nm/V, which is much larger than that in thin-film and bulk Pockels materials.