Fig. 1.

Quantum material showing habituation behavior observed in neural and non-neural organisms. a Nonassociative habituation learning observed in Physarum polycephalum. When exposed to stimulus, a diminished response is observed indicative of habituation. b Schematic showing the habituation process in a perovskite SmNiO₃ (SNO). Between repeated stimuli (H₂), the dynamics of carrier localization subsides, showing both non-neural habituation and neural synaptic plasticity. c Associative spike-timing based learning observed in a biological neural system (brain) responsible for memory formation. In the brain, synaptic plasticity is modulated by chemical transmitters, and is a function of the relative timing difference between the post and pre-neuronal spikes. The biological neural system is implemented as a Spiking Neural Network (SNN) that consists of a fully connected array of pre-neurons and post-neurons. The pre-neuronal voltage spike (V _pre) is modulated by the synaptic weight (w) to generate the resulting post-synaptic current (I _post). The post-neuron integrates the current that results in an increase in its membrane potential (V _mem) and spikes when the potential exceeds a certain threshold (θ). d In environment 1, the SNN was presented with different images of digit 2 and learnt several patterns corresponding to the given image. In environment 2, the SNN was presented with images of digits 0 and 1. Incorporating habituation-based nonassociative learning with standard associative spike-timing dependent plasticity (STDP) enables the SNN to learn new patterns without catastrophic forgetting in a resource-constrained dynamic input environment. The color intensity of the patterns are representative of the value of synaptic weights with lowest intensity (white) corresponding to a weight value of −0.5 and highest intensity (black) corresponding to 0.5