Quantized Hodgkin-Huxley Model for Quantum Neurons

The Hodgkin-Huxley model describes the behavior of the membrane voltage in neurons, treating each element of the cell membrane as an electric circuit element, namely capacitors, memristors and voltage sources. We focus on the activation channel of potassium ions, since it is simpler, while keeping the majority of the features identified with the original model. This simplification is physiologically meaningful, since it is related to some neurodegenerative and autoimmune diseases, which are associated with a process of demyelination in neurons. This model reduces to a memristor, a resistor whose resistance depends on the history of charges crossing it, coupled to a voltage source and a capacitor. Here, we use the recent quantization of the memristor to glance at the Hodgkin-Huxley model in the quantum regime. We compare the behavior of the potassium channel conductance in both the classical and quantum realm. In the latter, we firstly introduce classical sources to study the quantum-classical transition, and afterwards we switch to coherent quantum sources in order to study the effects of entanglement. Numerical simulations show an increment and adaptation depending on the history of signals. Additionally, the response to AC sources showcases hysteretic behavior in the I-V characteristic curve due to the presence of the memristor. We investigate the memory capacitance represented by the area of the I-V loops, which we call memory persistence. We find that it grows with entanglement, which can be interpreted in terms of the fundamental relation between information and thermodynamic entropies established by Landauer's principle. These results pave the way for the construction of quantum neuron networks inspired in the brain but capable of dealing with quantum information, a step forward towards the design of neuromorphic quantum architectures with implications in quantum machine learning.