1Department of Physical Chemistry, University of the Basque Country UPV/EHU, Apartado 644, 48080 Bilbao, Spain
2International Center of Quantum Artificial Intelligence for Science and Technology (QuArtist) and Physics Department, Shanghai University, 200444 Shanghai, China
3IKERBASQUE, Basque Foundation for Science, Maria Diaz de Haro 3, 48013 Bilbao, Spain
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Abstract
The Hodgkin-Huxley model describes the conduction of the nervous impulse through the axon, whose membrane’s electric response can be described employing multiple connected electric circuits containing capacitors, voltage sources, and conductances. These conductances depend on previous depolarizing membrane voltages, which can be identified with a memory resistive element called memristor. Inspired by the recent quantization of the memristor, a simplified Hodgkin-Huxley model including a single ion channel has been studied in the quantum regime. Here, we study the quantization of the complete Hodgkin-Huxley model, accounting for all three ion channels, and introduce a quantum source, together with an output waveguide as the connection to a subsequent neuron. Our system consists of two memristors and one resistor, describing potassium, sodium, and chloride ion channel conductances, respectively, and a capacitor to account for the axon’s membrane capacitance. We study the behavior of both ion channel conductivities and the circuit voltage, and we compare the results with those of the single channel, for a given quantum state of the source. It is remarkable that, in opposition to the single-channel model, we are able to reproduce the voltage spike in an adiabatic regime. Arguing that the circuit voltage is a quantum variable, we find a purely quantum-mechanical contribution in the system voltage’s second moment. This work represents a complete study of the Hodgkin-Huxley model in the quantum regime, establishing a recipe for constructing quantum neuron networks with quantum state inputs. This paves the way for advances in hardware-based neuromorphic quantum computing, as well as quantum machine learning, which might be more efficient resource-wise.
Featured image: The Hodgkin-Huxley model characterizes the role of the axon’s membrane in the transmission of nervous impulses. This membrane is constituted by multiple connected electric circuits, featuring capacitors, voltage sources, and memristors. The recently proposed quantum memristor allows us to study the dynamics of the Hodgkin-Huxley circuit in the quantum regime, including potassium, sodium, and chloride ion channels. We address this problem here, reproducing the behavior of the Hodgkin-Huxley circuit in the quantum regime, including the voltage spike, and finding purely quantum contributions to the voltage. This circuit might turn out to be a building block for the construction of hardware-based quantum neural networks.
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Cited by
[1] G. Alvarado Barrios, J. C. Retamal, E. Solano, and M. Sanz, “Analog simulator of integro-differential equations with classical memristors”, Scientific Reports 9, 12928 (2019).
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Source: https://quantum-journal.org/papers/q-2020-01-20-224/
