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The authors describe a new type of artificial neural cell using superconducting circuits. Circulating current flowing in a superconducting closed loop is used for implementing a weighted sum of inputs. The weight value and sign are digitally variable. The weight values are stored in superconducting memory loops, and can be controlled by an up-down counter. The performance of the cell, such as cell size, power dissipation, and input/output capability, were evaluated and the estimations show a promise for implementation of large scale neural networks.