This article presents a nanofluidic logic device, termed 'highly asymmetric channels' (HACs), which enables circuit-scale neuromorphic computing. The device, fabricated using a scalable process, combines single-digit nanometric confinement and large entrance asymmetry, operating on the second timescale with a conductance ratio of 9 to 60. In operando optical microscopy reveals that the memory effect is due to the reversible formation of liquid blisters that modulate the device's conductance. These mechano-ionic memristive switches are used to assemble logic circuits composed of two interactive devices and an ohmic resistor. The study highlights the potential of nanofluidic memristive devices for energy-efficient information processing, mimicking biological brains. Unlike previous fluidic memristors, HACs exhibit memory effects in simple electrolytes within the electrochemical window of water. The memory effect in HACs is attributed to the reversible formation of liquid blisters, which modulate the device's conductance. The device's large entrance asymmetry and single-digit confinement result in a switching behavior related to the reversible formation of liquid blisters. The HACs are used to implement a nanofluidic logic operation by connecting two fluidic cells. The study demonstrates the successful fabrication of scalable nanofluidic switches that exhibit excellent performance and operate effectively using simple monovalent salt solutions. The HACs are shown to be suitable for building logic circuits, with the ability to condition the switching of a nanofluidic memristor by the conductance state of another device. The study also shows that HACs can be used to implement a Boolean operation with two interacting devices, providing the fundamental building block for future aqueous computing machines. The results demonstrate that HACs are scalable and compact nanofluidic memristors that can be set or reset within a few seconds, with a conductance ratio reaching sixty. The study also highlights the potential of HACs for neuromorphic computing, with the ability to implement logic operations and perform computational tasks. The findings suggest that further developments, such as optimizing their design and connecting them with water channels to fabricate fully liquid circuits, should lead to improvements in performance. The study concludes that HACs represent a promising platform for neuromorphic computing, with the potential to create nanofluidic neural networks.This article presents a nanofluidic logic device, termed 'highly asymmetric channels' (HACs), which enables circuit-scale neuromorphic computing. The device, fabricated using a scalable process, combines single-digit nanometric confinement and large entrance asymmetry, operating on the second timescale with a conductance ratio of 9 to 60. In operando optical microscopy reveals that the memory effect is due to the reversible formation of liquid blisters that modulate the device's conductance. These mechano-ionic memristive switches are used to assemble logic circuits composed of two interactive devices and an ohmic resistor. The study highlights the potential of nanofluidic memristive devices for energy-efficient information processing, mimicking biological brains. Unlike previous fluidic memristors, HACs exhibit memory effects in simple electrolytes within the electrochemical window of water. The memory effect in HACs is attributed to the reversible formation of liquid blisters, which modulate the device's conductance. The device's large entrance asymmetry and single-digit confinement result in a switching behavior related to the reversible formation of liquid blisters. The HACs are used to implement a nanofluidic logic operation by connecting two fluidic cells. The study demonstrates the successful fabrication of scalable nanofluidic switches that exhibit excellent performance and operate effectively using simple monovalent salt solutions. The HACs are shown to be suitable for building logic circuits, with the ability to condition the switching of a nanofluidic memristor by the conductance state of another device. The study also shows that HACs can be used to implement a Boolean operation with two interacting devices, providing the fundamental building block for future aqueous computing machines. The results demonstrate that HACs are scalable and compact nanofluidic memristors that can be set or reset within a few seconds, with a conductance ratio reaching sixty. The study also highlights the potential of HACs for neuromorphic computing, with the ability to implement logic operations and perform computational tasks. The findings suggest that further developments, such as optimizing their design and connecting them with water channels to fabricate fully liquid circuits, should lead to improvements in performance. The study concludes that HACs represent a promising platform for neuromorphic computing, with the potential to create nanofluidic neural networks.