Biological neural networks achieve remarkable energy efficiency through network-level interactions among coupled neurons. Emulating these coupling mechanisms physically is crucial for developing next-generation neuromorphic systems. However, current nanofluidic ionic systems remain confined to single-neuron implementations, and multineuron coupling has not yet been realized. Here, we address this gap by developing a multineuron neuromorphic circuit that couples two Hodgkin-Huxley (H-H) models via programmable nanofluidic memristors. In LTspice, the H-H models are extended into scalable neuron-axon circuits that reproduce key neurobiological behaviors, including action potential generation with an all-or-none threshold of 18 μA, spike propagation, spike trains, and refractory periods of approximately 10 ms. Nanochannel network membranes (NCNMs) engineered as artificial synapses provide tunable excitatory and inhibitory coupling. The NCNM-coupled neurons further display network-level neuromorphic functions, including excitatory or inhibitory coupling and activity-dependent transitions from phasic to tonic spiking patterns, guiding the design of bioinspired nanofluidic neural networks.