ENGAGING SYNAPTIC PLASTICITY TO STABILIZE DEGENERATING NETWORKS

Neural networks are organized to optimize information processing and learning by balancing stability, resilience, and wiring cost efficiency. This is largely determined by the networks’ underlying structure, yet the brain must remain adaptable to remodel its structural and functional connectivity and encode novel information. The ability of neurons to modify their synaptic efficacy through long-term potentiation (LTP), a cellular correlate of memory, is critical for new memory formation and can strengthen existing circuits, potentially improving resilience to pathology. This intrinsic capacity to adjust synaptic strength is particularly relevant in neurodegenerative diseases, where the gradual loss of vulnerable neurons impairs the underlying network architecture and disrupts signaling efficiency. Here, we hypothesized that engaging synaptic plasticity can stabilize synapses and transiently restore network balance in vulnerable neuronal networks. We induced LTP in human patient-derived motor neuron networks with endogenous ALS pathology. By integrating extracellular electrophysiology, advanced image analysis, and synaptosome proteomics, we found that ALS networks display increased structural stability, proteomic changes consistent with reduced metabolic demand, and transient reductions in excessive network activity and synchrony following LTP. Overall, synaptic potentiation promoted network dynamics consistent with healthy neural function. By engaging key mechanisms underlying memory and learning, i.e., LTP, this work demonstrates that synaptic plasticity mechanisms can transiently reshape ALS network dynamics towards a more functional state.