Microscale dysfunction and mesoscale compensation in degenerating neuronal networks

Abstract Progressive neurodegenerative diseases involve neuronal dysfunction across cellular, circuit, and whole-brain levels. Despite differences in anatomical origins, vulnerable neuronal subtypes, and specific misfolded proteins, these diseases share key features. In presymptomatic phases, neural networks engage compensatory processes to maintain function, including increased centralisation and reliance on a rich-club of hub nodes. While such mechanisms have supporting evidence in some disorders, they remain less established in ALS, limiting understanding of potential shared pre-symptomatic responses. To address this, we investigated structural and functional properties of ALS patient-derived motor neuron networks compared to healthy controls using longitudinal multielectrode array recordings and graph theory-based analysis. We observed microscale dysfunction marked by TDP-43 proteinopathy, hyperactivity, and reduced spike amplitude. Structurally, ALS networks exhibited neurite hypertrophy, suggesting attempts to form new connections. Mesoscale analyses revealed functional reconfigurations, including increased rich-club connectivity and network assortativity, indicating compensatory centralisation. Our findings provide novel evidence that ALS network features can be recapitulated in in vitro models, and that these networks progressively become more centralised to preserve computational capacity, imposing growing demands on hub nodes and predisposing them to further damage. These results support models proposing common network reconfiguration mechanisms across neurodegenerative diseases.