Researchers develop new model to observe self-optimization phenomenon in neuronal networks

Researchers at the Cyber-Physical Systems Group at the USC Viterbi School of Engineering, in conjunction with the University of Illinois at Urbana-Champaign, have developed a new model of how information deep in the brain could flow from one network to another and how these neuronal network clusters self-optimize over time.

Their work, chronicled in the paper “Network Science Characteristics of Brain-Derived Neuronal Cultures Deciphered From Quantitative Phase Imaging Data,” is believed to be the first study to observe this self-optimization phenomenon in in vitro neuronal networks, and counters existing models. Their findings can open new research directions for biologically inspired artificial intelligence, detection of brain cancer and diagnosis and may contribute to or inspire new Parkinson’s treatment strategies.

The team examined the structure and evolution of neuronal networks in the brains of mice and rats in order to identify the connectivity patterns.

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