Neuron models provide a non-invasive way to investigate the brain, but most existing models are either computationally intensive or cannot model complex neuronal responses.

Neuron models provide a non-invasive way to investigate the brain, but most existing models are either computationally intensive or cannot model complex neuronal responses.

A new model of learning centers on bursts of neural activity that act as teaching signals — approximating backpropagation, the algorithm behind learning in AI.

By transforming cells from human skin into working nerve cells, researchers may have come up with a model for nervous-system diseases and perhaps even regenerative therapies based on cell transplants.

IN A NUTSHELL This model when inserted in neuromorphic AI networks for different applications such as data processing and automation, leads far more efficient and accurate results.

New insights have been uncovered into the regulatory network behind neuron growth, report scientists.