A revolutionary new theory contradicts a fundamental assumption in neuroscience about how the brain learns. According to researchers at Bar-Ilan University in Israel led by Prof. Ido Kanter, the theory promises to transform our understanding of brain dysfunction and may lead to advanced, faster, deep-learning algorithms.
A biological schema of an output neuron, comprising a neuron’s soma (body, shown as gray circle, top) with two roots of dendritic trees (light-blue arrows), splitting into many dendritic branches (light-blue lines). The signals arriving from the connecting input neurons (gray circles, bottom) travel via their axons (red lines) and their many branches until terminating with the synapses (green stars). There, the signals connect with dendrites (some synapse branches travel to other neurons), which then connect to the soma. (credit: Shira Sardi et al./Sci. Rep)
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