This theory contradicts the most common assumption in neuroscience and will transform our understanding of brain function, said Professor Ido Kanter of the department of physics and the Gonda Brain Multidisciplinary Research Center (Goldschmied) at Ramat Gan University.
] the brain is a complex network that contains billions of neurons, where each of these neurons communicates simultaneously with thousands of others through their synapses (structures that allow the nerve cell to pass an electrical or chemical signal to another neuron) . However, the nerve cell actually picks up its many incoming synaptic signals through several extremely long branched "arms" called "dendritic trees."
In 1949, the pioneering work of the late Canadian psychologist Prof. Donald Hebb suggested that learning occurs in the brain by modifying the strength of synapses, while neurons function as computational elements in the brain. So far, this is still the case.
But with the use of new theoretical results and experiments on neural cultures, a group of scientists led by Kanter has shown the central assumption of 70 years that learning only happens at the synapses of being wrong. In an article recently published in Scientific magazine Reports, Israeli researchers challenge conventional wisdom and show that learning is actually performed by several dendrites, similar to the slow learning mechanism currently attributed to synapses.
Hebb's theory has been so ingrained in the scientific world for so many years that no one proposed such a different approach. In addition, the synapses and dendrites are connected to the neuron in a series, so the exact localized location of the learning process seemed irrelevant, Kanter explained. "The newly discovered learning process in dendrites occurs at a much faster rate than in the previous scenario that suggested learning occurs only at synapses."
The new theory holds that learning occurs in a few dendrites that are in a proximity much closer to the neuron, contrary to the previous notion. "Does it make sense to measure the quality of the air we breathe through many small and distant satellite sensors in the elevation of a skyscraper or using one or several sensors near the nose?" Similarly, it is more efficient for the neuron to estimate its signals incoming near their computational unit, the neuron, "said Kanter.
Another important finding of the study is that weak synapses, previously considered insignificant even though they comprise the majority of our brain, play an important role in the dynamics of our brain. They induce oscillations of the learning parameters instead of bringing them to unrealistic fixed extremes, as suggested in the current synaptic learning scenario, said the BIU researchers.
The new discovery shows that learning occurs in different parts of the brain and therefore requires a re-evaluation of current treatments for disordered brain functionality.
Therefore, the popular phrase "neurons that fire together unite" (summarizing Hebb's hypothesis) must now be reformulated.
In addition, the learning mechanism is the basis of recent achievements in machine learning and deep learning. The change in the learning paradigm opens new horizons for different types of deep learning algorithms and applications based on artificial intelligence that mimic our brain functions, to assume advanced features at a much faster rate.