This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Our brain must be able to learn new things without losing previously stored information or the stability of its networks. Researchers at the Leibniz Institute for Neurobiology (LIN) in Magdeburg, together with partners in Bielefeld and Zurich, have investigated how this balance is achieved.
They show that learning alters the stability of inhibitory synapses in opposite ways depending on their position on the same nerve cell. On the dendrites—the input side of the nerve cell—inhibitory synapses are reorganized more frequently following learning. At the axon hillock, where the cell generates its own electrical signal, they become more stable.
This spatial division of labor could help process new information while ensuring that learned information remains reliably accessible. The study has been published in Nature Communications. Nerve cells receive and process signals from other cells via their branched extensions, the dendrites.
At the start of the axon, it is determined whether this results in the nerve cell generating and transmitting its own electrical signal. Inhibitory synapses regulate this flow of information and can therefore intervene in processing at different points, depending on their position. The researchers observed that learning alters these synapses differently depending on their position: on the dendrites, they were reorganized more frequently, while at the start of the axon they remained more stable.
Their total number hardly changed. The study thus points to a spatial division of labor within the same nerve cell: while the inhibitory connections on the input side become more flexible, they remain more stable on the output side. "It is surprising that inhibitory synapses within the same nerve cell do not respond uniformly to learning," says Alessio Attardo from the LIN.
"Their exact position appears to help determine whether they are remodeled or stabilized. This gives us a new insight into how a neural network can remain both plastic and stable at the same time." For the study, the researchers observed inhibitory synapses in the hippocampus of 23 mice over 13 days. Using two-photon microscopy, they were able to return repeatedly to the same nerve cells and synaptic contacts.
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