Home > Publications Database > Astrocytes enhance plasticity response during reversal learning. > print |
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100 | 1 | _ | |a Squadrani, Lorenzo |0 0000-0001-9758-6906 |b 0 |
245 | _ | _ | |a Astrocytes enhance plasticity response during reversal learning. |
260 | _ | _ | |a London |c 2024 |b Springer Nature |
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520 | _ | _ | |a Astrocytes play a key role in the regulation of synaptic strength and are thought to orchestrate synaptic plasticity and memory. Yet, how specifically astrocytes and their neuroactive transmitters control learning and memory is currently an open question. Recent experiments have uncovered an astrocyte-mediated feedback loop in CA1 pyramidal neurons which is started by the release of endocannabinoids by active neurons and closed by astrocytic regulation of the D-serine levels at the dendrites. D-serine is a co-agonist for the NMDA receptor regulating the strength and direction of synaptic plasticity. Activity-dependent D-serine release mediated by astrocytes is therefore a candidate for mediating between long-term synaptic depression (LTD) and potentiation (LTP) during learning. Here, we show that the mathematical description of this mechanism leads to a biophysical model of synaptic plasticity consistent with the phenomenological model known as the BCM model. The resulting mathematical framework can explain the learning deficit observed in mice upon disruption of the D-serine regulatory mechanism. It shows that D-serine enhances plasticity during reversal learning, ensuring fast responses to changes in the external environment. The model provides new testable predictions about the learning process, driving our understanding of the functional role of neuron-glia interaction in learning. |
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650 | _ | 7 | |a Receptors, N-Methyl-D-Aspartate |2 NLM Chemicals |
650 | _ | 2 | |a Animals |2 MeSH |
650 | _ | 2 | |a Astrocytes: physiology |2 MeSH |
650 | _ | 2 | |a Astrocytes: metabolism |2 MeSH |
650 | _ | 2 | |a Neuronal Plasticity: physiology |2 MeSH |
650 | _ | 2 | |a Mice |2 MeSH |
650 | _ | 2 | |a Reversal Learning: physiology |2 MeSH |
650 | _ | 2 | |a Serine: metabolism |2 MeSH |
650 | _ | 2 | |a Models, Neurological |2 MeSH |
650 | _ | 2 | |a Receptors, N-Methyl-D-Aspartate: metabolism |2 MeSH |
700 | 1 | _ | |a Wert-Carvajal, Carlos |b 1 |
700 | 1 | _ | |a Müller-Komorowska, Daniel |b 2 |
700 | 1 | _ | |a Bohmbach, Kirsten |0 0000-0002-6387-750X |b 3 |
700 | 1 | _ | |a Henneberger, Christian |0 P:(DE-2719)2811625 |b 4 |
700 | 1 | _ | |a Verzelli, Pietro |b 5 |
700 | 1 | _ | |a Tchumatchenko, Tatjana |0 0000-0001-9137-809X |b 6 |
773 | _ | _ | |a 10.1038/s42003-024-06540-8 |g Vol. 7, no. 1, p. 852 |0 PERI:(DE-600)2919698-X |n 1 |p 852 |t Communications biology |v 7 |y 2024 |x 2399-3642 |
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