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Quantitative Fluorescence Analysis Reveals Dendrite-Specific Thalamocortical Plasticity in L5 Pyramidal Neurons during Learning

MPG-Autoren
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Wegner,  Waja
Guest Group of Optical Nanoscopy in Neuroscience, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

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Willig,  Katrin I.
Guest Group of Optical Nanoscopy in Neuroscience, Max Planck Institute for Multidisciplinary Sciences, Max Planck Society;

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Zitation

Ray, A., Christian, J. A., Mosso, M. B., Park, E., Wegner, W., Willig, K. I., et al. (2023). Quantitative Fluorescence Analysis Reveals Dendrite-Specific Thalamocortical Plasticity in L5 Pyramidal Neurons during Learning. The Journal of Neuroscience, 43(4), 584-600. doi:10.1523/JNEUROSCI.1372-22.2022.


Zitierlink: https://hdl.handle.net/21.11116/0000-000C-D393-F
Zusammenfassung
High-throughput anatomic data can stimulate and constrain new hypotheses about how neural circuits change in response to experience. Here, we use fluorescence-based reagents for presynaptic and postsynaptic labeling to monitor changes in thalamocortical synapses onto different compartments of layer 5 (L5) pyramidal (Pyr) neurons in somatosensory (barrel) cortex from mixed-sex mice during whisker-dependent learning (Audette et al., 2019). Using axonal fills and molecular-genetic tags for synapse identification in fixed tissue from Rbp4-Cre transgenic mice, we found that thalamocortical synapses from the higher-order posterior medial thalamic nucleus showed rapid morphologic changes in both presynaptic and postsynaptic structures at the earliest stages of sensory association training. Detected increases in thalamocortical synaptic size were compartment specific, occurring selectively in the proximal dendrites onto L5 Pyr and not at inputs onto their apical tufts in L1. Both axonal and dendritic changes were transient, normalizing back to baseline as animals became expert in the task. Anatomical measurements were corroborated by electrophysiological recordings at different stages of training. Thus, fluorescence-based analysis of input- and target-specific synapses can reveal compartment-specific changes in synapse properties during learning.