» Articles » PMID: 36639912

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

Overview
Journal J Neurosci
Specialty Neurology
Date 2023 Jan 14
PMID 36639912
Authors
Affiliations
Soon will be listed here.
Abstract

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. Synaptic changes underlie the cellular basis of learning, experience, and neurologic diseases. Neuroanatomical methods to assess synaptic plasticity can provide critical spatial information necessary for building models of neuronal computations during learning and experience but are technically and fiscally intensive. Here, we describe a confocal fluorescence microscopy-based analytical method to assess input, cell type, and dendritic location-specific synaptic plasticity in a sensory learning assay. Our method not only confirms prior electrophysiological measurements but allows us to predict functional strength of synapses in a pathway-specific manner. Our findings also indicate that changes in primary sensory cortices are transient, occurring during early learning. Fluorescence-based synapse identification can be an efficient and easily adopted approach to study synaptic changes in a variety of experimental paradigms.

Citing Articles

Long-lasting, subtype-specific regulation of somatostatin interneurons during sensory learning.

Zhu M, Mosso M, Ma X, Park E, Barth A bioRxiv. 2024; .

PMID: 39605654 PMC: 11601575. DOI: 10.1101/2024.11.19.624383.


Early hippocampal hyperexcitability and synaptic reorganization in mouse models of amyloidosis.

Ray A, Loghinov I, Ravindranath V, Barth A iScience. 2024; 27(9):110629.

PMID: 39262788 PMC: 11388185. DOI: 10.1016/j.isci.2024.110629.


Goal-directed learning is multidimensional and accompanied by diverse and widespread changes in neocortical signaling.

Marrero K, Aruljothi K, Delgadillo C, Kabbara S, Swatch L, Zagha E Cereb Cortex. 2024; 34(8.

PMID: 39110412 PMC: 11304966. DOI: 10.1093/cercor/bhae328.


Transient enhancement of stimulus-evoked activity in neocortex during sensory learning.

Zhu M, Kuhlman S, Barth A Learn Mem. 2024; 31(6).

PMID: 38955432 PMC: 11261211. DOI: 10.1101/lm.053870.123.


Control of neuronal excitation-inhibition balance by BMP-SMAD1 signalling.

Okur Z, Schlauri N, Bitsikas V, Panopoulou M, Ortiz R, Schwaiger M Nature. 2024; 629(8011):402-409.

PMID: 38632412 PMC: 11078759. DOI: 10.1038/s41586-024-07317-z.


References
1.
Sun Y, Smirnov M, Kamasawa N, Yasuda R . Rapid Ultrastructural Changes in the PSD and Surrounding Membrane after Induction of Structural LTP in Single Dendritic Spines. J Neurosci. 2021; 41(33):7003-7014. PMC: 8372018. DOI: 10.1523/JNEUROSCI.1964-20.2021. View

2.
Schuman B, Dellal S, Pronneke A, Machold R, Rudy B . Neocortical Layer 1: An Elegant Solution to Top-Down and Bottom-Up Integration. Annu Rev Neurosci. 2021; 44:221-252. PMC: 9012327. DOI: 10.1146/annurev-neuro-100520-012117. View

3.
Chen S, Kim A, Peters A, Komiyama T . Subtype-specific plasticity of inhibitory circuits in motor cortex during motor learning. Nat Neurosci. 2015; 18(8):1109-15. PMC: 4519436. DOI: 10.1038/nn.4049. View

4.
Tennant K, Taylor S, White E, Brown C . Optogenetic rewiring of thalamocortical circuits to restore function in the stroke injured brain. Nat Commun. 2017; 8:15879. PMC: 5490053. DOI: 10.1038/ncomms15879. View

5.
Chandrasekaran S, Navlakha S, Audette N, McCreary D, Suhan J, Bar-Joseph Z . Unbiased, High-Throughput Electron Microscopy Analysis of Experience-Dependent Synaptic Changes in the Neocortex. J Neurosci. 2015; 35(50):16450-62. PMC: 4679825. DOI: 10.1523/JNEUROSCI.1573-15.2015. View