In our previous paper (Korogod et al., 2015), we used a cryo fixation method to study the neuropil of the adult mouse cerebral cortex, comparing it with a standard chemical fixation approach that has been used for many years to preserve brain tissue for analysis with electron microscopy (e.g. Spacek and Harris, 1997; Knott et al., 2002). This study had been motivated by the work of Anton Van Harreveld (Van Harreveld et al., 1965; Van Harreveld and Malhotra, 1967; see Korogod et al., 2015 for detailed description) who had been the first to show how fresh, cryo frozen brain tissue showed appreciable amounts of extracellular space which was not present in tissue asphyxiated for 8 min. Korogod et al., 2015 elaborated on this result showing how cryo fixation preserved an extracellular space matching previous in vivo measurements, whereas chemically fixed tissue shows reduced extracellular space. Furthermore, synapse density and vesicle docking, as well as astrocytic processes close to synapses and around blood capillaries, were significantly different between the two fixation methods. This led us in this study to investigate the extent to which dendritic spines might be affected by chemical fixation.

The dendritic spine is a small dendritic protrusion that carries the majority of the excitatory synaptic connections in the adult brain (Colonnier, 1968) with a size and shape that is closely linked with its function (reviewed by: Holtmaat and Svoboda, 2009; Harris and Kater, 1994). The larger the spine head, the larger its synapse (Harris and Stevens, 1988; Arellano et al., 2007; Knott et al., 2006), the number of its receptors (Kharazia and Weinberg, 1999; Noguchi et al., 2005; Nusser et al., 1998), and its synaptic strength (Matsuzaki et al., 2001). However, the synapse on the spine head is separated from the parent dendrite by the spine neck. This is often thin, compartmentalizing biochemical signals and creating a potentially significant electrical resistance between synapse and dendrite. Changes in the morphology of spine head and neck have been seen after different forms of activity including LTP induction and tetanic stimulation (Lang et al., 2004; Matsuzaki et al., 2004; Harvey and Svoboda, 2007; Tønnesen et al., 2014; Fifková and Anderson, 1981). The understanding of dendritic spine morphology and function has come from many years of analysis using ultrastructural and in vivo analysis with electron and light microscopy. Up until now, however, all the ultrastructural data comes from chemically fixed samples. These show that the brightness of in vivo imaged spines closely correlates with their volume measured in serial electron microscopy images (Knott et al., 2006; Cane et al., 2014; Nägerl et al., 2007; El-Boustani et al., 2018). Although the resolution of light microscopy had limited the comparison of such features of spine length, and width from living neurons, the super resolution methods of STED and FRAP have been able to make these measurements in hippocampal spines in both slices and in vivo (Tønnesen et al., 2014; Pfeiffer et al., 2018). We investigated these parameters using serial section electron microscopy to compare the sizes of spine heads, their neck lengths and neck widths between cryo and chemically fixed tissue (Figure 1). We show that although cryo fixation reveals unchanged spine neck length and head volume, the spine neck is significantly narrower in cryo-fixed tissue compared to chemically fixed tissue, likely having an important impact upon consideration of the communication between a spine and its parent dendrite.

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Coefficients of variation data used in Figure 1I.

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Spines were analyzed from 3D models constructed from serial images taken with either TEM (cryo fixation: n = 89 spines, N = 3 mice; chemical fixation: n = 75 spines, N = 1 mouse) or FIBSEM (cryo fixation: n = 27 spines, N = 2 mice; chemical fixation: n = 75 spines, N = 2 mice). No quantitative differences were found between the results obtained by TEM and FIBSEM, and the results were therefore pooled (Figure 1—figure supplement 1).

The tissue was prepared with identical protocols to those used in our previous paper (Korogod et al., 2015). As before, these revealed very little extracellular space with chemical fixation (Figure 1), while cryo fixation showed elements more dispersed with significant spaces separating them. The cryo-fixed membranes also had a distinct appearance from those exposed to chemical fixative. Cryo-fixed membranes were smoothly curving and lacked wrinkles typically seen after chemical fixation. Furthermore, the cryo-fixed tissue showed many thin processes, some of which were spine necks, which form the focus of the current study (Figure 1).

Quantifying spine geometry, we found that the mean spine neck cross-sectional area was significantly narrower in the cryo-fixed samples (cryo fixation, 0.0159 ± 0.0185 µm²; chemical fixation, 0.0284 ± 0.0197 µm²; unpaired Kolmogorov-Smirnov test, p<0.0001; Figure 2A). The same was seen for the minimum cross-sectional area (cryo fixation, 0.01 ± 0.016 µm²; chemical fixation, 0.017 ± 0.014 µm²; unpaired Kolmogorov-Smirnov test, p<0.0001; Figure 2B). The spine neck diameter was calculated from the measurements of spine neck cross-sectional area. The mean spine neck diameter was 128.0 ± 62.8 nm in cryo-fixed tissue, which was significantly smaller than the mean spine neck diameter of 182.4 ± 54.5 nm found for chemically fixed tissue (unpaired Kolmogorov-Smirnov test, p<0.0001; Figure 2C), and similarly for the minimum spine neck diameter (cryo fixation, 0.07 ± 0.057 µm; chemical fixation, 0.107 ± 0.037 µm; unpaired Kolmogorov-Smirnov test, p<0.0001; Figure 2D). Spine length measurements showed a large diversity in each group with no statistical difference between the two fixation conditions (cryo fixation, 0.770 ± 0.550 µm; chemical fixation 0.836 ± 0.569 µm; unpaired Kolmogorov-Smirnov test, p=0.53; Figure 2E). Measurements of the spine head volume also showed no difference between chemically fixed and cryo-fixed tissue (cryo fixation, 0.069 ± 0.062 µm³; chemical fixation, 0.081 ± 0.087 µm³; unpaired Kolmogorov-Smirnov test, p=0.65; Figure 2F).

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Spine parameter data used in Figure 2.

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Previously, we found that the synapse size, or area, was not different comparing the two fixation conditions (Korogod et al., 2015). Here, we further report that synapse area correlates with the volume of the spine head in cryo-fixed tissue (R² = 0.73, n = 33 spines) (Figure 2—figure supplement 1), similar to previous reports studying chemically fixed tissue (reviewed by Bourne and Harris, 2008).

We next examined correlations between spine head volume, spine neck diameter, and spine neck length (Figure 3). Similar to a previous study (Arellano et al., 2007), we found a weak correlation in the chemically fixed spines between head volume and neck diameter (r = 0.36; p<0.0001; non-parametric Spearman test). This was not observed, however, in the cryo-fixed spines (r = 0.14; p=0.12; non-parametric Spearman test). We also found no correlation between the head volume and neck length in either cryo-fixed or chemically fixed spines (cryo fixation, r = 0.124, p=0.18; chemical fixation, r = 0.044, p=0.59, non-parametric Spearman test) and also no correlation between the neck length and the neck diameter (cryo fixation, r = −0.020, p=0.83; chemical fixation, r = −0.155, p=0.059, non-parametric Spearman test).

Figure 3

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Spine parameter data used in Figure 3.

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The correlation of spine head volume and spine neck diameter in chemically fixed tissue could be due to significant structural differences in the spine neck when comparing the larger spines with smaller spines. Previous EM analyses have shown that spines with larger heads tend to be those where membranous structures, such as endoplasmic reticulum (ER), are present (Spacek and Harris, 1997). If, by their presence, these structures enlarge the neck then this may have an influence on the correlation between head volume and neck thickness. We investigated this question by grouping dendritic spines (chemical fixation, n = 75; cryo fix, n = 98) according to whether or not membranes were present in the neck (Figure 4). We scored this as ER, and did not classify them further as cisterns or vesicles as unequivocal classification in the cryo-fixed material was not possible. The cryo preparation method, where there is less extraction of molecules results in less contrast between the membranes, cytoplasm and extracellular compartments. Also, despite the sub-nanometre resolution of TEM imaging, the section thickness of 50 nm gives an obscured view of the details within the spine necks (Figure 4A’, B’, C’). FIBSEM imaging generates images with less contrast at a lower resolution. This analysis showed that spine neck length and the spine neck diameter were not different if membranes were present or absent, neither in cryo-fixed tissue nor in chemically fixed tissue (neck length, chemical fixation p=0.95, cryo fixation p=0.99; spine neck diameter, chemical fixation p=0.08, cryo fixation p=0.81; Figure 4D,E). Therefore, the presence of intracellular compartments within the neck do not appear to determine its thickness. However, spines in which ER is present in the spine neck do have larger heads after both cryo and chemical fixation (chemical fixation p<0.0001, cryo fixation p=0.0074; Tukey’s multiple comparison test; Figure 4F), in agreement with a previous study of chemically fixed spines (Spacek and Harris, 1997).

Figure 4

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Spine parameter data used in Figure 4.

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Finally, we considered how the electrical resistance of the spines would change on the basis of the different morphological parameters measured (Figure 5). We used Ohm's law and the formula R = ρ × spine neck length/spine neck cross-sectional area, with a resistivity constant ρ = 109 Ω cm (Cartailler et al., 2018). The mean value of the resistance of spines in cryo-fixed cortex was 109.7 ± 113.4 MΩ (spine number n = 116, N = 5), and in chemically fixed cortex was 44.1 ± 37.8 MΩ (spine number n = 150, N = 3) showing a significant difference in their distributions (p<0.0001, unpaired, Kolmogorov-Smirnov test; Figure 5A). We found obvious correlations between resistance and spine neck cross-sectional area (cryo, r = −0.74, p<0.0001, n = 116 spines, N = 5 mice; chemical, r = −0.64, p<0.0001, n = 150 spines, N = 3 mice, correlation, non-parametric Spearman; Figure 5B).

Figure 5

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Spine parameter data used in Figure 5.

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The aim of this study was to gain a better understanding of the native ultrastructure of dendritic spines and to investigate if chemical fixation alters the morphology of dendritic spines, a neuronal structure that for many years has been the focus of considerable research due to its significant role in neuronal connectivity and plasticity (Harris and Kater, 1994; Holtmaat and Svoboda, 2009). We found that the volume of spine heads and the length of spine necks are unaltered by chemical fixation, and only the size of the spine neck is changed, being 42% thicker in diameter in chemically fixed tissue compared to cryo-fixed tissue. The thinner spine necks observed in cryo-fixed tissue suggest a larger electrical resistance coupling spines to parent dendrites than previously indicated from analysis of chemically fixed tissue.

Several of the parameters we assessed here appear to show that spines remain largely unchanged between chemical and cryo fixation, in agreement with previously published work. Spine head volume in cryo-fixed tissue was 0.069 µm³, which was not different to the spine volume in chemically fixed tissue of 0.081 µm³ (Figure 2). Our spine volume measurements are similar to other studies in the same region of the mouse brain (0.06 ± 0.04 µm³, layer 4 [Rodriguez-Moreno et al., 2018]; 0.075 ± 0.005 µm³ - 0.079 ± 0.006 µm³, layer 1, adult and aged mice, layer 1 [Calì et al., 2018]). Our measurement of mean spine length after cryo-fixation of 0.77 ± 0.55 µm was not different from the length of 0.84 ± 0.57 µm in chemically fixed tissue (Figure 2), and is similar to other studies, for example rat CA1 hippocampus, 0.45 ± 0.29 µm (Harris and Stevens, 1989) rat cerebellum, 0.66 ± 0.32 µm (Harris and Stevens, 1988) and mouse layer 2/3 pyramidal cells, 0.66 ± 0.37 µm (Arellano et al., 2007). Despite the fact that chemical fixation causes important changes to the extracellular space and astrocytic arrangement (Korogod et al., 2015), the overall structure of dendritic spines appears to be resilient to the alterations that the aldehydes are causing.

On the other hand, our results suggest that spine neck thickness is affected by chemical fixation, with a mean diameter of 128 nm in cryo-fixed tissue compared to 182 nm in chemically fixed tissue (Figure 2). This finding raises the question as to what could be happening during the aldehyde preservation method that could explain the widening. Spines are highly dynamic structures, with their shape changing during development and also adulthood (Nimchinsky et al., 2002), and in concert with changes in synapse size (Sala and Segal, 2014; Knott et al., 2006). To explain dynamic spine morphology, we need to consider the structural components. Actin is present throughout spines, with branched and linear actin being in different proportions in the neck and head (Matus, 2000; Korobova and Svitkina, 2010). This cytoskeleton determines the size and shape of the spine, with synaptic activation capable of altering the quantities of filamentous actin, and changing spine shape (Honkura et al., 2008). Modeling of dendritic spines using the physical properties of different structural components suggests the presence and arrangement of different proteins, such as actin in the neck, maintain its diameter (Miermans et al., 2017). This is supported by evidence of a clear periodic arrangement of actin rings in the spine neck (Bär et al., 2016) as well as various experiments showing that disruption of the actin regulatory pathways lead to changes in the spine shape (Basu and Lamprecht, 2018). However, preserving the integrity of actin is difficult, due to its sensitivity to aldehyde fixatives such as the ones used here (Boyles et al., 1985). Therefore, the shape of spines appears to be critically dependent on the arrangement of actin, which is dismantled on exposure to aldehydes, and this is likely to contribute to the differences in spine necks comparing cryo-fixed and chemically fixed tissue.

Some spine necks have also been shown to be rich in other proteins, such as the GTPases from the septin family (Tada et al., 2007), thought to be involved in the restriction of movement of certain membrane proteins out of the spine head (Ewers et al., 2014). A differential protein concentration within this narrowed part of the spine could exert on oncotic pressure pulling water into this region during chemical fixation.

We cannot exclude the possibility that chemical fixation leaves the spine neck unchanged with the differences measured occurring during the process of tissue extraction, before cryo fixation. However, we think this unlikely, as although the effects of hypoxia on dendrites have been investigated - showing changes such as swelling, the formation of filopodia, and the elongation of immature spines - these were seen after 15 min (Jourdain et al., 2002; Segura et al., 2016). Our workflow vitrifies samples within 90 s of the heart stopping and within the first 30 s the tissue had been extracted and placed on a cooled surface. This method showed that in vivo levels of the extracellular space were preserved (Korogod et al., 2015) and there was no evidence of the compact neuropil, showing little extracellular space that is a feature of asphyxiated tissue as described by Van Harreveld and Malhotra, 1967.

Our data support the observation from light microscopy showing that the morphology of the spine neck is independent of the spine head volume (Araya et al., 2014; Tønnesen et al., 2014). Previous electron microscopy analysis had suggested a correlation, although only a weak one, between these parameters (Arellano et al., 2007; Bartol et al., 2015), which we also show here with chemical fixation. However, cryo-fixed spines, presumed to be in their native state, show no correlation. Spine neck thickness, therefore, appears to be independent of the spine head volume, and therefore synapse size.

Functionally, the smaller spine widths observed in cryo-fixed tissue without change in spine neck length suggest that spine neck resistances might be higher than that implied by previous studies of chemically fixed tissue. Assuming cytosolic resistivity of 109 Ω cm (Cartailler et al., 2018), we estimate a mean spine neck resistance of 110 MΩ ranging from 2 MΩ to 595 MΩ in cryo-fixed tissue compared to 44 MΩ ranging from 1 MΩ to 206 MΩ in chemically fixed tissue. It is important to note that these are likely lower bound estimates, since the presence of intracellular organelles, and large macromolecular complexes, in the spine neck will further increase spine neck resistance. Our results are consistent with estimates from physiological analyses (e.g. Bloodgood and Sabatini, 2005; Grunditz et al., 2008) as well as morphological analyses in vivo using STED microscopy of hippocampal dendrites in CA1 showing neck widths of 147 nm (Pfeiffer et al., 2018). The same imaging approach on cultured hippocampal slices gives similar results and estimated that half of spines had a resistance of greater than 56 MΩ. Here, the median value is 80 MΩ for cryo fixed, and 34 MΩ for chemically fixed spines.

At the upper end of the range of spine neck resistance, there could be a considerable impact upon spine voltage dynamics during synaptic signaling, with a 1 GΩ spine neck resistance causing a 1 mV drop in potential from spine to parent dendrite for each 1 pA of synaptic current. Given that synaptic currents are typically considered to be in the range of tens of pA, our data are consistent with tens of mV difference between spine head and dendrite for the smallest spine neck diameters. For these spines, regulation of spine neck diameter could therefore contribute to functional synaptic plasticity as previously proposed (Bloodgood and Sabatini, 2005; Grunditz et al., 2008). Our data showing smaller spine neck width in cryo-fixed tissue therefore suggest that spine neck resistance may play a more important role in synaptic signaling compared to estimates based on chemically fixed tissue.

These results, and those from our previous paper (Korogod et al., 2015), indicate how cryo fixation gives a truer representation of neuronal structure, at least at the level of dendritic spines. In future studies, it will be of great interest to examine axonal structure comparing cryo and chemical fixation. However, achieving a reliable preservation of neuronal tissue in its native state, and in significant volumes, is not possible with freezing due to the limited thickness to which vitrification can occur in samples with such high water content. Therefore, chemical fixation is still the best method for the preservation of significant volumes of nervous tissues, and variations to this approach that address some of its drawbacks have been used, such as alterations to osmolarity to correct for extracellular space loss (Pallotto et al., 2015). Our cryo fixation also uses a low-temperature embedding method with the replacement of water with solvents containing heavy metal stains. Advances in focused ion beam microscopy at cryo temperatures have shown that these steps may be avoidable in the future, removing any possible structural changes they may cause (Schertel et al., 2013; Zachs et al., 2020).

The sample preparation and imaging methods were identical to those used in our previous paper (Korogod et al., 2015) and described briefly below.

All data generated during this study are included in the manuscript and the supporting files. Source data files are provided for all results. These are: Figures 1, 2, 3, 4 and 5 and Figure supplements for Figure 1 and 2.

1. 1. Araya R
   2. Vogels TP
   3. Yuste R

   (2014) Activity-dependent dendritic spine neck changes are correlated with synaptic strength

   PNAS 111:E2895–E2904.

   https://doi.org/10.1073/pnas.1321869111

   • PubMed
   • Google Scholar
2. 1. Arellano JI
   2. Benavides-Piccione R
   3. Defelipe J
   4. Yuste R

   (2007) Ultrastructure of dendritic spines: correlation between synaptic and spine morphologies

   Frontiers in Neuroscience 1:131–143.

   https://doi.org/10.3389/neuro.01.1.1.010.2007

   • PubMed
   • Google Scholar
3. 1. Bär J
   2. Kobler O
   3. van Bommel B
   4. Mikhaylova M

   (2016) Periodic F-actin structures shape the neck of dendritic spines

   Scientific Reports 6:37136.

   https://doi.org/10.1038/srep37136

   • PubMed
   • Google Scholar
4. 1. Bartol TM
   2. Bromer C
   3. Kinney J
   4. Chirillo MA
   5. Bourne JN
   6. Harris KM
   7. Sejnowski TJ

   (2015) Nanoconnectomic upper bound on the variability of synaptic plasticity

   eLife 4:e10778.

   https://doi.org/10.7554/eLife.10778

   • PubMed
   • Google Scholar
5. 1. Basu S
   2. Lamprecht R

   (2018) The role of actin cytoskeleton in dendritic spines in the maintenance of Long-Term memory

   Frontiers in Molecular Neuroscience 11:143.

   https://doi.org/10.3389/fnmol.2018.00143

   • PubMed
   • Google Scholar
6. 1. Bloodgood BL
   2. Sabatini BL

   (2005) Neuronal activity regulates diffusion across the neck of dendritic spines

   Science 310:866–869.

   https://doi.org/10.1126/science.1114816

   • PubMed
   • Google Scholar
7. 1. Bourne JN
   2. Harris KM

   (2008) Balancing structure and function at hippocampal dendritic spines

   Annual Review of Neuroscience 31:47–67.

   https://doi.org/10.1146/annurev.neuro.31.060407.125646

   • PubMed
   • Google Scholar
8. 1. Boyles J
   2. Anderson L
   3. Hutcherson P

   (1985) A new fixative for the preservation of actin filaments: fixation of pure actin filament pellets

   Journal of Histochemistry & Cytochemistry 33:1116–1128.

   https://doi.org/10.1177/33.11.3902963

   • PubMed
   • Google Scholar
9. 1. Calì C
   2. Wawrzyniak M
   3. Becker C
   4. Maco B
   5. Cantoni M
   6. Jorstad A
   7. Nigro B
   8. Grillo F
   9. De Paola V
   10. Fua P
   11. Knott GW

   (2018) The effects of aging on neuropil structure in mouse somatosensory cortex-A 3D electron microscopy analysis of layer 1

   PLOS ONE 13:e0198131.

   https://doi.org/10.1371/journal.pone.0198131

   • PubMed
   • Google Scholar
10. 1. Cane M
    2. Maco B
    3. Knott G
    4. Holtmaat A

    (2014) The relationship between PSD-95 clustering and spine stability in vivo

    Journal of Neuroscience 34:2075–2086.

    https://doi.org/10.1523/JNEUROSCI.3353-13.2014

    • PubMed
    • Google Scholar
11. 1. Cardona A
    2. Saalfeld S
    3. Schindelin J
    4. Arganda-Carreras I
    5. Preibisch S
    6. Longair M
    7. Tomancak P
    8. Hartenstein V
    9. Douglas RJ

    (2012) TrakEM2 software for neural circuit reconstruction

    PLOS ONE 7:e38011.

    https://doi.org/10.1371/journal.pone.0038011

    • PubMed
    • Google Scholar
12. 1. Cartailler J
    2. Kwon T
    3. Yuste R
    4. Holcman D

    (2018) Deconvolution of voltage sensor time series and Electro-diffusion modeling reveal the role of spine geometry in controlling synaptic strength

    Neuron 97:1126–1136.

    https://doi.org/10.1016/j.neuron.2018.01.034

    • PubMed
    • Google Scholar
13. 1. Colonnier M

    (1968) Synaptic patterns on different cell types in the different laminae of the cat visual cortex. an electron microscope study

    Brain Research 9:268–287.

    https://doi.org/10.1016/0006-8993(68)90234-5

    • PubMed
    • Google Scholar
14. 1. El-Boustani S
    2. Ip JPK
    3. Breton-Provencher V
    4. Knott GW
    5. Okuno H
    6. Bito H
    7. Sur M

    (2018) Locally coordinated synaptic plasticity of visual cortex neurons in vivo

    Science 360:1349–1354.

    https://doi.org/10.1126/science.aao0862

    • PubMed
    • Google Scholar
15. 1. Ewers H
    2. Tada T
    3. Petersen JD
    4. Racz B
    5. Sheng M
    6. Choquet D

    (2014) A Septin-Dependent diffusion barrier at dendritic spine necks

    PLOS ONE 9:e113916.

    https://doi.org/10.1371/journal.pone.0113916

    • PubMed
    • Google Scholar
16. 1. Fifková E
    2. Anderson CL

    (1981) Stimulation-induced changes in dimensions of stalks of dendritic spines in the dentate molecular layer

    Experimental Neurology 74:621–627.

    https://doi.org/10.1016/0014-4886(81)90197-7

    • PubMed
    • Google Scholar
17. 1. Grunditz A
    2. Holbro N
    3. Tian L
    4. Zuo Y
    5. Oertner TG

    (2008) Spine neck plasticity controls postsynaptic calcium signals through electrical compartmentalization

    Journal of Neuroscience 28:13457–13466.

    https://doi.org/10.1523/JNEUROSCI.2702-08.2008

    • PubMed
    • Google Scholar
18. 1. Harris KM
    2. Kater SB

    (1994) Dendritic spines: cellular specializations imparting both stability and flexibility to synaptic function

    Annual Review of Neuroscience 17:341–371.

    https://doi.org/10.1146/annurev.ne.17.030194.002013

    • PubMed
    • Google Scholar
19. 1. Harris KM
    2. Stevens JK

    (1988) Dendritic spines of rat cerebellar purkinje cells: serial electron microscopy with reference to their biophysical characteristics

    The Journal of Neuroscience 8:4455–4469.

    https://doi.org/10.1523/JNEUROSCI.08-12-04455.1988

    • PubMed
    • Google Scholar
20. 1. Harris KM
    2. Stevens JK

    (1989) Dendritic spines of CA 1 pyramidal cells in the rat Hippocampus: serial electron microscopy with reference to their biophysical characteristics

    The Journal of Neuroscience 9:2982–2997.

    https://doi.org/10.1523/JNEUROSCI.09-08-02982.1989

    • PubMed
    • Google Scholar
21. 1. Harvey CD
    2. Svoboda K

    (2007) Locally dynamic synaptic learning rules in pyramidal neuron dendrites

    Nature 450:1195–1200.

    https://doi.org/10.1038/nature06416

    • PubMed
    • Google Scholar
22. 1. Holtmaat A
    2. Svoboda K

    (2009) Experience-dependent structural synaptic plasticity in the mammalian brain

    Nature Reviews Neuroscience 10:647–658.

    https://doi.org/10.1038/nrn2699

    • PubMed
    • Google Scholar
23. 1. Honkura N
    2. Matsuzaki M
    3. Noguchi J
    4. Ellis-Davies GC
    5. Kasai H

    (2008) The subspine organization of actin fibers regulates the structure and plasticity of dendritic spines

    Neuron 57:719–729.

    https://doi.org/10.1016/j.neuron.2008.01.013

    • PubMed
    • Google Scholar
24. 1. Jorstad A
    2. Nigro B
    3. Cali C
    4. Wawrzyniak M
    5. Fua P
    6. Knott G

    (2015) NeuroMorph: a toolset for the morphometric analysis and visualization of 3D models derived from electron microscopy image stacks

    Neuroinformatics 13:83–92.

    https://doi.org/10.1007/s12021-014-9242-5

    • PubMed
    • Google Scholar
25. 1. Jorstad A
    2. Blanc J
    3. Knott G

    (2018) NeuroMorph: a software toolset for 3D analysis of neurite morphology and connectivity

    Frontiers in Neuroanatomy 12:59.

    https://doi.org/10.3389/fnana.2018.00059

    • PubMed
    • Google Scholar
26. 1. Jourdain P
    2. Nikonenko I
    3. Alberi S
    4. Muller D

    (2002) Remodeling of hippocampal synaptic networks by a brief anoxia-hypoglycemia

    The Journal of Neuroscience 22:3108–3116.

    https://doi.org/10.1523/JNEUROSCI.22-08-03108.2002

    • PubMed
    • Google Scholar
27. 1. Kharazia VN
    2. Weinberg RJ

    (1999) Immunogold localization of AMPA and NMDA receptors in somatic sensory cortex of albino rat

    The Journal of Comparative Neurology 412:292–302.

    https://doi.org/10.1002/(SICI)1096-9861(19990920)412:2<292::AID-CNE8>3.0.CO;2-G

    • PubMed
    • Google Scholar
28. 1. Knott GW
    2. Quairiaux C
    3. Genoud C
    4. Welker E

    (2002) Formation of dendritic spines with GABAergic synapses induced by whisker stimulation in adult mice

    Neuron 34:265–273.

    https://doi.org/10.1016/S0896-6273(02)00663-3

    • PubMed
    • Google Scholar
29. 1. Knott GW
    2. Holtmaat A
    3. Wilbrecht L
    4. Welker E
    5. Svoboda K

    (2006) Spine growth precedes synapse formation in the adult neocortex in vivo

    Nature Neuroscience 9:1117–1124.

    https://doi.org/10.1038/nn1747

    • PubMed
    • Google Scholar
30. 1. Korobova F
    2. Svitkina T

    (2010) Molecular architecture of synaptic actin cytoskeleton in hippocampal neurons reveals a mechanism of dendritic spine morphogenesis

    Molecular Biology of the Cell 21:165–176.

    https://doi.org/10.1091/mbc.e09-07-0596

    • PubMed
    • Google Scholar
31. 1. Korogod N
    2. Petersen CC
    3. Knott GW

    (2015) Ultrastructural analysis of adult mouse neocortex comparing aldehyde perfusion with cryo fixation

    eLife 4:e05793.

    https://doi.org/10.7554/eLife.05793

    • PubMed
    • Google Scholar
32. 1. Lang C
    2. Barco A
    3. Zablow L
    4. Kandel ER
    5. Siegelbaum SA
    6. Zakharenko SS

    (2004) Transient expansion of synaptically connected dendritic spines upon induction of hippocampal long-term potentiation

    PNAS 101:16665–16670.

    https://doi.org/10.1073/pnas.0407581101

    • PubMed
    • Google Scholar
33. 1. Matsuzaki M
    2. Ellis-Davies GC
    3. Nemoto T
    4. Miyashita Y
    5. Iino M
    6. Kasai H

    (2001) Dendritic spine geometry is critical for AMPA receptor expression in hippocampal CA1 pyramidal neurons

    Nature Neuroscience 4:1086–1092.

    https://doi.org/10.1038/nn736

    • PubMed
    • Google Scholar
34. 1. Matsuzaki M
    2. Honkura N
    3. Ellis-Davies GC
    4. Kasai H

    (2004) Structural basis of long-term potentiation in single dendritic spines

    Nature 429:761–766.

    https://doi.org/10.1038/nature02617

    • PubMed
    • Google Scholar
35. 1. Matus A

    (2000) Actin-based plasticity in dendritic spines

    Science 290:754–758.

    https://doi.org/10.1126/science.290.5492.754

    • PubMed
    • Google Scholar
36. 1. Miermans CA
    2. Kusters RP
    3. Hoogenraad CC
    4. Storm C

    (2017) Biophysical model of the role of actin remodeling on dendritic spine morphology

    PLOS ONE 12:e0170113.

    https://doi.org/10.1371/journal.pone.0170113

    • PubMed
    • Google Scholar
37. 1. Nägerl UV
    2. Köstinger G
    3. Anderson JC
    4. Martin KA
    5. Bonhoeffer T

    (2007) Protracted synaptogenesis after activity-dependent spinogenesis in hippocampal neurons

    Journal of Neuroscience 27:8149–8156.

    https://doi.org/10.1523/JNEUROSCI.0511-07.2007

    • PubMed
    • Google Scholar
38. 1. Nimchinsky EA
    2. Sabatini BL
    3. Svoboda K

    (2002) Structure and function of dendritic spines

    Annual Review of Physiology 64:313–353.

    https://doi.org/10.1146/annurev.physiol.64.081501.160008

    • PubMed
    • Google Scholar
39. 1. Noguchi J
    2. Matsuzaki M
    3. Ellis-Davies GC
    4. Kasai H

    (2005) Spine-neck geometry determines NMDA receptor-dependent Ca2+ signaling in dendrites

    Neuron 46:609–622.

    https://doi.org/10.1016/j.neuron.2005.03.015

    • PubMed
    • Google Scholar
40. 1. Nusser Z
    2. Lujan R
    3. Laube G
    4. Roberts JD
    5. Molnar E
    6. Somogyi P

    (1998) Cell type and pathway dependence of synaptic AMPA receptor number and variability in the Hippocampus

    Neuron 21:545–559.

    https://doi.org/10.1016/S0896-6273(00)80565-6

    • PubMed
    • Google Scholar
41. 1. Pallotto M
    2. Watkins PV
    3. Fubara B
    4. Singer JH
    5. Briggman KL

    (2015) Extracellular space preservation aids the connectomic analysis of neural circuits

    eLife 4:e08206.

    https://doi.org/10.7554/eLife.08206

    • PubMed
    • Google Scholar
42. 1. Pfeiffer T
    2. Poll S
    3. Bancelin S
    4. Angibaud J
    5. Inavalli VK
    6. Keppler K
    7. Mittag M
    8. Fuhrmann M
    9. Nägerl UV

    (2018) Chronic 2P-STED imaging reveals high turnover of dendritic spines in the Hippocampus in vivo

    eLife 7:e34700.

    https://doi.org/10.7554/eLife.34700

    • PubMed
    • Google Scholar
43. 1. Rodriguez-Moreno J
    2. Rollenhagen A
    3. Arlandis J
    4. Santuy A
    5. Merchan-Pérez A
    6. DeFelipe J
    7. Lübke JHR
    8. Clasca F

    (2018) Quantitative 3D ultrastructure of thalamocortical synapses from the "Lemniscal" Ventral Posteromedial Nucleus in Mouse Barrel Cortex

    Cerebral Cortex 28:3159–3175.

    https://doi.org/10.1093/cercor/bhx187

    • PubMed
    • Google Scholar
44. 1. Sala C
    2. Segal M

    (2014) Dendritic spines: the locus of structural and functional plasticity

    Physiological Reviews 94:141–188.

    https://doi.org/10.1152/physrev.00012.2013

    • PubMed
    • Google Scholar
45. 1. Schertel A
    2. Snaidero N
    3. Han HM
    4. Ruhwedel T
    5. Laue M
    6. Grabenbauer M
    7. Möbius W

    (2013) Cryo FIB-SEM: volume imaging of cellular ultrastructure in native frozen specimens

    Journal of Structural Biology 184:355–360.

    https://doi.org/10.1016/j.jsb.2013.09.024

    • PubMed
    • Google Scholar
46. 1. Segura I
    2. Lange C
    3. Knevels E
    4. Moskalyuk A
    5. Pulizzi R
    6. Eelen G
    7. Chaze T
    8. Tudor C
    9. Boulegue C
    10. Holt M
    11. Daelemans D
    12. Matondo M
    13. Ghesquière B
    14. Giugliano M
    15. Ruiz de Almodovar C
    16. Dewerchin M
    17. Carmeliet P

    (2016) The oxygen sensor PHD2 controls dendritic spines and synapses via modification of filamin A

    Cell Reports 14:2653–2667.

    https://doi.org/10.1016/j.celrep.2016.02.047

    • Google Scholar
47. 1. Spacek J
    2. Harris KM

    (1997) Three-dimensional organization of smooth endoplasmic reticulum in hippocampal CA1 dendrites and dendritic spines of the immature and mature rat

    The Journal of Neuroscience 17:190–203.

    https://doi.org/10.1523/JNEUROSCI.17-01-00190.1997

    • PubMed
    • Google Scholar
48. 1. Tada T
    2. Simonetta A
    3. Batterton M
    4. Kinoshita M
    5. Edbauer D
    6. Sheng M

    (2007) Role of septin cytoskeleton in spine morphogenesis and dendrite development in neurons

    Current Biology 17:1752–1758.

    https://doi.org/10.1016/j.cub.2007.09.039

    • PubMed
    • Google Scholar
49. 1. Tønnesen J
    2. Katona G
    3. Rózsa B
    4. Nägerl UV

    (2014) Spine neck plasticity regulates compartmentalization of synapses

    Nature Neuroscience 17:678–685.

    https://doi.org/10.1038/nn.3682

    • PubMed
    • Google Scholar
50. 1. Van Harreveld A
    2. Crowell J
    3. Malhotra SK

    (1965) A study of extracellular space in central nervous tissue by freeze-substitution

    Journal of Cell Biology 25:117–137.

    https://doi.org/10.1083/jcb.25.1.117

    • PubMed
    • Google Scholar
51. 1. Van Harreveld A
    2. Malhotra SK

    (1967)

    Extracellular space in the cerebral cortex of the mouse

    Journal of Anatomy 101:197–207.

    • PubMed
    • Google Scholar
52. 1. Zachs T
    2. Schertel A
    3. Medeiros J
    4. Weiss GL
    5. Hugener J
    6. Matos J
    7. Pilhofer M

    (2020) Fully automated, sequential focused ion beam milling for cryo-electron tomography

    eLife 9:e52286.

    https://doi.org/10.7554/eLife.52286

    • PubMed
    • Google Scholar

Author details

1. Hiromi Tamada

   1. Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
   2. Biological Electron Microscopy Facility, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
   3. Functional Anatomy and Neuroscience, Graduate School of Medicine, Nagoya University, Nagoya, Japan
   4. Japan Society of the Promotion of Sciences (JSPS), Tokyo, Japan

   Contribution

   Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

2. Jerome Blanc

   Biological Electron Microscopy Facility, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

   Contribution

   Formal analysis, Investigation

   Competing interests

   No competing interests declared

3. Natalya Korogod

   1. Biological Electron Microscopy Facility, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
   2. School of Health Sciences (HESAV), University of Applied Sciences and Arts Western Switzerland (HES-SO), Lausanne, Switzerland

   Contribution

   Conceptualization, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

4. Carl CH Petersen

   Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

   Contribution

   Conceptualization, Resources, Funding acquisition, Validation, Writing - review and editing

   For correspondence

   carl.petersen@epfl.ch

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3344-4495

5. Graham W Knott

   Biological Electron Microscopy Facility, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

   Contribution

   Conceptualization, Resources, Data curation, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   graham.knott@epfl.ch

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2956-9052

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