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Counting synapses using FIB/SEM microscopy: a true revolution for ultrastructural volume reconstruction
Open accessAbstract
The advent of transmission electron microscopy (TEM) in the 1950s represented a fundamental step in the study of neuronal circuits. The application of this technique soon led to the realization that the number of synapses changes during the course of normal life, as well as under certain pathological or experimental circumstances. Since then, one of the main goals in neurosciences has been to define simple and accurate methods to estimate the magnitude of these changes. Contrary to analysing single sections, TEM reconstructions are extremely time-consuming and difficult. Therefore, most quantitative studies use stereological methods to define the three-dimensional characteristics of synaptic junctions that are studied in two dimensions. Here, to count the exact number of synapses per unit of volume we have applied a new three-dimensional reconstruction method that involves the combination of focused ion beam milling and scanning electron microscopy (FIB/SEM). We show that the images obtained with FIB/SEM are similar to those obtained with TEM, but with the advantage that FIB/SEM permits serial reconstructions of large volumes of tissue to be generated rapidly and automatically. Furthermore, we compared the estimates of the number of synapses obtained with stereological methods with the values obtained by FIB/SEM reconstructions. We concluded that FIB/SEM not only provides the actual number of synapses per volume but it is also much easier and faster to use than other currently available TEM methods. More importantly, it also avoids most of the errors introduced by stereological methods and overcomes the difficulties associated with these techniques.
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“Fortunately, the recent introduction of automated volume electron microscopy methods has proven to be a valuable and efficient approach for identifying synapses in three dimensions, becoming the gold standard technique for this purpose for this task (Merchán-Pérez et al., 2009).”
From Unambiguous identification of asymmetric and symmetric synapses using volume electron microscopy (2024) · cites this paper as Merchán-Pérez et al., 2009
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“This technology was chosen because it enables automated serial sectioning of large volumes of tissue, without any mechanical interaction with the sample (e.g., see Knott et al., 2008; Merchán-Pérez et al., 2009; Titze and Genoud, 2016; Kubota et al., 2018; Rollenhagen et al., 2020).”
From Unambiguous identification of asymmetric and symmetric synapses using volume electron microscopy (2024) · cites this paper as Merchán-Pérez et al., 2009
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Neila, P. M., Baumela, L., González‐Soriano, J., Rodríguez, J., DeFelipe, J., & Merchán-Pérez, Á. (2016) · Neuroinformatics · doi:10.1007/s12021-015-9288-z · Cited by 26
Automated segmentation of synapses in 3D EM data
Kreshuk, A., Straehle, C., Sommer, C., Köthe, U., Knott, G. W., & Hamprecht, F. A. (2011) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2011.5872392 · Cited by 26
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Kikuchi, T., González‐Soriano, J., Kastanauskaite, A., Benavides‐Piccione, R., Merchán-Pérez, Á., DeFelipe, J., & Blázquez‐Llorca, L. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa047 · Cited by 25
Shen, C., Sun, F., Zhang, R., Zhang, L., Li, Y.-L., Zhang, L., & Li, L. (2015) · Restorative Neurology and Neuroscience · doi:10.3233/rnn-150514 · Cited by 24
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SynapseJ: An Automated, Synapse Identification Macro for ImageJ
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Navlakha, S., Suhan, J. P., Barth, A. L., & Bar‐Joseph, Z. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt222 · Cited by 20
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Griffin, P. H., Patel, K. M., Zhu, T., Langford, R. M., Kamboj, V. S., Ritchie, D. A., & Oliver, R. A. (2020) · Journal of Applied Physics · doi:10.1063/5.0005770 · Cited by 18
Metadata
- Authors
- Merchan-Pérez, A.
- Venue
- Frontiers in Neuroanatomy
- Publisher
- Frontiers Media SA
- Published
- 2009
- Volume
- 3
- Pages
- 18-18
- ISSN
- 1662-5129 (ISSN-L)
- PMC
- PMC2784681
- OpenAlex
- W2063752629
- Cited by
- 191
- References
- 60
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 10 · 2023: 4 · 2022: 10 · 2021: 13 · 2020: 15 · 2019: 9 · 2018: 17 · 2017: 12 · 2016: 12 · 2015: 19 · 2014: 12 · 2013: 17 · 2012: 10
- FWCI
- 5.56
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Neuroanatomy (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- École Polytechnique Fédérale de Lausanne
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
- Physical Sciences › Materials Science › General Materials Science › Advanced Materials Characterization Techniques
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- FIB-SEM, 3D reconstruction, stereology, synapses, synaptic density, serial sectioning, neural circuits, transmission electron microscopy
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