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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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Cites
Two new Later Stone Age sites from the Final Pleistocene in the Falémé Valley, eastern Senegal
Ndiaye, M., Lespez, L., Tribolo, C., Rassé, M., Hadjas, I., Davidoux, S., Huysecom, É., & Douze, K. (2024) · Monash University Research Portal (Monash University) · doi:10.3929/ethz-b-000667478 · Cited by 24,214
The structure of the nervous system of the nematode Caenorhabditis elegans
White, J. G., Southgate, E., Thomson, J. N., & Brenner, S. (1986) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1986.0056 · Cited by 5,589
GUNDERSEN, H. J. G., BENDTSEN, T. F., KORBO, L., MARCUSSEN, N., MØLLER, A., NIELSEN, K., NYENGAARD, J. R., PAKKENBERG, B., SØRENSEN, F. B., VESTERBY, A., et al. (1988) · APMIS · doi:10.1111/j.1699-0463.1988.tb05320.x · Cited by 2,929
The unbiased estimation of number and sizes of arbitrary particles using the disector
Sterio, D. C. (1984) · Journal of Microscopy · doi:10.1111/j.1365-2818.1984.tb02501.x · Cited by 2,533
Gundersen, H. J. G., Bagger, P. V., Bendtsen, T. F., Evans, S. M., Korbo, L., Marcussen, N., Møller, A., Nielsen, K. N., Nyengaard, J. R., Pakkenberg, B., et al. (1988) · Apmis · doi:10.1111/j.1699-0463.1988.tb00954.x · Cited by 2,480
The Fine Structure of the Nervous System.
Tennyson, V. M. (1970) · Archives of Neurology · doi:10.1001/archneur.1970.00480240094019 · Cited by 1,946
Axo-somatic and axo-dendritic synapses of the cerebral cortex: an electron microscope study.
Eg, G. (1959) · PubMed · Cited by 1,768
Serial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure
Denk, W., & Horstmann, H. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020329 · Cited by 1,644
(1991) · Medical Entomology and Zoology · Cited by 1,512
Notes on the estimation of the numerical density of arbitrary profiles: the edge effect
Gundersen, H. J. G. (1977) · Journal of Microscopy · doi:10.1111/j.1365-2818.1977.tb00062.x · Cited by 1,265
Flagged first, then by citations
Research works printed but not linked: 2
- Colonnier M. (1981). The electron-microscopic analysis of the neuronal organization of the cerebral cortex. In The Organization of the Cerebral Cortex, Schmitt F. O. Worden F. G. Adelman G. Dennis S. G., eds (Cambridge, MA, MIT Press), pp. 125– 152
- Peters A. (1987). Synaptic specificity in the cerebral cortex. In Synaptic Function, Edelman G. M. Gall W. E. Cowan W. M., eds (New York, John Wiley), pp. 373– 397
Cited by
Sorted by citations
Items 101–191 of 191
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Mingard, K. P., Jones, H. G., & Gee, M. G. (2013) · Journal of Microscopy · doi:10.1111/jmi.12100 · Cited by 18
Böhm, T., Joseph, K., Kirsch, M., Moroni, R., Hilger, A., Osenberg, M., Manke, I., Johnston, M., Stieglitz, T., Hofmann, U., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-42544-9 · Cited by 20
Unambiguous identification of asymmetric and symmetric synapses using volume electron microscopy
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Rah, J., Feng, L., Druckmann, S., Lee, H., & Kim, J. (2015) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2015.00078 · Cited by 17
Huang, Z., Khaled, H. G., Kirschmann, M., Gobes, S. M. H., & Hahnloser, R. H. R. (2018) · eLife · doi:10.7554/elife.37571 · Cited by 16
Volume electron microscopy analysis of synapses in primary regions of the human cerebral cortex
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Lehmann, T., Heß, M., Wanner, G., & Melzer, R. R. (2014) · BMC Biology · doi:10.1186/s12915-014-0059-3 · Cited by 14
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Schauflinger, M., Read, C., & Walther, P. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-601-6_16 · Cited by 13
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Simhal, A. K., Aguerrebere, C., Collman, F., Vogelstein, J. T., Micheva, K. D., Weinberg, R. J., Smith, S. J., & Sapiro, G. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005493 · Cited by 15
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Plaza‐Alonso, S., Cano‐Astorga, N., DeFelipe, J., & Alonso‐Nanclares, L. (2025) · eLife · doi:10.7554/elife.96144 · Cited by 10
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Hoang, T. V., Kizilyaprak, C., Spehner, D., Humbel, B. M., & Schultz, P. (2016) · Journal of Structural Biology · doi:10.1016/j.jsb.2016.10.005 · Cited by 10
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Currin, C. B., & Raimondo, J. V. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010534 · Cited by 9
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Fukui, K. (2016) · Chromosome science · doi:10.11352/scr.19.51 · Cited by 8
Rai, D., Dey, S., & Ray, K. (2018) · BMC Neuroscience · doi:10.1186/s12868-018-0430-3 · Cited by 9
Glausier, J. R., Maier, M. J., Bouchet‐Marquis, C., Wu, K., Banks‐Tibbs, T., Melchitzky, D. S., Ning, J., Lewis, D. A., & Freyberg, Z. (2025) · iScience · doi:10.1016/j.isci.2025.112747 · Cited by 8
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Park, S. J., Schertel, A., Lee, K. E., & Han, S. (2013) · Microscopy · doi:10.1093/jmicro/dft039 · Cited by 7
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Han, W., Rajan, P., Frazier, P. I., & Jedynak, B. (2016) · IEEE Transactions on Information Theory · doi:10.1109/tit.2016.2628784 · Cited by 7
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Ayuob, N. N., & Balgoon, M. J. (2018) · Microscopy Research and Technique · doi:10.1002/jemt.23105 · Cited by 6
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Pei, X., Wang, H., Xu, P., Liang, K., & Yuan, L. (2022) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2022.08.084 · Cited by 4
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Hassan, D., Amin, S., Solangi, A. R., & Memon, S. Q. (2019) · IntechOpen eBooks · doi:10.5772/intechopen.88937 · Cited by 4
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Kizilyaprak, C., Bellis, D. D., Blanchard, W., Daraspe, J., & Humbel, B. M. (2019) · Wiley eBooks · doi:10.1002/9781118663233.ch26 · Cited by 5
Luján, R., Turégano-López, M., Aguado, C., & Merchán-Pérez, Á. (2024) · Advanced technology in neuroscience . · doi:10.4103/atn.atn-d-24-00009 · Cited by 3
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Colangelo, C., Muñoz, A., Antonietti, A., Antón‐Fernández, A., Romani, A., Herttuainen, J., Markram, H., DeFelipe, J., & Ramaswamy, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.11.516108 · Cited by 3
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Sebők-Tornai, A., Csabai, D., Szocsics, P., Gombás, P., Cobb, J. A., Mahajan, G., Stockmeier, C. A., & Czéh, B. (2026) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2026.111661 · Cited by 2
Tamada, H. (2026) · The Journal of Physiology · doi:10.1113/jp287612 · Cited by 2
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Kanemaru, T., & Oki, Y. (2015) · Microscopy · doi:10.1093/jmicro/dfv015 · Cited by 2
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LaTorre, A., Muelas, S., Peña, J.-M., Santana, R., Merchán-Pérez, Á., & Rodríguez, J. (2011) · IEEE Congress on Evolutionary Computation (CEC) · doi:10.1109/cec.2011.5949818 · Cited by 2
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Villalba, R. M., Paré, J., & Smith, Y. (2015) · Neuromethods · doi:10.1007/7657_2015_97 · Cited by 2
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Acebes, Á. (2017) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2017.00017 · Cited by 2
Enhancing Interrogation of Skeletal Muscle Samples for Informative Quantitative Data
Partridge, T. A. (2021) · Journal of Neuromuscular Diseases · doi:10.3233/jnd-210736 · Cited by 2
A Highly Accurate Model Based Registration Method for FIB-SEM Images of NeuronsPreprint
Stephensen, H. J. T., Darkner, S., & Jon Sporring, A. (2018) · Research at the University of Copenhagen (University of Copenhagen) · doi:10.48550/arxiv.1810.01159 · Cited by 2
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POPESCU, A. I., & Opriș, I. C. (2017) · Springer series in cognitive and neural systems · doi:10.1007/978-3-319-29674-6_2 · Cited by 1
Pathway-Specific Ultrastructure of Thalamocortical Synapses in Mouse Somatosensory Area S2
Martin-Correa, P. J., Rubio-Teves, M., Rodriguez-Moreno, J., Porrero, C., Rollenhagen, A., Hilgetag, C. C., Lübke, J. H. R., & Clascá, F. (2025) · Journal of Neuroscience · doi:10.1523/jneurosci.1212-25.2025 · Cited by 1
Li, J., Zhang, N., Zhang, Z., Fu, J., Ren, W., Sun, Y. E., Song, S., Liu, X., Liu, J., Wang, J., et al. (2025) · Molecular Medicine · doi:10.1186/s10020-025-01366-4 · Cited by 1
Three-Dimensional Imaging for Electron Microscopy of Plastic-Embedded Plant Specimens
Seguí-Simarro, J. M. (2015) · Springer eBooks · doi:10.1007/978-3-319-19944-3_8 · Cited by 1
Cox Processes for Counting by Detection
Rajan, P., Ma, Y., & Jedynak, B. (2018) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-018-0838-5 · Cited by 1
3D Quantitative Analysis of Synaptic Ultrastructure in Identified Long-Range Projection Axons
Martin-Correa, P. J., Rodriguez-Moreno, J., Rollenhagen, A., Lübke, J. H. R., & Clascá, F. (2024) · Neuromethods · doi:10.1007/978-1-0716-4019-7_11 · Cited by 1
Xiaojuan, Z. H. O. U., Chen, Y., Peng, J., Zuo, M., & Yingyu, S. U. N. (2021) · Integrative Zoology · doi:10.1111/1749-4877.12593 · Cited by 1
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Morales, J., Alonso‐Nanclares, L., Rodríguez, J., Merchán-Pérez, Á., DeFelipe, J., & Rodríguez, Á. (2011) · International Journal of Artificial Intelligence Tools · doi:10.1142/s0218213011000139 · Cited by 1
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Birolini, G., Valenza, M., Paolo, E. D., Vezzoli, E., Talpo, F., Maniezzi, C., Caccia, C., Leoni, V., Bocchi, V. D., Conforti, P., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.13.092742 · Cited by 1
Higher-order regularization and morphological techniques for image segmentation
Neila, P. M. (2014) · doi:10.20868/upm.thesis.28954 · Cited by 1
Rodriguez-Gatica, J. E., Tapia, J. C., Cardenas, G., & Guevara, P. (2015) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2015.7164011
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Morales, J., Alonso‐Nanclares, L., Rodríguez, J., Merchán-Pérez, Á., DeFelipe, J., & Rodríguez, Á. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13033-5_12
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Morales, J., ̃a, J. G. P., ́ndez, J. F., & ́guez, A. R. (2011) · ASME World Conference on Innovative Virtual Reality (WINVR) · doi:10.1115/winvr2011-5553
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Kim, K. W., Baek, S. G., Park, B. J., Kim, H., & Rhyu, I. J. (2010) · Han-guk hyeonmigyeong hakoeji/Applied microscopy
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Sánchez, L. A. (2017) · UPM Digital Archive (Technical University of Madrid) · doi:10.20868/upm.thesis.47383
Thapa-Chetri, P. S., Santiago-Robles, C. M., Martínez-Rivera, N., Torres‐Vazquez, I., Joshi, V. N., Powell, R., & Rosa‐Molinar, E. (2017) · IEEE International Conference on Nanotechnology (IEEE-NANO) · doi:10.1109/nano.2017.8117452
Image segmentation with boosted multi-class classifiers
Rojas, K. C. (2018) · doi:10.20868/upm.thesis.53192
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(2019) · Cytology & Histology Reports · doi:10.29011/2688-6421.100008
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Rollenhagen, A., Sätzler, K., & Lübke, J. H. R. (2024) · Neuromethods · doi:10.1007/978-1-0716-4019-7_12
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Erişir, A., Briegel, A. C., Maher, E. E., & Sciaccotta, F. (2024) · Neuromethods · doi:10.1007/978-1-0716-4019-7_4
Talapka, P., Kocsis, Z., Marsi, L. D., Szarvas, V. E., & Kisvárday, Z. F. (2025) · Frontiers in Neural Circuits · doi:10.3389/fncir.2025.1644572
Dallere, S., Mattioni, A., Turégano-López, M., Blázquez‐Llorca, L., Merchán-Pérez, Á., Schellino, R., Vercelli, A., DeFelipe, J., & Boido, M. (2026) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-026-01814-7
Colangelo, C., Múñoz, A., Antonietti, A., Sood, V., Antón‐Fernández, A., Herttuainen, J., Romani, A., DeFelipe, J., & Ramaswamy, S. (2026) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1014460
Tamada, H. (2026) · Frontiers in Neural Circuits · doi:10.3389/fncir.2026.1870424
Serial Block-Face Imaging by Field Emission Scanning Electron Microscopy
Kim, K. W. (2011) · Han-guk hyeonmigyeong hakoeji/Applied microscopy
Biophysics of Synaptic Inhibition in Dendrites
Gidon, A. (2013) · Springer series in computational neuroscience · doi:10.1007/978-1-4614-8094-5_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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