Comparison of ssSEM and FIB-SEM datasets

The synapse density in HVC were measured from the ssSEM datasets with dissector methods, and the results are presented in sections 2.3.2, 2.3.3, and 2.3.4. The percentage of the symmetric synapses were measured from the FIB-SEM datasets with sampling units of 3 × 3 × 3-µmsubcubes, and the results are presented in section 2.3.5. Both measurements were performed on tissue from the same brain and similar sampling volume (see Table S. 2). A comparison of the two datasets and methods were performed by repeating the measurements of the same parameters in the same samples (Supplementary Method and Data section S.4 & S.6).

As shown in the results, the synapse density measurements resulted in systematically higher value in the FIB-SEM datasets compared to the ssSEM datasets. Similar relative differences in HVC synapse density among the groups in Experiment I were found with both techniques, but the differences were larger when the ssSEM dataset and dissector method were used. The measurement of symmetric synapse percentage also resulted in systematically higher values in the FIB-SEM datasets compared with the ssSEM datasets. However, both methods revealed significantly higher symmetric synapse percentages in the SHORT group compared to the other two groups, ISO and LONG. In summary, the two methods yielded almost the same results when the comparisons were made between groups. However, when the absolute values of the synapse density or percentage were determined in a

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given HVC sample, the results obtained with the FIB-SEM dataset (density, see Table S. 5; percentage, see Table 2. 11) were systematically higher than those obtained with the ssSEM datasets (density, see Table 2. 3 and Table 2. 6; percentage, see Table S. 2).

These systematic differences in the results could have been due to the sampling population, datasets, and/or methods. These factors will be discussed in detail in the following paragraphs.

For the sampling population, the two methods sampled from different geometries forms of the tissue and different locations within HVC. The FIB-SEM dataset sampled from a cubic-shaped tissue block with an edge length of 7 – 8 µm that was located near the center of HVC (Figure 2. 4). In contrast, the ssSEM dataset was sampled from consecutive serial sections that formed a rectangle-shaped tissue block with a larger 2D area and very thin medial-lateral edge (~ 80 µm × 80 µm 2D area × 140 nm thickness), which was also located near the center of HVC (Figure 2.

5). Given that both of the measurements made in the same bird were similar in the sample volume (see Table S. 2), and that both were performed on the same HVC area in the same brain section, the differences in the measurement results probably did not result from inhomogeneities in the HVC tissue. HVC in the zebra finch was suggested to be organized in general homogeneous (Foster and Bottjer 1998), with recently reported rostrocaudal (Stauffer et al. 2012) and mediolateral (Elliott et al.

2017) organizations. Therefore I choose to always sampling close to the center in both rostrocaudal, mediolateral, as well as ventrodorsal axes of HVC, instead of randomized sampling location, to minimize the bias from potential inhomogeneity along these axes.

Alternatively, the different geometric forms of the tissue could have contributed to some of the deviations in the measurement results. The ssSEM datasets were sampled from a larger area in the parasagittal plane of HVC, and large Z steps with section thickness of approximately 70 nm, while the FIB-SEM datasets were sampled from a smaller para-sagittal area, with fine Z steps with image slice thickness of 10 nm. As a result, the ssSEM datasets might have been biased due to missing synapses, such as small synapses with size less than 70 nm that were parallel to the imaging plane, in the middle of two sections, and the FIB-SEM datasets might have been biased more by the sampling location, such as sampling close to synapse-free objects like blood vessels or cell bodies. As described in Methods section 2.2.4, these types of bias in the sampling population were expected.

During the imaging setup, attempts were made to imaging close to the center of HVC and avoid synapse-free objects. Nevertheless the HVC local neuronal population and circuits are suggested to be arranged in clusters spanning approximately 100 µm (Kosche, Vallentin, and Long 2015; Markowitz et al. 2015;

Wild et al. 2005), which rendered my ssSEM samplings more representative for HVC, compared to the FIB-SEM samplings.

In order to compare the methods for stereological accuracy, the two methods have been evaluated in previous studies, and as well in this study (Supplementary Method

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and Data sections S.4 and S.6). The FIB-SEM datasets provided excellent isotropy and sampling precision of a local tissue volume, and it rarely missed any synapses in the sampled volume. Therefore, measurements that were close to the actual number of synapses were obtained with the FIB-SEM datasets, which have been shown to provide very accurate estimations of synapse densities and synapse subtype percentages in sampled volumes (Merchan-Pérez 2009). However, the use of the dissector methods on the serial section datasets did not count every synapse in the sampled volume. The accuracy of the dissector method depends on the separation distance between the reference and look-up sections (Delaloye et al. 2009), and the number of dissectors used (Merchan-Pérez 2009). The dissector method provide reliable estimates with error less than 6% of neuron number in rat lumbar dorsal root ganglia when the separation distances between consecutive dissectors are not larger than 60 µm. When the separation distance increase to 100 µm, the error increases rapidly to 27% most probably from missing neurons fully contained within the dissector (Delaloye et al. 2009). Simulated dissector counting of synapses in the mice motor cortex revealed the estimated synapse density converged on the true value when more than 100 dissectors were summarized (Merchan-Pérez 2009). For the dissector counting performed in this study, I always summarize around 100 dissectors (see Table 2. 3 and Table 3. 5). Moreover I estimated the size of the HVC synapses (Results sections 2.3.6 and 2.3.7), and the average length (as the Feret diameter) of both asymmetric and symmetric synapses in HVC were around 200 nm (see Table 2. 21), which was much larger than the dissector separation distance of 140 nm. In addition I left an intermediate section in the middle of the dissector (see Figure 2. 5) so that synapses no smaller than 70 nm could still be detected. However smaller synapses or flat-shaped synapses could still fully contained within 70 nm length. In this case, the synapse might be missed from the dissector counting. This could explain why the dissector data resulted in lower density estimations compared to the estimations made with the FIB-SEM datasets in the results obtained in the study. In addition, symmetric synapses are generally smaller than asymmetric synapses (Results section 2.3.6) and have thinner synaptic clefts that range approximately from 20 to 40 nm (Figure 2. 6). These observations suggest that when using the same dissector to quantify the number of two categories of objects that differed in mean size, the counting results could underestimate more the number of the smaller objects since it systematically missed more smaller objects that fully contained within the dissectors. My dissector counting thus could have systematically missed more symmetric synapses than asymmetric synapses and therefore resulted in lower estimations of the percentage of symmetric synapses, as was observed in the results (see Table S. 2).

Nevertheless, both methods resulted in data that produced the same statistical test results on the differences among groups. Therefore, the findings of significantly higher percentage of symmetric synapses in HVC in the SHORT group were confirmed with these repeated measurements. Both methods have also been validated in previous studies of neural ultrastructure (DeFelipe 1999; Delaloye et al.

2009). If the goal of a study is to compare a variable among groups and the actual value does not need to be known, then either method can be selected.

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To briefly conclude, the FIB-SEM dataset with subcube sampling units provided more accurate measurements of the local symmetric synapse percentage in a smaller area (approximately 8 × 8 µmin the parasagittal plane). While the ssSEM dataset with dissector sampling units underestimated the true percentage value, it provided more representative estimations in a larger area (approximately 80× 80 µm² in the (Experiment II: Experimental design section 3.1), the ssSEM datasets and dissector methods were used to estimate the percentage of symmetric synapse in HVC (Experiment II: Method section 3.2.6).