The formation and consolidation of declarative memories require the interaction of rich networks that encompass multiple brain areas. Among them, the entorhinal–hippocampal connectivity is a key element (Buzsáki and Moser, 2013). In primates, the entorhinal cortex (EC) is a brain region located in the anterior part of the medial temporal lobe, close to the hippocampal formation and the perirhinal (PRC) and parahippocampal (PHC) cortices (Insausti et al., 2017). The EC acts as a major sensory interface, mediating the flow of information between the hippocampus and the neocortex (Eichenbaum et al., 2012; Insausti and Amaral, 2008; Schultz et al., 2015). In addition, several studies have linked major neurodegenerative disorders, such as Alzheimer’s disease, to alterations in the EC (Braak and Braak, 1992).

The EC is a complex brain region in terms of cytoarchitecture and connectivity. In human and non-human primates, it has been traditionally divided into several subdivisions, based on cytoarchitectonic features (Insausti et al., 2017). An alternative organization, which follows the connectivity patterns between the EC, the hippocampus, and parahippocampal regions, divides this area into two functionally defined parts: lateral and medial EC (LEC and MEC, respectively; Maass et al., 2015). Briefly, LEC is highly connected to the PRC, providing the hippocampus with information about the content of an experience. As for MEC, it receives projections from the PHC (or the post-rhinal cortex in rodents) and provides the hippocampus with the spatial context of an experience (Knierim et al., 2014; Reagh and Yassa, 2014). This connectivity-based division was first described in rodents and later in both human and non-human primates (Maass et al., 2015). The primate LEC comprises the rostrolateral region of the EC, whereas MEC extends through the caudomedial axis (Maass et al., 2015; Witter and Amaral, 2021).

The connectivity between EC represents the major cortical afferent source of the hippocampus and has been studied in great detail (Insausti and Amaral, 2008; Witter and Amaral, 1991). EC upper layers (II and III) give rise to the perforant pathway (Insausti and Amaral, 2008; Insausti and Amaral, 2012; Nilssen et al., 2019). In general, the classic trisynaptic circuit EC layer II → DG → CA3 → CA1 seems to be related to the acquisition of new memories, whereas the direct connection of EC layer III neurons with CA1 (and subiculum; S) (monosynaptic pathway) is thought to contribute to the strength of previously established memories (Cohen and Squire, 1980). Deep layers (V and VI) of the EC represent the main target of return connections from the hippocampus, which arise mainly from the CA1 and S (Insausti and Amaral, 2008; Saunders and Rosene, 1988). These deeply located neurons of the EC project to subcortical and cortical regions such as the amygdala, nucleus accumbens, the temporal pole and the superior temporal sulcus, as well as to frontal areas (Insausti and Amaral, 2008; Muñoz and Insausti, 2005; Ohara et al., 2021). Recent studies have proposed that these deep layers of the EC not only represent simply a relay station between the hippocampus and other telencephalic regions, but also act as a crucial hub for information processing in the EC—hippocampal connectivity. For example, it has been proposed that deep layers of the EC integrate diverse inputs, on a multistep circuit between the hippocampus, the cortex and the superficial EC layers, which may be essential for episodic and spatial memory (reviewed in Gerlei et al., 2021).

Most of the connectivity-based studies mentioned have been performed in experimental animals, mainly in rodents and monkeys. Although connectivity appears to be similar in all species studied, there are also species-specific variations. For this reason, we can only assume that the general pattern of connections of the human hippocampal formation is similar to that described in experimental animals, particularly non-human primates, but it is possible that there are significant differences. For example, in the monkey, only the most rostral part of the hippocampus is connected by commissural fibers from the subiculum to the contralateral EC (Insausti and Amaral, 2012). In humans, commissural connections seem to be even more reduced (Insausti and Amaral, 2012). Recently, Ben-Simon et al., 2022 reported that excitatory neurons in layer VIb of the mouse EC project to all subregions of the hippocampal formation and receive input from the CA1, thalamus and claustrum.

Connectivity in the brain is mostly based on point-to-point chemical synapses (DeFelipe, 2015). Therefore, the synaptic properties of a region are a crucial aspect to be described, both in terms of connectivity and functionality. We can distinguish two major goals in studying synapses. First, studying connections between identified neurons, which consists of identifying the specific presynaptic and postsynaptic neurons involved in each synapse. Second, studying synaptic features in general, which includes quantifying synaptic density, identifying different types and sizes of synapses, and determining their postsynaptic targets (dendrites, somas, or other structures). Assessing the synaptic density in a particular brain region is crucial for understanding both connectivity and functionality. In particular, both the synaptic density (number of synapses per volume) and excitatory/inhibitory proportions are meaningful parameters to describe the synaptic connections of a particular brain region, which can be considered useful for understanding the synaptic circuits of any brain region.

In the human EC, synaptic organization remains largely unknown. There are several approaches available to study synaptic connectivity at the ultrastructural level in the mammalian brain, with the gold standard being volume electron microscopy. Some scientists consider that the best strategy is to study a relatively large volume of tissue in a given region using serial block-face electron microscopy to obtain saturated or dense reconstructions, even if only one individual can be examined using this approach due to the technical difficulties associated with this technology (e.g., Karimi et al., 2020; Kasthuri et al., 2015; Motta et al., 2019; Winding et al., 2023; Shapson-Coe et al., 2024). However, we believe that volume electron microscopy can be exploited much more efficaciously if multiple samples of smaller volumes of tissue of the brain region of interest are examined in several individuals using focused ion beam (FIB)/SEM. Multiple sampling using volume electron microscopy is especially important when examining human brain tissue, not only because of the large size of the brain and extension of particular brain regions, but also because interindividual variability is clearly more pronounced than in animal models. To illustrate the magnitude of the technical challenges involved, it is useful to consider the reconstruction of a single fragment of the human temporal cortex from layer I to layer VI, with dimensions of only 1.7 mm × 2.1 mm × 28.3 microns (0.1 mm³), which represents 0.41 petabytes of data (Loomba et al., 2022). If the reconstructed volume is increased to 1 mm³ (3 mm × 2 mm × 170 µm), the data expand to 1.4 petabytes (Shapson-Coe et al., 2024). Nevertheless, the volume of the EC is relatively large and varies with age, showing differences between the left and right hemispheres ranging approximately from 730 to 1100 mm³, depending on age and hemisphere (Wang et al., 2019). Thus, in order to explore the synaptic characteristics present in a given region, our approach is to determine the range of variability by sampling relatively small volumes of the region of interest multiple times and in several individuals. More specifically, we used this technology to obtain data on the density and spatial distribution of different types of synapses (excitatory and inhibitory), as well as to determine the size and shape of the synaptic junctions and the postsynaptic targets of the axon terminals.

Our previous studies of the EC in autopsy tissue have analyzed the neuropil of layers II and III using FIB/SEM (Domínguez-Álvaro et al., 2021a). However, in these studies, we did not distinguish between the neuropil of the cell island and transition zones that characterize layer II (Insausti et al., 2017; Kobro-Flatmoen and Witter, 2019), nor were the rest of the cortical layers and subdivisions analyzed. In the present article, we further examined the ultrastructure of the normal human MEC by analyzing brain tissue obtained at autopsy with FIB/SEM. The purpose was to perform a volume electron microscopy study (3D analysis) in the neuropil of the MEC, including all layers and subdivisions, namely I, II (cell islands and transition zones), III, V (a/b and c), and VI to define the ultrastructural characteristics of synapses. This dataset is critical not only for understanding connectivity, but also from a functional perspective, and it is currently virtually unavailable for the human brain. This kind of analysis has already yielded high-quality data on synaptic ultrastructural properties from other regions of the human cerebral cortex obtained at autopsy (e.g., Cano-Astorga et al., 2021; Domínguez-Álvaro et al., 2021a; Montero-Crespo et al., 2020). Thus, the data presented here aim to represent a step toward a better understanding of the networks and connectivity characteristics of the human cerebral cortex.

In the present study, we used coronal sections of the MEC at a caudal level—following the subarea delimitation proposed in Insausti et al., 2017—to analyze layers I, II, III, IV, V, and VI of the EC. The layers were individually delimited based on cytoarchitectural characteristics, identified by two different staining techniques (i.e., Nissl and toluidine blue on semithin sections), as well as by direct visualization using FIB/SEM. Layer I showed a uniform, thick band with very few neurons present. Layer II presented clear islands occupied by large, stellate cells and modified pyramidal neurons, and transition zones with very few neurons between islands (Insausti et al., 2017; Kobro-Flatmoen and Witter, 2019). This clear separation enabled us to study both areas separately (referred to here as ‘layer II-is’ for the area occupied by the islands, and ‘layer II-ni’ for the neuropil between islands). Layer III comprised a homogeneous population of medium-sized pyramidal neurons, radially organized (Insausti et al., 2017). Layer V, in turn, was characterized by the presence of large pyramidal neurons homogeneously distributed throughout the layer (Insausti et al., 2017; Insausti and Amaral, 2012). This layer is traditionally divided into three subdivisions: layers Va, Vb, and Vc. However, at the level analyzed in the present study, sublayers Va and Vb are often indistinguishable (Insausti et al., 2017). Therefore, here we considered both as a single layer (for the sake of clarity, we will refer to it as Va/b). Layer Vc consisted of a pronounced band formed by a few neurons and a dense plexus of fibers. In the analyzed sections, this sublayer became apparent and it could be mistaken for the caudal extension of the lamina dissecans (or layer IV) (Insausti et al., 2017; Insausti and Amaral, 2012). Finally, layer VI presented a heterogeneous population of neurons, forming a thick layer that exhibits an abrupt border with the underlying white matter (Insausti et al., 2017; Insausti and Amaral, 2012). Given these evident cytoarchitectural differences, data from all layers included in the present study were displayed and analyzed separately.

Neuropil occupies most of the grey matter volume

Estimation of the volume fraction (Vv) occupied by different cortical elements (i.e., neuropil, cells bodies—neuronal, glial, and undetermined somata—and blood vessels) was performed in all MEC layers studied, applying the Cavalieri principle (Gundersen et al., 1988). The neuropil constituted the main element in all layers, with the minimum proportion found in layer III (86%) and the maximum in layer I (96%). (Figure 1; Supplementary file 1a and b). Cell bodies occupied a variable range, with the lowest Vv in layer I (1%) and the highest in layers II-is, III, and Va/b (9% in each layer) (Figure 1; Supplementary file 1a and b). The Vv of blood vessels ranged from 3% in layer I to 6% in layer III—and the rest of the layers presented values within this range (Figure 1; Supplementary file 1a and b).

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AS are larger than SS

The study of the synaptic size was performed by analyzing the area of the synaptic apposition surface (SAS) of each synapse identified and 3D reconstructed in all stacks of images (Figure 2). Considering all layers, the mean SAS areas of AS and SS were 119,242 nm² and 71,384 nm², respectively (Table 1; Supplementary file 1d). Data regarding AS and SS area per layer are shown in Table 1 and Supplementary file 1d. Regardless of the layer analyzed, AS presented significantly larger SAS areas than SS (Mann–Whitney [MW], p<0.0001 in layers I, II-is, II-ni, III; p<0.01 in layer Va/b and Vc; p<0.05 in layer VI; p<0.0001 considering all layers; Figure 3).

Figure 2

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The analyses of the mean SAS area of AS were also performed to compare the analyzed cortical layers (Table 1; Supplementary file 1d). The SAS area of AS showed differences between layers (KW, p<0.0001). We did observe that layer VI had smaller AS (99,489 nm²) than layer III and Vab, which showed the largest AS (130,268 nm² and 136,111 nm²; Dunn’s test, p<0.05; Figure 3). Additionally, layer Va/b showed a larger mean SAS than layer I (105,906 mm²; Dunn’s test, p<0.01). Moreover, these differences were also found when comparing the probability density functions between these two layers, indicating that smaller SAS areas of AS were more frequent in layer VI (Kolmogorov–Smirnov [KS], p<0.0001; Figure 3). The size of SS was also compared between MEC layers. Layer I had the lowest mean values (53,367 nm²), whereas layer Vc showed the largest mean sizes (87,377 nm²; Dunn’s test; p<0.05; Table 1).

In order to study the frequency distribution of the SAS area between AS and SS for each individual layer, we performed probabilistic density functions, revealing that smaller synapses were more frequent in SS than in AS, in all layers studied (KS, p<0.0001 in layers I, II-is, II-ni, III, Va/b and Vc; p<0.05 in layer VI; p<0.0001 considering all layers; Figure 3).

Macular small synapses are the most frequent regardless of the layer

To analyze the shape of the synaptic contacts, we classified each identified synapse into one of four categories: macular (with a flat, disk-shaped PSD), perforated (with one or more holes in the PSD), horseshoe (with an indentation in the perimeter of the PSD), or fragmented (with two or more physically discontinuous PSDs). For the sake of clarity, the last three categories (perforated, horseshoe, and fragmented) were considered complex-shaped synapses. The percentages regarding macular and complex synaptic shapes for AS and SS are shown in Figure 4 and Supplementary file 1f (see also Supplementary file 1g for values for each individual case). The majority of both AS and SS presented a macular shape, regardless of the cortical layer. However, we found some significant differences in the distribution of these synaptic shapes between layers. Particularly, macular synapses (both AS and SS) were less frequent in layer VI (78 and 59%, respectively), whereas the highest values were found in layer II-is (χ², p<0.0001; Figure 4—figure supplement 1).

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The proportion of the synaptic type (AS and SS) on macular and complex synaptic shapes was also determined. Considering all layers, 95% of all macular synapses were AS and 5% were SS. In the case of complex synapses, 92% were AS, with the rest being SS. Slight variations in these percentages were found in the different layers (shown in Figure 4—figure supplement 2). No significant differences were found compared to the general distribution of AS:SS (χ², p>0.0001).

Most synapses are established on dendritic spines

Postsynaptic targets were identified and classified as dendritic spines (including both complete and incomplete spines, as detailed in 'Material and methods') or dendritic shafts (Figure 5 displays 3D reconstruction examples of dendritic segments in which synapses were established). In addition, when the postsynaptic element was identified as a dendritic shaft, it was classified as ‘spiny’ or ‘aspiny’. Considering all layers, 59.3% of the total synapses were AS established on dendritic spine heads, 34.3% were AS on dendritic shafts (including spiny and aspiny shafts), 5.1% were SS on dendritic shafts (including spiny and aspiny shafts), 0.7% were SS on dendritic spine heads, 0.5% were AS established on dendritic spine necks, and 0.1% were SS on dendritic spine necks (Figure 6, see also Supplementary file 1j). When the different layers were compared, layer VI presented the highest proportion of AS established on dendritic spine heads (76.2%), whereas layer Va/b had the lowest value (52.9%, χ², p<0.0001; Figure 6; Supplementary file 1j).

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We also analyzed the proportion of AS and SS synapses separately, categorized by their location on dendritic spines (heads or necks) or dendritic shafts. The proportion of AS formed on the different postsynaptic targets greatly resembled the general distribution of synapses established on the postsynaptic targets described above, given the greater number of AS than SS. In all layers of the MEC, AS were mostly established on dendritic spine heads (63%), followed by AS established on dendritic shafts (36.5%; 17.6% on spiny shafts and 18.9% on aspiny shafts) and, lastly, we found a small percentage of AS formed on dendritic spine necks (0.5%; Supplementary file 1k). Our analysis revealed significant differences between MEC layers regarding the proportions of AS synapses established on dendritic spine heads. Layer VI exhibited the highest proportion of AS on spine heads (79.6%), whereas layer Va/b had the lowest proportion (54.9%; χ², p<0.0001). These findings are illustrated in Figure 6 and Supplementary file 1k.

The distribution of SS on different postsynaptic targets differed significantly from that observed for AS. The majority of SS were found on dendritic shafts (85.7%), with 47.5% on shafts containing dendritic protrusions (spiny shafts) and 38.2% on smooth dendritic shafts (aspiny shafts). A smaller proportion of SS were established on dendritic spine heads (12.1%) and spine necks (2.2%). Due to the low number of SS identified as axospinous in each layer (ranging from 3 in layer Va/b to 19 in layer Vc), statistical comparisons of this proportion between layers were not performed. However, we observed some variations between layers. Layer Va/b had the highest proportion of SS on dendritic shafts (92.3%), whereas layer Vc exhibited the lowest percentage of SS formed on shafts (77%; Figure 6; Supplementary file 1k).

Considering all types of synapses established on dendritic spines, the proportion of AS:SS was 99:1, whereas the proportion of AS:SS established on dendritic shafts was 87:13. The overall ratio of AS:SS was 96:4, which indicates a ‘preference’ of AS and SS for a particular postsynaptic destiny: AS are most frequently found on dendritic spine heads, and SS are predominantly established on dendritic shafts (χ², p<0.0001). These results were consistent across the different layers (Figure 6—figure supplement 1).

Additionally, we were able to detect dendritic spines that contained more than one synapse (i.e., multisynaptic spines). The vast majority of dendritic spines (96%) contained only one AS, followed by a small pool of spines that showed different combinations regarding the type (AS or SS), number, and localization (head or neck) of synapses (Figure 6—figure supplement 2). There were no significant differences in the proportion of multisynaptic spines between the different layers (χ², p>0.0001). Nevertheless, interestingly, the proportion of spines presenting one AS and one SS (0.73%) was higher than the percentage of dendritic spines containing a single SS (0.50%)——and this was consistent in most of the layers (Figure 6—figure supplement 2).

Complex-shaped synapses are more frequently found on dendritic spines

Finally, we examined whether macular and complex synapses have a particular distribution on different postsynaptic targets. The general distribution of AS established on dendritic spine heads and dendritic shafts was 63:37, considering all layers. This proportion ranged from 80:20 in layer VI to 55:45 in layer Va/b. When considering macular AS, 61% of them were established on dendritic spine heads, and 39% were formed on shafts (Figure 7). Complex-shaped AS were even more predominantly established on dendritic spine heads (75%, Figure 7); in fact, this proportion was significantly different from the general distribution (χ², p<0.0001). All layers exhibited similar tendencies (Figure 7—figure supplements 1 and 2), although layer VI exhibited both the highest proportion of macular and complex-shaped synapses established on dendritic spines (78% and 85%, respectively).

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To further study this, we carried out frequency distribution analyses of the SAS from the macular and complex synapses established on dendritic spines and dendritic shafts. We found that smaller macular synapses were more frequent on spine heads than on dendritic shafts (Figure 7; KS, p<0.0001), whereas smaller complex-shaped synapses were more frequent on dendritic shafts than on dendritic spine heads (Figure 7; KS, p<0.0001). All layers displayed similar tendencies (Figure 7—figure supplements 1 and 2). There were not enough SS established on dendritic spines to perform a robust analysis.

In the present study, we have performed the first detailed description of the synapses of layers I, II (both between and within the cell islands), III, Va/b, Vc, and VI from the human MEC using FIB/SEM technology. The main findings indicate that the MEC exhibits a distinct set of synaptic features that differentiates this region from other human cortical areas. Additionally, our results reveal common patterns in the synaptic structure across mammalian brains, such as the proportion of synaptic types and shapes. Furthermore, ultrastructural synaptic characteristics within the MEC are predominantly similar, although layers I and VI exhibit several synaptic characteristics that are distinct from those in the other layers.

Ultrastructural characteristics of synapses are similar across layers of the MEC

Similarity of the synaptic characteristics of the MEC may seem surprising given its cytoarchitectonic and innervation complexity. Indeed, MEC layers contain a variety of neuronal classes heterogeneously distributed across layers, as extensively reviewed in Kobro-Flatmoen and Witter, 2019. All these neurons are highly innervated, receiving information from both local and intercortical connections. Figure 8 summarizes the extrinsic and intrinsic circuits formed in the different layers of the MEC. Unfortunately, all these connectivity data come from experimental animals, and information from the human brain is very scarce in this regard. Nevertheless, Figure 8 illustrates clear differences in the connectivity pattern between the different layers, where superficial neurons mainly receive information from other brain areas (such as the PRC and PHC) to be transmitted to the hippocampus, whereas deep-located cells are the recipient of the hippocampal return connections, giving rise to the cortical output of the EC (Insausti and Amaral, 2008; Insausti and Amaral, 2012; Melzer et al., 2012; Muñoz and Insausti, 2005; Nilssen et al., 2019; Ohara et al., 2021; Ohara et al., 2023; Sürmeli et al., 2016; Vandrey et al., 2022). In addition, the MEC shows profuse intracortical connectivity, with (i) deep-located neurons sending projections to upper layers (Chrobak and Amaral, 2007; Ohara et al., 2021; Sürmeli et al., 2016) and (ii) both excitatory and inhibitory intralayer innervation (Nilssen et al., 2019; Rozov et al., 2020; Winterer et al., 2017).

Figure 8

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The analysis of MEC layer II is of particular interest. This layer is characterized by the presence of reelin-positive stellate cells and calbindin-positive pyramidal neurons clustered together to form ‘cell islands’ with gaps between them that contain almost no neurons (Insausti et al., 2017; Kobro-Flatmoen and Witter, 2019). In the present study, we were able to selectively analyze the neuropil of both zones independently. Our data showed no differences in any parameter studied. In fact, these results were very similar to those described in one of our previous studies performed in the same layer on different autopsy samples, but with no distinction made between islands and non-island areas (Domínguez-Álvaro et al., 2021a). For example, in this study, a density of 0.40 synapses/μm³ was found in EC layer II, which is very close to the 0.42 and 0.44 synapses/μm³ found in the present study in layer II, in the island and non-island regions, respectively.

Conversely, layer VI stood out in many of the synaptic parameters analyzed. Although the synaptic density in this layer was comparable to that of other layers, overall it had the smallest synapses and both the smallest macular and complex-shaped AS. It also had the lowest proportion of macular synapses (78%) and the highest proportion of synapses established on dendritic spine heads (76%). In humans, layer VI contains a variety of cell types, ranging from small- to medium-sized bipolar and multipolar calbindin-positive cells, large pyramidal calretinin-positive neurons, and multipolar parvalbumin interneurons, among others (Kobro-Flatmoen and Witter, 2019 and references wherein). Additionally, this layer receives projections from numerous regions, including the hippocampus, the medial frontal and orbitofrontal cortex, the thalamus, and the claustrum (see Figure 8). The synaptic peculiarities described in the present study may have a critical impact on how this layer processes the information it receives.

Despite the complexity of the MEC in terms of its cytoarchitecture, connectivity, and function, it is remarkable that the ultrastructural synaptic characteristics remain rather similar across layers. One possible explanation is that several of the parameters investigated in this study (e.g., synaptic density, proportion of AS:SS) do not depend on the cytoarchitecture or connectivity of the region, at least in the case of the MEC neuropil. Very few papers have analyzed the synaptic characteristics at the ultrastructural level of different layers in the same human brain region. However, Montero-Crespo et al., 2020 found that the ultrastructural synaptic characteristics of the human hippocampus may be influenced by the innervation that the different layers receive. The ultrastructural synaptic characteristics in the layers receiving CA3 Schaffer collaterals (e.g., stratum pyramidale and stratum radiatum) differ from those in stratum lacunosum moleculare, which mainly receives information from the EC. Similarly, Cano-Astorga et al., 2023—when analyzing the ultrastructural synaptic characteristics of layer III in different cingulate and temporopolar cortices—described remarkable differences in synaptic size and density between the ventral and dorsal part of BA38, which may also be correlated with the differential connectivity pattern exhibited by this brain area.

Finally, another crucial aspect is the interindividual variability of human samples. There are numerous studies describing interindividual variability in the human cerebral cortex, both in terms of structure and function (e.g., DeFelipe, 2015). However, in the present study, the synaptic parameters analyzed showed relatively little variability (see Supplementary file 1b,d,g,i,k, and m, which provide data from all MEC layers for each individual case). Indeed, the proportion of AS:SS showed remarkable uniformity across individuals in all layers (Table 1). This apparent similarity was further confirmed through the examination of the variability between cases (Table 2, Figure 1—figure supplement 2, Figure 3—figure supplement 1, Figure 4—figure supplements 4 and 5; Supplementary file 3) and stacks of images (Supplementary file 1n), supporting the regularity of the data in all layers of the MEC. Furthermore, in all individuals, layers, and stack of images, SS had significantly smaller sizes and were in much lower numbers than AS. This is in line with the fact that, as already discussed, synaptic characteristics of SS are similar in the different cerebral regions, layers, and animals examined so far (e.g., Cano-Astorga et al., 2023; Cano-Astorga et al., 2024a).

Overall, the present data point to a set of highly conserved synaptic characteristics in all layers of the MEC, while some data point to a laminar specificity. Future studies on human synaptic nanoconnectivity of different layers in additional brain regions could confirm whether there is a commonly shared trend across the human cortex.

Most data are available in the main text or the supplementary files. Raw data used for analysis are provided in Supplementary file 4. Stack of images are available at BossDB. The datasets used and analyzed during the current study are published in the EBRAINS Knowledge Graph: https://doi.org/10.25493/3GMJ-FEZ, https://doi.org/10.25493/QGH8-MTS, https://doi.org/10.25493/CSB1-Q07.

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Author details

1. Sergio Plaza-Alonso

   1. Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
   2. Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain
   3. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Madrid, Spain

   Contribution

   Conceptualization, Formal analysis, Validation, Investigation, Visualization, Writing – original draft, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2484-5791

2. Nicolas Cano-Astorga

   1. Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
   2. Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain
   3. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Madrid, Spain

   Contribution

   Validation, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-3724-0481

3. Javier DeFelipe

   1. Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
   2. Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain
   3. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Madrid, Spain

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Validation, Visualization, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5484-0660

4. Lidia Alonso-Nanclares

   1. Laboratorio Cajal de Circuitos Corticales, Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Madrid, Spain
   2. Instituto Cajal, Consejo Superior de Investigaciones Científicas (CSIC), Madrid, Spain
   3. Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), ISCIII, Madrid, Spain

   Contribution

   Conceptualization, Data curation, Supervision, Validation, Investigation, Visualization, Methodology, Project administration, Writing – review and editing

   For correspondence

   aidil@cajal.csic.es

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-2649-7097

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