The brain allows us to perceive and interact with our environment and to create and recall memories about our day-to-day lives. A sea-horse shaped structure in the brain, called the hippocampus, is critical for translating our perceptions into memories, and it does so in coordination with other brain regions. For example, different regions of the cerebral cortex (the outer layer of the brain) support different aspects of cognition, and pathways of information flow between the cerebral cortex and hippocampus underpin the healthy functioning of memory.

Decades of research conducted into the brains of non-human primates show that specific regions of the cerebral cortex anatomically connect with different parts of the hippocampus to support this information flow. These insights form the foundation for existing theoretical models of how networks of neurons in the hippocampus and the cerebral cortex are connected. However, the human cerebral cortex has greatly expanded during our evolution, meaning that patterns of connectivity in the human brain may diverge from those in the brains of non-human primates.

Deciphering human brain circuits in greater detail is crucial if we are to gain a better understanding of the structure and operation of the healthy human brain. However, obtaining comprehensive maps of anatomical connections between the hippocampus and cerebral cortex has been hampered by technical limitations. For example, magnetic resonance imaging (MRI), an approach that can be used to study the living human brain, suffers from insufficient image resolution.

To overcome these issues, Dalton et al. used an imaging technique called diffusion weighted imaging which is used to study white matter pathways in the brain. They developed a tailored approach to create high-resolution maps showing how the hippocampus anatomically connects with the cerebral cortex in the healthy human brain. Dalton et al. produced detailed maps illustrating which areas of the cerebral cortex have high anatomical connectivity with the hippocampus and how different parts of the hippocampus preferentially connect to different neural circuits in the cortex. For example, the experiments demonstrate that highly connected areas in a cortical region called the temporal cortex connect to very specific, circumscribed regions within the hippocampus.

These findings suggest that the hippocampus may consist of different neural circuits, each preferentially linked to defined areas of the cortex which are, in turn, associated with specific aspects of cognition. These observations further our knowledge of hippocampal-dependant memory circuits in the human brain and provide a foundation for the study of memory decline in aging and neurodegenerative diseases.

There is long-standing agreement that the hippocampus is essential for supporting episodic long-term memory (Scoville and Milner, 1957) and facilitating spatial navigation (Maguire et al., 2006; O’Keefe and Nadel, 1978). The hippocampus has more recently been linked with other roles including imagination of fictitious and future experiences (Hassabis et al., 2007; Addis et al., 2007), visuospatial mental imagery (Dalton et al., 2018), visual perception (McCormick et al., 2021; Lee et al., 2012), and decision-making (McCormick et al., 2016). It is a complex structure containing multiple subregions (referred to as subfields) including the dentate gyrus (DG), cornu ammonis (CA) 4-1, subiculum, presubiculum, and parasubiculum. Accumulating evidence suggests that different hippocampal subfields are preferentially recruited during different cognitive functions (Dalton et al., 2018; Dimsdale-Zucker et al., 2018). Functional differences are also present along the anterior–posterior axis of the hippocampus (Poppenk et al., 2013; Plachti et al., 2019; Brunec et al., 2018; Przeździk et al., 2019; Poppenk, 2020; Strange et al., 2014) and its subfields (Dalton et al., 2019b; Dalton et al., 2019a). Despite recent advances in understanding functional differentiation within the hippocampus, much less is known about the neuroanatomical underpinnings of these functional differences in the human brain. A more detailed understanding of anatomical connectivity along the anterior–posterior axis of the human hippocampus is needed to better understand and interpret these functional differences.

Much of our knowledge regarding the anatomical connectivity of the human hippocampus is inferred from the results of tract-tracing studies in rodent and non-human primate brains. While this information has been fundamental to inform theoretical models of hippocampal-dependent memory function, recent investigations have highlighted potential differences between connectivity of the human and non-human primate hippocampus (Zeineh et al., 2017). This suggests that, in addition to evolutionarily conserved patterns of hippocampal connectivity, human and non-human primates may also have unique patterns of connectivity. More detailed characterisations of human hippocampal connectivity are, therefore, essential to advance our understanding of the neural architecture that underpins hippocampal-dependent memory and cognition in the human brain.

Tract-tracing studies in rodents and non-human primates have revealed that the hippocampus is highly connected with multiple cortical areas. It is well established that the entorhinal cortex (EC) is the primary interface between the hippocampus and multiple brain regions (Garcia and Buffalo, 2020; Witter et al., 2017). Other medial temporal lobe (MTL) structures including the perirhinal (PeEc) and posterior parahippocampal (PHC) cortices also have direct anatomical connections with the hippocampus (Aggleton and Christiansen, 2015; Yukie, 2000; Insausti and Muñoz, 2001; Agster and Burwell, 2013) albeit to a lesser degree. However, direct cortico-hippocampal pathways are not confined to MTL cortices. Anterograde and retrograde labelling studies in non-human primates have revealed direct and reciprocal connections between the hippocampus and multiple cortical areas in temporal (Yukie, 2000; Van Hoesen et al., 1979), parietal (Rockland and Van Hoesen, 1999; Ding et al., 2000), and frontal (Goldman-Rakic et al., 1984; Barbas and Blatt, 1995) lobes. These detailed investigations show that specific cortical areas preferentially connect with circumscribed portions along the anterior–posterior axis of hippocampal subfields. For example, retrograde labelling studies in the macaque reveal that the retrosplenial cortex (RSC) in the parietal lobe has direct connectivity with posterior portions of the presubiculum while area TE in the inferior temporal lobe displays preferential connectivity with posterior portions of the CA1/subiculum transition area (Insausti and Muñoz, 2001). While patterns of cortico-hippocampal connectivity such as these have been observed in the non-human primate brain, we know less about these patterns in the human brain. It is important to note that nomenclature relating to the long axis of the hippocampus differs between the human, non-human primate, and rodent literature. The human MRI literature predominantly refers to the anterior–posterior axis of the hippocampus. This corresponds to the rostral–caudal axis in the non-human primate literature and the ventral–dorsal axis in the rodent literature. For clarity, we exclusively use the term anterior–posterior throughout this article.

Detailed examination of structural connectivity (SC) of the human hippocampus has been difficult to pursue mainly due to the technical difficulties inherent to probing hippocampal connectivity in vivo using MRI. Limitations in both image resolution and fibre-tracking methods have precluded our ability to probe cortico-hippocampal pathways in a sufficient level of detail. Some researchers have partially circumvented these constraints by investigating blocks of ex vivo MTL tissue using high-field MRI scanners (Augustinack et al., 2010; Coras et al., 2014; Beaujoin et al., 2018) or novel methods such as polarised light microscopy (Zeineh et al., 2017). While these studies have provided important insights relating to MTL–hippocampal pathways, we have less knowledge regarding how the human hippocampus connects with more distant cortical areas. Detailed characterisations of anatomical connectivity between the hippocampal long-axis and broader cortical networks are needed to better understand functional heterogeneity within the hippocampus (Olsen and Robin, 2020).

Of the extant in vivo MRI studies that have examined SC of the human hippocampus, several have focused on the connectivity between the hippocampus and specific cortical or subcortical areas (Dinkelacker et al., 2015; Wei et al., 2017; Arrigo et al., 2017; Rangaprakash et al., 2017; Edlow et al., 2016) with a primary focus on disease states. To our knowledge, only one study has attempted to characterise the broader hippocampal ‘connectome’ in the healthy human brain. Maller et al., 2019 used diffusion MRI (dMRI) data with multiple diffusion strengths and high angular resolution combined with track density imaging (TDI) to characterise SC between the whole hippocampus and cortical and subcortical brain regions. A quantitative analysis of streamline numbers (as a surrogate measure of connectivity) seeded from the whole hippocampus showed that the most highly connected brain regions were the temporal lobe followed by subcortical, occipital, frontal, and parietal regions. The primary focus of their study, however, was a description of six dominant white matter pathways that accounted for most cortical and subcortical streamlines connecting with the whole hippocampus. Together, these studies have provided an important glimpse into the complexity of human hippocampal SC but important gaps in our knowledge remain. Specifically, there has been no systematic examination of SC between the cortical mantle and the anterior–posterior axis of the human hippocampus, and we do not know where, within the hippocampus, specific cortical areas preferentially connect.

In typical fibre-tracking studies, we cannot reliably ascertain where streamlines would naturally terminate as they have been found to also display unrealistic terminations, such as in the middle of white matter or in cerebrospinal fluid (Calamante, 2019). While methods have been proposed to ensure more meaningful terminations (Smith et al., 2012), for example, with terminations forced at the grey matter–white matter interface (gmwmi), this approach is still not appropriate for characterising terminations within complex structures like the hippocampus. A key methodological advance of our approach was to remove portions of the gmwmi inferior to the hippocampus (where white matter fibres are known to enter/leave the hippocampus). This allowed streamlines to permeate the hippocampus in a biologically plausible manner. Importantly, we combined this with a tailored processing pipeline that allowed us to follow the course of streamlines within the hippocampus and identify their ‘natural’ termination points. These simple but effective methodological advances allowed us to map the spatial distribution of streamline ‘endpoints’ within the hippocampus. We further combined this approach with state-of-the-art tractography methods that incorporate anatomical information (Smith et al., 2012) and assign weights to each streamline (Smith et al., 2015a) to achieve quantitative connectivity results that more faithfully reflect the biological accuracy of the connection’s strength (Calamante, 2019).

In this study, we aimed to systematically examine the patterns of SC between cortical brain areas and the anterior–posterior axis of the human hippocampus. We combined dMRI data from the Human Connectome Project (HCP), quantitative fibre-tracking methods, and a processing pipeline specifically tailored to study hippocampal connectivity with three primary aims: (i) to quantitatively characterise SC between the cortical mantle (focused on non-MTL areas) and the whole hippocampus; (ii) to quantitatively characterise how SC varies between cortical areas and the head, body, and tail of the hippocampus; and (iii) to use TDI combined with ‘endpoint density mapping’ to quantitatively assess, visualise, and map the spatial distribution of streamline endpoints within the hippocampus associated with each cortical area.

Our results represent a major advance in (i) our ability to map the anatomical connectivity of the human hippocampus in vivo and (ii) our understanding of the neural architecture that underpins hippocampal-dependent memory systems in the human brain. We provide fundamental insights into how specific cortical areas preferentially connect along the anterior–posterior axis of the hippocampus and identify where streamlines associated with a given cortical area preferentially connect within the hippocampus. These detailed anatomical insights will help fine-tune network connectivity models and will have an impact on current theoretical models of human hippocampal memory function. (A preliminary version of this work was presented at the 30th Annual Meeting of the International Society for Magnetic Resonance in Medicine; 17 May 2021).

We first characterised SC between the whole hippocampus and all cortical areas of the HCP Multi-Modal Parcellation (HCPMMP) (Glasser et al., 2016). The primary focus of this study was SC between the hippocampus and non-MTL cortical areas. We therefore focus on cortical areas outside of the MTL (information relating to MTL cortices is presented in Appendix 1, Figure 1—figure supplement 1, Figure 2—figure supplement 1, and Supplementary files 1 and 2).

Which specific cortical areas most strongly connect with the whole hippocampus?

For brevity, we present results relating to the 20 cortical areas with the highest degree of SC with the whole hippocampus. Abbreviations for all cortical areas are defined in Supplementary file 3. The location of the most highly connected cortical areas are displayed in Figure 2—figure supplements 2–4. For the location of all other cortical areas, we refer the reader to the labelled Human Connectome Project Multi-modal Parcellation of Human Cerebral Cortex, which can be found at https://balsa.wustl.edu/sceneFile/Zvk4.

The hippocampus displayed the highest degree of SC with discrete cortical areas in temporopolar (areas TGv, TGd), inferolateral temporal (areas TF, TE2a, TE2p), medial parietal (areas RSC, ProS, POS1, POS2, DVT) dorsal and ventral stream visual (areas V3A, V6, FFC, VVC, VMV1, VMV2), and early visual (occipital) cortices (areas V1, V2, V3, V4). Results are summarised in Figure 1A, and Table 1 lists each cortical area and their associated strength of connectivity with the whole hippocampus. A full list of all cortical areas of the HCPMMP and their associated strengths of connectivity is provided in Supplementary file 1 .

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Table 1

Cortical area	Location of area	Whole hippocampus
		Mean SIFT2-weighted value(connectivity strength; n=10)	Standard error of mean	Percent of all cortical connections accounted for by area(percent of cortical connections excluding MTL areas)
TF	Lateral temporal cortex	7673	886	5.10 (10.61)
ProS	Medial parietal cortex (including posterior cingulate)	5483	784	3.64 (7.58)
V1	Early visual cortex (occipital)	5385	579	3.58 (7.45)
V2	Early visual cortex (occipital)	3840	462	2.55 (5.31)
POS1	Medial parietal cortex (including posterior cingulate)	3712	424	2.47 (5.13)
TGd	Temporal pole	3465	288	2.30 (4.79)
TGv	Temporal pole	3337	313	2.22 (4.61)
V3	Early visual cortex (occipital)	3079	450	2.05 (4.26)
TE2a	Lateral temporal cortex	2214	288	1.47 (3.06)
VMV2	Ventral stream visual cortex	2105	247	1.40 (2.91)
RSC	Medial parietal cortex (including posterior cingulate)	2063	121	1.37 (2.85)
VVC	Ventral stream visual cortex	1956	220	1.30 (2.71)
DVT	Medial parietal cortex (including posterior cingulate)	1939	335	1.29 (2.68)
POS2	Medial parietal cortex (including posterior cingulate)	1802	248	1.20 (2.49)
VMV1	Ventral stream visual cortex	1788	248	1.19 (2.47)
FFC	Ventral stream visual cortex	1670	172	1.11 (2.31)
V4	Early visual cortex (occipital)	1601	127	1.06 (2.21)
TE2p	Lateral temporal cortex	1288	198	0.86 (1.78)
V6	Dorsal stream visual cortex	1050	195	0.70 (1.45)
V3A	Dorsal stream visual cortex	1029	197	0.68 (1.42)

1. Column 1 displays cortical areas as defined by the Human Connectome Project Multi-Modal Parcellation (HCPMMP) scheme and ordered by strength of connectivity with the whole hippocampus (abbreviations for all cortical areas are defined in Supplementary file 3). Column 2 indicates the broader brain region within which each cortical area is located. Column 3 displays the mean SIFT2-weighted value (connectivity strength) associated with each brain area. Column 4 displays the standard error of the mean. Column 5 displays the percent of all cortical connections accounted for by each area. Values in brackets indicate the percent of cortical connections accounted for by each area when excluding medial temporal lobe (MTL) areas.

Do cortical areas display unique distributions of endpoint density within the hippocampus?

Our tractography pipeline was specifically tailored to allow streamlines to enter/leave the hippocampus and quantitatively measure the location and density of streamline endpoints within the hippocampus using TDI. We created endpoint density maps (EDMs) that allowed us to visualise the spatial distribution of hippocampal endpoint density associated with each cortical area (described in ‘Materials and methods’). While it is not feasible to present the results for all cortical areas of the HCPMMP, we describe results for the 20 most highly connected cortical areas described above. In relation to nomenclature, our use of the term ‘medial’ hippocampus refers to inferior portions of the hippocampus aligning with the distal subiculum, presubiculum, and parasubiculum. Our use of the term ‘lateral’ hippocampus refers to inferior portions of the hippocampus aligning with the proximal subiculum and CA1. In instances that we refer to portions of the hippocampus that align with the DG/CA4 or CA3/2, we state these regions explicitly by name.

The results of group-level analyses confirmed that specific cortical areas preferentially connect with different regions within the human hippocampus. For example, areas in the medial parietal cortex (ProS, POS1, RSC, DVT, POS2) displayed high endpoint density primarily in medial portions of the posterior hippocampus (see yellow arrows in Figure 2A for a representative example of endpoint densities associated with RSC; see Figure 2—figure supplement 2 for other areas). In contrast, areas in temporopolar and inferolateral temporal cortex (TF, TGd, TGv, TE2a, TE2p) displayed high endpoint density primarily along the lateral aspect of the anterior 2/3 of the hippocampus and in a circumscribed region of the anterior medial hippocampus (see blue and white arrows, respectively, in Figure 2B for a representative example of endpoint densities associated with TGv; see Figure 2—figure supplement 3 for other areas). Similar to areas in the medial parietal cortex, areas in the occipital cortices (V1–4, V6, V3a) displayed high endpoint density primarily in the posterior medial hippocampus and, to a lesser degree, in a circumscribed region of the anterior medial hippocampus (see yellow and white arrows, respectively, in Figure 2C for endpoint densities associated with V1; see Figure 2—figure supplement 4 for other areas).

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In parallel with these differences, specific regions within the hippocampus displayed high endpoint density for multiple cortical areas. For example, several medial parietal and occipital cortical areas displayed high endpoint density in the posterior medial hippocampus (yellow arrows in Figure 2—figure supplements 2 and 4). In contrast, several cortical areas in the temporal pole and inferolateral temporal lobe displayed high endpoint density in the anterior lateral hippocampus (blue arrows in Figure 2—figure supplement 3). Another cluster of high endpoint density in the anterior medial hippocampus (at the level of the uncal apex) was more broadly associated with specific areas in temporal, medial parietal, and occipital cortices (white arrows in Figure 2—figure supplements 2–4).

To further probe hippocampal endpoint density common to these cortical regions, we averaged the EDMs for anatomically related cortical areas. For example, we averaged the EDMs of the five most highly connected cortical areas in the temporal lobe (TF, TGd, TGv, TE2a, TE2p) and observed high endpoint density common to these areas was more clearly localised along the anterior lateral hippocampus and in a circumscribed region of the anterior medial hippocampus (blue and white arrows, respectively, in Figure 3A). Likewise, when we averaged the most highly connected cortical areas in the medial parietal and occipital cortices, respectively, high endpoint density common to each of these areas was localised in the posterior medial hippocampus and, to a lesser degree, in a circumscribed region of the anterior medial hippocampus (yellow and white arrows, respectively, in Figure 3B and C). When we averaged the EDMs across all of these areas, high endpoint density common to this broader collection was localised to separate circumscribed clusters in the posterior and anterior medial hippocampus (yellow and white arrows, respectively, in Figure 3D) and in punctate clusters along the anterior–posterior extent of the lateral hippocampus (blue arrows in Figure 3D). Our results suggest that these specific regions within the hippocampus are highly connected with multiple cortical areas in medial parietal, temporal, and occipital lobes.

Figure 3

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In addition, our novel method allowed us to isolate and visualise streamlines between specific cortical areas and the hippocampus and map the spatial distribution of hippocampal endpoint density at the single-participant level. Representative examples are presented in Figure 4. Figure 4B displays isolated streamlines associated with areas TF and V1 in a single participant. Figure 4D displays the hippocampal EDMs associated with each of these cortical areas in the same participant. When overlaid on the T1-weighted image, EDMs resemble histological staining of postmortem tissue, albeit in vivo and at a coarser level of detail (see bottom panels of Figure 4D). For example, for area TF, in a coronal slice taken at the uncal apex (red line) endpoint density was primarily localised to specific areas in the medial hippocampus (red panel). For area V1, in a coronal slice taken at the hippocampal tail (turquoise line) endpoint density was also localised to the medial hippocampus (turquoise panel). When compared with equivalent sections of histologically stained tissue, the location of these clusters of endpoint density roughly aligns with the location of the distal subiculum/proximal presubiculum for both TF and V1 (indicated by black arrows; see also Figure 5A). The location of endpoint density associated with each cortical area was broadly consistent across participants (evidenced by the results of our group-level analyses).

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Finally, while we observed clear overlaps in the group-averaged EDMs associated with specific cortical areas, a closer inspection of individual endpoints at the single-participant level revealed that endpoints associated with different cortical areas displayed both overlapping and spatially unique characteristics within these areas of overlap. For example, at the group level, areas V1 and V2 showed preferential connectivity with overlapping regions of the posterior medial hippocampus (see Figure 2—figure supplement 4) while, at the single-participant level, individual endpoints associated with each of these areas display both overlapping and spatially unique patterns (see Figure 4—figure supplement 1). This suggests that, while specific cortical areas display overlapping patterns of connectivity with specific regions of the hippocampus, subtle differences in how these cortical regions connect within these areas of overlap likely exist. A detailed examination of individual variability in these patterns, however, was beyond the scope of the current investigation and will be addressed in future studies.

This study represents a comprehensive in vivo characterisation of SC between cortical brain areas and the human hippocampus. We identified cortical areas with the highest degree of SC with the whole hippocampus, measured the degree to which these cortical areas preferentially connect along the anterior–posterior axis of the hippocampus, and deployed a tailored method to characterise where, within the hippocampus, each cortical area preferentially connects. Our results reveal how specific cortical areas preferentially connect with circumscribed regions along the anterior–posterior and medial–lateral axes of the hippocampus. Our results broadly reflect observations from the non-human primate literature (discussed below) and contribute new neuroanatomical insights to inform debates on human hippocampal function as it relates to its anterior–posterior axis. This work represents an important advance in our understanding of the neural architecture that underpins hippocampal-dependent memory systems in the human brain. In addition, our method represents a novel approach to conduct detailed in vivo investigations of the anatomical connectivity of the human hippocampus with implications for basic and clinical neuroscience.

Endpoint density mapping of human cortico-hippocampal connectivity

To date, our knowledge of human cortico-hippocampal anatomical connectivity is largely inferred from the results of tract-tracing studies conducted in non-human primates and rodents. We know much less about these patterns in the human brain. To address this gap, we adapted a tractography pipeline to track streamlines entering/leaving the hippocampus, identify the location of their ‘endpoints’, and create spatial distribution maps of endpoint density within the hippocampus associated with each cortical area. The resulting EDMs allowed us to quantitatively assess and visualise where, within the hippocampus, different cortical areas preferentially ‘connect’. To our knowledge, this is the first time such a specific approach has been used to map anatomical connectivity of the human hippocampus in vivo.

We observed striking differences in the location of endpoint density along both the anterior–posterior and medial–lateral axes of the hippocampus. For example, temporopolar and inferolateral temporal cortical areas displayed the greatest endpoint density along the lateral aspect of the head and body of the hippocampus (Figure 2—figure supplement 3; aligning with the location of distal CA1/proximal subiculum; see Figure 5A) and in a circumscribed cluster in the anterior medial hippocampus at the level of the uncal apex (Figure 2—figure supplement 3; aligning with the location of distal subiculum/proximal presubiculum; see Figure 5A). In contrast, areas in the medial parietal and occipital cortices displayed the greatest endpoint density along the medial aspect of the tail and body of the hippocampus (Figure 2—figure supplement 2A–E [medial parietal] and Figure 2—figure supplement 4A–E [occipital]; aligning with the location of the distal subiculum/proximal presubiculum; see Figure 5A). We discuss these observations in relation to the non-human primate literature below.

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New evidence for hubs of anatomical connectivity in the human hippocampus?

High endpoint density within the hippocampus was restricted to areas that aligned with the location of CA1, subiculum and the pre- and parasubiculum and was notably absent from areas aligning with DG/CA4 (hilus), CA3, and CA2. These observations mirror reports in the rodent and non-human primate literature where non-EC cortical areas predominantly connect with subicular cortices and the CA1/subiculum transition area (Aggleton and Christiansen, 2015; Insausti and Muñoz, 2001). Indeed, in non-human primates, the CA1/subiculum transition area and the presubiculum appear to be ‘hotspots’ of anatomical connectivity for multiple cortical areas (Insausti and Muñoz, 2001; Kravitz et al., 2011). In accordance with this, we observed that these specific regions within the human hippocampus displayed high endpoint density for multiple cortical areas. For example, the anterior lateral hippocampus (aligning with the distal CA1/proximal subiculum) displayed high endpoint density for multiple temporal cortical areas (Figure 3A) and the posterior medial hippocampus (aligning with the distal subiculum/proximal presubiculum) displayed high endpoint density for multiple areas of the medial parietal and occipital cortices (Figure 3B and C, respectively). Another cluster of high endpoint density in the anterior medial hippocampus (aligning with the distal subiculum/proximal presubiculum) was more broadly associated with temporal, medial parietal, and occipital areas (Figure 3A–D). Taken together, these observations provide evidence that discrete hubs of dense anatomical connectivity may exist along the anterior–posterior axis of the human hippocampus and that these hubs align with the location of the CA1/subiculum transition area and the distal subiculum/proximal presubiculum.

To the best of our knowledge, this is the first quantitative report of these patterns in the human brain and we highlight the intriguing possibility that two medial hippocampal hubs of high anatomical connectivity may exist; a posterior medial hub preferentially linked with visuospatial processing areas in medial parietal and occipital cortices and an anterior medial hub more broadly linked with temporopolar, inferotemporal, medial parietal, and occipital areas. We tentatively speculate that these circumscribed areas of the medial hippocampus could represent highly connected hubs of information flow between the hippocampus and distributed cortical networks. Indeed, the cortical areas identified in this study may represent key areas for direct cortico-hippocampal interactions in support of episodic/semantic memory processing and consolidation (Nadel et al., 2000).

Accumulating evidence from neuroimaging and clinical studies suggests that the medial hippocampus plays an important role in visuospatial cognition. The anterior medial hippocampus is consistently engaged during cognitive tasks that require processing of naturalistic scene stimuli in aid of episodic memory (Addis et al., 2012), visuospatial mental imagery (Dalton et al., 2018), and perception and mental construction (e.g. imagination) of scenes (Zeidman et al., 2015b; Lee et al., 2013). Strikingly, the location of the anterior medial cluster of anatomical connectivity observed in this study aligns with the location of functional clusters commonly observed in functional MRI investigations of these cognitive processes (Dalton et al., 2018; Addis et al., 2012; Zeidman et al., 2015b; Lee et al., 2013; Zeidman and Maguire, 2016; see Figure 6 for comparison). Furthermore, recent evidence from the clinical domain suggests that the posterior medial hippocampus may be a critical hub in a broader memory circuit (Ferguson et al., 2019). The medial hippocampus has more broadly been proposed as a putative hippocampal hub for visuospatial cognition (Dalton and Maguire, 2017). Our results lend further support to these proposals by showing that specific regions of both the anterior and posterior medial hippocampus display dense anatomical connectivity with multiple cortical areas in the human brain.

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In addition, our results provide new anatomical insights to inform current debates on functional differentiation along the anterior–posterior axis of the human hippocampus. Our anterior–posterior axis analyses revealed that specific cortical areas displayed a gradient style increase in connectivity strength along the anterior–posterior axis of the hippocampus while others displayed non-linear patterns of connectivity. In parallel, the results of our endpoint density analyses suggest that discrete clusters of dense connectivity may also exist within the hippocampus. Together, these observations provide new evidence to support recent proposals that both gradients and circumscribed parcels of extrinsic connectivity may exist along the anterior–posterior axis of the human hippocampus (Plachti et al., 2019; Brunec et al., 2018; Przeździk et al., 2019; Poppenk, 2020; Strange et al., 2014) and that different circuits may exist within the hippocampus, each associated with different cortical inputs that underpin specific cognitive functions (Dalton et al., 2018). How the complex patterns of anatomical connectivity observed in this study relate to functional differentiation along the long axis of the hippocampus (Plachti et al., 2019; Brunec et al., 2018; Przeździk et al., 2019; Poppenk, 2020; Strange et al., 2014) and its subfields (Dalton et al., 2019b; Dalton et al., 2019a) will be a fruitful area of research in coming years.

Our results also have implications for the use of existing hippocampal subfield segmentation protocols as they relate to the anatomical connectivity of the human hippocampus. The patterns of anatomical connectivity we observed in this study may not map well to classical definitions of subfield boundaries currently used in MRI investigations of human hippocampal subfields (Dalton et al., 2017; Berron et al., 2017; Iglesias et al., 2015). For example, the anterior medial clusters of high endpoint density observed in this study appear to extend across the distal subiculum and proximal presubiculum and lateral clusters appear to extend across the proximal subiculum and distal CA1. This mirrors recent observations in the functional literature that suggest functional clusters also extend across classically defined subfield boundaries (Dalton et al., 2019a; Grande et al., 2022). Indeed, more fine-grained segmentation can reveal that results, initially attributed to a specific subfield, may actually be driven by a specific subportion within that subfield (Dalton et al., 2019a). Results of this study provide a neuroanatomical rationale for these observations and further support the notion that, in some contexts, it may be advantageous to eschew classical concepts of hippocampal subfields. Future studies will aim to assess how patterns of SC relate to patterns of functional connectivity within the hippocampus and, subsequently, inform decisions of how we structurally and functionally define hippocampal subfields in human MRI studies.

Are there human-specific patterns of cortico-hippocampal connectivity?

Despite areas of concordance with the non-human primate literature noted above, we also observed important differences. As noted earlier, we observed broader patterns of endpoint density for area TE2a than we expected based on the non-human primate literature. Also, non-human primate studies have found direct and substantial connectivity between the hippocampus and orbitofrontal and superior temporal cortices (Insausti and Muñoz, 2001). We found only weak patterns of connectivity between the hippocampus and these regions. Also of note, we found denser patterns of anatomical connectivity between the posterior medial hippocampus and early visual processing areas in the occipital lobe than would be expected based on observations from the non-human primate literature. However, this observation supports recent reports of similar patterns of anatomical connectivity as measured by DWI in the human brain (Maller et al., 2019) and functional associations between these areas (Tang et al., 2020; Dugré et al., 2021). Collectively, these findings are potentially of great conceptual importance for how we think about the hippocampus and its connectivity with early sensory cortices in the human brain and open new avenues to probe the degree to which these regions may interact to support visuospatial cognitive functions such as episodic memory, mental imagery, and imagination and perhaps even more abstract cognitive functions relating to creativity. It is important to note that our methods differ significantly from the carefully controlled injection of tracer into circumscribed portions of the brain. MRI investigations of SC are inherently less precise, and methodological limitations likely explain some of our observed differences. It is equally important to note, however, that while we expect to see evolutionarily conserved overlaps in SC between macaque and human brains, we should not expect exactly the same patterns of connectivity. Since splitting from a common ancestor, macaques and humans have likely evolved species-specific patterns of cortico-hippocampal connectivity to support species-specific cognitive functions. Whether differences observed in this study reflect methodological limitations, species differences or perhaps most likely, a mix of both, require further investigation.

To our knowledge, only one prior study has attempted to characterise the broader hippocampal ‘connectome’ in the healthy human brain (Maller et al., 2019). Our study differs from this recent report in several important technical aspects. We analysed connectivity profiles of the head, body, and tail portions of the hippocampus separately in addition to the whole hippocampus. We manually delineated the hippocampus for each participant to ensure full coverage of the hippocampus and minimise the hippocampus mask ‘spilling’ into adjacent white matter (a common occurrence with automated segmentation methods; see Figure 7). We used the HCPMMP scheme, which provides more detailed subdivisions of cortical grey matter (Glasser et al., 2016). We also included SIFT2 (Smith et al., 2015a) in our analysis pipeline to increase biological accuracy of quantitative connectivity estimates. Finally, we used a carefully adapted tractography method that incorporates anatomical constraints and allowed streamlines to enter/leave the hippocampus, which provided us with a means to determine the location and topography of streamline ‘endpoints’, and therefore their distribution within the hippocampus (see ‘Materials and methods’ for detail relating to each of these points).

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In conclusion, this study represents a first attempt to apply this method and has some limitations. Specifically, our method relies on several manual steps to delineate the hippocampus and amend the gmwmi that abuts the inferior portion of the hippocampus (described in ‘Materials and methods’). This can be time consuming and requires expertise to accurately identify the hippocampus along its entire anterior–posterior extent on structural MRI scans. However, considering automated methods of hippocampal segmentation are sometimes not sufficiently accurate, particularly in the anterior and posterior most extents of the hippocampus (see Figure 7 for representative examples), manual delineation is the gold standard and ensures the best results. We restricted our analysis to a limited number of subjects under the age of 35 and selected participants whose hippocampus was clearly visible along its entire anterior–posterior axis on T1-weighted structural scans. While this ensured we used the best data quality available, further work should explore how these results may differ in the context of healthy ageing and in diseases that affect the hippocampus such as Alzheimer’s disease, epilepsy, and schizophrenia. How reliable our pipeline is in data acquired with more traditional clinical protocols remains to be explored and was beyond the scope of this study. Fibre-tracking results are known to be greatly influenced by the particular algorithm implementation. To ensure the robustness of our results, we used state-of-the-art methods, which included a diffusion model that is robust to crossing fibres and presence of partial volume effect (Jeurissen et al., 2014), an advanced probabilistic tractography algorithm that incorporates anatomical priors (Smith et al., 2012), and a streamline to fibre density matching to improve its quantitative properties (Smith et al., 2015a). The interested reader is referred to a recent review article where these and other key issues of ensuring the reliability of fibre tracking are discussed (Calamante, 2019). Despite these advances and the high-quality HCP data used in this study, limitations in spatial resolution likely restrict our ability to track particularly convoluted white matter pathways within the hippocampus and our results should be interpreted with this in mind. Indeed, this may explain the surprising lack of endpoint density observed in the DG/CA4-CA3 regions of the hippocampus where we would expect to see high endpoint density associated with, for example, the EC, which is known to project to these regions. Future dedicated studies using higher resolution data are needed to assess these pathways in greater detail. Also, we cannot rule out that some connections observed in this study may result from limitations inherent to current probabilistic fibre-tracking methods whereby tracks can mistakenly ‘jump’ between fibre bundles (e.g. for connections between the posterior medial hippocampus and area V1 due to the proximity to the optic radiation), especially in ‘bottleneck’ areas. Again, future work using higher resolution data may allow more targeted investigations necessary to confirm or refute the patterns we observed here. These limitations notwithstanding, our results provide new detailed insights into anatomical connectivity of the human hippocampus, can inform theoretical models of human hippocampal function as they relate to the long axis of the hippocampus, and can help fine-tune network connectivity models.

It should also be noted that we did not attempt to map the connections outlined in this study to canonical white matter tracts. The reliable segmentation of white matter fibre bundles is currently an area of contention in the DWI community. This pervasive and problematic issue was highlighted in a recently published large multisite study that revealed a high degree of variability in how white matter bundles are defined, even from the same set of whole-brain streamlines (Schilling et al., 2021). This significantly limits meaningful comparison and/or interpretation. Indeed, such an approach may paradoxically take away from the detailed characterisations we have achieved in this study. As highlighted by Schilling et al., 2021, it is now paramount that consensus is reached to define criteria to reliably and reproducibly define white matter fibre bundles.

From a clinical perspective, the hippocampus is central to several neurodegenerative and neuropsychiatric disorders. Considering healthy memory function is dependent upon the integrity of white matter fibres that connect the hippocampus with the rest of the brain, developing a more detailed understanding of the anatomical connectivity of the anterior–posterior axis of the hippocampus and its subfields has downstream potential to help us better understand hippocampal-dependent memory decline in ageing and clinical populations. Our novel method can potentially be harnessed to measure changes in anatomical connectivity between the hippocampus and cortical areas known to be affected in neurodegenerative diseases, to assist with monitoring of disease progression and/or as a diagnostic tool. In addition, our method could be deployed to visualise patient-specific patterns of hippocampal connectivity to support surgical planning in patients who require MTL resection for intractable MTL epilepsy.

We used data from the Human Connectome Project (HCP) 100 unrelated subject database; https://www.humanconnectome.org/study/hcp-young-adult/data-releases. All data needed to evaluate the conclusions in the paper are present in the paper and/or the Appendix. Code used for our analyses are available via github at the following address; https://github.com/Marshall-Dalton/Pipeline_for_anatomical_connectivity_along_the_anterior-posterior_axis_of_the_human_hippocampus (copy archived swh:1:rev:c341129cf85fb5345321b60c7ec76faa858698fb).

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Author details

1. Marshall A Dalton

   1. School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, Australia
   2. Brain and Mind Centre, The University of Sydney, Sydney, Australia
   3. School of Psychology, Faculty of Science, The University of Sydney, Sydney, Australia

   Contribution

   Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   marshall.dalton@sydney.edu.au

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4089-6801

2. Arkiev D'Souza

   1. Brain and Mind Centre, The University of Sydney, Sydney, Australia
   2. Faculty of Medicine and Health Translational Research Collective, The University of Sydney, Sydney, Australia
   3. Sydney Imaging, University of Sydney, Sydney, Australia

   Contribution

   Data curation, Formal analysis, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5932-2042

3. Jinglei Lv

   1. School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, Australia
   2. Brain and Mind Centre, The University of Sydney, Sydney, Australia

   Contribution

   Formal analysis, Investigation, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-4906-2646

4. Fernando Calamante

   1. School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, Australia
   2. Brain and Mind Centre, The University of Sydney, Sydney, Australia
   3. Sydney Imaging, University of Sydney, Sydney, Australia

   Contribution

   Conceptualization, Resources, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing – review and editing

   Competing interests

   is listed as one of the inventors in a patent awarded for the track-density imaging method

   "This ORCID iD identifies the author of this article:" 0000-0002-7550-3142

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