Introduction
Vision is a key asset for most mammals, depending on their habitat and evolution. From the hedgehog, a model for the ancestral mammalian brain, to primates, there has been considerable nonlinear phylogenetic specialization of the visual system, depending on prey
vs. predatory status, night
vs. day activity, terrestrial
vs. aquatic life and so forth. Although the mammalian visual sensory system has been extensively investigated, studies on species variations are still scarce. Most lines of research focused on primates (Livingstone and Hubel
1984,
1988; Lund
1987; Lund et al.
1988,
1991,
1997; Barton
1998; Van Essen et al.
1992; Goebel et al.
2012), cats (Rosenquist
1985) and rodents (for references see Pearlman
1985), although earlier works also included other mammalian orders (van Sluyters and Stewart
1974; Clarke et al.
1979a,
b; Duke-Elder
1961; Hebel
1976; Karamanlidis
1979).
Different taxa reveal a different organization of their visual system. Primates are characterized in part by their pronounced binocularity, an understandable evolution for mammals with a prehensile hand (Szalay
1975). Carnivores possess a certain degree of binocularity attributed to their predatory activities (Hughes
1977). Terrestrial Cetartiodactyls are herbivore species that developed a phylogenetic adaptation to extremely contrasting habitats, from arid land to water, with consequent various degrees of differential evolution of their visual system and other senses. The horse is a perissodactyl that shares several adaptive features with most terrestrial Cetartiodactyls, including the general morphology of the visual system (Harman et al.
1999; Timney and Kiel
1999; Kendrick et al.
2001; Hall et al.
2003; Knolle et al.
2017). All Cetartiodactyls (including sea-living cetaceans) and perissodactyls developed a broad field of view mostly relying on monocular signal (table, Johnson
1901; Duke-Elder
1958), although their vision has been deemed fairly good (Piggins et al.
1996, Jacobs et al.
1998; Coimbra et al.
2013,
2017). However, most of these species are also endowed with a binocular field (Duke-Elder
1958; Hughes and Whitteridge
1973; Clarke et al.
1979b; Timney and Kiel
1999); and pioneer experiments found binocular neurons in the visual cortex of the sheep and goat (Clarke and Whitteridge
1976; Clarke et al.
1976,
1979a,
b). Notwithstanding these latter studies, knowledge on the visual system of ungulates remains relatively limited. The visual system of cetaceans, i.e., marine Cetartiodactyla, drew some attention (Cuvier
1836; Kellogg
1938; Rochon-Duvigneaud
1939; Duke-Elder
1958; Walls
1963; Dral
1972,
1975; Herman et al.
1975), because the eyes are placed almost exactly opposite to each other and appear to be able to move independently (Dawson et al.
1981). Binocular vision in cetaceans is therefore necessarily extremely limited (Dawson et al.
1981; Garey et al.
1985; Mobley and Helweg
1990; von Fersen et al.
2000; Kilian et al.
2000), but remains possible, given the examples of binocular vision demonstrated in other lateral-eyes species (Holden and Low
1989). Independence of the eyes implies that we should expect complete decussation of the optic nerves, which has been observed in very few specimens, albeit with conflicting reports (Ridgeway
1990 citing Hatschek
1903 and Jacobs et al.
1964,
1975; Korneliussen, personal communication in Morgane and Jacobs
1972).
The mammalian primary visual cortex (V1) corresponds to Brodmann’s area 17 and is the target of the geniculo-calcarine tract. Six distinct layers are commonly recognized in V1, according to Brodmann’s original description (Brodmann
1909), including a further subdivision of layer 4 (L4) in 3 sublayers. The V1 of primates is also called “striate cortex” because of the presence of the line of Gennari (Gennari
1782), visible macroscopically as a stripe (Ström and Ekesten
2016). The line is formed by myelinated axons that originate in the lateral geniculate nucleus (LGN) and synapse in the inner granular layer (L4) of the cortical gray matter, in sublayers 4Cα for magnocellular (M) projections and 4A and 4Cβ for parvocellular (P) projections (Fitzpartrick et al.
1985). This basic organization has since been thoroughly updated to include koniocellular (K) projections (Dacey and Lee
1994; Sincich and Horton
2005). Some other inputs to V1 are also found in L6, with both types of cells, but in a separate manner (Fitzpatrick and Einstein
1989; Lund and Boothe
1975).
The boundaries, however, of the striate and peristriate cortex have been extensively discussed since its original mapping (Brodmann
1909) and remained contradictory, up until the development of additional staining techniques (Braak
1977; Rosa and Krubitzer
1999; Amunts et al.
2000). The organization of V1 is the hallmark of the sensory cortex in primates, also called koniocortex, and is characterized by the presence of intense granularity in L2 and L4 (outer and inner granular layers). The lack of a classic koniocortex, as described in man, was noted by Sanides and Hoffmann (
1969) in the cat, in which granules are substituted by larger cells. In fact, according to Brodmann (Brodmann
1909) area 17 concerns primates, and although the 6 layers are constant in all mammals, L4 has undergone such vast alterations across species that it is often overlooked, including in ungulates. As a matter of fact, the cytoarchitecture of V1 in ungulates has received little attention aside from mostly the sheep (Rose
1942; Karamanlidis
1979).
Although V1 is only a part of the complex visual apparatus which can take various forms (Duke Elder
1958), it is the main cortical stage for inputs from the LGN in mammals for the vast majority of the transmitted signal (Snicich and Horton
2005). V1 has recently been found to be the primary zone of activity for the early reaction to frightful stimuli, together with the pulvinar (Koizumi et al.
2019), which almost all animals experience. This indication suggests further study of the organization of the visual cortex in mammalian prey species, which potentially favor width of the visual field instead of binocular potential. For this reason, here we focused our attention on the V1 of several Cetartiodactyls, including the terrestrial giraffe (
Giraffa camelopardalis), Pere Davide’s deer (
Elaphurus davidianus), and sheep (
Ovis aries), the semi-aquatic hippopotamus (
Hippopotamus amphibius), and the marine bottlenose dolphin (
Tursiops truncatus), Risso’s dolphin (
Grampus griseus), long-finned pilot whale (
Globicephala melas), Cuvier’s beaked whale (
Ziphius cavirostris) sperm whale (
Physeter macrocephalus) and fin whale (
Balaenoptera physalus). Their visual systems share a typical feature, the presence of the visual streak (Hughes and Whitteridge
1973; Hughes
1977; Shinozaki et al.
2010; Coimbra et al.
2013,
2017), although its structure is somewhat different in cetaceans (Mass and Supin
2007). The temporal region of the retina of Cetartiodactyls is thought to facilitate frontal vision (Collin
1999; Hughes,
1977). However, the visual streak of terrestrial ungulates is functional to a panoramic horizontal view (Hughes
1977), while in cetaceans it specialized into two high resolution points in the retina, marked by higher ganglion cell density (Dawson and Perez
1973; Dral
1975; Herman et al.
1975; Dawson et al.
1982; Mass and Supin
2007). In the present study we also considered the horse, the typical representative of the perissodactyls, because its original environment, dietary habits and especially the position of the eyes, are similar to those of terrestrial Cetartiodactyls and a comparison of the organization of the respective visual systems may yield insights on the development of potentially similar phylogenetic adaptations. As a general reference we also examined the visual cortices of two primates, the chimpanzee, and the pig-tailed macaque.
Materials and methods
Animal tissues
The specimens were collected at the Department of Comparative Biomedicine and Food Science (BCA) of the University of Padova. The brains were fixed by immersion in 4% phosphate buffered formalin immediately after extraction. For large-brained specimens, the cerebrum was cut in thick slices to allow a faster fixation. The list of specimens used can be seen in Table
1.
Table 1
Sampling data, references on sampling topography and information on the visual field of each examined species (CC: conservation code, used in stranding protocols, Ijsseldijk et al.
2019)
Primates |
Macaca nemestrina | Pig-tailed macaque | 1 | Immediate, perfused animal | | | 1.657 ± 0.16 |
Pan troglodytes | Chimpanzee | 2 | 6 h | Bailey et al. ( 1950); Allman and McGuinness ( 1988) | | 2.108 ± 0.29 |
Perissodactyls |
Equus caballus | Horse | 2 | 6–12 h | | 320; 80; Harman et al. ( 1999) 65°; Duke-Elder ( 1958); Timney and Keil ( 1999) | 2.041 ± 0.49 |
Terrestrial Cetartiodactyls |
Ovis aries | Sheep | 3 | 2–4 h | Rose ( 1942); Clarke and Whitteridge ( 1976) | < 360; 60; Lindsay Johnson ( 1901) | 1.488 ± 0.21 |
Elaphurus davidianus | Père David’s deer | 2 | 6–12 h | Clarke and Whitteridge ( 1976) | 50° of optical divergence; Lindsay Johnson 1901 | 1.947 ± 0.13 |
Giraffa camelopardalis | Giraffe | 2 | 6–12 h | | 75° of optical divergence; 60° overlap Lindsay Johnson ( 1901); Mitchell et al. ( 2013) | 2.637 ± 0.31 |
Semi-aquatic Cetartiodactyls |
Hippopotamus amphibius | Hippopotamus | 2 | 6–12 h | | 60° of optical divergence; Lindsay Johnson ( 1901) | 2.205 ± 0.59 |
Marine Cetartiodactyls |
Toothed dolphins and whales (Odontocetes) |
Tursiops truncatus | Bottlenose dolphin | 2 | < 24 h from stranding (CC 1–2) | Sokolov et al. ( 1972); Kesarev et al. ( 1977); Ladygina et al. ( 1978) | 20–30° binocular field; 120–130, panoramic vision; Mass and Supin ( 2009) | 1.366 ± 0.13 |
Grampus griseus | Risso’s dolphin | 2 | < 24 h from stranding (CC 2) | | 20–30° binocular field; 120–130, panoramic vision; Mass and Supin ( 2009) | 1.553 ± 0.19 |
Globicephala melas | Long-finned pilot whale | 1 | < 24 h from stranding (CC 2) | | 20–30° binocular field; 120–130, panoramic vision; Mass and Supin ( 2009) | 1.258 ± 0.18 |
Ziphius cavirostris | Cuvier’s beaked whale | 2 | < 24 h from stranding (CC 2) | | 20–30° binocular field; 120–130, panoramic vision; Mass and Supin ( 2009) | 1.748 ± 0.19 |
Physeter macrocephalus | Sperm whale | 1 | < 24 h from stranding (CC 2) | | No binocular field; 120–130, panoramic vision; Mass and Supin ( 2009) | 2.585 ± 0.37 |
Baleen whales (Mysticetes) |
Balaenoptera physalus | Fin whale | 1 | < 24 h from stranding (CC 2) | Huggenberger et al. ( 2019) | No binocular field; 120–130, panoramic vision; Mass and Supin ( 2009) | 1.548 ± 0.16 |
The brains of marine mammals were sampled by the
Mediterranean Marine Mammal Tissue Bank (
www.marinemammals.eu) a CITES-recognized tissue bank (CITES IT 020) located at BCA that harvests and stores tissue from marine mammals that
a) stranded along the Mediterranean and European coastline; or
b) died in marine theme park. The brains of all terrestrial and semi-aquatic Cetartiodactyls (except those of the sheep) and those of the chimpanzees were collected during necropsy of animals that died in theme park and were delivered to BCA for postmortem diagnosis. The brains of the sheep and horses were harvested at local abattoirs during routine slaughtering of animals raised for meat production. During these latter procedures, the sheep and horses were constantly monitored by veterinary medical personnel that ensured the conditions of animal welfare requested by the current European (EC # 1099/2009;
https://ec.europa.eu/food/animals/welfare/practice/slaughter_en) and Italian laws that regulate slaughtering. Finally, samples of the pig-tailed macaque are archival.
Post-mortem intervals (PMI) are noted in Table
1. From the onset of death, the process of autolysis starts to degrade biological tissues, and the brain is involved in the process. In laboratory contexts, where relatively small animals can be perfused with fixative right after euthanasia, post-mortem intervals are maintained to an absolute low. In the case of larger animals, brains harvested in the occasion of necropsies and strandings were put and kept in 4 °C refrigerators for a few hours until the necropsy. This common practice is routinely employed to avoid damaged induced by longer PMI and thus curtail substantial loss of tissue quality, and stain. The preservation status of the bodies of stranded cetaceans is classified following an internationally recognized coding system (Ijsseldijk et al.
2019, see Table
1).
Sampling and histological techniques
The visual cortex of each species was sampled based on the topography reported in published references (see Table
1). The tissue blocks were processed for paraffin embedding and cut into thin Sections (5 µm). The resulting sections were mounted on glass slides (Superfrost plus, Menzel Gläser, Thermo Scientific, J1800AMNZ) and stained using Nissl and Klüver-Barrera techniques. Briefly, for Nissl staining, after deparaffinization in xylene and hydration in alcohol series, sections were rinsed in distilled water, dipped for 4 min in a 0.4% thionine solution, quenched in tap water, then rinsed again in distilled water, before passing in graded ethanol for dehydration, subsequent xylene baths, and coverslipped in mounting medium. For Klüver–Barrera staining, after the rehydrated sections spent a night in luxol fast blue at 57 °C, they were washed in ethanol 95% for 15 min, then in tap water for 10 min, and briefly in distilled water before differentiation in a 0.05% lithium carbonate solution for one minute. Sections passed through a 70% ethanol bath and subsequent additional lithium carbonate differentiation if the staining seemed too strong. Secondly, sections were immerged in cresyl violet 0.1% for 20 min before rinsing in tap water, graded dehydration in ethanols and ultimately in xylene, to be coverslipped.
Nissl-stained sections (three per specimen) were then scanned using a semi-automated digital microscope (D-Sight, Menarini Diagostics, Florence, Italy) at a 40 × enlargement, at the best focal plane. Within the high-resolution images acquired, we selected a large (approx. 2000 µm) straight cortical region and 3 independent operators (J-MG, AP, and BC) segregated them in layers, later analyzed separately, based on the canonical accepted structure of the striated cortex (Goebel et al.
2012). The resulting layers were then analyzed individually, for each specimen. References to large or small neurons and glia follow Garcia-Cabezas et al. (
2016). The presence of granule cells, usually accompanied by slightly wider neuropil spaces, in the vicinity of lower layer 3 and upper layer 5 were critical to identify a layer 4.
Immunohistochemistry
Immunohistochemistry was performed on paraffin Sections (8 μm). Immunoreaction was achieved using the following antibodies against calcium binding proteins (CBPs): a mouse monoclonal anti-parvalbumin (PV, 1:2000, Swant), a rabbit polyclonal anti-Calbindin D-28 k (CB, 1:1000, Swant), a mouse anti-Calretinin (CR, 1:1000, Swant) (see Table
2). Antigen retrieval was carried out at 90 °C for 10 min in a 0.05 M Tris/HCl solution buffer, pH 9.0. To block endogenous peroxidase activity, sections were treated with a 1% H2O2 solution in Tris-buffered saline (TBS, 150 mM NaCl, 50 mM Tris–HCl, pH 7.6) for 10 min. Sections were then incubated for 1 h at room temperature, then overnight at 4 °C in a solution containing the primary anti-PV, anti-CB or anti-CR in SuMi (0.5% Triton X-100 and 0.25% gelatin in TBS). Sections treated with rabbit antibodies were then rinsed in TBS (3 × 5 min), and incubated in biotinylated anti-rabbit IgG (5 μg/ml, Vector Labs, Burlingame, CA) diluted 1:400 in SuMi for one hour at room temperature. After rinsing in TBS, sections were incubated in 1:800 avidin–biotin complex (Vectastain Kit, PK-7200, Vector Labs, Burlingame, CA) for an hour. Sections were again rinsed in TBS. Staining was revealed by incubating the sections in a diaminobenzidine solution with 0.2% nickel ammonium sulfate and 0.01% hydrogen peroxidase. Sections with mouse primary antibodies were treated using a horseradish peroxidase reaction, first with a FLEX/HRP labeled polymer, revealed by a diaminobenzidine–chromogen solution (EnVision FLEX system, Dako). Subsequently, all sections were counter-stained with thionine for 4 min, then dehydrated in graded ethanol solutions (3 min each) and finally in xylene before glass coverslipping with mounting medium.
Table 2
Primary antibodies used in the present work
Anti-PV | Produced by hybridization of mouse myeloma cells with spleen cells from mice immunized with parvalbumin purified from carp muscles | Swant, mouse monoclonal, Code No: 235, Lot no: 10–11 (F) RRID: AB_10000343 | 1:1000 |
Anti-CR | Produced in mice by immunization with recombinant human calretinin − 22 k (identical with calretinin up to Arg178 N-terminal) | Swant, mouse monoclonal, Cat# 6B3, Lot n° 010,399 RRID: AB_10000320 | 1:1000 |
Anti-CB | Produced against recombinant rat calbindin D-28 K (CB) | Swant, rabbit polyclonal, Lot No.: 9.03, Code No.: CB − 38a RRID: AB_10000340 | 1:1000 |
Negative controls were performed by replacing one of the steps with TBS or non-immune serum, in which case staining was abolished. Positive controls were carried out testing the primaries antibodies on mouse brain sections. Additionally, specificity of the antibodies had already been tested in previous studies (see Table
2).
Image analyses
Shortly, the image analysis process was performed on the Nissl-stained material using space-varying thresholds to identify all the cell bodies stained by thionine in the area and separate them from the background. Cell clusters were separated by identifying cell centers by local density estimation, layer ordering constraints based on the object values of eccentricity, areas and solidity (Grisan et al.
2018). The resulting populations of cells were then analyzed through Matlab function algorithms (Matlab, Mathworks, Natick, MA, USA), identifying cell area, perimeter, and shape descriptors circularity, solidity, extent and a surface density (number of cells in a radius of 50 µm for any given cell). Given the thickness of the Sections (5 µm), no overlapping of cells could be expected, however an estimation of volume density would overestimate the number of neurons (for details see Corain et al.
2020). This measure allows us to perform comparisons across brains of different sizes, and implicitly assess how neuron count and neuron size is scaling with the brain volume.
Cortical thickness was measured using the calibrated software provided for the automated microscope (Navi Viewer, Visia Imaging, San Giovanni Valdarno, Italy), using a tool measuring the length perpendicular to a line placed on the pial surface of the cortex. Measurements were made at least 5 times per sample, outside of sulcus bottom or top to avoid distortions.
Statistical analysis
The same approach has been used for every grouping variable, that is the species, the phylogenetic grouping and the orbit orientation, as it was used in previous works (Corain et al.
2020).
The comparison of the morphometric descriptors (
Y) among the groups has been formalized by the following statistical linear model
$${\mathbf{Y}}_{ij} = {{\varvec{\upmu}}} + {{\varvec{\uptau}}}_{j} + {{\varvec{\upvarepsilon}}}_{ij} ,$$
(1)
where specific location
τj for the group
j can be a random variable (i.e. not a fixed effect) and scale effects
σ2(
τj) =
σ2j, are both allowed to differ across populations under the alternative hypothesis, while the random components
εij are assumed to be the same for each observation—at least under the null hypotheses–but are not specified in their distributional form according to a nonparametric permutation-oriented approach (Pesarin
2001; Arboretti et al.
2014).
Under the null hypothesis the observations of the groups are assumed to be equal, that is the random variable τj is assumed to follow the same distribution in each group.
Permutation-based
p values (Pesarin
2001; Corain and Salmaso
2015) have been calculated under the null hypothesis of exchangeability.
The tests of the same domains (size, shape and density) are further combined in a multivariate test by the Fisher combining function in order to assess the equality in distribution of the groups in a multivariate perspective.
Finally, pairwise test have been performed through constrained permutation among the two groups and using the same method described above. Furthermore, Shaffer post-hoc correction for multiple comparison was performed.
The R package “flip” together with custom codes were used to run the analysis (Finos
2018).
Limits of the present study
The present study describes domestic but also rare and wild species. The low number of specimens for some of the latter species is a limit. Statistically, the potentially comparative high value of the quantitative results provided here is hindered by the small number of specimens (n = 1 for some). Furthermore, tissues were collected through the years, and sampling conditions in the field may have affected Klüver–Barrera stain of myelin sheaths, and in rare cases a diminished immunoreactivity. Nonetheless, even considering these limitations, the statistical weight of the semi-independent analysis of a large cohort of cells in each sample (see below) should alleviate some of this impact. Extrapolation of some of our absolute numbers to another context may challenging. However, their analysis maintains a comparative significance if referred to species often largely overlooked or never analyzed before in detail. We also emphasize that density is absolute, not relative to body size or cortical thickness, and uncorrected for processing.
Discussion
The Order Cetartiodactyla includes two clades, the terrestrial Artiodactyla (even-toed mammals) and the marine Cetacea (dolphins and whales). The fusion in a single order (or SuperOrder) derives by molecular evidence pointing to a common artiodactyl precursor from which marine cetaceans differentiated in early Eocene (> 50 million years ago). The resemblance between terrestrial artiodactyls and their marine cousin cetaceans is difficult to grasp immediately, but the position of the eyes, quite lateral in the head, is evident in all species. This latter characteristic may be related to the necessity to scan the horizon for the terrestrial herbivores, but the same does not necessarily apply to cetaceans that include classic predator species (toothed whales) that rely on echolocation for hunting, and krill filterers (whalebone whales). The present study started from simple questions: does the visual cortex of Cetartiodactyls follow a common evolutionary Bauplan and share organizational features? Are there differences between terrestrial and marine species of the same Order, or even among species that share the same environment but belong to different families? To better understand the evolution of the visual cortex of Cetartiodactyls we studied several members of the Order. We also compared the results obtained with data from the closely related herbivore perissodactyls, and with findings in primates, whose visual cortex is generally considered to be the most complex because of the advanced extent of the binocular field and stereoscopy.
In a last few years, our group analyzed the brains of large ungulates, including the horse (Cozzi et al.
2014a, b,
2017b), the bovine (Peruffo and Cozzi
2014; Ballarin et al.
2016; Graïc et al.
2018; Corain et al.
2020); the pig (Minervini et al.
2016); the sheep (Peruffo et al.
2019) and the giraffe (Graïc et al.
2017). The cytoarchitectonics of these mammals indicates a substantial difference from primates and rodents, with a consistent reduction of L4 and different targets of thalamic afferent within the cortical column (for details and reference see Cozzi et al.
2017b; Peruffo et al.
2019). The cytoarchitectonics of the cetacean brain has been the subject of numerous studies (Breathnach
1960; Morgane et al.
1986; Ridgway
1990; Glezer et al.
1992b,
1995; Poth et al.
2005; Kern et al.
2011; Butti et al.
2011,
2014a,
b; van Kann et al.
2017; for general reference see Cozzi et al.
2017a; Huggenberger et al.
2019). Specifically, the cetacean visual cortex has been thoroughly studied by relatively few authors (Kesarev and Malofeeva
1977; Morgane et al.
1985,
1988,
1990; Oelschläger et al.
1987; Garey et al.
1985; Garey and Leuba
1986; Garey and Revishchin
1986; Garey et al.
1989; Glezer et al
1992a,
1993; Manger et al
1998; Graïc et al.
2021), sometimes with a broad comparative scope (Glezer et al.
1998; Hof et al.
2000; Raghanti et al.
2014; Cozzi et al.
2017a; van Kann et al.
2017). In general, the organization of the cetacean cerebral cortex differs from that of terrestrial mammals, with predominance of phylogenetically older L1 and L6, a poorly differentiated population of relatively large neurons, and consequently a low degree of granularity (Morgane et al.
1990). Furthermore, direct comparison of absolute thickness, lamination, myelination and cytoarchitecture indicates that there is no unique cetacean type, as found in other taxa (Krubitzer et al.
2011) but different variations, further emphasized by immunocytochemical results. Our data confirm that specific characteristics of the cetacean cortex are more evident in the visual cortex (Figs.
30,
31), as already reported (Morgane et al.
1988). In particular, the size of cetacean cells in “granular” layers (L2 and L4) were notably larger than that of ungulates, either terrestrial cetartiodactyl or perissodactyl, and of primates. Again, this tends to confirm a certain lack of granular cells and lamination. However, interestingly, odontocetes and mysticetes had the widest variation of size across layers, with a wide variability (Fig.
30). Granted that the low number of specimens might explain part of it, this nevertheless suggests the existence of different neuron sizes within each layer, which seems to be confirmed by CBP immunostaining.
Lamination
The lamination and cytoarchitectonics of the visual cortices of the two primates that we studied fully correspond to what described in classic texts and references (see Blümcke et al.
1990; Morrison et al.
1998). Calculation of cortical thickness in the chimpanzee and macaque suffers from the limitations of our sample size and age (Natu et al.
2019), but the results for the macaque agree with values reported by others for the primary visual cortex (1.5 to 1.6 mm thick; Peters and Sethares
1991).
The visual cortex of most Cetartiodactyls and of the horse was poorly laminated if compared to those of the macaque and chimpanzee. Interestingly, statistical analysis showed a relatively high homogeneity between even-toed and one-toed ungulates, correlated with a closer phylogenetic position compared to the other taxa tested (Fig.
30).
Our results in the sheep partially agreed with what was reported by Rose (
1942). The cortex is thin and relatively rich in cells. L2 and L3 are difficult to separate, L4 is discreetly wide and can sometimes be separated into L4a containing feebly staining, small granular cells, and L4b with darker more pointed cells. L5 is quite thin and contains few large neurons, and yet fewer much larger cells. L6 is wider than L5 and quite dense. Its cells are arranged in rows and generally smaller than those of L5.
In the other species, although inherently variable with cortical region and circumvolution positioning, L1 was distinctively large compared to primates, as previously reported. L1 was particularly large especially in the sperm whale, giraffe and Risso’s dolphin.
In all ungulates, L2 was also usually larger and less dense, as previously described (Morgane et al
1985). There are analogies with the visual cortex of bats, including the presence of extraverted neurons (Sanides and Sanides
1972). The large array of sizes present throughout L2-L5 in cetaceans (Fig.
30) suggests that the layered cortical pattern is more diffuse, and that granular, smaller neurons, including interneurons, are dispersed among inner and outer pyramidal layers.
The large granular lamination of L2 and L4, considered characteristic of sensory cortex, are reduced in all ungulates, but became evanescent in cetaceans, although previously signaled in V1 (Morgane et al.
1988; Supin et al.
2001; Graïc et al. 2020). The density results reflect this fact, as L4 is extremely low in cetaceans, this being due to the sparse distribution of few recognizable cells in the area, hardly forming an actual layer.
In most cases, identification of L4 at the L3–L5 border was problematic. The presence of granule cells by Nissl staining and/or the appearance of a layer of myelin in Klüver-Barrera staining are the simplest form of inner granular layer sign. In some species, a proper L4 was identifiable, as in the giraffe, where the presence of a L4A and C was hinted by smaller granule-like neurons with a cell-poor thin stripe in between (Fig.
13) as previously described in Jacobs et al. (
2014). In the horse, L4 was equally shrunk to a minimum, coherent with previous publications (Cozzi et al
2017b). The difficulty for the community to agree on a limit between L3 and L4 exists also in primates (Peters
1994; Balaram et al.
2014); nevertheless, the limit between almost all other layers is blurred in most terrestrial Cetartiodactyls and particularly in cetaceans.
According to (Morgane et al.
1988), the primary visual cortex of the striped dolphin is heterolaminar and contains a weak (“incipient”) L4 with distinct granules, which has recently been found in the long-finned pilot whale (Graïc et al.
2021), and differentiate V1 from V2. In the same study, Morgane and colleagues (
1988) found by Golgi staining that L2 contained extraverted neurons with widespread spinous apical dendrites directed towards L1. The presence, distribution, and morphology of these features in both these species was hinted in our work in the Risso’s dolphin, another
Delphinidae, but not as clearly in the Cuvier’s beaked whale, sperm whale or fin whale.
As can be seen in Fig.
1, the distinct line of Gennari progressively fades from primates to cetaceans, although it can still be faintly seen. Our results suggest the presence of a circuitry at least partially different from that of primates. Yet, a different circuitry does not imply lesser performance, as the use of visual cues has been reported repeatedly even in several marine Cetartiodactyls (von Fersen et al.
2000; Reiss and Marino
2001; Karenina et al.
2010; Mitchell et al.
2013; Tomonaga et al.
2014; Knolle et al.
2017).
The organization of the
fasciculi is clear in the myelin stains. However, the columnar arrangement usually well seen in primates (Braak
1976; Figs.
3,
5), is not obvious in ungulates. Rather, myelin histological stains show some bundles arising from the white matter and expanding through the cortical grey. This organization is relatively present in both terrestrial and marine Cetartiodactyls, and in Perissodactyls. There are variations among the species with a pattern that suggests a progressive evolutionary shift in cortical organization. In fact, we noted a more definite aspect, and consequently clearer identification of the myelin bundles, in the sheep and horse. The deep diving sperm whale is at the opposite end, with no clear bundles despite a thick, neuropil-rich cortex (Fig.
25).
Immunohistochemistry of the calcium binding proteins
The existence of GABA-ergic cells in V1 has been extensively described in primates (Peters
1994; Jones et al.
1994; Morrison et al.
1998; Ulfig
2002), and is part of the visual area circuitry both for parallel processing and signal enhancement. GABA-ergic neurons are in large majority interneurons (DeFelipe et al.
2013), which are critical for signal modulation throughout sensitive pathways, naturally including the cortex (Fino et al.
2013). More importantly, evidence showed that inhibitory neurons varied in relative proportions among mammalian groups and relative to brain size (Hof et al.
1999; Sherwood et al.
2007,
2009). There is also evidence that those interneurons are not exclusively local, but reach the white matter (Micheva et al.
2016), and have been proven to connect relatively distant areas (Melzner et al.
2012). Calcium-binding proteins (CB, CR and PV) which have been shown to identify almost exclusively non-overlapping populations of GABAergic neurons (Andressen et al.
1993; Glezer et al.
1993; DeFelipe
1997).
CBPs as GABA markers in terrestrial and semi-aquatic species
Our data substantially confirm previous histological studies on the lamination and organization of the giraffe, including the presence of neuronal morphology typical of Eutheria (Jacobs et al.
2014). Immunohistochemical investigation indicates the existence of a marked neuropil band in L4, as demonstrated both by PV and CR. On the contrary, CB-ir was much less useful to see the structure of the cortical layers than the former two. The CR-ir neurons in our hippopotamus V1 closely resemble those already described in the pygmy hippopotamus (Butti et al.
2014a). The difference in complexity between the giraffe and hippopotamus V1 follows similar findings made in their respective retinas (Coimbra et al.
2013,
2017).
Alternatively, CR clearly marked neuropil in L1 of the sheep, deer, giraffe, hippopotamus, and horse. Somata were most numerous in the giraffe, in which CR-ir neurons were dispersed also in L2 and L3 (Fig.
14).
In the macaque and chimpanzee, PV-ir neurons identified a band corresponding to L4C, known from the literature to receive both magnocellular and parvocellular inputs from the lateral geniculate nucleus (LGN) (Sincich and Horton
2005; Fitzpatrick et al.
1987). Several PV-ir neurons marked a distinct neuropil band in the sheep and in Pere David’s deer. In the giraffe the latter band was doubled with somata visible throughout and in between the two bands. In the horse the said band did not split in two, but seemed to expand towards L3. The distribution of PV-ir neurons was much more diffuse in the hippopotamus, a semi-aquatic species.
CBPs as GABA markers in cetaceans
We are aware that CR is a powerful tool to detect GABAergic neurons, especially in the central nervous system (Glezer et al.
1992b). Former comparative studies in Cetartiodactyls and primates noted that CR-containing neurons were much more abundant and brightly stained than CB-ir ones (Hof et al.
2000; Graïc et al.
2021), as we also report. However, in our experimental series most CR cells were distributed in the upper layers L1-L2, but also in L3 and L5. Additional to the fusiform neurons described by Glezer and coworkers (Glezer et al.
1992a,
b), we identified multipolar cells (Fig.
20). Furthermore, in our specimens the neuropil ramified into bands impossible to miss. Interestingly, the visual cortex of the pilot whale (Fig.
22) contained a higher number of cells compared to other cetaceans, with an exceptional amount of neuropil. We were not able to identify PV-ir neurons in the visual cortex of cetaceans, as already previously noted in the bottlenose dolphin (Glezer et al.
1998). Interestingly, former studies of our group failed to identify PV-ir neurons in the claustrum of the bottlenose dolphin (Cozzi et al.
2014a,
b). We were not able to identify PV-ir neurons in the visual cortex of cetaceans, as already previously noted in the bottlenose dolphin (Glezer et al.
1998). Interestingly, former studies of our group failed to identify PV-ir neurons in the claustrum of the bottlenose dolphin (Cozzi et al.
2014a,
b), although some other groups reported PV staining in subcortical areas of other cetaceans (Dell et al.
2016a,
b). We also note that the potential issue of a clear PV staining in the cetacean cortex might raise questions as to the evolution of the CBPs in these mammals. In some cases, such as the immunostaining in the Cuvier’s beaked whale and the CB staining in the fin whale, there is the possibility of some influence of the time of fixation after death, always potentially difficult to determine in stranded wildlife.
Significance of CBPs results
Comparison of immunohistochemical results with Nissl images strongly suggests that the cetacean visual cortex, composed of large pyramidal-like cells, is indeed furtherly subdivided in additional functional layers (Graïc et al.
2021). These, in turn, suggest potentially different connection patterns within the column and towards other areas. Species differences in the pattern of CBP distribution have been reported and discussed in the literature (Glezer et al.
1993; Sherwood et al.
2007; van Kann
2017). However, here we emphasize that the changes that we observed are unexpected and do not fully match the current view on the cortical column of marine Cetartiodactyls in the different species. The sperm whale, e.g., displayed two dense neuropil bands clearly marked, which do not correspond to the canonical view either of the mammalian visual cortex or even to the commonly accepted pattern for the cetacean cortex (Fig.
26). Conversely, the patterns observed in the fin whale, the only baleen whale in our series, were relatively like the more classic cetacean model, and similar to delphinids in general.
In our series, Nissl stain failed to identify what we would
conventionally define a clear L4 layer in marine Cetartiodactyls, confirming what already reported by former studies. However, immunostaining did reveal a
diffuse band of CR-ir neurons, that, although not identifiable in a separate layer, may indeed act as a
functional L4, as also described in other mammals, (Fig.
18). The potential evolutionary significance of the prevalence and distribution of CR-ir neurons is worth noting, but requires further studies. It is generally assumed that thalamic afferents reach L4 and L3c (Sanides and Hoffmann
1969; Sincich and Horton
2005). The presence in cetaceans of GABA-ergic interneurons in the upper layers (L1 to upper L3) may point out that inputs reach the cortex mainly via L1 instead of L4, as in rodents, primates, and carnivores. However, the presence of a strong neuropil signal at the border between L3 and L5 implies synapsing either to efferent neurons in lower layers, or potentially to the other cortical afferents ascending from white matter. Moreover, specific cases such as the sperm whale might even support the coexistence of both routes. The neuropil band in L3–L5 seen with CR and the dense neuronal fiber plexus in marginal zone/L1 seen in the Risso’s dolphin (Fig.
20) suggest that the cetacean cortex is far more complex than that of the hedgehog model (Morgane et al.
1990). Thus, thalamic inputs may not be limited to L1, but are probably dual, as found in other mammals, with matrix (M) thalamic inputs arriving via L1 and core thalamic inputs passing through L4 (Jones
1998; Rubio-Garrido et al.
2009). This in turn would require the existence of a
functional L4, albeit the neurons endowed with this role are diffuse in the neighboring L3 and L5.
Laterality
Stereopsis is a characteristic of several vertebrates and is present also in species whose eyes are placed laterally (Clarke et al.
1976; Hughes
1977; Ramachandran et al.
1977; Pettigrew et al.
1984; Timney and Keil
1999; Martin
2009; Nityananda and Read
2017). A lesser frontalization of the eyes means a much larger area devoted to monocular cortical representation, as is the case of the cat compared to primates (Sanides and Hoffmann
1969; Fox and Blake
1971). Nonetheless, neurons sensitive to ocular disparity have been found in the sheep and goat (Clarke and Witteridge
1976; Clarke et al.
1976,
1979a,
b). The 60° binocular field (overlap) of goats suggests that their high agility could rely on stereopsis (Howard and Rogers
1996), although no behavioral evidence seems to exist, unlike in the horse (Timney and Kiel
1992,
1999), in which binocular vision reaches 80° (Harman et al.
1999) (see Table
1).
The cost in terms of neuronal circuitry for stereopsis is substantial (Nityananda and Read
2017); therefore, the cortical architecture of mammals could be a reliable predictor for the existence of stereopsis, which is not easily demonstrated from eye features or behavioral experiments. Despite the lack of direct link between orbital plane and eye field (Hughes
1977), the gross segregation we made based on eye position (Fig.
31) did correlate quite strongly with the results obtained for the V1 cytoarchitecture morphometrics of the different species (Fig.
32). In particular, lateral-eyed specimens (cetaceans and amphibious species) had a notably lower density (Fig.
32,
p ≤ 0,01 for all but L1) and larger neuron size (perimeter and area in Fig.
32). Wide field animals (all terrestrial, all ungulates) had significantly lower density compared to frontal-eyed animals (primates), but were relatively similar in terms of size. Interestingly, wide-field animals had much more slender neurons (indicated by Extent in Fig.
32) than both frontal-eyed and lateral-eyed ones, which would tend to suggest the prevalence of pyramidal cells, or alternatively the relative lack of round granule cells as in primates.
The proposed statistical approach is nonparametric and multivariate in nature, it allows for a flexible and hierarchical exploration of the results while providing a valid inference in a multiple testing paradigm. In spite of this, in this work, the phylogenetic relatedness of the data are not accounted for. The lack of interaction of the relative phylogenetic distance on the data may partially dilute the solidity of the results. Within the parametric framework, the recommended tool is the phylogenetic generalized least squares (Symonds et al.
2014). The proposed method can account for this information (Winkler et al.
2014) as well. In spite of this, collecting phylogenetic information may be demanding, costly and was beyond the scope of this work. We do not exclude to use these in future work to further corroborate our claims.
The eyes of marine Cetartiodactyls are invariably placed laterally, allowing panoramic (120–130° on each side) view but little to no binocularity, with independent eye, eyelid and pupil movement (Mass and Supin
2007). As per the low density of ganglion neurons in the retina (about 500–750 per mm2, Murayama et al. 1992; Mass and Supin
2007) compared to terrestrial Cetartiodactyls (Hebel
1976; Shinosaki et al.
2010), the optic nerve is distinctively composed of fewer larger fibers in cetaceans compared to terrestrial mammals and humans (Dawson et al.
1983; Dral
1983; Jonas et aI.
1990; Mass and Supin
1990,
1997). Fibers in the optic nerve completely decussate in the chiasma and run contralaterally in the bottlenose dolphin. Some doubts remain in other species such as the porpoise (
Phocoena phocoena) or to a lesser degree in the minke whale (Morgane and Jacobs
1972). A narrow binocular field of view corresponding to the temporal opening of the opercular-shaped iris, and possible active accommodation were described in the bottlenose dolphin (Dral
1975). Additionally, bottlenose dolphins seem to visually recognize their surrounding environment similarly to primates (Tomonaga et al.
2014). Therefore, in selected delphinid species, the theoretical possibility of stereopsis could exist on these grounds but remains to be demonstrated. However, stereopsis must be excluded in species endowed with a large head and completely lateral eye, hence without binocular field, as the sperm whale and the fin whale.
It was clearly demonstrated that LGN connections are ipsilateral to at least V1, V2 and V3 in the cat and monkey (Wilson
1968). The few binocular cell studies have shown that in animals with almost total decussation, binocular cells have little in common with that of frontal-eyed species such as the cat or primates (Van Sluyters and Stewart
1974). On the other hand, Morgane and Jacobs (
1972) noted a significant loss (to the point of apparent
disappearance) of fibers at the chiasmatic level (up to 19% in the minke whale). These missing fibers might run to the hypothalamus and constitute a retino-hypothalamic connection, which is well known to exist in mammals and form a loop between the retinal ganglion cells, the suprachiasmatic nucleus and the intergeniculate leaflet of the thalamus (Pickard
1985). This connection alone is not sufficient to explain a 19% decrease, since the connection is made of collateral branches or retinofugal axons, which also reach the optic tract. The prevalence of retinothalamic projections compared to the incipient pretectal connection has also been compared to a “primate-like” pattern rather than that of carnivores. The latter was judged “puzzling” by Jacobs et al. (
1975) given the strong pupillary light reflex noted by Dral (
1972).
The canonical paradigm is that magnocellular (M), parvocellular (P) and koniocellular (K) ganglion cells provide separate routes through the optic nerve and the lateral geniculate nucleus, to reach separated sublayers in L4 and L3 of the visual cortex (Sincich and Horton
2005). However, L4 is all but evanescent in Cetartiodactyls and especially in cetaceans, with significant variations among species as portrayed in the present study. This poses the question of how these putative inputs reach the dedicated cortex. Since their retina seems to contain only L-opsins and rods (Jacobs
2009; Springer et al.
2016) implying colorblindness, does there remain separate pathways, which could be seen in the LGN and ending in different cortical layers? The retina comprises giant ganglion cells (Dawson
1973) and smaller ones, and different neuron sizes can have been reported in the LGN (Kruger
1959; Jacobs et al.
1975). Additionally, cetaceans could compensate their lack of cortical specialization by an increase in cortical surface (Morgane et al.
1990), and thereby explaining the myeloarchitectonic increase of L6, known to be the cortico-cortical connection site. Wiring strategies in developing vision and hearing follow different routes and targets (Rygvold et al.
2021; Sitko and Goodrich
2021) and may also rely on specific variation in the cortical column based on the presence and distribution of immature neurons in L2 and potential plasticity (La Rosa et al.
2020).
Conclusions
Our data suggest that the lateral position of the eyes in Cetartiodactyls is accompanied by specific organization, structure, and complexity of the visual cortex. Overall, said characteristics include lesser lamination, diminished density, and general apparent simplification of the cortical column. Changes are not linear across species, but comparison between Cetartiodactyls and Perissodactyls indicate either a feature present in a common ancestor, or a substantial parallel evolution, contrarily to what observed in primates.
Cetaceans, usually considered altogether as a group, include species (Families?) that present several types of cortical lamination which may reflect differences in function. Activity patterns of the sensory systems seems to heavily influence relative brain and neuronal allocation (Karlen and Krubitzer
2009). Toothed whales rely on echolocation for orientation and hunting, an activity than may be independent from the support of sight, at least in the Cuvier’s beaked whale and in the sperm whale.
Moreover, all cetaceans live in the aquatic environment, and inputs to V1 may reflect environmental conditions of fading luminance and contrast (Tang et al.
2021) due to light progressively absorbed with increasing depth of the water column.
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