The widespread variation in brain size and complexity that is evident in sharks and holocephalans is related to both phylogeny and ecology. Relative brain size (expressed as encephalization quotients) and the relative development of the five major brain areas (the telencephalon, diencephalon, mesencephalon, cerebellum, and medulla) was assessed for over 40 species from 20 families that represent a range of different lifestyles and occupy a number of habitats. In addition, an index (1–5) quantifying structural complexity of the cerebellum was created based on length, number, and depth of folds. Although the variation in brain size, morphology, and complexity is due in part to phylogeny, as basal groups have smaller brains, less structural hypertrophy, and lower foliation indices, there is also substantial variation within and across clades that does not reflect phylogenetic relationships. Ecological correlations, with the relative development of different brain areas as well as the complexity of the cerebellar corpus, are supported by cluster analysis and are suggestive of a range of ‘cerebrotypes’. These correlations suggest that relative brain development reflects the dimensionality of the environment and/or agile prey capture in addition to phylogeny.

Several patterns of brain allometry previously observed in mammals have been found to hold for sharks and related taxa (chondrichthyans) as well. In each clade, the relative size of brain parts, with the notable exception of the olfactory bulbs, is highly predictable from the total brain size. Compared with total brain mass, each part scales with a characteristic slope, which is highest for the telencephalon and cerebellum. In addition, cerebellar foliation reflects both absolute and relative cerebellar size, in a manner analogous to mammalian cortical gyrification. This conserved pattern of brain scaling suggests that the fundamental brain plan that evolved in early vertebrates permits appropriate scaling in response to a range of factors, including phylogeny and ecology, where neural mass may be added and subtracted without compromising basic function.T he allometric relationship of brain parts to overall brain size has been studied and debated extensively (1-7). At the core of the debate lies the question of whether the brain is best characterized as a collection of independently varying structures/devices evolved for particular behavioral requirements or niches or as a single coordinated processing structure/device in which adaptation for species-specific behavioral capacities occurs without the production of delineable modules (8, 9). Many methodological issues have arisen as well, including what about a brain should be quantified [cells or volumes (10)], what should be compared and how, and how to take into account the statistical dependence of both structural and species relationships (11).Until recently, a single data corpus comprising primates, bats, and insectivorous mammals was the sole source for comparison (2), leaving the question of whether these mammals represented all vertebrates, or even all other mammals, unresolved. The addition of carnivorous mammals (including marine mammals), ungulates, xenarthrans, and the manatee demonstrated that the original conclusions drawn from primates, bats, and insectivores could be extended to this larger data set (8, 12). These studies revealed that mammalian brain structure exhibits a pattern of variation containing two principal components. The first component, accounting for ≈96% of the total variance of related brain parts to total brain size, loads most highly on neocortex and cerebellum. The second component loads most highly on the olfactory bulb and associated limbic structures and accounts for ≈3% of the original variance. Each brain part also has a characteristic slope with respect to absolute brain size, such that every large mammalian brain is composed disproportionately of neocortex and cerebellum. The remaining 1% of the variance must subsume all remaining sources, including niche, sex and individual differences, and measurement error. This 1% contribution is large in one sense: In two species with the same brain size, a single structure might differ by a factor of 2.5. The total range of structure sizes may differ by a factor of 100,000 or more b...

The total number, distribution and peak density of presumed retinal ganglion cells was assessed in 10 species of elasmobranch (nine species of shark and one species of batoid) using counts of Nissl-stained cells in retinal wholemounts. The species sampled include a number of active, predatory benthopelagic and pelagic sharks that are found in a variety of coastal and oceanic habitats and represent elasmobranch groups for which information of this nature is currently lacking. The topographic distribution of cells was heterogeneous in all species. Two benthic species, the shark Chiloscyllium punctatum and the batoid Taeniura lymma, have a dorsal or dorso-central horizontal streak of increased cell density, whereas the majority of the benthopelagic and pelagic sharks examined exhibit a more concentric pattern of increasing cell density, culminating in a central area centralis of higher cell density located close to the optic nerve head. The exception is the shark Alopias superciliosus, which possesses a ventral horizontal streak. Variation in retinal ganglion cell topography appears to be related to the visual demands of different habitats and lifestyles, as well as the positioning of the eyes in the head. The upper limits of spatial resolving power were calculated for all 10 species, using peak ganglion cell densities and estimates of focal length taken from cryo-sectioned eyes in combination with information from the literature. Spatial resolving power ranged from 2.02 to 10.56 cycles deg^–1, which is in accordance with previous studies. Species with a lower spatial resolving power tend to be benthic and/or coastal species that feed on benthic invertebrates and fishes. Active, benthopelagic and pelagic species from more oceanic habitats which feed on larger, more active prey, possess a higher resolving power. Additionally, ganglion cells in a juvenile of C. punctatum, were retrogradely-labeled from the optic nerve with biotinylated dextran amine (BDA). A comparison of the BDA- labeled material and tissue stained for Nissl substance indicates that 76% of the cells in the retinal ganglion cell and inner plexiform layers of the central retina in this species are non-ganglion cells.

Relatively little is known about the physical structure and ecological adaptations of elasmobranch sensory systems. In particular, elasmobranch vision has been poorly studied compared to the other senses. Virtually nothing is known about whether elasmobranchs possess multiple cone types, and therefore the potential for colour vision, or how the spectral tuning of their visual pigments is adapted to their different lifestyles. In this study, we measured the spectral absorption of the rod and cone visual pigments of the blue-spotted maskray, Dasyatis kuhlii, using microspectrophotometry. D. kuhlii possesses a rod visual pigment with a wavelength of maximum absorbance (lambda(max)) at 497 nm and three spectrally distinct cone types with lambda(max) values at 476, 498 and 552 nm. Measurements of the spectral transmittance of the ocular media reveal that wavelengths below 380 nm do not reach the retina, indicating that D. kuhlii is relatively insensitive to ultraviolet radiation. Topographic analysis of retinal ganglion cell distribution reveals an area of increased neuronal density in the dorsal retina. Based on peak cell densities and using measurements of lens focal length made using laser ray tracing and sections of frozen eyes, the estimated spatial resolving power of D. kuhlii is 4.10 cycles per degree.