Variation of telencephalon morphology of the threespine stickleback (<i>Gasterosteus aculeatus</i>) in relation to inferred ecology

Park, Peter J.; Bell, Michael A.

doi:10.1111/j.1420-9101.2010.01987.x

Cited by 65 publications

(76 citation statements)

References 119 publications

(239 reference statements)

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“…Additionally, there are subtle differences in the shape of the tectum that influence the conformity of the tectum to an idealized half-ellipsoid, both among species and among individuals within a species. This reflects Park and Bell's [2010] finding that there are significant differences (both intraand gender-specific) in the shape of certain brain regions in threespine sticklebacks (Gasterosteus aculeatus) . Another factor that will influence how well the idealized half-ellipsoid model estimates tectum volume is the size of the ventricular cavity that the bilateral lobes of the optic tectum surround ( fig.…”

Section: Comparison Of Techniques Used To Determine Tectum Volumementioning

confidence: 82%

Allometric Scaling of the Optic Tectum in Cartilaginous Fishes

Yopak

Lisney

2012

Brain Behav Evol

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In cartilaginous fishes (Chondrichthyes; sharks, skates and rays (batoids), and holocephalans), the midbrain or mesencephalon can be divided into two parts, the dorsal tectum mesencephali or optic tectum (analogous to the superior colliculus of mammals) and the ventral tegmentum mesencephali. Very little is known about interspecific variation in the relative size and organization of the components of the mesencephalon in these fishes. This study examined the relative development of the optic tectum and the tegmentum in 75 chondrichthyan species representing 32 families. This study also provided a critical assessment of attempts to quantify the size of the optic tectum in these fishes volumetrically using an idealized half-ellipsoid approach (method E), by comparing this method to measurements of the tectum from coronal cross sections (method S). Using species as independent data points and phylogenetically independent contrasts, relationships between the two midbrain structures and both brain and mesencephalon volume were assessed and the relative volume of each brain area (expressed as phylogenetically corrected residuals) was compared among species with different ecological niches (as defined by primary habitat and lifestyle). The relatively largest tecta and tegmenta were found in pelagic coastal/oceanic and oceanic sharks, benthopelagic reef sharks, and benthopelagic coastal sharks. The smallest tecta were found in all benthic sharks and batoids and the majority of bathyal (deep-sea) species. These results were consistent regardless of which method of estimating tectum volume was used. We found a highly significant correlation between optic tectum volume estimates calculated using method E and method S. Taxon-specific variation in the difference between tectum volumes calculated using the two methods appears to reflect variation in both the shape of the optic tectum relative to an idealized half-ellipsoid and the volume of the ventricular cavity. Because the optic tectum is the principal termination site for retinofugal fibers arising from the retinal ganglion cells, the relative size of this brain region has been associated with an increased reliance on vision in other vertebrate groups, including bony fishes. The neuroecological relationships between the relative size of the optic tectum and primary habitat and lifestyle we present here for cartilaginous fishes mirror those established for bony fishes; we speculate that the relative size of the optic tectum and tegmentum similarly reflects the importance of vision and sensory processing in cartilaginous fishes.

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Section: Comparison Of Techniques Used To Determine Tectum Volumementioning

confidence: 82%

Allometric Scaling of the Optic Tectum in Cartilaginous Fishes

Yopak

Lisney

2012

Brain Behav Evol

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“…Previously studies that utilized the idealized ellipsoid method assumed that in closely related species volumetric overestimation was uniform [Pollen et al, 2007;Gonzalez-Voyer et al, 2009] as slight deviations in brain shape were not thought to be present at a species level. However, Park and Bell [2010] have recently demonstrated that not only do significant shape differences exist at a species level, but also that shape does not always correlate with the size of a brain region. The second assumption made when using either idealized ellipsoid method is that an external measure of a specific brain region does not include additional brain areas that are responsible for alternative behaviors or sensory abilities.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Assessment of Brain Volumes in Fish: Comparison of Methodologies

Ullmann¹,

Cowin

Collin³

2010

Brain Behav Evol

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When correlating brain areas with behavioral and environmental characteristics, a variety of techniques are employed. In fishes (elasmobranchs and teleosts), 2 methods, histology and the idealized ellipsoid and/or half-ellipsoid technique, are primarily used to calculate the volume of a brain area and therefore its relationship to social or ecological complexity. In this study on a perciform teleost, we have quantitatively compared brain volumes obtained using the conventional techniques of histology and approximating brain volume to an idealized ellipsoid (or half ellipsoid) and magnetic resonance imaging, an established clinical tool typically used for assessing brain volume in other vertebrates. Our results indicate that, when compared to brain volumes measured using magnetic resonance imaging of brain regions in situ, variations in brain shape and histological artifacts can lead to significant differences in brain volume, especially in the telencephalon and optic tecta. Consequently, in comparative studies of brain volumes, we advise caution when using the histological and/or ellipsoid methods to make correlations between brain area size and environmental, behavioral and social characteristics and, when possible, we propose the use of magnetic resonance imaging.

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“…These have identified mosaic patterns of brain evolution at a micro-evolutionary scale. Interpopulation differences in brain architecture, associated with environmental or behavioural variation, have been reported to affect telencephalon, optic tectum and cerebellum size in nine-spine sticklebacks (Pungitius pungitius) [40], telencephalon morphology in threespine sticklebacks (Gasterosteus aculeatus) [41] and cerebellum size in migratory brown trout (Salmo trutta) [42], independently of overall brain size. These suggest conclusions derived from the products of artificial selection are not aberrant but may accurately reflect the evolvability of brain structure.…”

Section: (A) Selective Decoupling Of Coevolving Traitsmentioning

confidence: 99%

Brain evolution and development: adaptation, allometry and constraint

2016

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Phenotypic traits are products of two processes: evolution and development. But how do these processes combine to produce integrated phenotypes? Comparative studies identify consistent patterns of covariation, or allometries, between brain and body size, and between brain components, indicating the presence of significant constraints limiting independent evolution of separate parts. These constraints are poorly understood, but in principle could be either developmental or functional. The developmental constraints hypothesis suggests that individual components (brain and body size, or individual brain components) tend to evolve together because natural selection operates on relatively simple developmental mechanisms that affect the growth of all parts in a concerted manner. The functional constraints hypothesis suggests that correlated change reflects the action of selection on distributed functional systems connecting the different sub-components, predicting more complex patterns of mosaic change at the level of the functional systems and more complex genetic and developmental mechanisms. These hypotheses are not mutually exclusive but make different predictions. We review recent genetic and neurodevelopmental evidence, concluding that functional rather than developmental constraints are the main cause of the observed patterns. How brains evolve: the importance of scaling relationshipsThe components of any adaptive complex by definition undergo coordinated evolution. Brains, bodies and individual brain components therefore exhibit distinctive patterns of correlated evolution. But what do these patterns tell us about the roles of adaptation and constraint in shaping phenotypes? In particular, how and to what extent do constraints imposed by shared developmental programmes dictate allometric relationships between components, limiting their response to selection? These questions have shaped two key debates central to how we view brain evolution: the functional relevance of brain size and the adaptive potential of brain structure [1][2][3]. These debates hinge on whether observed patterns of scaling relationships, between brain and body size or different brain components, are the product of selection to maintain functional correspondence or constraints imposed by shared developmental programmes. Crucially, however, a sound understanding of the significance of scaling relationships in brain evolution has been limited by a lack of data on the genetic and developmental mechanisms that regulate brain size and structure. Here we discuss how recent discoveries about the genetic control of neural development shed new light on the issue.(a) Brain: body coevolution and the importance of size

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Variation of telencephalon morphology of the threespine stickleback (Gasterosteus aculeatus) in relation to inferred ecology

Cited by 65 publications

References 119 publications

Allometric Scaling of the Optic Tectum in Cartilaginous Fishes

Allometric Scaling of the Optic Tectum in Cartilaginous Fishes

Quantitative Assessment of Brain Volumes in Fish: Comparison of Methodologies

Brain evolution and development: adaptation, allometry and constraint

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