Evolutionary Biology
Shape Analysis for Phenomics with 3D Imaging Data (SAPID)
Project Description
Sophisticated imaging technologies such as MRI and CT provide the ability to detect and measure subtle and complex anatomical variations among organisms, thus offering powerful insight into evolutionary processes. Following the success of our NSF-funded Digital Fish Library Project (DFL) (DBI-0446389) which developed methods for imaging, visualizing, and archiving large 3D volumetric datasets, we recognized the need to develop methods that facilitated the quantitative analysis of this emergent 3D imaging data for evolutionary comparative morphology. This led to the NSF-funded Shape Analysis for Phenomics with 3D Imaging Data (SAPID) project (DBI-1147260), which had the overarching goal of developing new image analysis and registration methods for high resolution anatomical data, in parallel with the adaptation of new methods developed for the analysis of multivariable, multimodal human neuroimaging data for use in comparative morphology.
The SAPID project set out to solve two important technological issues involved in the application of shape analysis to 3D volumetric data to phenomics: 1) characterizing and 2) comparing shapes. Characterizing shapes involves shape analysis and is done on single specimens, while comparing shapes involves image registration and is done between specimens.
One of the major developments of this project has therefore been our spherical wave decomposition (SWD) method, developed for volumetric segmentation and shape analysis of high resolution anatomical (HRA) data. The SWD method provides a general computational solution for geometric characterization and analysis of complex morphological shapes, such as brains, bones, and other structures, and even whole organisms, as has been applied to the quantitative analysis of brain shape in cartilaginous fishes as an initial demonstration of its utility for comparative morphology (see Yopak et al., 2016). The second major development of this project has been the Symplectomorphic Registration using Entropy Spectrum Pathways (SYMREG-ESP) method, which provides a method for non-linear registration of volumetric data from multiple specimens to compare their shape. Together, these new analysis methods, which we call the SAPID Toolkit (or STK) provide a robust approach for the quantitative statistical assessment of morphological variation and have the potential to transform the way evolutionary morphology research is performed. These methods also significantly enhance the utility of the vast and growing resource of volumetric data currently being stored in publicly-funded specimen databases such as MorphoSource and DigiMorph. CSCI’s ultimate goal is to automate the archiving and analysis of this data.
The SAPID STK analysis methods are currently being integrated into the NSF-funded QUEST-NI and QUEST-WX software applications (ABI-1550405), which is allowing access to these methods regardless of the computational expertise or resources available to the user. The QUEST-NI software is available via the Software links below.
Publications
Berquist RM, Galinsky VL, Kajiura SM, Frank LR. The coelacanth rostral organ is a low-resolution electro-detector that facilitates the strike. Sci Reps 5: 8962, 2015.
Galinsky VL, Frank LR. Automated segmentation and shape characterization of volumetric data. Neuroimage 92: 156-168, 2014.
Galinsky VL, Frank LR. A unified theory of neuro-MRI data shows scale–free nature of connectivity modes. Neural Comput, 29(6): 1441-67, 2017.
Galinsky VL, Frank LR. Symplectomorphic registration with phase space regularization by entropy spectrum pathways. Magn Reson Med (Accepted), 2018.
Yopak KE, Berquist RM, Galinsky VL, Frank LR. Quantitative classification of cerebellar foliation in cartilaginous fishes (Class: Chondrichthyes) using 3D shape analysis and its implications for evolutionary biology. Brain Behav Evol, 87(4): 252-264, 2016.
Software
Structural and Functional Morphology in Fishes
Project Description
CSCI's research on functional morphology in fishes has involved a number of collaborative projects on a variety of different species. For example, one of our most recent studies involved investigations into variations in structural and functional brain morphology in cartilaginous fishes (sharks, skates, rays, and chimaeras). This work utilized high resolution anatomical and functional MRI to quantitatively characterize the diversity of brain shapes among different species and to elucidate patterns in neural connectivity. Despite the importance of their basal place in vertebrate evolution, little more than qualitative data had previously been available on variations in brain size and organization in these fish, and the implications these morphological variations may have for evolutionary adaptations in physiology and behavior had not yet been quantitatively explored. We were able to use powerful, cutting-edge imaging technology and image analysis methods to obtain high-resolution brain images from different cartilaginous fishes, not only occupying a variety of habitats but also exhibiting phylogenetic diversity. For example, using specialized software, these methods enabled us to digitally segment the five major brain structures (telencephalon, diencephalon, mesencephalon, cerebellum, and medulla) and provide new data on structure volume, surface area, and surface curvature in these animals. This data was then compared between species to elucidate some of the potential evolutionary selective pressures that shaped the early vertebrate brain.
This work was supported by a number of NSF grants, including the Digital Fish Library project (DBI-0446389), The Evolutionary Origins of the Vertebrate Brain: Neural Organization (ABI-EF-0850369), EAGER: Brain Responses to Visual Stimuli in Sharks Using Functional (DBI-1143389), and Shape Analysis for Phenomics with 3D Imaging Data (SAPID) (DBI-1147260).
Publications
Berquist RM, Galinsky VL, Kajiura SM, Frank LR. The coelacanth rostral organ is a low-resolution electro-detector that facilitates the strike. Sci Reps 5: 8962, 2015
Chakrabarty P, Davis MP, Smith WL, Berquist R, Gledhill KM, Frank LR, Sparks JS. Evolution of the light organ system in ponyfishes (Teleostei: Leiognathidae). J Morphol 272: 704-21, 2011
Graham JB, Wegner NC, Miller LA, Jew CJ, Lai NC, Berquist RM, Frank LR, Long JA. Spiracular air breathing in polypterid fishes and its implications for aerial respiration in stem tetrapods. Nat Commun 5: e3022, 2014.
Perry CN, Cartamil DC, Bernal D, Sepulveda CA, Theilmann RJ, Graham JB, Frank LR. Quantification of red myotomal muscle volume and geometry in the shortfin mako shark (Isurus oxyrinchus) and the salmon shark (Lamna ditropis), using T1-weighted magnetic resonance imaging. J Morphol 268: 284-92, 2007.
Rogers B, Lowe CG, Fernandez-Juricic E, and Frank LR. Ultilizing magnetic resonance imagining (MRI) to assess the effects of angling- induced barotraumas on rockfish (Sebastes). Can J Fish Aquat Sci 65: 1245-1249, 2008
Runcie RM, Dewar H, Hawn DR, Frank LR, Dickson KA. Evidence for cranial endothermy in the opah (Lampris guttatus). J Exp Biol 212: 461-70, 2009
Sepulveda CA, Dickson KA, Frank LR, Graham JB. Cranial endothermy and a putative brain heater in the most basal tuna species, Allothunnus fallai. J Fish Biol 70: 1720-1733, 2007
Yopak KE, Frank LR. Brain size and brain organization of the whale shark, Rhincodon typus, using magnetic resonance imaging. Brain Behav Evol, 74: 121-142, 2009.
Yopak KE, Berquist RM, Galinsky VL, Frank LR. Quantitative classification of cerebellar foliation in cartilaginous fishes (Class: Chondrichthyes) using 3D shape analysis and its implications for evolutionary biology. Brain Behav Evol, 87(4): 252-264, 2016.
Yopak, K.E. and Frank, L.R. Variation in cerebellar foliation in cartilaginous fishes: Ecological and behavioral considerations. Brain, Behavior, and Evolution 70: 210, 2007