Speakers

Prof. Robert Černý
Charles University Prague (CZ)

Shaping a Shape: Developmental Formation of Vertebrate Craniofacial Structures

Shape and shaping a shape, its developmental formation, were always among central issues of morphology, embryology and recently also of evolutionary-developmental biology. Craniofacial development, for its tremendous diversity and disparity in forms and formations, is undoubtedly a well-suited area for analyzing shape in both development and evolution. In my talk, shaping and developmental formation of several vertebrate craniofacial structures representing fundamental larval characters will be analyzed, including external gills or attachment organs. Despite remarkable similarities among these vertebrate traits it will be revealed that the same phenotypic form of these organs is developmentally arrived by dissimilar developmental processes and mechanisms. Exploring these examples of convergent similarity of phenotypes might provide insights into mechanisms generating diversity and test whether “descent with modification” may follow predictable pathways. The conceptual role of developmental constraints and their nature in shape formation will be discussed; shape and form represent certain attractors of spatial organization and integrated developmental and molecular pathways are evolutionary canalized to fit into well-tried forms.


Prof. Ed Connor
John Hopkins University (US)

Neural Representation of Shape in Primate Visual Cortex

Humans have a remarkable ability, unmatched by the best computer vision systems, to perceive, understand, and interact with shapes in the natural world. Our perception of shape depends on stage-wise transformation of image information in the ventral visual pathway of the brain. We use electrode recording from old world monkeys (an extremely close model for human vision) to reverse engineer transformation and representation of shape in the brain. We find that neural populations represent shapes as 3D spatial configurations of medial axis and surface fragments. Neurons act as filters tuned for the relative 3D position, 3D orientation, and 3D curvature of these shape fragments. This explicit representation of geometric information underlies our ability to understand, describe, and manipulate 3D structure.


Prof. Vittorio Ferrari
University of Edinburgh (GB)

Segmentation propagation in ImageNet

In Computer Vision the term 'shape' typically refers to the spatial arrangement of points on the outer boundary of an object. Several methods appeared for learning shape models of object classes, such as horses or mugs. Such a model typically entails a distribution over the possible shapes of objects in the class, and therefore compactly captures the valid range of intra-class variations. In order to learn a shape model, typically several images with manually segmented object outlines are required for each class. In this talk I will present a technique for automatically segmenting hundreds of thousands of images in the large scale ImageNet database, which could potentially be used to automate the learning of shape models. These auto-annotated bounding-boxes and segmentations are available for download at our website .


Prof. Massimo Ferri,
Bologna University (IT)

From Geometry to Topology in Shape Description

Is shape just geometric similarity? Surely not; on the other hand, the main topological type of equivalence, i.e., homeomorphism, is much too far from the human idea of "having the same shape". Still, this does not mean that we have to avoid mathematical tools in shape description, analysis, comparison, classification, retrieval...
We start from the work of Jan Koenderink, seeing how differential topology yields important cues for understanding shape, and we end up with ideas and applications of persistent homology.



Prof. Chaim Goodman-Strauss
University of Arkansas (US)

Big from small: local properties and global shape

Local properties give rise to global structure, wherever we look in sciences and mathematics: an algebraic group is determined by its generators and their relations; the universe itself arises from the physical properties of its constituents; the topology of a surface is largely determined by its local curvature; the theorems in a formal system are fixed by its deductive scheme — local rules describing how theorems follow one after another. This points to the deep and unsettling connection to the foundations of mathematical logic: in essence any system in which local rules give interesting global structure is inherently, provably, unknowable.



Prof. Isaac Salazar-Ciudad
Universitat Autònoma de Barcelona (ES)

Pattern Formation Models and the Direction of Evolutionary Change

Pattern formation mechanisms are a key to understanding morphological variation patterns and the relationship between genotype and phenotype. To understand the direction of morphological evolution one must understand which morphological variation is possible in each generation and which of it selected for by ecological factors. The former thing is not currently understood. This talk exemplifies how an understanding of the mechanisms of pattern formation during development can be used to explore this questions and the question of the relationship between phenotype and genotype. What is meant by pattern formation is the change over developmental time of one spatial distribution of cell types into another spatial distribution of cell types.
I will present theoretical work identifying the set of gene network topologies able to produce pattern formation and their properties. From that I will discuss work exploring the relative involvement of these in different contexts in development and evolution, and about the evolution of development in general. Work in more advanced and realistic models including not only cell signalling but also cell movement and growth will also be introduced, specially in relationship to the study of the genetic and developmental bases of multivariate complex morphological variation in natural populations.