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The dissertation deals with the general problem of how the brain can establish correspondences between neural patterns stored in different cortical areas. Although an important capability in many cognitive areas like language understanding, abstract reasoning, or motor control, this thesis concentrates on invariant object recognition as application of correspondence finding. One part of the work presents a correspondence-based, neurally plausible system for face recognition. Other parts address the question of visual information routing over several stages by proposing optimal architectures for such routing ('switchyards') and deriving ontogenetic mechanisms for the growth of switchyards. Finally, the idea of multi-stage routing is united with the object recognition system introduced before, making suggestions of how the so far distinct feature-based and correspondence-based approaches to object recognition could be reconciled.
Lisa Handels Beitrag geht in der Lösung des Spiels von seiner Bezogenheit auf ein Subjekt oder ein Leben, das über Bewusstsein verfügt, wohl am weitesten. Das führt Handel allerdings nicht zur mythischen oder religiösen Idee des kosmischen Spiels, sondern zu einem 'earthly play', wie sie es mit der Biologin Lynn Margulis formuliert. Im Zentrum der Evolutionstheorie von Margulis steht die These, dass komplexe Formen des Lebens aus einer Symbiose von einzelligen Lebewesen entstehen und dass dies auch die Anwesenheit von bakterieller Fremd-DNA im Cytoplasma der Zellen mit Zellkern erkläre. Ontogenese ist damit aber nicht mehr als eine Autogenese und wurzelförmige Entwicklung darstellbar, sondern als ein Werden-Mit, ein Spiel heterogener Lebewesen. In "Zoo City", einem Cyberpunk-Roman von Lauren Beukes, in dem es um die Ausbreitung prekärer symbiontischer Existenzweisen zwischen menschlichen und nichtmenschlichen Tieren geht, sieht Handel eben diese Heterogenese in einem literarischen Spiel ausbuchstabiert.
This dissertation connects two independent fields of theoretical neuroscience: on the one hand, the self-organization of topographic connectivity patterns, and on the other hand, invariant object recognition, that is the recognition of objects independently of their various possible retinal representations (for example due to translations or scalings). The topographic representation is used in the presented approach, as a coordinate system, which then allows for the implementation of invariance transformations. Hence this study shows, that it is possible that the brain self-organizes before birth, so that it is able to invariantly recognize objects immediately after birth. Besides the core hypothesis that links prenatal work with object recognition, advancements in both fields themselves are also presented. In the beginning of the thesis, a novel analytically solvable probabilistic generative model for topographic maps is introduced. And at the end of the thesis, a model that integrates classical feature-based ideas with the normalization-based approach is presented. This bilinear model makes use of sparseness as well as slowness to implement "optimal" topographic representations. It is therefore a good candidate for hierarchical processing in the brain and for future research.