Biological Information in Cortical Communication

Biological systems have evolved at many scales, ranging from molecular pathways to organism behavior to interspecies symbiosis. At each level, operational principles can be identified which help us to form quantitatively meaningful models. In this project, we aim at a particularly poorly under-stood level of mammalian systems which is responsible for most mammalian behaviors: the form of information processing between cortical areas. Anatomy, electrophysiology, and fMRI all make it abundantly clear that specific cortical areas communicate specific types of information with each other to accomplish specific tasks. Given the relatively uniform layered pattern of cells forming the neocortex, including the interareal axonal projections, it seems certain that general information processing principles must be at work. However, surprisingly little is known about these principles. Biological data on the exact form of the information transmitted by these projections is technically very difficult if not impossible to measure directly.

The aim of this project is to develop in silico simulations of possible dynamic interplays among areas of the visual pathway. Cortical processing of visual input is known to use a distributed representation, with different areas encoding different aspects of the visual interpretation. In this project we test the general applicability of such types of models to visual processing tasks (like depth perception, three-dimensional information processing, and incorporation of other sensory inputs) and thereby develop a set of principles of inter-areal communication which can be used not only in systems of our own design, but also to allow quantitative predictions regarding the mammalian visual system’s structure and dynamics.