Generation of Direction Selectivity by Isotropic Intracortical Connections

To what extent do the mechanisms generating different receptive field properties of neurons depend on each other? We investigated this question theoretically within the context of orientation and direction tuning of simple cells in the mammalian visual cortex. In our model a cortical cell of the "simple" type receives its orientation tuning by afferent convergence of aligned receptive fields of the lateral geniculate nucleus (Hubel and Wiesel 1962). We sharpen this orientation bias by postulating a special type of radially symmetric long-range lateral inhibition called circular inhibition. Surprisingly, this isotropic mechanism leads to the emergence of a strong bias for the direction of motion of a bar. We show that this directional anisotropy is neither caused by the probabilistic nature of the connections nor is it a consequence of the specific columnar structure chosen but that it is an inherent feature of the architecture of visual cortex

Continuous Simulation for Urban Energy Planning Based on a Non-Linear Data-Driven Modelling Approach

The thesis develops the argument for scale sensitive local energy planning, combining energy demand simulation with the development of continuous benchmarks. A non-linear data driven modelling approach is selected to represent space heating needs for urban areas. The model is applied to the scale of buildings, building clusters and neighbourhoods and compared to measured data in order to test its scalability. The results confirm the applicability of the approach to the scale of neighbourhoods