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Project A1 - Neural Circuits for Motion Detection: From 3D-Reconstruction to Computational Modeling

Alexander Borst (MPI) and Bert Sakmann (MPI)

We think that neural algorithms for processing of sensory signals are shaped by the connectivity structure of the respective sensory systems. Identifying synaptic contacts requires electron microscopy, which previously meant that many serial ultra-thin sections had to be taken by hand and manually aligned. To achieve a 3D-reconstruction of the neural processes, human experts identified the contour lines of interest within each section. These steps can now be automated, thanks to the Serial Block Face Scanning Electron Microscopy (SBFSEM) technique [1] and efficient pattern recognition algorithms for contour detection [2].

Objectives and description of the project

In close collaboration with Winfried Denk (Heidelberg), we plan to study the circuits underlying visual [A. Borst] and somato-sensory [B. Sakmann] motion detection in flies and rodents, respectively. We think that biological motion detection relies on spatio-temporal correlations emerging from the circuit’s computations on the incoming sensory signals; by refining our knowledge of the circuitry, we seek to elucidate the neural basis of elementary motion detection in the fly [3] and understand computation within a cortical column of the rodent barrel cortex [4-6]. For the Drosophila visual system, we will use transgenic flies expressing membrane-tagged HRP. For the cortical tissue, HRP will be injected in the extracellular space. Work on this project will also improve existing algorithms to automatically trace contours in 3D image stacks, which can be used to build detailed network simulations based on multi-compartment models for each cell [7,8].

[1]: Denk & Horstmann, PLoS Biol 2004, [2]: Macke et al. J Neurosci Methods 2008, [3]: Joesch et al. Current Biology 2008, [4]: Helmstaedter et al. Brain Res Rev 2008, [5]: Helmstaedter et al. J Neurosci 2008, [6]: Helmstaedter et al. Cerebral Cortex 2009, [7]: Cuntz et al. PNAS 2003, [8]: Cuntz et al. PNAS 2007.