The Seung Lab

Education

• 2009- Post-doc, Massachusetts Institute of Technology (MIT)
• 2007-2008 Post-doc, Max-Planck-Institute for Biological Cybernetics in Tübingen / Germany
• 2007 Ph.D. (Dr. rer. nat.) in Computer Science, University of Ulm / Max-Planck-Institute for Biological Cybernetics in Tübingen / Germany

Keywords

Research Interest

The emerging field of Connectomics pushes the automatization of precise cutting and imaging of biological tissue samples at electron-microscopic resolution. This allows neuroscientists for the first time to analyze large volumes of brain tissue in 3D, to study the actual connectivity of networks of neurons.

To this end, I am collaborating with the lab of Jeff Lichtman at Harvard University, where methods of automated ultramicrotome tissue cutting, slice collection and imaging in electron microscopes are developed. Slices are typically thinner than 30 nm, and stacks of thousands of such slices can be cut and collected reliably. Very large electron-microscopic images are then taken at very high resolution (i.e., 32k*32k pixels at 0.8 nm pixel size).

The Seung Lab specializes in automating the analysis of such image stacks. This involves aligning the images in the stacks to produce a consistent 3D volume, segmenting the volume into individual neurons and pieces of neurons, finding synapses, and analyzing the connectivity.

My work so far involved the alignment and stitching of very large image stacks, manual labeling of neurites and synapses in those data sets, 3D rendering of those objects, and analysis of local connectivity. This work was introduced in my PI's TED talk, "I am my connectome". I also wrote software to help the acquisition of large electron-microscopic image stacks in the Lichtman Lab, and I have recently also done tissue preparations for electron microscopy as well as ultra-thin cutting.

Selected Publications

• Berger DR, Schulte-Pelkum J and Bülthoff HH (2010). Simulating believable forward accelerations on a Stewart motion platform. ACM Transactions on Applied Perception 7(1:5) 1-27. [ACM Link]
• Berger DR and Bülthoff HH (2009). The role of attention on the integration of visual and inertial cues.
  Experimental Brain Research 198(2-3) 287-300. [PubMed] [Fulltext]
• Berger DR (2008). Towards automatic and fast segmentation in SBFSEM image stacks. Computational and Systems Neuroscience Conference 2008 (COSYNE), 2008(II-83). [Abstract] [Poster]
• MacNeilage PR, Banks MS, Berger DR and Bülthoff HH (2007). A Bayesian model of the disambiguation of gravitoinertial force by visual cues. Experimental Brain Research 179(2) 263-290. [PubMed]
• Berger DR, Terzibas C, Beykirch K and Bülthoff HH (2007). The role of visual cues and whole-body rotations in helicopter hovering control. In: AIAA 2007, AIAA Modeling and Simulation Technologies Conference and Exhibit (MST), American Institute of Aeronautics and Astronautics, Reston, VA, USA, 1-13. [Fulltext]
• Berger DR (2007). Sensor Fusion in the Perception of Self-Motion, Doctoral Thesis, MPI for Biological Cybernetics / Universität Ulm. [Fulltext] [Book]
• Berger DR (2003). Spectral Texturing for Real-Time Applications, Siggraph 2003 Sketch, San Diego, CA. [Abstract] [Link] [ACM Link]