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The brain is a complex network of billions of nerve cells giving rise to our cognitive abilities. Understanding the structure of this network is an important step in understanding how it functions. Today the field of Neuroscience has entered the age of connectomics, with the ultimate goal of providing a comprehensive description of the physical coupling among all neural elements of the brain. Consequently, great efforts are devoted to studying brain network structure at multiple scales: from the detailed connectivity of local neural circuits comprising small numbers of neurons to the large scale connection patterns between entire brain areas, comprising hundreds of millions of nerve cells. The multi-scale network structure is studied directly both at the anatomical or structural level and at the functional level defined by the activity patterns of neural elements. Since both anatomical and functional connectivity patterns change across different time scales, the dynamics of brain connectivity and its relation to learning and adaptation are also of great importance.

Recent progress in experimental techniques as well as continuous advances in information technology have led to improved reconstructions of small circuits at a scale of millimeters and large-scale wiring patterns between entire brain areas in different species. High throughput approaches promise to produce data sets of unprecedented size at unprecedented speed. But just as deciphering the genome hasn’t meant that we now understand genetic networks, charting the brain’s wiring diagram will not mean that we will understand its function. To fully capitalize on the new technological developments in obtaining wiring diagrams of the brain, the refinement of experimental techniques must be accompanied by corresponding computational and theoretical developments. Specifically, as experimental techniques are maturing, there is a growing need to develop new computational approaches to facilitate the automated reconstruction of connectivity from experimental approaches, to support the curation and open-access distribution of large-scale data sets, to undertake systematic analysis of complex connectivity networks, as well as computational modeling, and ultimately understanding of these data sets. The Computational Connectomics SPP addresses this growing need. Our SPP is also supporting the German Computational Connectomics Network (GCCN).

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News

Brain Connectivity Workshop 2021

The annual Brain Connectivity Workshop (BCW) 2020 for in-depth discussion of all aspects of brain connectivity has been postponed to 2021 because of the COVID-19 pandemic. It is scheduled for …

Dynamic Connectome Online Workshop Schedule

The Dynamic Connectome A workshop of SPP2041 Computational Connectomics Date:                    October 15, 2020 Location:             https://us02web.zoom.us/j/83945542743 Organizers:        Jochen Triesch, Frankfurt Institute for Advanced Studies, Germany                           Claus Hilgetag, University Medical Center Hamburg-Eppendorf, Germany Schedule (all …