Project Details
SPP 2041: Computational Connectomics
Subject Area
Biology
Computer Science, Systems and Electrical Engineering
Mathematics
Medicine
Physics
Computer Science, Systems and Electrical Engineering
Mathematics
Medicine
Physics
Term
since 2017
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 313856816
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. The field of Connectomics has the ultimate goal of providing a comprehensive description of the physical coupling among all neural elements of the brain. In this context, 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 both directly 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 development, learning and adaptation are also of great importance. Progress in experimental techniques as well as continuous advances in information technology have led to improved reconstructions of brain circuits at all scales in different species. High throughput approaches 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, to support the curation and open-access distribution of large-scale data sets, to undertake systematic analyses of complex connectivity networks, as well as to model and ultimately understand these data sets. The Computational Connectomics SPP addresses this growing need and will advance our understanding of the relationship between brain structure and function.
DFG Programme
Priority Programmes
International Connection
Japan, Spain
Projects
- Cellular, connectional and molecular heterogeneity in a large-scale computational model of the human cerebral cortex (Applicants van Albada, Sacha Jennifer ; Dickscheid, Timo ; Hilgetag, Claus Christian )
- Clinical Connectomics: A network approach to deep brain stimulation (Applicants Hamker, Fred Henrik ; Kühn, Andrea ; Ritter, Petra )
- Combining theory and experiments to infer how recurrent and top-down connectivity in the corticothalamic circuit gives rise to V1 selectivity (Applicants Busse, Laura ; Tchumatchenko, Tatjana )
- Computational and Physiological Approaches to the Primate Anxiety Connectome (Applicant Dayan, Peter )
- Computational connectomics of the cockroach circadian clock (Applicants Herzel, Hanspeter ; Stengl, Monika )
- Connectome based modelling to reveal multi-scale mechanisms in stroke (Applicants Gerloff, Christian ; Ritter, Petra )
- Coordination Funds (Applicant Triesch, Jochen )
- Functional connectomics of the binocular optic flow processing circuit in zebrafish (Applicants Denk, Winfried ; Kubo, Fumi )
- High resolution connectivity analysis of CA3/ DG engrams: from behavior to structure (Applicants Beck, Heinz ; Kubitscheck, Ulrich ; Schwarz, Ph.D., Karl Martin )
- Machine-learning on brain connectomics: Individual prediction of cognitive functioning in health and cerebral small vessel disease (Applicants Eickhoff, Simon ; Thomalla, Götz )
- Multi-scale analysis and computational modeling of intrinsic coupling modes in the ferret brain (Applicants Engel, Andreas K. ; Hilgetag, Claus Christian )
- Next Generation Connectomics: Laminar and Spectral Specificity (Applicants Scheffler, Ph.D., Klaus ; Siegel, Markus )
- Predicting the Impact of Connectomes on Cortical Function using Statistical Inference (Applicants Baum, Daniel ; Macke, Jakob ; Oberlaender, Marcel )
- The comprehensive microstructural human connectome (COMIC): from long-range to short-association fibres (Applicants Kirilina, Evgeniya ; Mohammadi, Siawoosh ; Morawski, Ph.D., Markus ; Weiskopf, Nikolaus )
- The dynamic connectome: dynamics of learning (Applicants Kaschube, Matthias ; Rumpel, Simon ; Triesch, Jochen )
- The dynamic connectome underlying language in the brain (Applicants Anwander, Alfred ; Deco, Gustavo ; Friederici, Angela ; Knösche, Thomas )
- The Language Connectome in Brain Tumor Patients (Applicants Fekonja, Lucius ; Picht, Thomas ; Ritter, Petra )
- The role of dynamic neural functional coupling in spontaneous thoughts (Applicant Schuck, Nicolas )
- Towards a connectomics-based predictive model of the inner retina (Applicants Berens, Philipp ; Briggman, Ph.D., Kevin ; Euler, Thomas )
Spokesperson
Professor Dr. Jochen Triesch