topic Hightech Strategy

National Network Computational Neuroscience

The human brain is one of the most complex results of biological evolution. Investigating its function is a major scientific challenge: How does the brain work? Which scientific insights can be translated to applications in information technology or to the field of education? Innovations that result from a deeper understanding of the brain's function deserve every effort: prostheses that react to nerve impulses and that can 'feel', a treatment for Alzheimer's disease or developing some form of artificial intelligence might become possible.

The brain consists of billions of neurons which are interlinked in networks with multiple feedback loops. By complex dynamic processes, neurons interact with each other and thereby process enormous amounts of information. Within this network of connections, sensory inputs are transmitted through weak electrical impulses. In this way, our neurons work incessantly on processing sensory impressions and on controlling our behavior.

Up until today, these neuronal processes are only partially scientifically understood. The concept of computational neuroscience aims at deciphering the neuronal basis of the brain's performance, simulating it in computer models and thereby accelerating progress in research.

The research field of computational neuroscience encompasses the elucidation of the neuronal principles of all levels of brain functions - ranging from the processing of complex sensory stimuli through learning processes up to the recall of stored information and the planning and precise coordination of behaviorally relevant movement patterns. The highly dynamic discipline of computational neuroscience combines experiments, data analysis and computer simulations on the basis of well-defined theoretical concepts. This research approach requires targeted and interdisciplinary cooperation between the neurosciences, biology, medicine, physics, mathematics, and computer science.

The results of this research can be translated to medical applications, e.g. for the development of prostheses and tools for paraplegics or stroke patients. In the educational sector, the results of computational neuroscience research may lead to an improved scientific understanding of cognitive processes in the course of learning. In computer science, new approaches to robot control and the development of high performance computing may be derived from insights into the neuronal principles of information processing.

With specific funding, the Federal Ministry of Education and Research aims at stimulating the innovative potential of the neurosciences in Germany. With the National Network Computational Neuroscience it has established a structure that focuses, supports and interconnects the existing excellent expertise in the experimental and theoretical neurosciences in Germany and thereby increases its international visibility. 

Bernstein Centers for Computational Neuroscience

Core structural elements of the National Network are the four Bernstein Centers for Computational Neuroscience in Berlin, Freiburg, Göttingen and Munich. The Centers were named after the German physiologist Julius Bernstein (1839 - 1917) who, with his 'membrane theory', provided the first biophysical explanation for the transmission of information in neurons (action potentials). The 'membrane theory' is regarded the first really quantitative theory in the neuroscientifically crucial field of electrophysiology. In honor of his scientific achievements, the BMBF conferred the name and predicate "Bernstein Centers for Computational Neuroscience" to the founded centers.
Within the Bernstein Centers, scientists from different disciplines like mathematics, physics, biology, medicine, computer science and neurosciences collaborate to decode the secrets of human thinking, and to unravel the principles of neural information processing and the development of diseases.

Bernstein Award

Since 2006, the German Federal Ministry of Education and Research (BMBF) annually confers the "Bernstein Award for Computational Neuroscience" to excellent junior scientists with outstanding research ideas in the field of computational neuroscience. The award is announced internationally and is equipped with up to 1.25 Mio Euros. The funding allows the awardees to establish their own research group at a German research institution.

The Bernstein Award 2008 was conferred during the annual Bernstein Symposium. The award winner was the 32 year old Dr. Susanne Schreiber from the Humboldt-Universität zu Berlin. Her work will contribute to a better understanding of how cellular malfunctions arise in the molecular setup of neurons. This may lead to new insights into and treatments of diseases like epilepsy.

Bernstein Partner

The four Bernstein Centers for Computational Neuroscience have achieved a new quality of concentration of the existing neuroscientific potential in Germany and have allowed enhancing the integration of theoretical approaches. To improve the integration of further capacities from the field of computational neuroscience into the National Network, since 2007, the BMBF supports Bernstein Partner projects.

1. With five Bernstein Groups (in Bochum, Bremen, Heidelberg, Jena and  Magdeburg) new local structural centers were established that extend the Bernstein Centers' range of research approaches. The following research themes are studied within the Bernstein Groups:
2. • Dynamics of neuronal networks
   • Functional adaptation of the visual cortex
   • Modelling signal processing as well as cognitive functions in neurons resp. neuronal networks
   • Neuronal processing of pain
3. With eleven topically focused Bernstein Collaborations, the Bernstein Centers are interconnected with mainly experimentally working partners throughout Germany. In Bernstein Collaborations, the following research themes are investigated:
4. • Information coding of sensory stimuli (hearing, smelling)
   • Various modern imaging techniques
   • Methods for the measurement and analysis of neuronal activities with respect to memory
   • Neuronal basis of epilepsy
   • Plasticity of the visual cortex
   • Non-invasive brain-computer interfaces for the development of neuroprostheses
   • Mechanisms and applications of transcranial magnetic stimulation (TMS)
   • New systems for the simulation of visual perception

• 

  topic Hightech Strategy

  Bernstein Newsletter

  We generally use the resources of our brain very carefully - we direct our attention to the most essential. In the latest Bernstein Newsletter, scientists from Goettingen explain the neuronal basis of this process. Further topics: advances in encephalography, processing sensory inputs despite background noise in the brain, appropriateness of mice for the investigation of eye diseases. At this year's Bernstein Symposium, the Bernstein Award was conferred to Susanne Schreiber, allowing her to set up her own research group in Berlin.
  more (URL: http://www.bmbf.de/en/7594.php)
   
  
• 

  topic Hightech Strategy

  Support of Young Researchers in Computational Neuroscience

  The new discipline of computational neuroscience investigates the questions of how our brain works. Since 2004, the German Federal Ministry of Education and Research (BMBF) supports this new research field in the neurosciences with the funding initiative 'National Bernstein Network Computational Neuroscience'. The National Bernstein Network links the theoretical and experimental neurosciences and investigates the neuronal basis of the capacities of the brain. This research will allow a better understanding of brain functions and will thereby contribute to promoting applications in the areas of information technologies, health and education.
  more (URL: http://www.bmbf.de/en/12888.php)
   
  

• topic Hightech Strategy

  Bernstein Network Computational Neuroscience

  Thinking, sensing, learning, remembering - all mental functions reside within the brain. At the same time, this organ is probably the most complex structure that evolution has ever produced. Understanding the brain is the prerequisite for creating new methods for prevention and treatment of diseases of the nervous system. It may also help developing new strategies for learning and teaching. It may even be used for the design of new, 'intelligent' technical devices, such as neuroprostheses or more powerful computer systems.
  more (URL: http://www.bmbf.de/en/3122.php)