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Mission Statement

Mission Statement

TEACHING AND RESEARCH

TEACHING AND RESEARCH

Animal Research and Computational Neuroscience

Computational neuroscience cannot do without experimental data. Therefore, animal experiments will remain necessary in the neurosciences in order to clarify fundamental questions about the function of the nervous systems of humans and animals. Only if basic data are reliably collected can hypotheses be verified or medical and technological applications safely tested before being used on humans.

However, by optimizing and sharing data and methods, the Bernstein Network helps to keep animal testing to a minimum while maximizing knowledge. Sometimes computer simulations and theoretical models can even replace experiments altogether, especially when research data management facilitates its further usability.

The scientists of the Bernstein Network are therefore clearly committed to the 3R principles (Replace, Reduce, Refine): All research is designed to improve animal experiments, reduce their amount or replace animal experiments by other methods. The 3Rs stand for the need to replace, refine and reduce the use of animals in experimental research.

See also:

General Information on Animal Research in Science

General Information on Animal Research in Science

  • Directive of the European Parliament and of the Council on the protection  of  animals  used  for  scientific  purpose (2010/63/EU)

Gender Balance

Preventing gender bias is a central concern of the Bernstein Network Computational Neuroscience to advance science.

The members of the Bernstein Network have approved the following amendment to the statutes:

“The Bernstein Network Computational Neuroscience is devoted to the promotion of research and teaching in Computational Neuroscience. To this end the conferences, workshops and prizes organized by the Bernstein Network are of great significance. The annual Bernstein Conference aims to highlight a broad spectrum of recent developments by inviting both young and established scientists to present their latest work or by recognizing their achievement with an award. Minimizing potential gender bias when choosing the best candidates is of key importance to maintain excellence, to meet the goals of national funding partners such as the DFG, and to encourage young female scientists to pursue their career within academia. In the past two years, the Bernstein Network has set a great example in promoting the visibility of female scientists, and is fully committed to continue on this track in the future.”

>> see here for the complete appendix to the statutes of the Bernstein Network Computational Neuroscience e.V. regarding measures to prevent gender bias.