Bottom-up neuroscience

 

Understanding the brain is one of the grand challenges of the 21st century. At present research in this field revolves around two approaches: First, the study of individual neurons by electronic and biochemical means and, second, the imaging of the whole brain using MRI. We have developed a tool-box in order to create a bridge between these two approaches and to build small networks of neurons with controlled topography on a chip. We apply micro- and nanostructuring to control the attachment of neurons, the direction of the neurite growth and the formation of synapses. This allows us to study the activity of such bottom-up neuron networks and, thus, the basic processes of memory and learning. In addition, the controlled small neural networks can be used to test the effect of potential drugs for diseases of the central nervous system.

Axons on a HD-MEA

Projects

  • Benedikt Maurer Investigating plasticity in small neural networks with machine learning 
  • Joël Küchler Hybrid intelligence
  • Giulia Amos In vitro neuroscience
  • Vaiva Vasiliauskaite Experimentally guided computational neuroscience
  • Fariba Karimi Temporal interference stimulation in vitro
  • Nicolai Winter-Hjelm In vitro model of Alzheimer's disease 
  • Josephine Löhle Infering network parameters from activity data
  • Florian Willi Adaptive stimulation learning for biological neural networks
  • Fiona Konnerth In vitro model of nociception using human iPSC-derived cells to enable screening drugs for chronic pain
  • Nina Doorn In vitro brain circuits and computational models to study genetic brain disorders
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