A Focus on Networks
Brain circuits can be considered at many different levels. These levels span the interests of the MPI for Brain Research.
For example, the intracellular protein network present in synapses includes all essential features of circuits including connected elements, communication, regulation and feedback. In response to signals from other neurons in a circuit, synapses interpret their inputs and transform them into outputs. Some inputs modify the intracellular network by modifying the local ionic and protein environment, resulting in a change in the synaptic response.
Neural networks are another fundamental unit of brain function: the brain computes (transforms) inputs (external, via senses, or internal, such as thoughts, memories etc) into adaptive outputs (motor behaviors, percepts etc), according to some rules, or families of rules, that most often emerge from its components and their interactions; interestingly, those rules can change with time, experience, or context.
Our common goal is a mechanistic understanding of the components of these networks, of the structural and functional circuits which they form, of the computational rules which describe their operations, and ultimately, of their roles in driving perception and behavior. Our experimental focus is on all scales (in space and time) required to achieve this understanding. That is, some of our work focuses on networks of molecules in dendritic compartments, while other focuses on networks of interacting brain areas. This requires analyses at the molecular, cellular, multi-cellular, network and behavioral levels, with the full understanding that macroscopic phenomena (spatial patterns, dynamics) can be scale-dependent; thus, while essential, reductionist approaches are not always sufficient, emphasizing also the need for theory.
10 October 2018
Neuroscience Lecture by Richard Morris (Centre of Cognitive and Neural Systems, University of Edinburgh)
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26 November 2018
Minerva Lecture by Maria Barna (Departments of Developmental Biology and Genetics, Stanford University, USA)
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