Associated Institute - Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max-Planck-Society

Red has a signaling and warning effect. How is this color specificity reflected in the brain?

To explain certain brain waves, it doesn't have to get complicated at all

ESI-researchers investigate how the brain responds to the predictability of natural images

Communication does not require coherence

Researchers find principle of dendritic constancy

How does neuronal activity represent complementary cognitive processes simultaneously at any given moment? Different animal species have used different strategies to solve this neural processing challenge – are they evolutionarily conserved or species-specific? To study these questions, our lab conducts parallel experiments in the two most dominant model species of systems neuroscience: monkeys and mice. We examine visually guided decision-making and responses of these animals in a natural context.

Is coherence between brain areas a mechanism for communication, or is it a byproduct of inter-areal connectivity and oscillatory power? At the Ernst Strüngmann Institute (ESI) for Neuroscience we added new experiments, developed and tested a model how inter-areal coherence results from communication, based on inter-areal connectivity and oscillatory power.

Our perception of the world relies on the coordinated activity of many billions of neurons in the brain. We at the Ernst Strüngmann Institute (ESI) have found evidence for a processing strategy of the brain that uses repeated encounters with a visual stimulus to respond more efficiently in a short time. Detailed knowledge of this mechanism could open up ways to use these abilities for medical therapies in the future.

Whatever we perceive, feel or do, is accomplished through communication between neurons in the brain. Neural communication is shaped by temporal interactions between inhibitory and excitatory neurons. We at the Ernst Strüngmann Institute for neuroscience have discovered a new type of cell that might aid precise information transmission by providing the right timing.

In many domains, artificial intelligent systems are already able to outperform biological systems. However, some computational strategies that were realized by biological systems, in particular the cerebral cortex, differ substantially from those applied in artificial systems. Our research aims to elucidate these principles, expecting that a better understanding of the functions of natural systems will help uncover the causes of disease related disturbances and allow the design of much more efficient artificial systems.