We are currently accepting nominations for this year's Valentin Braitenberg Award for Computational Neuroscience. The deadline for nominations is April 30, 2025.

Using artificial intelligence to understand the visual system in the brain: An international research team (MICrONS) with the participation of the University of Göttingen has developed new AI models to decode the complex processing of visual stimuli in the brain. The researchers investigated how the shape, connectivity pattern and activity of nerve cells in the mouse brain are related. The project's key findings have been published in a series of articles in the journals Nature and Nature Communications.

A new study by neuroscientists at the German Primate Center (DPZ) - Leibniz Institute for Primate Research in Göttingen shows that our brain deals with different forms of visual uncertainty during movements in distinct ways. Depending on the type of uncertainty, planning and execution of movements in the brain are affected differently. These findings could help to optimize brain-computer interfaces that, for example, help people with paralysis to control prostheses or computers with their thoughts alone (Nature Communications).

Göttingen research team constructs network of self-learning infomorphic neurons

How does the brain retain a sequence of events in memory? Researchers from the University Hospital Bonn (UKB), the University of Bonn, the University Hospital Tübingen and the University of Tübingen investigated this question. Using a unique measurement technique with implanted electrodes in the human brain, they were able to test a widely accepted theory of memory processes for the first time. The response pattern of the nerve cells did not align with the theory, but could be explained by a new model. The results have now been published in the journal "Nature Neuroscience".

The locus coeruleus and the ventral tegmental area vie for influence over the formation of memory content. This has been demonstrated by a team of neuroscientists using light-gated nerve cells.

Researchers find more synapses and postsynaptic partners in the brain of Drosophila melanogaster correlating to lower environmental temperature during pupal development.

Binary neutron star mergers emit gravitational waves followed by light. To fully exploit these observations and avoid missing key signals, speed is crucial. In a study to be published in Nature on March 5, 2025, an interdisciplinary team of researchers presents a novel machine learning method that can analyze gravitational waves emitted by neutron star collisions almost instantaneously – even before the merger is fully observed. A neural network processes the data and enables a fast search for visible light and other electromagnetic signals emitted during the collisions. This new method could be instrumental in preparing the field for the next generation of observatories.

Creative thinking uses specific patterns to store information

The "Signatures of criticality in efficient coding networks" study provides new insights into the fundamental mechanisms of brain function. An international research team from Dresden, Tübingen, Paris and Shanghai developed a mathematical model to simulate a neural network that mimics the functioning of real brain cells. Unlike in previous studies, the network was not tuned directly towards a critical state, but optimized to process information as efficiently as possible – similar to our brain in everyday life.