This year’s two Nobel Laureates in Physics have used tools from physics to develop methods that are the foundation of today’s powerful machine learning. John Hopfield created an associative memory that can store and reconstruct images and other types of patterns in data. Geoffrey Hinton invented a method that can autonomously find properties in data, and so perform tasks such as identifying specific elements in pictures.

A serotonin specific receptor can determine how important visual stimuli are perceived. This explains the effects of certain drugs and could help in understanding psychiatric diseases.

Computer models of neural networks developed by humans can be arbitrarily far removed from reality. Nevertheless, they are a great help to researchers in planning and evaluating learning experiments.

A team of scientists from HHMI’s Janelia Research Campus and the University of Tübingen have found a way to build artificial neural networks which accurately predict computations in living brains

Bonn researchers get to the bottom of the social aspect of
communication for mental activity

In a pioneering study, the two scientists Dr. Patrick Krauss and Dr. Achim Schilling from the Cognitive Computational Neuroscience Group at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) have now used artificial intelligence to gain major insights into how our brains work that may substantially change our understanding of human thought processes and emotions.

Researchers from Bonn and Japan clarify how neighboring synapses coordinate their response to plasticity signals

New York – While Julie Andrews famously sang about “whiskers on kittens”, a new study published in Annals of the New York Academy of Sciences shines a light on the role of elephant whiskers, and the impact of trunk-directed eating behavior on them. The study by Yildiz and colleagues reports that the locations and types of elephant mouth whiskers (“vibrissae”), as well as altered elephant mouth anatomy, differ from that of other mammals. These modifications appear to be in response to the evolution of an elephant’s distinctive method of eating.

The brain is constantly storing new experiences that it has to integrate into the jumble of existing memories. Surprisingly, it does not overwrite previous memory traces in the process.

A team of scientists led by Prof. Dr Ilka Diester, Professor of Optophysiology and spokesperson of the BrainLinks-BrainTools research centre at the University of Freiburg, has developed a formal description of internal world models and published it in the journal Neuron. The formalised view helps scientists to better understand the development and functioning of internal world models. It makes it possible to systematically compare world models of humans, animals and artificial intelligence (AI). This makes it clearer, for example, where AI still has deficits compared to human intelligence and how it could be further developed in the future. Eleven Freiburg researchers from four faculties were involved in the interdisciplinary publication.