In a village in western Africa, a tsetse fly bites a human, injecting a swarm of the deadly sleeping sickness-causing parasite Trypanosoma brucei into the bloodstream. Once inside its human host, the parasite spreads through the body, rapidly using its flexible flagellum to propel itself, eventually hiding the structure inside its body to evade the host's immune system once it is safely ensconced. Imagine a swarm of microscopic bots that mimics Trypanosoma brucei's behavior. In this case, though, instead of killing their hosts, the bots are designed to circulate through the bloodstream to perform highly-targeted drug deliveries and carry out invasive and delicate surgeries that may otherwise be too risky to perform. This is what a team of scientists at the Swiss Federal Institute of Technology in Zurich (ETHZ) and the Swiss Federal Institute of Technology in Lausanne (EPFL) are working toward.
Artificial intelligence software combined with a robotic harness could help spinal injury and stroke patients walk again. Rehabilitation programs for spinal cord injuries or strokes usually have patients walk on treadmills at a steady pace while harnesses support their weight to varying degrees. In the new study, researchers sought to develop a system that better mimicked the conditions that people might experience during everyday life, where they would have to move in more than one direction and vary their gaits. "The idea is to provide the most appropriate environment for patients to be active during training," says study co-author Grégoire Courtine, a neuroscientist at the Swiss Federal Institute of Technology Lausanne. "The goal of this rehabilitation is to have patients repeat natural activities for an extended amount of time."
Researchers at the University of Zurich's Brain Research Institute have recently developed a technique to automatically detect neurons of different types in a variety of brain regions at different developmental stages. They presented this deep learning-based tool, called DeNeRD, in a paper published in Nature Scientific Reports. Mapping the structure of the mammalian brain at the cellular level is an important, yet demanding task, which typically involves capturing specific anatomical features and analyzing them. In the past, researchers were able to gather several interesting observations and insights about the mammalian brain's structure using classical histological and stereological techniques. Although these methods have proved to be very useful for studying the anatomy of the brain, carrying out a truly brain-wide analysis typically requires a different approach.
A team of researchers from the Brain Research Institute of the University of Zurich and the Swiss Federal Institute of Technology (ETH) have developed a fully automated brain registration method that could be used to segment brain regions of interest in mice. Neuroscientists are always seeking out new methods of exploring the structure and function of different brain regions, which are initially applied on animals but could eventually lead to important discoveries about the organization of the human brain. "My lab aims to reveal how the mammalian brain develops its abilities to process and react to sensory stimuli," Theofanis Karayannis, one of the researchers who carried out the study told Tech Xplore. "Most of the work we do is on the experimental side, utilizing the mouse as a model system and techniques that range from molecular-genetic to functional and anatomical." This study is part of a larger project, which also includes "Exploring Brain-wide Development of Inhibition through Deep Learning," a study in which Karayannis and his colleagues use deep learning algorithms to comprehensively track the so-called inhibitory neurons over time in order to gauge the development of capabilities of the brain at specific points in time.
The "deep artificial composer", or "DAC" for short, generates brand-new melodies that imitate traditional folk music of Irish or Klezmer origin. It does so without plagiarizing already existing ones, since melodies it writes are as original as those produced by a human composer. The results were presented in April at this year's edition of the Evostar conference. The DAC actually produces musical scores of melodies, symbolic music written using notation, and does not generate audio files. The deep artificial composer can produce complete melodies, with a beginning and an end, that are completely novel and that share features that we relate to style," says Swiss Federal Institute of Technology in Lausanne (EPFL) scientists Florian Colombo who developed the artificial intelligence under the guidance of Wulfram Gerstner, director of the Computational Neuroscience Laboratory.