Neuroforum 

About: Neuroforum is an academic journal published by De Gruyter. The journal publishes majorly in the area(s): Biology & Chemistry. It has an ISSN identifier of 0947-0875. Over the lifetime, 180 publications have been published receiving 501 citations. The journal is also known as: Perspektiven der Hirnforschung : Organ der Neurowissenschaftlichen Gesellschaft & Perspektiven der Hirnforschung ; Organ der Neurowissenschaftlichen Gesellschaft.

Long-term potentiation in the hippocampus: discovery, mechanisms and function

Abstract: Abstract In this review we reflect upon our contributions to the study of the properties and mechanisms of long-term potentiation (LTP) and describe some of the major influences on our work. We then go on to consider whether LTP has fulfilled its early promise of providing a compelling account of the synaptic basis of learning and memory.

From synapse to behavior: Rapid modulation of defined neuronal types with engineered GABAA receptors

Abstract: In mammals, identifying the contribution of specific neurons or networks to behavior is a key challenge. Here we describe an approach that facilitates this process by enabling the rapid modulation of synaptic inhibition in defined cell populations. Binding of zolpidem, a systemically active allosteric modulator that enhances the function of the GABAA receptor, requires a phenylalanine residue (Phe77) in the 2 subunit. Mice in which this residue is changed to isoleucine are insensitive to zolpidem. By Cre recombinase–induced swapping of the 2 subunit (that is, exchanging Ile77 for Phe77), zolpidem sensitivity can be restored to GABAA receptors in chosen cell types. We demonstrate the power of this method in the cerebellum, where zolpidem rapidly induces significant motor deficits when Purkinje cells are made uniquely sensitive to its action. This combined molecular and pharmacological technique has demonstrable advantages over targeted cell ablation and will be invaluable for investigating many neuronal circuits.

Artificial Intelligence in Basic and Clinical Neuroscience: Opportunities and Ethical Challenges

Abstract: Abstract The analysis of large amounts of personal data with artificial neural networks for deep learning is the driving technology behind new artificial intelligence (AI) systems for all areas in science and technology. These AI methods have evolved from applications in computer vision, the automated analysis of images, and now include frameworks and methods for analyzing multimodal datasets that combine data from many different source, including biomedical devices, smartphones and common user behavior in cyberspace. For neuroscience, these widening streams of personal data and machine learning methods provide many opportunities for basic data-driven research as well as for developing new tools for diagnostic, predictive and therapeutic applications for disorders of the nervous system. The increasing automation and autonomy of AI systems, however, also creates substantial ethical challenges for basic research and medical applications. Here, scientific and medical opportunities as well ethical challenges are summarized and discussed.

Learning to navigate – how desert ants calibrate their compass systems

Abstract: Abstract Navigating through the environment is a challenging task that animals cope with on a daily basis. Many animal species have impressive capabilities to navigate in complex or even harsh environments. Cataglyphis desert ants are a famous example. These ants use a remarkable navigational repertoire to find their way home after far-reaching foraging trips. How do naïve ants calibrate their visual navigational systems? The ants perform stereotyped sequences of learning walks before switching from tasks inside the darkness of their nest, to foraging under bright sunlight. Here, naïve ants align nest-directed views using the earth’s magnetic field as a compass reference. Neuronal plasticity was mapped in two visual pathways to higher brain centers during this transition. Both their first exposure to light, and the performance of learning walks lead to distinct changes in synaptic circuits along both visual pathways, reflecting calibration and memory formation in the ants’ visual compass systems.

Fight or flee? Lessons from insects on aggression

Abstract: Abstract Aggression between members of the same species serves to secure resources, but the costs can quickly outweigh benefits. Hence, for aggression to be evolutionarily adaptive, animals must decide when best to flee, rather than fight. How its done, is arguably best understood in crickets. These insects implement the decision by simply modulating the behavioural threshold to flee. This threshold is raised by potentially rewarding experiences (e. g. resource possession), via the amine octopamine, so that the animal is less prone to flee and persists longer in fighting. Conversely, the threshold is lowered by nitric oxide, released in response to aversive stimuli (e. g. the opponent’s agonistic signals), thus increasing the tendency to flee. A cricket then flees, when the sum of its opponent’s actions exceeds the threshold. Subsequently, serotonin keeps the threshold low, so that losers remain submissive; possibly by inhibiting dopamine, which is necessary for recovery of aggression in losers.