[NEST Users] Free NESTML and NEST Desktop Workshop (27.03.2023)

Hello everyone, we are pleased to announce that NESTML and NEST Desktop will be represented at the satellite training sessions (https://flagship.kip.uni-heidelberg.de/jss/HBPm?mI=252&m=showAgenda&…) as part of the HBP Summit 2023 in Marseille! These sessions will take place on *27 March 2023*. Participation is free of charge, but a registration is mandatory. Please note that only a limited number of participants can register - at the moment there are still places available! The registration page is https://flagship.kip.uni-heidelberg.de/jss/HBPm?meetingID=252. You might need to create a free EBRAINS account for that, if you do not have one yet. The abstract of the workshop can be found below, as well as on the conference page. We also have a dedicated page for this tutorial with detailed information on the topics covered (https://clinssen.github.io/HBP-summit-2023-workshop/). Catering will be provided on site. We are looking forward to meeting you at the workshop! On behalf of the tutorial organizers,     Jens Bruchertseifer PS: Please have also a look at the other exciting topics at the training session! ;) ----- License to Spike - A NEST Desktop and NESTML Workshop NEST is an established, open-source simulator for spiking neuronal networks, which can capture a high degree of detail of biological network structures while retaining high performance and scalability from laptops to HPC [1]. This tutorial provides hands-on experience in building and simulating neuron, synapse, and network models. It introduces several tools and front-ends to implement modeling ideas most efficiently. Participants do not have to install software as all tools can be accessed via the cloud. First, we look at NEST Desktop [2], a web-based graphical user interface (GUI), which allows the exploration of essential concepts in computational neuroscience without the need to learn a programming language. This advances both the quality and speed of teaching in computational neuroscience. To get acquainted with the GUI, we will create and analyze a balanced two-population network. In the second half of the session, we will create a new, custom neuron model that extends the capabilities of NEST Simulator by introducing new mechanisms, such as an active spiking dendritic compartment. NESTML [3] makes it quick and easy it is to implement and simulate model variants. A neuronal plasticity rule is then introduced, which allows a network to be trained by means of reinforcement learning. This is accomplished by combinating a typical spike-timing dependent plasticity learning rule with a global neuromodulatory dopamine signal. We will use the new learning rule to train a stimulus preference in the balanced network. Citations [1] https://nest-simulator.readthedocs.org/ [2] https://nest-desktop.readthedocs.org/ [3] https://nestml.readthedocs.org/