April 16 Thursday at 1PM UTC
Lecturer: Markus Diesmann and Sebastian Spreizer
Affiliation: Institute of Neuroscience and Medicine – Computational and Systems Neuroscience, Research Centre Jülich. The former is also a member of the NeuroMat International Advisory Board.
Title: "Neuronal network models as building blocks and for the classroom"
Abstract: Prominent features of the local cortical neuronal network of mammals are conserved in the evolution from mouse to man and across sensory and motor areas. This raises hope that a universal computing architecture can be found. Still, single brain functions are distributed across the brain requiring us to use models created by other scientists as building blocks. The talk discusses a model of the macaque’s vision-related areas as an example and the corresponding simulation technology implemented in the NEST code. The digitalization of computational neuroscience
workflows is a chance to overcome the complexity barriers we are facing and to advance open science. This extends to the classroom. With graphical user interfaces like NEST Desktop, presented online in the talk, students can learn about
neuroscience concepts and understand the purpose of mathematical models without the need to master the details of programming. NEST Desktop runs installation-free in the browser based on a client-server architecture and is therefore suitable for e-learning and a contribution to equal opportunities.
References:
https://nest-simulator.readthedocs.io
https://nest-desktop.readthedocs.io
April 30 Thursday at 1PM UTC
Lecturer: Daniel Y. Takahashi
Affiliation: Universidade Federal do Rio Grande do Norte, NeuroMat associate Investigator
Title: "Emerging phenomena from random paths to model animal behavior"
Abstract: What distinguishes animal behavior from other physical phenomena? This is a question that Aristotle asked in his De Anima and still occupies our minds to these days. In this talk, I will first make some ontological and empirical remarks on animal behavior. Then, I will propose a simplistic mathematical model that helps to explain some phenomena related to animal behavior.
May 14 Thursday at 1PM UTC
Lecturer: Susanne Ditlevsen
Affiliation: Department of Mathematical Sciences of the University of Copenhagen, member of the NeuroMod Think Tank
Title: "Rapid regulation of vesicle priming explains synaptic facilitation despite heterogeneous vesicle:Ca2+ channel distances"
Abstract: Chemical synaptic transmission relies on the Ca2+-induced fusion of transmitter-laden vesicles whose coupling distance to Ca2+ channels determines synaptic release probability and short-term plasticity, the facilitation or depression of repetitive responses. Here, using electron- and super-resolution microscopy at the Drosophila neuromuscular junction we quantitatively map vesicle:Ca2+ channel coupling distances. These are very heterogeneous, resulting in a broad spectrum of vesicular release probabilities within synapses. Stochastic simulations of transmitter release from vesicles placed according to this distribution revealed strong constraints on short-term plasticity; particularly facilitation was difficult to achieve. We show that postulated facilitation mechanisms operating via activity-dependent changes of vesicular release probability (e.g. by a facilitation fusion sensor) generate too little facilitation and too much variance. In contrast, Ca2+-dependent mechanisms rapidly increasing the number of releasable vesicles reliably reproduce short-term plasticity and variance of synaptic responses. We propose activity-dependent inhibition of vesicle un-priming or release site activation as novel facilitation mechanisms.
Acknowledgment: Joint work with Janus RL Kobbersmed, Andreas T Grasskamp, Meida Jusyte, Mathias A Böhme, Jakob Balslev Sørensen, Alexander M Walter
References: Janus RL Kobbersmed, Andreas T Grasskamp, Meida Jusyte, Mathias A Böhme, Susanne Ditlevsen, Jakob Balslev Sørensen, Alexander M Walter. Rapid regulation of vesicle priming explains synaptic facilitation despite heterogeneous vesicle:Ca2+ channel distances. eLife 2020;9:e51032 DOI: 10.7554/eLife.51032
May 28 Thursday at 1PM UTC
Lecturer: Eva Löcherbach and Christophe Pouzat
Affiliation: Université Paris 1 Panthéon-Sorbonne – Université Paris Descartes. Both are also NeuroMat's distinguished associate investigators.
Title: Stochastic modeling of interacting neuron's systems
Abstract: The first part of our talk will review the main sources of variability and stochasticity both at a single neuron's level and at the inter-neuron communication (synaptic) level. This justifies, not to say requires, to build a stochastic model of interacting neurons when we want to understand network properties from the behavior of single units. We will present in detail a model that is: simple enough to allow a thorough mathematical investigation; easy to simulate exactly while exhibiting interesting macroscopic properties.
Acknowledgment: Joint work with Antonio Galves.
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