Hippocampus Microcircuit Simulation: Advanced Neuroscience
Hippocampal Circuit Simulation: Advanced computational methods for modeling and analyzing neural networks in the hippocampus.
Hippocampal Circuit Simulation: Advanced computational methods for modeling and analyzing neural networks in the hippocampus.
Dive into the world of Simulation Neuroscience with this advanced course on hippocampus microcircuit modeling. Learn to integrate diverse neuroscientific data into computer simulations, bridging the gap between molecular and clinical neuroscience. Master the skills needed to analyze and simulate microcircuit models of the rodent hippocampus using state-of-the-art modeling tools from the Human Brain Project Brain Simulation Platform. Explore the anatomy and properties of the hippocampus, analyze its connectome, and perform network simulations. Gain hands-on experience in launching, visualizing, and analyzing simulations, including computing and analyzing local field potentials. This course is ideal for those passionate about reconstructing, simulating, and understanding the brain through computational neuroscience.
Instructors:
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What you'll learn
Understand the basic properties and anatomy of the hippocampus
Analyze the connectome of hippocampal microcircuits
Launch, visualize, and analyze network simulations using advanced tools
Compute and analyze local field potentials in hippocampal models
Integrate diverse neuroscientific data into computer simulations
Apply simulation techniques to study biological mechanisms of brain function
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This course provides an in-depth exploration of hippocampus microcircuit simulation, a key aspect of computational neuroscience. It covers the fundamental properties and anatomy of the hippocampus, focusing on microcircuit characteristics. Students will learn to analyze the hippocampal connectome and perform advanced network simulations. The course emphasizes practical skills, teaching students how to launch, visualize, and analyze simulations using state-of-the-art tools from the Human Brain Project Brain Simulation Platform. A significant component involves computing and analyzing local field potentials, providing insights into brain function at multiple scales. Throughout the course, students will gain expertise in integrating diverse neuroscientific data into comprehensive computer simulations, contributing to the emerging field of Simulation Neuroscience.
Fee Structure
Instructors
2 Courses
Pioneer in Computational Neuroscience and Brain Simulation
Felix Schürmann is the Computing Director and co-director of the Blue Brain Project at EPFL, where he serves as an adjunct professor. After completing his physics studies at the University of Heidelberg as a German National Academic Foundation scholar, he earned his M.S. in Physics from SUNY Buffalo as a Fulbright Scholar, studying quantum computing simulation under Richard Gonsalves. He completed his Ph.D. at the University of Heidelberg under Karlheinz Meier, focusing on neural network hardware implementation. At EPFL's Blue Brain Project, he works alongside Henry Markram and Adriana Salvatore in the Leadership Team, where he guides the project's strategic direction and oversees computing initiatives
2 Courses
Pioneer in Computational and Systems Neuroscience
Srikanth Ramaswamy is a Swiss-Indian computational neuroscientist who currently holds positions as a NUAcT Fellow at Newcastle University and Fulbright Visiting Professor at MIT. After beginning his career in electrical engineering, he transitioned to neuroscience, joining the Blue Brain Project where he completed his Ph.D. under Henry Markram. His research focuses on understanding how neuromodulators like acetylcholine, histamine, dopamine, serotonin, and noradrenaline impact neural circuits and behavior across different species. He pioneered a novel cross-disciplinary approach integrating experiments, computational modeling, and data science to study the neocortex's organization. His discoveries include revealing calcium's fundamental role in controlling neural network state transitions. As a champion of open science, he created the Neocortical Microcircuit Collaboration Portal, providing free access to experimental data and models to over 70,000 users. He is also passionate about diversity in neuroscience, serving as a founding member of the ALBA network and leading their Global Diversity Task Force. In 2023, he received the prestigious Lister Prize, supporting his innovative research at the interface of biological and artificial neural networks.
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