About this course

Simulation Neuroscience is an innovative approach aiming to integrate the vast knowledge base across different domains of neuroscience to create a cohesive and empirical picture of the brain. The course facilitates understanding the biological foundations of brain functionality, behavior, and diseases by using computational simulations. This course, being the first in a series, focuses on training the learners to build simulations of biological neurons and synapses using cutting-edge modelling tools available on the HBP Brain Simulation Platform.

Course Description

This course offers an in-depth understanding of simulation neuroscience, where you'll be using tools to create and analyze simulations of neuronal activity. You'll learn how to work with different types of neuroscience data, develop models of neurons and synapses, and use these models in simulation experiments.

What students will learn

• Understanding and discussion of various types of neuroscience data required for simulation.
• Techniques for collecting, annotating, and registering diverse neuroscience data.
• Simulation neuroscience strategies and their applications.
• Features and classifications of neurons and synapses.
Building and simulating models of neurons to replicate biological processes.
• Application of experimental data to refine and constrain models.

Prerequisites or skills necessary

Participants should have knowledge of ordinary differential equations and experience in programming with languages like Python (preferred), C/C++, Java, MATLAB, or R.

Course Content

• Introduction to simulation neuroscience and its importance.
• Data collection and management strategies in neuroscience.
• Detailed neuron modeling including soma, dendrites, axons, and synapses.
• Use of the HBP Brain Simulation Platform for conducting simulation experiments.

Who this course is for

This course is designed for advanced students, researchers, and professionals interested in neuroscience, computational biology, and related fields, aiming to get hands-on experience in simulation neuroscience.

Application of skills in the real world

The skills acquired from this course are essential in the fields of neuroscience research and development. Learners can contribute to advancements in understanding brain mechanisms and disorders, aiding in the development of neurological treatments and therapies. Additionally, these skills are valuable in academic research, particularly in computational neuroscience and neuroinformatics.

Syllabus

• Week 1: Basics of Simulation Neuroscience, experimental data collection.
• Week 2: Introduction to Neuroinformatics, brain atlases, knowledge graphs.
• Week 3: Detailed modeling of neurons.
• Week 4: Modeling of synapses, synaptic potentials and transmission.
• Week 5: Constraining neuron models using experimental data.
• Week 6: Comprehensive exams and use of NMC portal for model simulation.