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Simulation Neuroscience

5.0 Filled star Filled star Filled star Filled star Filled star
Based on 3 ratings
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Henry Markram, Idan Segev, Sean Hill, Werner Van Geit, Samuel Kerrien, Lida Kanari, Felix Schürmann, Eilif Muller, Srikanth Ramaswamy, and Anne-Kristin Kaufmann

Simulation Neuroscience is an emerging approach to integrate the knowledge dispersed throughout the field of neuroscience.

The aim is to build a unified empirical picture of the brain, to study the biological mechanisms of brain function, behaviour and disease. This is achieved by integrating diverse data sources across the various scales of experimental neuroscience, from molecular to clinical, into computer simulations.

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Simulation Neuroscience is an emerging approach to integrate the knowledge dispersed throughout the field of neuroscience.

The aim is to build a unified empirical picture of the brain, to study the biological mechanisms of brain function, behaviour and disease. This is achieved by integrating diverse data sources across the various scales of experimental neuroscience, from molecular to clinical, into computer simulations.

This is a unique, massive open online course taught by a multi-disciplinary team of world-renowned scientists.In this first course, you will gain the knowledge and skills needed to create simulations of biological neurons and synapses.

This course is part of a series of three courses, where you will learn to usestate-of-the-art modeling tools of the HBP Brain Simulation Platform to simulate neurons, build neural networks, and perform your own simulation experiments. We invite you to join us and share in our passion to reconstruct, simulate and understand the brain!

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What's inside

Learning objectives

  • Discuss the different types of data for simulation neuroscience
  • How to collect, annotate and register different types of neuroscience data
  • Describe the simulation neuroscience strategies
  • Categorize different classification features of neurons
  • List different characteristics of synapses and behavioural aspects
  • Model a neuron with all its parts (soma, dendrites, axon, synaps) and its behaviour
  • Use experimental data on neuronal activity to constrain a model

Syllabus

Week 1: Simulation neuroscience: An introduction, Understanding the brainApproaches and Rationale of Simulation Neuroscience The principles of simulation neuroscience Data strategies Neuroinformatics Reconstruction and simulation strategies Summary and Caveats
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Develops skills and techniques that align with important industry practices
Taught by a multidisciplinary team of world-renowned scientists
Examines important aspects of simulation neuroscience, which is highly relevant to the field of neuroscience
Covers neuron modeling and analysis techniques that are essential for understanding brain functions
Provides hands-on experience with modeling tools and experimental data through tutorials and exercises
Requires students to have a solid understanding of neuroscience and computer science

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Reviews summary

Introduction to simulation neuroscience and modeling

According to learners, this course offers a solid introduction to simulation neuroscience. Many appreciate the high quality lectures and the integration of theoretical concepts with practical application. A major strength highlighted is the opportunity for hands-on modeling using tools like NEURON and the HBP Brain Simulation Platform. However, some students note that the course requires a strong prerequisite background in math, programming, and neuroscience, finding the pace challenging if they lacked this foundational knowledge. The assignments and labs are often praised as useful but also demanding. Overall, the course is viewed as a valuable starting point for understanding how to simulate neurons and synapses.
First of multiple courses covering the topic.
"Note that this is just the first course in the series, it doesn't cover neural networks or large-scale simulations yet."
"Plan to take the subsequent courses to get the full picture of the field and advanced topics."
"The focus is primarily on single neurons and synapses in this part, setting the stage for later courses."
Well-explained concepts by experts.
"The instructors are experts in the field and explain complex topics clearly and effectively."
"Videos were high quality and easy to follow, breaking down difficult concepts into manageable parts."
"Appreciated the depth and clarity of the lecture content, it was very informative."
Provides a solid base in the field.
"This course gave me a great introduction to the core concepts of simulation neuroscience."
"I feel like I have a solid foundation after completing the modules and assignments."
"It really helped me grasp the fundamentals of modeling single neurons and synapses."
Excellent practical exercises using tools.
"The labs using NEURON and the HBP platform were incredibly valuable for practical experience."
"I appreciated the hands-on tutorials showing how to build and constrain neuron models."
"Coding assignments helped solidify the theoretical concepts through implementation."
Software setup and usage can be difficult.
"Getting the HBP platform tools configured correctly was a major hurdle for me."
"Using NEURON for the first time had a steep learning curve and took a lot of troubleshooting."
"The technical aspects of running the simulations were sometimes frustrating, requiring significant effort outside the course."
Moves quickly, especially without background.
"The pace of the lectures and assignments is very fast; you need to dedicate significant time."
"Found it difficult to absorb everything in the time given each week if you aren't already familiar with the topic."
"Not a course for casual learning, requires significant time commitment to master the material."
Needs strong background in math/coding/neuro.
"Be warned, you need a solid understanding of calculus, linear algebra, and Python..."
"I struggled with the pace and complexity due to my limited programming background."
"Prior knowledge of basic neuroscience is definitely required to keep up with the concepts."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Simulation Neuroscience with these activities:
Review neuron electrophysiology and morphology data
Improves the foundational understanding of the data structures and methods used in this course.
Browse courses on Electrophysiology
Show steps
  • Identify different types of neuron electrophysiology and morphology data
  • Learn how to collect, annotate and register different types of neuroscience data
  • Understand the experimental techniques used to collect neuron electrophysiology and morphology data
Review the following mathematical concepts
Refresh relevant mathematical concepts to reinforce understanding of course materials
Browse courses on Linear Algebra
Show steps
  • Review linear algebra concepts such as matrices, vectors, and eigenvalues
  • Review calculus concepts such as derivatives, integrals, and differential equations
  • Review statistics concepts such as probability, distributions, and hypothesis testing
Compile a list of resources on simulation neuroscience
Compiling a list of resources on simulation neuroscience will help you stay up-to-date on the latest research and developments in the field.
Browse courses on Resources
Show steps
  • Search the web for resources on simulation neuroscience.
  • Create a list of resources that you find helpful.
  • Share your list of resources with other students or online.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Participate in peer review sessions to discuss neuron models
Fosters collaboration and facilitates the exchange of knowledge among students.
Show steps
  • Find a peer review group
  • Present your neuron model to the group
  • Receive feedback from the group
  • Revise your neuron model based on the feedback
Follow tutorials on using the HBP Brain Simulation Platform
Following tutorials on using the HBP Brain Simulation Platform will help you gain the necessary skills to simulate neurons and neural networks.
Show steps
  • Find tutorials on the HBP Brain Simulation Platform website.
  • Follow the instructions in the tutorials to simulate a neuron or neural network.
  • Experiment with different parameters to see how they affect the simulation results.
Design a neuron model
Create a model of a neuron to demonstrate understanding of its structure and function
Show steps
  • Gather information about neuron structure and function
  • Select a modeling tool and learn its capabilities
  • Design the neuron model, including its morphology, ion channels, and synaptic connections
  • Simulate the neuron model to observe its behavior under different conditions
Follow tutorials on modeling synaptic transmission
Provides additional guidance and support for understanding the complex concepts covered in the course.
Show steps
  • Find tutorials on modeling synaptic transmission
  • Follow the steps in the tutorials
  • Implement the models in your own simulations
Practice modeling neurons and synapses using the HBP Brain Simulation Platform
Practicing modeling neurons and synapses using the HBP Brain Simulation Platform will help you develop the skills necessary to create your own simulations.
Show steps
  • Create a simple model of a neuron using the HBP Brain Simulation Platform.
  • Create a simple model of a synapse using the HBP Brain Simulation Platform.
  • Connect the neuron and synapse models together to create a simple neural network.
Write a report on the current state of simulation neuroscience
Encourages students to synthesize their knowledge and communicate their findings in a professional manner.
Browse courses on Simulation Neuroscience
Show steps
  • Research the current state of simulation neuroscience
  • Organize the information into a logical flow
  • Write the report
  • Proofread the report
Solve practice problems on neuron modeling
Practice solving problems related to neuron modeling to enhance understanding and skills
Show steps
  • Find practice problems from textbooks, online resources, or instructors
  • Attempt to solve the problems using the concepts and techniques learned in the course
  • Check your solutions against provided answers or consult with instructors for feedback
Follow tutorials on advanced neuron modeling techniques
Enhance understanding of neuron modeling by exploring advanced techniques through guided tutorials
Show steps
  • Identify areas where you want to improve your neuron modeling skills
  • Find tutorials or online courses that cover these advanced techniques
  • Follow the tutorials step-by-step, experimenting with the techniques
Build a neural network to simulate a simple behavior
Provides an opportunity to apply the knowledge and skills learned in the course to a practical problem.
Browse courses on Neural Networks
Show steps
  • Design the neural network architecture
  • Implement the neural network in a simulation environment
  • Train the neural network on a dataset
  • Evaluate the performance of the neural network
Create a simulation of a simple neural network using the HBP Brain Simulation Platform
Creating a simulation of a simple neural network using the HBP Brain Simulation Platform will help you apply your skills and knowledge to a real-world problem.
Browse courses on Neural Networks
Show steps
  • Design a simple neural network.
  • Implement the neural network using the HBP Brain Simulation Platform.
  • Run the simulation and analyze the results.
Participate in a neuron modeling competition
Challenge yourself and showcase your skills by participating in a neuron modeling competition
Show steps
  • Find a suitable neuron modeling competition that aligns with your interests and skills
  • Develop a novel neuron model or refine an existing one to address the competition's challenge
  • Submit your model and documentation for evaluation
  • Attend the competition, present your model, and engage with other participants

Career center

Learners who complete Simulation Neuroscience will develop knowledge and skills that may be useful to these careers:
Research Scientist
Research Scientists conduct scientific research to advance knowledge and understanding in various fields. Simulation Neuroscience is an emerging field that combines neuroscience with computer science and engineering to understand the brain's functions. This course will provide Research Scientists with a solid foundation in the principles and methodologies of Simulation Neuroscience, enabling them to contribute to this exciting field.
See salaries and explore the career path for Research Scientist
Neuroinformatics Scientist
Neuroinformatics blends data science with neuroscience to organize and interpret vast amounts of data relating to the nervous system. Simulation Neuroscience draws on this data to build models of the brain, study its biological mechanisms, and understand how it relates to behavior and disease. By completing this MOOC, students will be exposed to the basics of neuroinformatics (e.g., data integration and knowledge graphs) and will learn how this field supports Simulation Neuroscience research.
See salaries and explore the career path for Neuroinformatics Scientist
Biomedical Engineer
Biomedical Engineers apply engineering principles to solve problems in biology and medicine. Simulation Neuroscience draws on engineering principles to simulate and understand the brain's functions, making this course highly relevant for those interested in this intersection. The focus on neuron and neural network simulation, as well as the integration of experimental data, will give Biomedical Engineers the skills and knowledge to contribute to this field.
See salaries and explore the career path for Biomedical Engineer
Neuroscientist
A Neuroscientist studies the nervous system to understand its impact on behavior and cognition. As Simulation Neuroscience's goal is to understand the brain's biological mechanisms of brain function, behavior and disease, the knowledge and skills obtained through this course on simulating neurons and neural networks will be valuable for such research.
See salaries and explore the career path for Neuroscientist
Computational Neuroscientist
A Computational Neuroscientist investigates and models the nervous system through mathematical and computational platforms. To ensure models of neurons and networks accurately reflect real-world scenarios, they must be constantly compared with experimental data on physiology and structure. With this course's emphasis on constraining neuron models using experimental data and using state-of-the-art modeling tools of the HBP Brain Simulation Platform, a student will learn to create simulations of biological neurons and synapses, as well as build neural networks, preparing them for work in the field.
See salaries and explore the career path for Computational Neuroscientist
Machine Learning Engineer
Machine Learning Engineers develop, deploy, and maintain machine learning models to solve real-world problems. Simulation Neuroscience leverages machine learning and AI to create models of the brain and study its functions. This course's focus on modeling neurons and synapses, as well as using experimental data to constrain models, would provide a solid foundation for Machine Learning Engineers interested in this field.
See salaries and explore the career path for Machine Learning Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. Simulation Neuroscience relies heavily on software tools and platforms to create and run simulations of the brain. This course will provide Software Engineers with the knowledge and skills to develop and contribute to these software tools, enabling them to play a crucial role in advancing the field.
See salaries and explore the career path for Software Engineer
Data Analyst
Data Analysts collect, analyze, and interpret data to extract meaningful insights and inform decision-making. Simulation Neuroscience generates vast amounts of data that need to be analyzed and interpreted to gain insights into the brain's functions. This course will provide Data Analysts with the skills and knowledge to work with Simulation Neuroscience data, enabling them to contribute to this rapidly growing field.
See salaries and explore the career path for Data Analyst
Science Writer
Science Writers communicate complex scientific concepts to a broad audience. Simulation Neuroscience is a rapidly growing field that has the potential to revolutionize our understanding of the brain. This course will provide Science Writers with the knowledge and skills to effectively communicate the principles and applications of Simulation Neuroscience to the public.
See salaries and explore the career path for Science Writer
Educator
Educators teach and inspire students in various academic settings. Simulation Neuroscience is an emerging field that has the potential to transform the way we teach and learn about the brain. This course will provide Educators with the knowledge and skills to incorporate Simulation Neuroscience into their teaching, enabling them to engage students and foster a deeper understanding of the subject.
See salaries and explore the career path for Educator
Technical Writer
Technical Writers create and maintain technical documentation, such as manuals, white papers, and training materials. Simulation Neuroscience is a complex field that requires clear and concise documentation. This course will provide Technical Writers with the knowledge and skills to create effective documentation for Simulation Neuroscience tools and technologies.
See salaries and explore the career path for Technical Writer
Healthcare Professional
Healthcare Professionals provide medical care and treatment to patients. Simulation Neuroscience has the potential to transform the way we diagnose and treat brain-related disorders. This course will provide Healthcare Professionals with a basic understanding of Simulation Neuroscience and its potential applications in clinical practice, enabling them to stay informed about the latest advancements in this field.
See salaries and explore the career path for Healthcare Professional
Project Manager
Project Managers plan, execute, and oversee projects to ensure their successful completion. Simulation Neuroscience projects often involve complex collaborations between scientists, engineers, and clinicians. This course will provide Project Managers with the knowledge and skills to effectively manage Simulation Neuroscience projects, ensuring their timely and successful delivery.
See salaries and explore the career path for Project Manager
Consultant
Consultants provide expert advice and support to organizations on various business and technical matters. Simulation Neuroscience is an emerging field with the potential to revolutionize healthcare and other industries. This course will provide Consultants with the knowledge and skills to advise clients on the applications and implications of Simulation Neuroscience, enabling them to stay ahead of the curve in this rapidly evolving field.
See salaries and explore the career path for Consultant
Data Scientist
Data Scientists leverage massive datasets and AI techniques to extract meaningful insights and solve complex business problems. Simulation Neuroscience integrates diverse data sources across various scales of experimental neuroscience to create computer simulations of the brain. This course will help a Data Scientist understand how to collect, annotate, and register different types of neuroscience data, as well as how to use data integration strategies to create models.
See salaries and explore the career path for Data Scientist

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Simulation Neuroscience.
Cover image
The Handbook of Brain Theory and Neural Networks
Save
This handbook provides a comprehensive overview of the field of brain theory and neural networks, covering a wide range of topics from the history of the field to the latest advances in research.
The Handbook of Brain Theory and Neural Networks
Paperback
Check
The Handbook of Brain Theory and Neural Networks
Kindle Edition
Check
Cover image
Principles of Neural Science, Fifth Edition
Save
Classic textbook on neuroscience, providing a comprehensive overview of the field. It valuable resource for students and researchers alike.
Principles of Neural Science, Fifth Edition...
Hardcover
$$$$
Principles of Neural Science, Fifth Edition...
Kindle Edition
$$$
Cover image
Advances and Technical Standards in Neurosurgery
Save
Provides a detailed overview of the structure and function of synapses. It valuable resource for students and researchers interested in the synaptic mechanisms of brain function.
Advances and Technical Standards in Neurosurgery...
Paperback
$$$$
Advances and Technical Standards in Neurosurgery
Kindle Edition
$$$$
Cover image
Neurogastronomy
Save
*The Synaptic Organization of the Brain* classic textbook that provides a comprehensive overview of the synapse. It is an essential resource for anyone who wants to learn about the latest advances in the field.
Neurogastronomy
Paperback
Check
Neurogastronomy
Kindle Edition
Check
Cover image
Visuomotor Coordination
Save
*Modeling Brain and Behavior* textbook that provides a comprehensive overview of the field of computational neuroscience. It covers a wide range of topics, from the basics of neuronal modeling to the latest advances in machine learning for neuroscience.
Visuomotor Coordination: Amphibians, Comparisons,...
Hardcover
$$$$
Cover image
Memory
Save
*The Neurobiology of Learning and Memory* textbook that provides a comprehensive overview of the field of neurobiology of learning and memory. It covers a wide range of topics, from the basics of memory processes to the latest advances in brain imaging.
Memory: From Mind to Molecules (Scientific American...
Hardcover
$$
Cover image
Memory
Save
*The Cognitive Neuroscience of Memory* textbook that provides a comprehensive overview of the field of cognitive neuroscience of memory. It covers a wide range of topics, from the basics of memory processes to the latest advances in brain imaging.
Memory
Paperback
$$$
Memory
Paperback
$$
Memory
Paperback
$$
Oroimena
Paperback
$$
Memory
Kindle Edition
$$$
Cover image
Cognitive Science
Save
*The Foundations of Cognitive Science* textbook that provides a comprehensive overview of the field of cognitive science. It covers a wide range of topics, from the basics of cognitive psychology to the latest advances in artificial intelligence.
Cognitive Science: An Introduction to the Study of...
Kindle Edition
$$$
Cover image
Handbook of Farm, Dairy, and Food Machinery
Save
*Biomedical Engineering and Design Handbook* comprehensive reference work that covers all aspects of biomedical engineering, from the basics of biomaterials to the latest advances in medical imaging.
Handbook of Farm, Dairy, and Food Machinery
Paperback
Check
Handbook of Farm, Dairy, and Food Machinery
Kindle Edition
Check
Biological Psychology EBook
Save
Provides an overview of biological psychology, covering a wide range of topics from the basics of neural function to the latest advances in research.
Biological Psychology EBook
Paperback
Check
Biological Psychology EBook
Kindle Edition
Check
Cover image
Neuroscience: Exploring the Brain, Enhanced Edition
Save
Provides a comprehensive overview of neuroscience. It valuable resource for students and researchers interested in learning about the brain.
Neuroscience: Exploring the Brain, Enhanced Edition
Paperback
Check
Neuroscience: Exploring the Brain, Enhanced Edition
Kindle Edition
Check

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Course image
Rating
5.0 Filled star Filled star Filled star Filled star Filled star
Effort
5 to 8 hours per week for 6 weeks
Level
Advanced
Via
edX
Institution
École Polytechnique Fédérale de Lausanne
Instructors
Henry Markram
Idan Segev
Sean Hill
Werner Van Geit
Samuel Kerrien
Lida Kanari
Felix Schürmann
Eilif Muller
Srikanth Ramaswamy
Anne-Kristin Kaufmann
Language
English
Transcript
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Develops skills and techniques that align with important industry practices
Taught by a multidisciplinary team of world-renowned scientists
Examines important aspects of simulation neuroscience, which is highly relevant to the field of neuroscience
Covers neuron modeling and analysis techniques that are essential for understanding brain functions
Provides hands-on experience with modeling tools and experimental data through tutorials and exercises
Requires students to have a solid understanding of neuroscience and computer science
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