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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.
Read more
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.
Read more
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!
Register for this course and see more details by visiting:
OpenCourser.com/course/rzhuk7/simulation
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
- 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
Read more
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
Read more
Experimental data Single neuron data collection techniquesMorphological profiles Electrophysiological profiles Caveats and summary of experimental data techniques
Single neuron dataIon channels Combining profiles Cell densities Summary and Caveats SynapsesSynapses Synaptic dynamics
Week 2: NeuroinformaticsIntroduction to neuroinformaticsText mining Data integration and knowledge graphsKnowledge graphsOntologiesNeuroinformatics Brain atlases and knowledge space Motivation of data-integration Fixed data approach to data integration Blue Brain Nexus Architecture of Blue Brain Nexus Design a provenance entityOntologies Creating your own domain MINDSConclusion Acquisition of neuron electrophysiology and morphology dataGenerating data Using data Design an entityAn entity design and the provenance modelConclusion Morphological feature extractionMorphological structures, Understanding neuronal morphologies using NeuroMStatistics and visualisation of morphometric data
Week 3: Modeling neuronsIntroduction to the single neuronIntroductionMotivation for studying the electrical brain The neuronA structural introductionAn electrical deviceElectrical neuron modelModeling the electrical activity Hodgkin & Huxley Tutorial creating single cell electrical modelsSingle cell electrical model: passive Making it active Adding a dendrite Connecting cells
Week 4: Modeling synapsesModeling synaptic potentialModeling the potential Rall's cable model Modeling synaptic transmission between neuronsSynaptic transmission Modeling synaptic transmission Modeling dynamic synapses tutorialDefining your synaps Compiling your modifies Hosting & testing your synaps model Reconfigure your synaps to biological ranges Defining a modfile for a dynamic TM synapse Compiling and testing the modfile
Week 5: Constraining neurons models with experimental dataConstraining neuron models with experimental dataConstraining neuron model with experimental data. Computational aspects of optimization Tools for constraining neuron models Tutorials for optimizationSetting up the components
Week 6: Exam weekNMC portalAccessing the NMC portalRunning models on your local computerDownloading and interacting with the single cell modelsInjecting a current
Good to know
Good to know
Know what's good ,
what to watch for , 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
Save this course
Save Simulation Neuroscience to your list so you can find it easily later:
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Reviews summary
Simulation neuroscience masterclass
Learners say this is a wonderful course that teaches the fundamentals of Computational Neuroscience. It's great for beginners and students of all levels with a strong interest in Neuroscience and related fields. Students particularly enjoyed the opportunity to use the resources from the Human Brain Project to simulate neurons.
Some Python programming knowledge is recommended.
"It is recommended that you know how to program in python before you take this course."
Suitable for beginners of all levels.
"Very good introductory course to the basics of Neuroscience."
Course uses resources from the Human Brain Project.
"Very good introductory course to the basics of Neuroscience. It was very interesting to use the resources from the Human Brain Project!"
"Magnificent course where you will learn to use the Human Brain Project tools to simulate neurons."
Highly rated by learners.
"Very good introductory course to the basics of Neuroscience."
"Magnificent course where you will learn to use the Human Brain Project tools to simulate neurons."
"This is a very specialized course."
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Show steps
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
Review neuron electrophysiology and morphology data
Show steps
Improves the foundational understanding of the data structures and methods used in this course.
Browse courses on
Electrophysiology
Show steps
Show steps
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
Show steps
Refresh relevant mathematical concepts to reinforce understanding of course materials
Browse courses on
Linear Algebra
Show steps
Show steps
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
Show steps
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
Show steps
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
Show steps
Fosters collaboration and facilitates the exchange of knowledge among students.
Show steps
Show steps
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
Show steps
Following tutorials on using the HBP Brain Simulation Platform will help you gain the necessary skills to simulate neurons and neural networks.
Show steps
Show steps
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
Show steps
Create a model of a neuron to demonstrate understanding of its structure and function
Show steps
Show steps
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
Show steps
Provides additional guidance and support for understanding the complex concepts covered in the course.
Show steps
Show steps
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
Show steps
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
Show steps
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
Show steps
Encourages students to synthesize their knowledge and communicate their findings in a professional manner.
Browse courses on
Simulation Neuroscience
Show steps
Show steps
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
Show steps
Practice solving problems related to neuron modeling to enhance understanding and skills
Show steps
Show steps
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
Show steps
Enhance understanding of neuron modeling by exploring advanced techniques through guided tutorials
Show steps
Show steps
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
Show steps
Provides an opportunity to apply the knowledge and skills learned in the course to a practical problem.
Browse courses on
Neural Networks
Show steps
Show steps
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
Show steps
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
Show steps
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
Show steps
Challenge yourself and showcase your skills by participating in a neuron modeling competition
Show steps
Show steps
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 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.
Neuroinformatics 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.
Biomedical Engineer
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.
Neuroscientist
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.
Data Analyst
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.
Software 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.
Computational 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.
Machine Learning Engineer
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.
Science Writer
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.
Data Scientist
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.
Educator
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.
Consultant
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.
Healthcare Professional
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.
Technical Writer
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.
Project Manager
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.
For more career information including salaries, visit:
OpenCourser.com/course/rzhuk7/simulation
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.
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.
Classic textbook on neuroscience, providing a comprehensive overview of the field. It valuable resource for students and researchers alike.
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.
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.
*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.
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.
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.
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.
*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.
Provides an overview of biological psychology, covering a wide range of topics from the basics of neural function to the latest advances in research.
Provides a comprehensive overview of neuroscience. It valuable resource for students and researchers interested in learning about the brain.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rzhuk7/simulation
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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
Good to know
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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