Simulation Neuroscience from edX

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

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

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

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

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Improves the foundational understanding of the data structures and methods used in this course.

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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

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Refresh relevant mathematical concepts to reinforce understanding of course materials

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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

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Compiling a list of resources on simulation neuroscience will help you stay up-to-date on the latest research and developments in the field.

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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

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Participate in peer review sessions to discuss neuron models

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Fosters collaboration and facilitates the exchange of knowledge among students.

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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

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Following tutorials on using the HBP Brain Simulation Platform will help you gain the necessary skills to simulate neurons and neural networks.

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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

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Create a model of a neuron to demonstrate understanding of its structure and function

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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

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Provides additional guidance and support for understanding the complex concepts covered in the course.

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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

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Practicing modeling neurons and synapses using the HBP Brain Simulation Platform will help you develop the skills necessary to create your own simulations.

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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

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Encourages students to synthesize their knowledge and communicate their findings in a professional manner.

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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

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Practice solving problems related to neuron modeling to enhance understanding and skills

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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

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Enhance understanding of neuron modeling by exploring advanced techniques through guided tutorials

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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

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Provides an opportunity to apply the knowledge and skills learned in the course to a practical problem.

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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

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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

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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

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Challenge yourself and showcase your skills by participating in a neuron modeling competition

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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