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Principles of fMRI 2

Martin Lindquist, PhD, MSc and Tor Wager, PhD

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data. It is a continuation of the course “Principles of fMRI, Part 1”.

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What's inside

Syllabus

Week 1

This week we will discuss psychological and behavioral inference, as well as advanced experimental design.

Week 2

This week we will continue with advanced experimental design, and also discuss advanced GLM modeling.

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what should give you pause

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Covers advanced topics that build upon the knowledge gained in Part 1 of this course series

Suitable for intermediate learners who already have a foundation in fMRI

Provides a comprehensive overview of advanced fMRI analysis techniques

Provides practical guidance through case studies

Taught by instructors who are recognized for their work in neuroimaging

Requires extensive background knowledge in fMRI and related fields

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Reviews summary

Advanced fmri data analysis deep dive

According to learners, the course 'Principles of fMRI 2' provides a strong theoretical foundation for understanding advanced functional magnetic resonance imaging data analysis. Students praise its coverage of advanced topics like brain connectivity and multi-voxel pattern analysis, noting it's a crucial next step after Part 1. However, reviewers frequently mention the course is very challenging and requires strong prerequisites beyond just Part 1, particularly in statistics and mathematics. Some also felt it lacks hands-on practical examples, focusing more heavily on theory over implementation.

Provides comprehensive theoretical basis.

"The course provides a strong theoretical foundation for understanding the underlying principles of fMRI analysis methods."

"I appreciated the deep dive into the statistical models and assumptions behind GLM and MVPA."

"It really solidified my understanding of the 'why' behind the analysis techniques we use."

Covers complex methods effectively.

"The coverage of brain connectivity and MVPA was particularly strong and up-to-date."

"I found the discussions on advanced GLM modeling very insightful for my research."

"Provides a great overview of cutting-edge techniques in fMRI analysis."

More theory, less hands-on practice.

"The course is very theory-heavy... I would have liked more practical examples or coding exercises."

"While the concepts are explained well, applying them to actual data required seeking outside resources."

"Could use more step-by-step guides on implementing these analyses in standard software like SPM or FSL."

Challenging, requires strong background.

"This course is very challenging, definitely not for beginners... assumes significant prior knowledge."

"You absolutely need a solid background in statistics and neuroscience before taking this."

"While Part 1 is listed as a prerequisite, I felt I needed more background in linear algebra too."

"The pace is quite fast, especially if you don't have a strong math or stats background already."

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 Principles of fMRI 2 with these activities:

Volunteer at a neuroimaging lab

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Volunteering at a neuroimaging lab will give you hands-on experience with fMRI data collection and analysis.

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Find a neuroimaging lab to volunteer at
Contact the lab and inquire about volunteering opportunities
Attend a training session on the lab's fMRI equipment
Assist with data collection and analysis

Practice GLM modeling

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Practicing GLM modeling will help you gain a better understanding of how to use this technique to analyze fMRI data.

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Review the GLM theory
Create a simple GLM model
Fit the GLM model to your data
Interpret the results of the GLM model

Attend an fMRI data analysis workshop

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Attending an fMRI data analysis workshop will provide you with the opportunity to learn from experts in the field and gain hands-on experience with the latest techniques.

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Find an fMRI data analysis workshop
Register for the workshop
Attend the workshop
Participate in the hands-on exercises

Four other activities

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Participate in a peer review session

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Participating in a peer review session will help you gain feedback on your work and improve your understanding of the material.

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Find a peer review group
Submit your work to the peer review group
Review the work of other group members
Provide feedback on the work of other group members

Practice brain connectivity analysis

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Practicing brain connectivity analysis will help you gain a better understanding of how to use this technique to identify and characterize the connections between different brain regions.

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Review the theory of brain connectivity
Create a brain connectivity matrix
Cluster the brain connectivity matrix
Interpret the results of the brain connectivity analysis

Develop a tutorial on fMRI data analysis

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Creating a tutorial on fMRI data analysis will help you summarize and strengthen your understanding of the techniques used in this course.

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Identify the key concepts in fMRI data analysis
Organize the key concepts into a logical flow
Develop the content for each section of the tutorial
Create visual aids to illustrate the concepts
Record yourself presenting the tutorial

Practice multi-voxel pattern analysis

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Practicing multi-voxel pattern analysis will help you gain a better understanding of how to use this technique to decode the information that is represented in the brain.

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Review the theory of multi-voxel pattern analysis
Create a multi-voxel pattern classifier
Train the multi-voxel pattern classifier
Test the multi-voxel pattern classifier
Interpret the results of the multi-voxel pattern analysis

Career center

Learners who complete Principles of fMRI 2 will develop knowledge and skills that may be useful to these careers:

Postdoctoral Researcher

As a Postdoctoral Researcher specializing in neuroimaging, you will play a critical role in advancing our understanding of the brain. Functional Magnetic Resonance Imaging (fMRI) is a vital tool for studying the living, functioning human brain, and this course will equip you with the advanced analytical skills necessary to excel in this field. The course covers topics like advanced experimental design, GLM modeling, brain connectivity, and multi-voxel pattern analysis, all of which are essential for conducting groundbreaking research in neuroimaging.

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Research Scientist

As a Research Scientist in the field of neuroimaging, you will be responsible for designing, conducting, and analyzing research studies that investigate the structure and function of the brain. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this role. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to make meaningful contributions to the field of neuroimaging research.

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Cognitive Neuroscientist

As a Cognitive Neuroscientist, you will study the relationship between the brain and cognition. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to investigate the neural mechanisms underlying cognitive processes.

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Neuropsychologist

As a Neuropsychologist, you will assess and diagnose brain injuries and disorders. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to better understand the neural mechanisms underlying brain injuries and disorders.

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Neurologist

As a Neurologist, you will diagnose and treat disorders of the nervous system. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to better understand the neural mechanisms underlying neurological disorders.

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Psychiatrist

As a Psychiatrist, you will diagnose and treat mental disorders. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to better understand the neural mechanisms underlying mental disorders.

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Biomedical Engineer

As a Biomedical Engineer specializing in neuroimaging, you will design and develop new technologies for imaging the brain. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to develop more effective neuroimaging technologies.

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Data Scientist

As a Data Scientist specializing in neuroimaging, you will use statistical and computational methods to analyze fMRI data. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to make meaningful contributions to the field of neuroimaging research.

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Software Engineer

As a Software Engineer specializing in neuroimaging, you will develop software for analyzing and visualizing fMRI data. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to develop more effective neuroimaging software.

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Statistician

As a Statistician specializing in neuroimaging, you will develop and apply statistical methods for analyzing fMRI data. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to make meaningful contributions to the field of neuroimaging research.

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Physicist

As a Physicist specializing in neuroimaging, you will develop and apply physical principles to the study of the brain. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to develop more effective neuroimaging technologies.

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Computer Scientist

As a Computer Scientist specializing in neuroimaging, you will develop and apply computational methods for analyzing fMRI data. This course in Principles of fMRI 2 will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to develop more effective neuroimaging software.

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Mathematician

As a Mathematician specializing in neuroimaging, you will develop and apply mathematical models to the study of the brain. This course in Principles of fMRI 2 may be useful as it will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to develop more effective neuroimaging models.

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Electrical Engineer

As an Electrical Engineer specializing in neuroimaging, you will design and develop hardware for imaging the brain. This course in Principles of fMRI 2 may be useful as it will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to develop more effective neuroimaging hardware.

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Biostatistician

As a Biostatistician specializing in neuroimaging, you will develop and apply statistical methods to the analysis of biological data, including fMRI data. This course in Principles of fMRI 2 may be useful as it will provide you with the advanced analytical skills and knowledge of experimental design that are essential for success in this field. You will learn techniques for analyzing fMRI data, including advanced GLM modeling, brain connectivity, and multi-voxel pattern analysis, which will enable you to make meaningful contributions to the field of neuroimaging research.

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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 Principles of fMRI 2.

After Phrenology

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An advanced textbook on brain connectivity dynamics, this book is suitable for researchers and students who want to learn more about this topic.

Principles of fMRI 2

What's inside

Syllabus

Traffic lights

Save this course

Reviews summary

Advanced fmri data analysis deep dive

Activities

Career center

Reading list

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