Principles of Neuroimaging - 2013-2014

Principles of Neuroimaging A, Fall, 2013 - Class Schedule and Syllabus

THIS IS A DOCUMENT IN PREPARATION AS OF 10/6/13

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M284B Principles of Neuroimaging B

Lecture Videos

Thank you Alan and Edward!

• 2012/11/07 - EKG System Design Lecture Video

• 2012/11/21 - Statistics for Imaging II Lecture Video

Course Reading

Required Reading

Signal Processing for Neuroscientists by Wim van Drongelen

This can be found as a PDF on scribd.com, for a small fee of $8.99

Supplemental Reading

Matlab for Neuroscientists

Link for download found here for a small fee: http://www.scribd.com/doc/88212458/Matlab-Matlab-for-Neuroscientists

Cartoon Guide to Statistics

Link for download found here for a small fee: http://www.scribd.com/doc/148072668/Cartoon-Guide-to-Statistics

NOTE: if you subscribe for a Scribd account for a day, you can download as many documents as you like for one fee.

Week 1: Orientation to Neuroimaging, Neurons, Brains; Linear Systems

Monday 10/7/13

- Orientation & Neurons. Speaker: Mark Cohen

In this first class we will review the basics of neurophysiology with an eye towards what signals of brain function might be visible to the neuroimager. We will discuss information coding, energetics, size and time scales.

File:Neurons.jpg

Required Readings - Please complete these readings prior to class.

• The Active Brain
• Neuron function slides shown in class
• Caveat Lector - the misuse of neuroimaging

Suggested Further Reading

• "If Neuroimaging is the Answer, What is the Question?" Kosslyn, 1999
• Neuroanatomy Programmed Learning
• Squire, Fundamentals of Neuroscience
• Kandel, et al., "Principles of Neural Science"

This paper, by Malhi, is a nice orientation in methods of neuroimaging. *Making sense of neuroimaging in psychiatry

• Replacement of the axoplasm of giant nerve fibres with artificial solutions

Wednesday 10/9/13

Transforms and the Convolution Theorem. Speaker: Mark Cohen

Why the emphasis on Linear Systems? Because they are actually easy (as compared to non-linear systems, which are not.) As we go through this course, we will see many ways in which linear systems theory is applied to:

Modeling of Neural Systems

Extraction of Signal from Noise

Design of Circuits

Image Enhancement

Understanding of Image artifacts, and others.

Linear systems analysis is one of the great technologies of the 20th and 21st century. It is now the basis for virtually all electronics design, and its extension into the discrete (digital) domain is the basis for most of modern signal processing.

In our specific case, we will use these few basic principles of linear systems to understand both the instruments we use and the neuroimaging signals we collect. When you have mastered this material, you should be in a much better position to model the systems that you study in order to develop an approach to studying them.

Here is A primer I wrote on imaginary numbers that might be a helpful review.

There is a nice Wikibook on Calculus.

Required Readings

• van Drongelen: Chapter 1
• Mathematical Tools - updated 10/10/13 before class

Suggested Further Reading

Introduction to matlab

Slides shown in class

Linearity and the Fourier Transform

Please see MATLAB linearity demo

If you are the type who sees beauty in mathematics, the Euler identity may be one of the most beautiful pieces of math in the world.

Problem Set 1. Due by email xx/xx. Please remember that the preferred way for us to receive problem sets is via email to Mark and to Cameron and to Mahsa.

Week 2: Circuits I & II

Monday 10/14/13

- Circuits I. Mark Cohen

Why circuits?

(Virtually) Every device you use in your research is electronic. You access your primary data only indirectly

The device you really want in your lab doesn't exist. You very well may have to make it.

There are electronic analogs to most of the linear systems that you have so far studied (and vice versa - the tools you now understand can be used to analyze and predict circuit behavior).

If you have not had any of this background, you might want to have a look at this handout, Electrical Circuits, in advance. There are near infinite numbers of resources on the web that cover similar material (near enough to infinite that by the time you read all of them, there would be a whole new set.) I have recently come across a link to Online Books: All About Circuits IF you want practical hands-on knowledge about this material, my all-time favorite text is "Horowitz and Hill: The Art of Electronics." The latest edition, however, is dated 1989 and a new third edition is promised. I have therefore stopped short of recommending a purchase unless your need to make circuits is immediate. In this book, you will find an excellent education on the fundamental principles of electrical circuits and an incredible compendium of practical data, such as how to assemble circuit boards, how to make measurements, etc...)

Readings:

• Circuits 1 & 2
• Filter Design in 30 Seconds
• van Drongelen: Chapter 2 and 10
• Circuit Lab A Free Circuit Web Base Simulator

• • You may or may not find this comprehensible without chapters 5 through 9.

We will discuss:

• Passive Circuit Elements: Resistors, Capacitors, Inductors
• Gain
• Transformers
• Rectifiers
• Active Elements

- Amplifiers

- Transistors

- Op Amps

• Solutions with Matrices

Suggested Further Reading

• Video intro lecture on charge, current and voltage.
• Well organized text on electrical concepts by Tony R. Kuphaldt
• Circuit Theory - Wikibook

- Recap of Last Wednesdays Talk

Suggested, Optional Readings from DSPguide.com:

• Linear Systems
• Convolution
• Discrete Fourier Transform (DFT)

Note: These chapters are light on math and try to focus on a conceptual understanding

Time and Frequency / Spectral Filters

---

Practice using the Fourier transform:

Fourier transform and Convolution Worksheet. (Solutions).

Sound file for worksheet above.

Wednesday 10/16/13

- Circuits II. Mark Cohen

• Circuits 1 & 2

Other

• Getting Started with Arduino

Week 3 Circuits

Monday 10/21/13 - Circuits (cont'd)

Class will be held today. I apologize for the late update on the web site.

- Noise. Mark Cohen

• Noise Slides

It is what you don't want - usually - but things change in quantized systems

Additive noise

White Noise

Boltzmann noise

Colored Noise

Gaussian Noise

Coherent noise

Sampling Errors

Aliasing

Quantization noise

Spectral filtering

Noise comes in all shapes and colors. It is present in every measurement we make, from an EEG voltage to an estimate of the effects of dopamine on forebrain signal. Our best weapons are an understanding of the statistical properties of noise, the sources of noise and the ways to control it. Noise in the discrete digital domain is special, as it is both created by digitization and amplified by sampling.

Readings:

• van Drongelen: Chapters 2 through 4

Week 5: Optics II & Finding Data in the Noise

Monday 11/4/13

Printed Circuit Board (PCB) Layout Tools

• Through holesoldering.
• Printed Circuit Board Basics.
• Installing and Setting Up Eagle.
• Using Eagle Schematic.
• Using Eagle Board Layout.

• PCB Layout 1 - According to Pete;
• PCB Layout 2 - According to Pete;

Wednesday 11/6/13

Optics I. Speaker: Zachary Taylor

File:Reflection.jpg

The overall goal of this lecture is to establish that: - Physical constants have tangible meanings - Plane waves form a physically unrealizable but extremely good approximation to real systems - Boundaries bend light - Physical constants, plane wave mechanics, and boundaries can be used to describe the operation of a lens - The PSF gives a good indication of the overall performance of an imaging system - All of these concepts have analogues in other areas of engineering (ie circuits, mechanical vibrations, etc.)''

Outline:

• Constitutive parameters (ε, μ, η, n, etc.)
• Plane wave basics
• Plane waves at boundaries
• Lenses
• Advanced imaging properties of lenses
• Point spread function.

Required Readings Zach has very kindly agreed to post his Optics lecture notes. Suggested Further Reading

Monday 11/25/13

- Statistical Fundamentals. Speaker: Catherine Sugar

We will consider the general problems of statistical inference, with a concentration on developing an intuitive understanding of statistical concepts.

File:MeasureForMeasure.jpg

• Slides used in class (set 1)

Review of:

• Descriptive Statistics: mean, mode, variance, standard deviation
• Statistical Inference. The Binomial and Normal Distribution
• Basic Tests: t-test, linear correlation
• Modeling and non-linear relations
• Bayes rule

Suggested reading

• Statsoft online text (free)
• The Cartoon Guide to Statistics - Gonick $17.95 new

The latter teaches stats at what I feel to be the right level - developing intuitions about the kinds of questions that can be answered using stats and about the statistical tests and measures

Problem Set 5 - Statistics in matlab

Problem set using stats and MATLAB

More practice with stats and MATLAB

Week 8:

Monday 12/2/13

- Statistics for Imaging. Speaker: Catherine Sugar

1. Outline

File:BVTradeoff.jpg

Required Readings

• Statistical Modeling and Inference (pdf)
• Slides used in class 12/2/13 and 12/4/13

• The General Linear Model

• Linear Algebra applied to Statistical Solutions

• Analysis of Variance

Suggested Further Reading

Wednesday 11/20/13 ...

- Statistics for Imaging II. Speaker: Catherine Sugar

• Fixed and Random Effects
• Repeated measures

• Bonferroni and Other Corrections

• Non-Parametric Methods
• Autocorrelation
• Unknown Distributions

Required Readings

• same as 12/2/13

Suggested Further Reading

• Lecture Video - To be Posted Shortly - Please Right Click and Save rather than Stream - Thank you Alan and Edward!

Week 9:

Wednesday 11/27/13

- The Organization of the Human Brain. Speaker: Susan Bookheimer

We will discuss the general organization of the human brain, and the regional specialization of cortical areas. The emphasis will be on understanding principles of organization:

• Phylogenetic Layering
• Functional Specialization
• Principles Divisions of the Brain
• Brain Systems

Required Readings

• Neuroanatomy Programmed Learning
• Slides shown in Class UPDATED 2012/10/17

Suggested Further Reading

• Solution to Problem Set 1

Week 10: Optical Neuroimaging

Wednesday 12/4/13

- TBD. Mark Cohen

1. Outline

Required Readings

• Lecture Slides

Week 11: Human Electrophysiology

Monday 12/9/13

FINALS WEEK

- Human Electrophysiology Speakers: Agatha Lenartowicz, John Stern

Evoked Responses - Guest Lecturer: Jonathan Wynn

• A look at real EEG data
• Preprocessing:
  • filtering
  • artifact detection/removal
• averaging
• single events
• interpretation

Clinical EEG - Guest Lecturer: John Stern

• Normal and Abnormal EEG
• EEG as a marker for brain state
  • sleep staging
  • alpha and relaxation
• Neurofeedback???