# Principles of Neuroimaging A - 2015

Principles of Neuroimaging A, Fall, 2015 - Class Schedule and Syllabus

# N.B. This is a draft-only as of 9-16-2015

**Neuroimaging journal Club (***required for NITP certificate*)

*required for NITP certificate*)

Contact Katherine Lawrence (katherine.E.Lawrence@ucla.edu) or Janelle Liu (janelle.j.liu@ucla.edu)

## This schedule *will* change!

**Coming up next!: M284B Principles of Neuroimaging B**

# Lecture Videos

- Hopefully, we can start recording the class sessions for those who cannot make a few lectures.

# 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 9/28/15*

### - 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.

*Required Readings* - Please complete these readings prior to class.

*Suggested Further Reading*

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

*Wednesday 9/30/15*

### 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

*Suggested Further Reading*

**Introduction to matlab**

*Slides shown in class*

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 10/5/15.** Please remember that the preferred way for us to receive problem sets is *via email* to Mark

# Week 2: Math & Circuits I

*Monday 10/5/15*

This problem set refers largely to last week's contents:
**Problem Set 1. Due by email 10/20/14.** Please remember that the preferred way for us to receive problem sets is *via email* to Mark and to John Dell'Itlalia .

### - Circuits I. Mark Cohen

We will continue with the linear systems lecture and move to circuits

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*

**Suggested, Optional Readings from DSPguide.com:**

*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:

*Wednesday 10/7/15*

### - Circuits II. Mark Cohen

Other

# Week 3: Stats begins!

*Monday 10/12/15*

### - 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.

*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

- 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 3 - Statistics in matlab**

*Wednesday 10/14/15*

### - Statistical Fundamentals II. *Speaker*: Catherine Sugar

# Week 4 - Stats and circuits

*Monday 10/19/15*

### - Statistical Fundamentals III. *Speaker*: Catherine Sugar

*Wednesday 10/21/15*

### Circuits continued: Active devices. Mark Cohen

=Week 5 - Circuits and applications

*Monday 10/26/15*

### Practical circuit design and noise Mark Cohen

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

*Wednesday 10/28/15*

### Electrophysiology and EEG *Speaker*: Agatha Lenartowicz

# Week 6 - applied electrophysiology

*Monday 11/2/15*

### Electrophysiology and EEG *Speaker*: Agatha Lenartowicz

*Wednesday 11/4/15*

### Class Project Design

# Week 7 - Imaging with light

*Monday 11/9/15*

### Optics I. *Speaker*: Zachary Taylor

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*