Course Syllabus

W18-PSYCH-204A-01

An introduction to human neuroimaging using magnetic resonance

The course begins with an introduction to the basic MR instrumentation (magnet, gradients, coils) and signals (PD, T1, T2, T2*). Next, we cover how MR images are formed. We then review the acquisition and analysis of some of the most common human neuroimaging measurements, including anatomical, diffusion, and functional signals.

Throughout the course we review methods designed to infer the biological basis of MRI signals. The goal of this work is to connect the MRI measurements to brain tissue, structures, and cellular activity. The emphasis on modeling involves the use of some programming and simulation methodology (based on either Python or Matlab). The course includes a series of homework assignments that are short questions or calculations.

This course leads naturally to Psych 204b: Computational Neuroimaging (Spr 2017, TuTh 9:00AM-10:20AM, 420-419) taught by Prof. Grill-Spector and Prof. Yamins.

Classroom    Science Teaching and Learning Center, 105
Schedule    Tuesday, Thursday from 1:30-2:50pm
Textbook:     Huettel et al., FMRI (Third Edition, Oxford).  
                      The book can be rented from the VitalSource site  or 
                      purchased (about $115 dollars).

Course assistant:  Mona Rosenke 
Office hours:          Monday 2:00 - 3:00 pm, room: 420-432
By appointment:    Friday

Link to lecture videos
https://talks.stanford.edu/psychology/psych-204a-introduction-to-human-neuroimaging-using-mri/ 
(Sign in with SUNET ID and password)

Github sites for Matlab tutorials

  • Homework tutorials - Only the mri sub-directory is for this class.
  • MRI Simulator         - Under development, and a potential extra credit project for programmers

 

Lecture Schedule

Week/Day Date

Topic

Reading Homework
1.1 1/09

Introduction: The Instrument 

Chapters 1

Link to homework tutorials (github)

1.2 1/11

MR signals I

Chapters 2
2.1 1/16

MR signals II

Chapters  3 (Conceptual)  HW 1 posted
mrTutMR.m 
(or mlx form) 
2.2 1/18

Contrast mechanisms

Chapter 4
(Conceptual)
3.1 1/23
  • Image formation I
  • Linear Systems

Chapter 5

HW 1 due 
HW 2 posted
mrTutImaging.m
(or mlx form) 

3.2 1/25 Image formation II
Multiband acquisitions

Chapter 5
(p. 147 et seq.)

 

4.1 1/30
  • Gross anatomy and vasculature

Chapter 6, 7
Logothetis & Wandell; Boynton et al. 

HW 2 due
HW 3 posted

 

4.2   2/1
  • BOLD physiological mechanisms
  • Electrophysiological thinking
  • History of MRI

Dumoulin and Wandell;

Wandell and Winawer

5.1 2/6
  • BOLD contrast and time series
  • Quantitative modeling: Population Receptive Fields 
  • Signal detection, ROC
HW 3 due
5.2 2/8

Quantifying anatomy. Cortical thickness ... (others, such as VBM)

 Gari

Midterm starts

(24 hours to complete, once you start)

6.1 2/13

Diffusion Imaging: Principles and applications

Chapter 5
(p. 138 et seq.) 

Le Bihan review

Midterm due

HW 4 posted

6.2 2/15 Modeling diffusion data I –
Ball and stick, multiple tensors, multishell, NODDI
Wandell review mrTutDiffusion
(or mlx form)
7.1 2/20

Fiber tractography principles
Fascicle labeling (Tracula, AFQ)
Tractography evaluation (LiFE)

HW 4 due
HW 5 posted
7.2 2/22

Ensemble tractography
Diffusion Kurtosis Imaaging
Quantitative MRI measures.
Proton density, Molecular Tissue Volume, T1, T2

8.1 2/27

Quantitative modeling
NODDI
G-Ratio imaging

HW 5 due
HW 6 posted

8.2 3/1

Advanced Imaging Techniques: 
Fingerprinting, QSM, Ultra high field

9.1 3/6 The human face perception system Mona (tentative) HW 6 due

9.2 3/8

Integration with other modalities (ECoG, MEG, EEG)

Dora mrTutVisualization (or mlx form) 
10.1  3/13

Visualization methods
Cortical flattening

Wandell, Chial, Backus;
Pestilli self-potraits of the brain
Dale, Fischl & Sereno

 

10.2 3/15 Data and computational management tools

Tentative - LMP
Markus;
Calhoun;

Final available

24 hours to complete once you start.

 March 19-23 Final Exam: 24 hour time period of your choosing Grades Due 3/27 

Course Summary:

Date Details