SPM Essentials

 

SPM8 Essentials is an introductory, on-line course designed for new investigators having some familiarity with the fundamental principles of fMRI data acquisition and analysis. Requiring no previous experience using SPM, it provides a basic grounding in the conceptual and practical issues associated with using SPM8 for fMRI analysis. It will be available for investigators planning to take other Neurometrika courses who require some concentrated training in the essentials of SPM use.

The workshop will cover the basics of using SPM8 for preprocessing, statistical modeling and visualization of data associated with basic fMRI experimental designs. The primary emphasis will involve using the core SPM8 programs for these purposes.

As the course will include tutorials utilizing SPM8, participants must have access to a computer with MATLAB and  SPM8 already installed. Detailed setup instructions can be found here.

This course will be offered beginning in February 2012. Inquiries about arranging a 3-day concentrated workshop covering the same material in your area should be directed to admin@neurometrika.org.

 

Educational Objectives

  • Understand the basic organization of the SPM GUI
  • Understand the organization of the SPM "toolbox"
  • Be able to construct simple batch processing scripts for preprocessing and statistical modeling
  • Understand the basic fMRI data preprocessing steps
  • Be able to convert MRI data from DICOM to NIFTI file format.
  • Be able to construct a preprocessing sequence including slice time correction, realignment, spatial normalization and spatial filtering
  • Understand the basic fMRI single subject experimental design types
  • Be able to implement statistical analysis procedures for the basic single subject fMRI designs

Topics

Introduction to SPM8

Workshop overview
SPM8 interface
SPM8 architecture
MATLAB basics
File format conversion: DICOM -> NIFTI

Basic Preprocessing

Preprocessing overview and background
Realignment
Slice time correction
Spatial filtering
Spatial normalization

Basic First-level experimental design and analysis

First-level fMRI designs overview
Temporal filtering
Global normalization
First-level fMRI design examples

Basic Second-level experimental design and analysis

Visualization

Batch Processing

Batch processing introduction


 

Topics