Skip to content

SPM Documentation

Bayesian inference

Initializing search

Home
Getting started
Tutorials
Courses
Reference documentation
Development

SPM Documentation

Home
Home
Getting started
Getting started
Tutorials
Tutorials
- fMRI
  fMRI
  - Block design fMRI
    
    Block design fMRI
    
    Preprocessing
    Preprocessing
    
    Introduction
    
    Visual inspection
    
    Removal of dummy scans
    
    Realignment
    
    Slice timing correction
    
    Coregistration
    
    Segmentation
    
    Normalisation
    
    Smoothing
    
    Batch interface
    
    Scripting
    
    Statistical modelling
    Statistical modelling
    
    First-level modelling - block design
  - Event-related fMRI
    
    Event-related fMRI
    
    Preprocessing
    
    Categorical Modelling
    
    Parametric Modelling
    
    Bayesian Analysis
  - Group-level fMRI
    
    Group-level fMRI
    
    One-sample t-test
    
    Two-sample t-test
    
    Factorial
- VBM
  VBM
  - Preprocessing
  - Analysis
- M/EEG
  M/EEG
  - EEG mismatch negativity data
  - Advanced topics in artefact removal
  - M/EEG convolution modelling
  - MEG source localisation
  - Multimodal
    
    Multimodal
    
    EEG
    
    MEG
    
    fMRI
    
    Fusion
  - Multimodal, multisubject data fusion
    
    Multimodal, multisubject data fusion
    
    Preprocessing
    
    Evoked analysis
    
    Time-frequency analysis
    
    fMRI
    
    Source
    
    References
- OPM
  OPM
- DCM
  DCM
- DAiSS
  DAiSS
Courses
Courses
- M/EEG
  M/EEG
- fMRI/VBM
  fMRI/VBM
Reference documentation
Reference documentation
- M/EEG
  M/EEG
Development
Development
- Git
- Guidelines
- Testing
- Compilation

Bayesian inference¶

In this talk, Dr Dimitrios Pinotsis introduces the concepts underpinning Bayesian analysis.

Analysis of optically pumped magnetometer (OPM) data (talk & demo)

M/EEG source analysis (talk & demo)

Copyright © 1991 - 2024 SPM Team and Collaborators