Advanced neuroimaging methods
General details of the subject
- Mode
- Face-to-face degree course
- Language
- English
Description and contextualization of the subject
Basis of electrophysiological signal and synchrony; Sensor-level analysis, Component analysis; Source reconstruction: Dipole modeling, Distributed approaches, Frequency-domain methods, functional and effective connectivityTeaching staff
| Name | Institution | Category | Doctor | Teaching profile | Area | E-mail |
|---|
| MATAR , SUHAIL | BCBL- Basque Center on Cognition, Brain and Language | Otros | Doctor | | | s.matar@bcbl.eu |
| RICHTER , CRAIG | BCBL- Basque Center on Cognition, Brain and Language | Otros | Doctor | | | c.richter@bcbl.eu |
| SOTO BLANCO, DAVID | BCBL- Basque Center on Cognition, Brain and Language | Otros | Doctor | | | d.soto@bcbl.eu |
Competencies
| Name | Weight |
|---|
| CE1. Advanced knowledge of research methods in electrophysiology. | 50.0
%
|
| CE2. Applying knowledge creatively to identify research questions and plan data analysis in studies using electroencephalography and megnetoencephalography. | 50.0
%
|
Study types
| Type | Face-to-face hours | Non face-to-face hours | Total hours |
|---|
| Lecture-based | 10 | 10 | 20 |
| Applied laboratory-based groups | 10 | 10 | 20 |
| Applied computer-based groups | 10 | 25 | 35 |
Assessment systems
| Name | Minimum weighting | Maximum weighting |
|---|
| Attendance and participation | 20.0
%
| 20.0
%
|
| Works and projects | 80.0
%
| 80.0
%
|
Temary
This course will introduce the fundamental methods for the analysis of functional MRI, and electrophysiological (i.e. EEG and MEG) data.
The goal is to provide the students with the core ideas necessary to understand current data analysis methods used in the literature from a critical point of view, and provide sufficient hands-on experience on relevant software packages that implement them. The course is divided into three sections. The first part will consist of hands-on sessions covering the essentials of MRI data processing, using a standard neuroimaging software packages. There will be practical sessions on the analysis of electrophysiological data, mainly using BrainVision Analyzer and EEGlab.
In addition, the course will describe the basic theoretical background of the most common methods for analysis of functional MRI data, such as the general linear model and independent component analysis, the main software packages (AFNI, FSL), also with an introduction to multivariate pattern analyses (MVPA).
Bibliography
Compulsory materials
-FSL (see http://fsl.fmrib.ox.ac.uk/fslcourse), AFNI, Brain Vision Analyzer 2. User Manual - User Manual of EEGLab (http://sccn.ucsd.edu/eeglab/) - Statistical Parametric Mapping: The analysis of functional brain images. Edited by K. J. Friston, J.T. Ashburner, S. J. Kiebel, T. E. Nichols and W.E. Penny. Elsevier 2008. - Statistical analysis of fMRI data. F. G. Ashby. MIT Press 2011. - Handbook of functional MRI data analysis. R.A. Poldrack, J. A. Mumford and T.E. Nichols. Cambridge University Press 2011. Basic bibliography
Hansen, P.C., et al. MEG: An Introduction to Methods (selected chapters)
Friston, K. J. et al. Statistical Parametric Mapping, The Analysis of Functional Brain Images (selected chapters)
nireEHU 