Neuroimaging Tecniques in Cognitive Neuroscience

Recommended Prerequisites

Some command of English

Teaching Methods

Classes will focus on a more lecture method and some more practical aspects where students are introduced to the analysis software. Students are encouraged to intervene in class, in response to class questions and mandatory readings.

Learning Outcomes

 

1. Understand the basic concepts of (functional) magnetic resonance imaging

2. Understand aspects of imaging in scientific articles.

3. Understand aspects of neuroimaging and functional analysis, specifically, familiarize students with fMRI data analysis software and the typical steps to follow.

Work Placement(s)

No

Syllabus

1. MRI physics, acquisition parameters and MRI safety

2. Experimental design

3. Data preprocessing

4. Univariate analysis - GLMs, ROIs, etc.

5. The problem of multiple comparisons in fMRI

6. Multivoxel Pattern Analysis

7. Connectivity

Head Lecturer(s)

Jorge Manuel Castelo Branco de Albuquerque Almeida

Assessment Methods

Avaliação
Resolution Problems: 20.0%
Synthesis work: 35.0%
Frequency: 45.0%

Bibliography

Bibliografia principal:

Huettel, S.A., Song, A.W. & McCarthy, G. (2014). Functional Magnetic Resonance Imaging (3rd Edition). Sunderland (Massachusetts): Sinauer Associates.

 

Poldrock, R. A., Mumford, J. A., & Nichols, T. E. (2011). Handbook of functional MRI data analysis. Cambridge University Press. https://doi.org/10.1017/CBO9780511895029

 

Ashby, F. G. (2011). Statistical analysis of fMRI data. Cambridge, Mass: MIT Press.